[Tensors]

Table of Contents

• Available objects and their input file syntax
  • CSVSR2
  • CSVScalar
  • CSVVec
  • CenterMillerIndex
  • CenterQuaternion
  • CenterR2
  • CenterR3
  • CenterR4
  • CenterRot
  • CenterSFFR4
  • CenterSFR3
  • CenterSR2
  • CenterSSR4
  • CenterSWR4
  • CenterScalar
  • CenterTensor
  • CenterVec
  • CenterWFFR4
  • CenterWR2
  • CenterWSR4
  • CenterWWR4
  • DifferenceMillerIndex
  • DifferenceQuaternion
  • DifferenceR2
  • DifferenceR3
  • DifferenceR4
  • DifferenceRot
  • DifferenceSFFR4
  • DifferenceSFR3
  • DifferenceSR2
  • DifferenceSSR4
  • DifferenceSWR4
  • DifferenceScalar
  • DifferenceTensor
  • DifferenceVec
  • DifferenceWFFR4
  • DifferenceWR2
  • DifferenceWSR4
  • DifferenceWWR4
  • FillR2
  • FillRot
  • FillSR2
  • FillWR2
  • FullMillerIndex
  • FullQuaternion
  • FullR2
  • FullR3
  • FullR4
  • FullRot
  • FullSFFR4
  • FullSFR3
  • FullSR2
  • FullSSR4
  • FullSWR4
  • FullScalar
  • FullTensor
  • FullVec
  • FullWFFR4
  • FullWR2
  • FullWSR4
  • FullWWR4
  • GaussianScalar
  • GaussianTensor
  • IdentityTensor
  • LinspaceMillerIndex
  • LinspaceQuaternion
  • LinspaceR2
  • LinspaceR3
  • LinspaceR4
  • LinspaceRot
  • LinspaceSFFR4
  • LinspaceSFR3
  • LinspaceSR2
  • LinspaceSSR4
  • LinspaceSWR4
  • LinspaceScalar
  • LinspaceTensor
  • LinspaceVec
  • LinspaceWFFR4
  • LinspaceWR2
  • LinspaceWSR4
  • LinspaceWWR4
  • LogspaceMillerIndex
  • LogspaceQuaternion
  • LogspaceR2
  • LogspaceR3
  • LogspaceR4
  • LogspaceRot
  • LogspaceSFFR4
  • LogspaceSFR3
  • LogspaceSR2
  • LogspaceSSR4
  • LogspaceSWR4
  • LogspaceScalar
  • LogspaceTensor
  • LogspaceVec
  • LogspaceWFFR4
  • LogspaceWR2
  • LogspaceWSR4
  • LogspaceWWR4
  • MillerIndex
  • MillerIndexFromTorchScript
  • MultiColumnCSVScalar
  • Orientation
  • Quaternion
  • QuaternionFromTorchScript
  • R2
  • R2FromTorchScript
  • R3
  • R3FromTorchScript
  • R4
  • R4FromTorchScript
  • RandomMillerIndex
  • RandomQuaternion
  • RandomR2
  • RandomR3
  • RandomR4
  • RandomRot
  • RandomSFFR4
  • RandomSFR3
  • RandomSR2
  • RandomSSR4
  • RandomSWR4
  • RandomScalar
  • RandomTensor
  • RandomVec
  • RandomWFFR4
  • RandomWR2
  • RandomWSR4
  • RandomWWR4
  • Rot
  • RotFromTorchScript
  • SFFR4
  • SFFR4FromTorchScript
  • SFR3
  • SFR3FromTorchScript
  • SR2
  • SR2FromTorchScript
  • SSR4
  • SSR4FromTorchScript
  • SWR4
  • SWR4FromTorchScript
  • Scalar
  • ScalarFromTorchScript
  • SymmetryFromOrbifold
  • Tensor
  • Vec
  • VecFromTorchScript
  • WFFR4
  • WFFR4FromTorchScript
  • WR2
  • WR2FromTorchScript
  • WSR4
  • WSR4FromTorchScript
  • WWR4
  • WWR4FromTorchScript

Note

Clicking on the option with a triangle bullet ▸ next to it will expand/collapse its detailed information.

Type name written in PascalCase typically refer to a NEML2 object type, oftentimes a primitive tensor type.

The 🔗 symbol means that the tensor value can be cross-reference another object. See Model parameters (revisited) for details.

You can always use Ctrl+F or Cmd+F to search the entire page.

Available objects and their input file syntax

Refer to System Documentation for detailed explanation about this system.

CSVSR2

Construct a SR2 from a CSV file. Each component of the SR2 should be provided as a column in the CSV. By default the entire CSV is read in order of the columns. A subset/different order of columns can be selected using column_indices or column_names. Each row of the CSV corresponds to a batch. The default batch shape is the number of rows in the CSV.

column_indices Indices of CSV columns.

• Type: list of non-negative number
• Required: No

column_names Names of CSV columns.

• Type: list of string
• Required: No

csv_file Path to the CSV file

• Type: string
• Required: Yes

delimiter Delimiter used to parse the CSV file. Options are SPACE, TAB, SEMICOLON, COMMA

• Type: EnumSelection
• Required: No
• Default: COMMA

no_header Whether the CSV file has a header row.

• Type: bool
• Required: No
• Default: false

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

starting_row Starting row of the CSV file (0-indexed). Rows before this row are ignored. This should be the header row if the CSV file has a header, otherwise it should be the first row of the data. By default the starting row is the 0th row.

• Type: number
• Required: No

Detailed documentation link

CSVScalar

Construct a Scalar from a CSV file. Each component of the Scalar should be provided as a column in the CSV. By default the entire CSV is read in order of the columns. A subset/different order of columns can be selected using column_indices or column_names. Each row of the CSV corresponds to a batch. The default batch shape is the number of rows in the CSV.

column_indices Indices of CSV columns.

• Type: list of non-negative number
• Required: No

column_names Names of CSV columns.

• Type: list of string
• Required: No

csv_file Path to the CSV file

• Type: string
• Required: Yes

delimiter Delimiter used to parse the CSV file. Options are SPACE, TAB, SEMICOLON, COMMA

• Type: EnumSelection
• Required: No
• Default: COMMA

no_header Whether the CSV file has a header row.

• Type: bool
• Required: No
• Default: false

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

starting_row Starting row of the CSV file (0-indexed). Rows before this row are ignored. This should be the header row if the CSV file has a header, otherwise it should be the first row of the data. By default the starting row is the 0th row.

• Type: number
• Required: No

Detailed documentation link

CSVVec

Construct a Vec from a CSV file. Each component of the Vec should be provided as a column in the CSV. By default the entire CSV is read in order of the columns. A subset/different order of columns can be selected using column_indices or column_names. Each row of the CSV corresponds to a batch. The default batch shape is the number of rows in the CSV.

column_indices Indices of CSV columns.

• Type: list of non-negative number
• Required: No

column_names Names of CSV columns.

• Type: list of string
• Required: No

csv_file Path to the CSV file

• Type: string
• Required: Yes

delimiter Delimiter used to parse the CSV file. Options are SPACE, TAB, SEMICOLON, COMMA

• Type: EnumSelection
• Required: No
• Default: COMMA

no_header Whether the CSV file has a header row.

• Type: bool
• Required: No
• Default: false

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

starting_row Starting row of the CSV file (0-indexed). Rows before this row are ignored. This should be the header row if the CSV file has a header, otherwise it should be the first row of the data. By default the starting row is the 0th row.

• Type: number
• Required: No

Detailed documentation link

CenterMillerIndex

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: MillerIndex 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterQuaternion

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: Quaternion 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterR2

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: R2 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterR3

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: R3 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: R4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterRot

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: Rot 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterSFFR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: SFFR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterSFR3

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: SFR3 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterSR2

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: SR2 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterSSR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: SSR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterSWR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: SWR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterScalar

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: Scalar 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterTensor

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: Tensor 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterVec

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: Vec 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterWFFR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: WFFR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterWR2

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: WR2 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterWSR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: WSR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

CenterWWR4

Compute interval centers along an intermediate dimension.

dim Intermediate dimension to compute centers

• Type: number
• Required: No

points The input tensor to be centered

• Type: WWR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceMillerIndex

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: MillerIndex 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceQuaternion

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: Quaternion 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceR2

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: R2 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceR3

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: R3 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: R4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceRot

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: Rot 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceSFFR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: SFFR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceSFR3

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: SFR3 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceSR2

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: SR2 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceSSR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: SSR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceSWR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: SWR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceScalar

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: Scalar 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceTensor

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: Tensor 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceVec

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: Vec 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceWFFR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: WFFR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceWR2

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: WR2 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceWSR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: WSR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

DifferenceWWR4

Compute finite differences along an intermediate dimension.

dim Intermediate dimension to take the finite difference

• Type: number
• Required: No

points The input tensor to be differenced

• Type: WWR4 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

FillR2

Construct a R2 with a vector of Scalars. The vector length must be 1, 3, 6, or 9. When vector length is 1, the Scalar value is used to fill the diagonals; when vector length is 3, the Scalar values are used to fill the respective diagonal entries; when vector length is 6, the Scalar values are used to fill the tensor following the Voigt notation; when vector length is 9, the Scalar values are used to fill the tensor in the row-major fashion.

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Scalars used to fill the R2

• Type: list of Scalar> 🔗
• Required: Yes

Detailed documentation link

FillRot

Construct a Rot from a vector of Scalars.

method Fill method, options are 'modified' and 'standard'.

• Type: string
• Required: No
• Default: modified

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Scalars used to fill the Rot

• Type: list of Scalar> 🔗
• Required: Yes

Detailed documentation link

FillSR2

Construct a SR2 with a vector of Scalars. The vector length must be 1, 3, or 6. See the full documentation on neml2::SR2 on the dispatch of fill method. When vector length is 1, the Scalar value is used to fill the diagonals; when vector length is 3, the Scalar values are used to fill the respective diagonal entries; when vector length is 6, the Scalar values are used to fill the tensor following the Voigt notation.

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Scalars used to fill the SR2

• Type: list of Scalar> 🔗
• Required: Yes

Detailed documentation link

FillWR2

Construct a WR2 from a vector of Scalars.

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Scalars used to fill the WR2

• Type: list of Scalar> 🔗
• Required: Yes

Detailed documentation link

FullMillerIndex

Construct a full MillerIndex with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullQuaternion

Construct a full Quaternion with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullR2

Construct a full R2 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullR3

Construct a full R3 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullR4

Construct a full R4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullRot

Construct a full Rot with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullSFFR4

Construct a full SFFR4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullSFR3

Construct a full SFR3 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullSR2

Construct a full SR2 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullSSR4

Construct a full SSR4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullSWR4

Construct a full SWR4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullScalar

Construct a full Scalar with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullTensor

Construct a full Tensor with given batch shape. Tensor values are set to the specified value.

base_shape Base shape

• Type: tensor shape
• Required: No

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullVec

Construct a full Vec with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullWFFR4

Construct a full WFFR4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullWR2

Construct a full WR2 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullWSR4

Construct a full WSR4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

FullWWR4

Construct a full WWR4 with given batch shape. Tensor values are set to the specified value.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

value Value to fill the tensor with

• Type: number
• Required: Yes

Detailed documentation link

GaussianScalar

Construct a Scalar with values sampled from a Gaussian profile at given points. The Gaussian is \(g(x) = h \exp(-\tfrac{1}{2} z^2)\) with \(z = (x - c) / w\), where \(h\) is the height, \(w\) is the width, and \(c\) is the center.

center The Gaussian center in the domain

• Type: Scalar 🔗
• Required: No

height The Gaussian height

• Type: Scalar 🔗
• Required: Yes

points The coordinates to evaluate the Gaussian at

• Type: Scalar 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

width The Gaussian width

• Type: Scalar 🔗
• Required: Yes

Detailed documentation link

GaussianTensor

Construct a Tensor with values sampled from a Gaussian profile at given points. The Gaussian is \(g(x) = h \exp(-\tfrac{1}{2} z^2)\) with \(z = (x - c) / w\), where \(h\) is the height, \(w\) is the width, and \(c\) is the center.

center The Gaussian center in the domain

• Type: Scalar 🔗
• Required: No

height The Gaussian height

• Type: Scalar 🔗
• Required: Yes

points The coordinates to evaluate the Gaussian at

• Type: Tensor 🔗
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

width The Gaussian width

• Type: Scalar 🔗
• Required: Yes

Detailed documentation link

IdentityTensor

Construct an identity Tensor with given batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

n Diagonal size of the identity tensor, i.e., base shape of the identity tensor will be (n,n)

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

LinspaceMillerIndex

Construct a MillerIndex linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: MillerIndex 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: MillerIndex 🔗
• Required: Yes

Detailed documentation link

LinspaceQuaternion

Construct a Quaternion linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Quaternion 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Quaternion 🔗
• Required: Yes

Detailed documentation link

LinspaceR2

Construct a R2 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: R2 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: R2 🔗
• Required: Yes

Detailed documentation link

LinspaceR3

Construct a R3 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: R3 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: R3 🔗
• Required: Yes

Detailed documentation link

LinspaceR4

Construct a R4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: R4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: R4 🔗
• Required: Yes

Detailed documentation link

LinspaceRot

Construct a Rot linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Rot 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Rot 🔗
• Required: Yes

Detailed documentation link

LinspaceSFFR4

Construct a SFFR4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SFFR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SFFR4 🔗
• Required: Yes

Detailed documentation link

LinspaceSFR3

Construct a SFR3 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SFR3 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SFR3 🔗
• Required: Yes

Detailed documentation link

LinspaceSR2

Construct a SR2 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SR2 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SR2 🔗
• Required: Yes

Detailed documentation link

LinspaceSSR4

Construct a SSR4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SSR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SSR4 🔗
• Required: Yes

Detailed documentation link

LinspaceSWR4

Construct a SWR4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SWR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SWR4 🔗
• Required: Yes

Detailed documentation link

LinspaceScalar

Construct a Scalar linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Scalar 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Scalar 🔗
• Required: Yes

Detailed documentation link

LinspaceTensor

Construct a Tensor linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Tensor 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Tensor 🔗
• Required: Yes

Detailed documentation link

LinspaceVec

Construct a Vec linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Vec 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Vec 🔗
• Required: Yes

Detailed documentation link

LinspaceWFFR4

Construct a WFFR4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WFFR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WFFR4 🔗
• Required: Yes

Detailed documentation link

LinspaceWR2

Construct a WR2 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WR2 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WR2 🔗
• Required: Yes

Detailed documentation link

LinspaceWSR4

Construct a WSR4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WSR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WSR4 🔗
• Required: Yes

Detailed documentation link

LinspaceWWR4

Construct a WWR4 linearly spaced on the batch/intermediate dimensions. See neml2::dynamic_linspace, neml2::intmd_linspace, or neml2::base_linspace for a detailed explanation.

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WWR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WWR4 🔗
• Required: Yes

Detailed documentation link

LogspaceMillerIndex

Construct a MillerIndex logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: MillerIndex 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: MillerIndex 🔗
• Required: Yes

Detailed documentation link

LogspaceQuaternion

Construct a Quaternion logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Quaternion 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Quaternion 🔗
• Required: Yes

Detailed documentation link

LogspaceR2

Construct a R2 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: R2 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: R2 🔗
• Required: Yes

Detailed documentation link

LogspaceR3

Construct a R3 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: R3 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: R3 🔗
• Required: Yes

Detailed documentation link

LogspaceR4

Construct a R4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: R4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: R4 🔗
• Required: Yes

Detailed documentation link

LogspaceRot

Construct a Rot logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Rot 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Rot 🔗
• Required: Yes

Detailed documentation link

LogspaceSFFR4

Construct a SFFR4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SFFR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SFFR4 🔗
• Required: Yes

Detailed documentation link

LogspaceSFR3

Construct a SFR3 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SFR3 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SFR3 🔗
• Required: Yes

Detailed documentation link

LogspaceSR2

Construct a SR2 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SR2 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SR2 🔗
• Required: Yes

Detailed documentation link

LogspaceSSR4

Construct a SSR4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SSR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SSR4 🔗
• Required: Yes

Detailed documentation link

LogspaceSWR4

Construct a SWR4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: SWR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: SWR4 🔗
• Required: Yes

Detailed documentation link

LogspaceScalar

Construct a Scalar logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Scalar 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Scalar 🔗
• Required: Yes

Detailed documentation link

LogspaceTensor

Construct a Tensor logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Tensor 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Tensor 🔗
• Required: Yes

Detailed documentation link

LogspaceVec

Construct a Vec logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: Vec 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: Vec 🔗
• Required: Yes

Detailed documentation link

LogspaceWFFR4

Construct a WFFR4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WFFR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WFFR4 🔗
• Required: Yes

Detailed documentation link

LogspaceWR2

Construct a WR2 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WR2 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WR2 🔗
• Required: Yes

Detailed documentation link

LogspaceWSR4

Construct a WSR4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WSR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WSR4 🔗
• Required: Yes

Detailed documentation link

LogspaceWWR4

Construct a WWR4 logarithmically spaced on the batch dimensions. See neml2::dynamic_logspace, neml2::intmd_logspace, or neml2::base_logspace for a detailed explanation.

base The base of the logarithm

• Type: number
• Required: No
• Default: 10

dim Where to insert the new dimension

• Type: number
• Required: No

end The ending tensor

• Type: WWR4 🔗
• Required: Yes

group Dimension group to apply the operation. Options are: intermediate, dynamic

• Type: EnumSelection
• Required: No
• Default: dynamic

nstep The number of steps with even spacing along the new dimension

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

start The starting tensor

• Type: WWR4 🔗
• Required: Yes

Detailed documentation link

MillerIndex

Construct a MillerIndex from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

MillerIndexFromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

MultiColumnCSVScalar

Construct a two-dimensional Scalar from a CSV file. A subset of columns can be selected using column_indices or column_names. By default, the CSV is interpreted as column-major, i.e., each column in the CSV corresponds to one row of the 2D Scalar. This behavior can be altered via the indexing option.

column_indices Indices of CSV columns.

• Type: list of non-negative number
• Required: No

column_names Names of CSV columns.

• Type: list of string
• Required: No

csv_file Path to the CSV file

• Type: string
• Required: Yes

delimiter Delimiter used to parse the CSV file. Options are SPACE, TAB, SEMICOLON, COMMA

• Type: EnumSelection
• Required: No
• Default: COMMA

indexing Indexing interpretation. Options are ROW_MAJOR, COLUMN_MAJOR

• Type: EnumSelection
• Required: No
• Default: COLUMN_MAJOR

no_header Whether the CSV file has a header row.

• Type: bool
• Required: No
• Default: false

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

starting_row Starting row of the CSV file (0-indexed). Rows before this row are ignored. This should be the header row if the CSV file has a header, otherwise it should be the first row of the data. By default the starting row is the 0th row.

• Type: number
• Required: No

Detailed documentation link

Orientation

An orientation, internally defined as a set of Modified Rodrigues parameters given by \( r = n \tan{\frac{\theta}{4}} \) with \( n \) the axis of rotation and \( \theta \) the rotation angle about that axis. However, this class provides a variety of ways to define the orientation in terms of other, more common representations.

angle_convention Euler angle convention, 'Kocks', 'Roe', or 'Bunge'

• Type: string
• Required: No
• Default: kocks

angle_type Type of angles, either 'degrees' or 'radians'

• Type: string
• Required: No
• Default: degrees

input_type The method used to define the angles, 'euler_angles' or 'random'

• Type: string
• Required: No
• Default: euler_angles

normalize If true do a shadow parameter replacement of the underlying MRP representation to move the inputs farther away from the singularity

• Type: bool
• Required: No
• Default: false

quantity Number (batch size) of random orientations

• Type: non-negative number
• Required: No
• Default: 1

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Input Euler angles, as a flattened n-by-3 matrix

• Type: list of number
• Required: No

Detailed documentation link

Quaternion

Construct a Quaternion from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

QuaternionFromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

R2

Construct a R2 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

R2FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

R3

Construct a R3 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

R3FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

R4

Construct a R4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

R4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

RandomMillerIndex

Construct a random MillerIndex with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomQuaternion

Construct a random Quaternion with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomR2

Construct a random R2 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomR3

Construct a random R3 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomR4

Construct a random R4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomRot

Construct a random Rot with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomSFFR4

Construct a random SFFR4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomSFR3

Construct a random SFR3 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomSR2

Construct a random SR2 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomSSR4

Construct a random SSR4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomSWR4

Construct a random SWR4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomScalar

Construct a random Scalar with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomTensor

Construct a random Tensor with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

base_shape Base shape

• Type: tensor shape
• Required: No

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomVec

Construct a random Vec with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomWFFR4

Construct a random WFFR4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomWR2

Construct a random WR2 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomWSR4

Construct a random WSR4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

RandomWWR4

Construct a random WWR4 with given batch shape. Tensor values are set to random values. Values are drawn uniformly from the sample space.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

max Maximum random value.

• Type: number
• Required: Yes

min Minimum random value.

• Type: number
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

Rot

Construct a Rot from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

RotFromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

SFFR4

Construct a SFFR4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

SFFR4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

SFR3

Construct a SFR3 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

SFR3FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

SR2

Construct a SR2 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

SR2FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

SSR4

Construct a SSR4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

SSR4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

SWR4

Construct a SWR4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

SWR4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

Scalar

Construct a Scalar from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

ScalarFromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

SymmetryFromOrbifold

Returns a tensor of symmetry operations for a given symmetr group represented in orbifold notation.

orbifold A string giving the orbifold representation of the group, for example 432 for the typical cubic crystal system defined by chiral octahedral symmetry

• Type: string
• Required: Yes

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

Detailed documentation link

Tensor

Construct a Tensor from a vector values. The vector will be reshaped according to the specified batch shape.

base_shape Base shape

• Type: tensor shape
• Required: No

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

Vec

Construct a Vec from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

VecFromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

WFFR4

Construct a WFFR4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

WFFR4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

WR2

Construct a WR2 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

WR2FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

WSR4

Construct a WSR4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

WSR4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link

WWR4

Construct a WWR4 from a vector values. The vector will be reshaped according to the specified batch shape.

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

values Values in this (flattened) tensor

• Type: list of number
• Required: Yes

Detailed documentation link

WWR4FromTorchScript

Get the tensor from torch script. The torch script should define a Module with named_buffers that stores the tensor to load. Refer to tests/regression/liquid_infiltration/gold/generate_load_file.py for an example

batch_shape Batch shape

• Type: tensor shape
• Required: No

intermediate_dimension Intermediate dimension

• Type: non-negative number
• Required: No

shape_manipulation_args A list of arguments corresponding to each shape manipulation operation. The number of entries should match the number of operations in 'shape_manipulations'. Each entry is a tensor shape that encodes the arguments for the corresponding operation. For operations that do not require any argument, an empty shape, i.e. (), should be used.

• Type: list of tensor shape
• Required: No

shape_manipulations A list of shape manipulation operations to apply to the created tensor. Supported operations are: intmd_flatten, dynamic_expand, dynamic_reshape, dynamic_squeeze, intmd_expand, dynamic_transpose, dynamic_flatten, intmd_reshape, intmd_squeeze, INVALID, intmd_unsqueeze, dynamic_movedim, intmd_transpose, dynamic_unsqueeze, intmd_movedim

• Type: MultiEnumSelection
• Required: No
• Default: (INVALID)

tensor_name Key of named_buffers to extract the tensor from.

• Type: string
• Required: Yes

torch_script Name of the torch script file.

• Type: string
• Required: Yes

Detailed documentation link