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NEML2 2.1.0
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This is the complete list of members for Tensor, including all inherited members.
| __add__(neml2.Tensor self, neml2.Tensor arg0) | Tensor | |
| __add__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __add__(neml2.Tensor self, float arg0) | Tensor | |
| __iadd__(neml2.Tensor self, float arg0) | Tensor | |
| __imul__(neml2.Tensor self, float arg0) | Tensor | |
| __init__(self) | Tensor | |
| __init__(self, torch.Tensor tensor, int dynamic_dim, int intmd_dim) | Tensor | |
| __init__(self, neml2.Vec other) | Tensor | |
| __init__(self, neml2.Rot other) | Tensor | |
| __init__(self, neml2.WR2 other) | Tensor | |
| __init__(self, neml2.R2 other) | Tensor | |
| __init__(self, neml2.SR2 other) | Tensor | |
| __init__(self, neml2.R3 other) | Tensor | |
| __init__(self, neml2.SFR3 other) | Tensor | |
| __init__(self, neml2.R4 other) | Tensor | |
| __init__(self, neml2.SFFR4 other) | Tensor | |
| __init__(self, neml2.WFFR4 other) | Tensor | |
| __init__(self, neml2.SSR4 other) | Tensor | |
| __init__(self, neml2.SWR4 other) | Tensor | |
| __init__(self, neml2.WSR4 other) | Tensor | |
| __init__(self, neml2.WWR4 other) | Tensor | |
| __init__(self, neml2.Quaternion other) | Tensor | |
| __init__(self, neml2.MillerIndex other) | Tensor | |
| __init__(self, neml2.Tensor other) | Tensor | |
| __init__(self, neml2.Scalar other) | Tensor | |
| __init__(self, torch.Tensor tensor, int dynamic_dim, int intmd_dim=0) | Tensor | |
| __isub__(neml2.Tensor self, float arg0) | Tensor | |
| __itruediv__(neml2.Tensor self, float arg0) | Tensor | |
| __mul__(neml2.Tensor self, neml2.Tensor arg0) | Tensor | |
| __mul__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __mul__(neml2.Tensor self, float arg0) | Tensor | |
| __neg__(neml2.Tensor self) | Tensor | |
| __pow__(neml2.Tensor self, float arg0) | Tensor | |
| __pow__(neml2.Tensor self, neml2.Tensor arg0) | Tensor | |
| __radd__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __radd__(neml2.Tensor self, float arg0) | Tensor | |
| __repr__(neml2.Tensor self) | Tensor | |
| __rmul__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __rmul__(neml2.Tensor self, float arg0) | Tensor | |
| __rpow__(neml2.Tensor self, float arg0) | Tensor | |
| __rsub__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __rsub__(neml2.Tensor self, float arg0) | Tensor | |
| __rtruediv__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __rtruediv__(neml2.Tensor self, float arg0) | Tensor | |
| __str__(neml2.Tensor self) | Tensor | |
| __sub__(neml2.Tensor self, neml2.Tensor arg0) | Tensor | |
| __sub__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __sub__(neml2.Tensor self, float arg0) | Tensor | |
| __truediv__(neml2.Tensor self, neml2.Tensor arg0) | Tensor | |
| __truediv__(neml2.Tensor self, neml2.Scalar arg0) | Tensor | |
| __truediv__(neml2.Tensor self, float arg0) | Tensor | |
| base(self) | Tensor | |
| base_linspace(neml2.Tensor start, neml2.Tensor end, int step, int dim=0) | Tensor | static |
| base_logspace(neml2.Tensor start, neml2.Tensor end, int step, int dim=0, Number|torch.SymInt|torch.SymFloat|torch.SymBool base=10.0) | Tensor | static |
| batch(self) | Tensor | |
| clone(neml2.Tensor self) | Tensor | |
| contiguous(neml2.Tensor self) | Tensor | |
| copy_(neml2.Tensor self, torch.Tensor arg0, bool arg1) | Tensor | |
| defined(neml2.Tensor self) | Tensor | |
| detach(neml2.Tensor self) | Tensor | |
| detach_(neml2.Tensor self) | Tensor | |
| device(self) | Tensor | |
| dim(neml2.Tensor self) | Tensor | |
| dtype(self) | Tensor | |
| dynamic(self) | Tensor | |
| dynamic_linspace(neml2.Tensor start, neml2.Tensor end, int step, int dim=0) | Tensor | static |
| dynamic_logspace(neml2.Tensor start, neml2.Tensor end, int step, int dim=0, Number|torch.SymInt|torch.SymFloat|torch.SymBool base=10.0) | Tensor | static |
| empty(tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| empty(tuple[int,...] dynamic_sizes, tuple[int,...] intmd_sizes, tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| empty_like(neml2.Tensor arg0) | Tensor | static |
| full(tuple[int,...] base_sizes, float fill_value, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| full(tuple[int,...] dynamic_sizes, tuple[int,...] intmd_sizes, tuple[int,...] base_sizes, float fill_value, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| full_like(neml2.Tensor other, float fill_value) | Tensor | static |
| grad(self) | Tensor | |
| identity(int n, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| intmd(self) | Tensor | |
| intmd_linspace(neml2.Tensor start, neml2.Tensor end, int step, int dim=0) | Tensor | static |
| intmd_logspace(neml2.Tensor start, neml2.Tensor end, int step, int dim=0, Number|torch.SymInt|torch.SymFloat|torch.SymBool base=10.0) | Tensor | static |
| inv(neml2.Tensor self) | Tensor | |
| item(neml2.Tensor self) | Tensor | |
| norm(neml2.Tensor self) | Tensor | |
| ones(tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| ones(tuple[int,...] dynamic_sizes, tuple[int,...] intmd_sizes, tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| ones_like(neml2.Tensor arg0) | Tensor | static |
| rand(tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| rand(tuple[int,...] dynamic_sizes, tuple[int,...] intmd_sizes, tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| rand_like(neml2.Tensor arg0) | Tensor | static |
| requires_grad(self) | Tensor | |
| requires_grad_(neml2.Tensor self, bool arg0) | Tensor | |
| shape(self) | Tensor | |
| static(self) | Tensor | |
| tensor(neml2.Tensor self) | Tensor | |
| to(neml2.Tensor self, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | |
| torch(neml2.Tensor self) | Tensor | |
| zero_(neml2.Tensor self) | Tensor | |
| zeros(tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| zeros(tuple[int,...] dynamic_sizes, tuple[int,...] intmd_sizes, tuple[int,...] base_sizes, *, torch.dtype dtype=..., torch.device device=..., bool requires_grad=False) | Tensor | static |
| zeros_like(neml2.Tensor arg0) | Tensor | static |