Line data    Source code

       1              : // Copyright 2024, UChicago Argonne, LLC
       2              : // All Rights Reserved
       3              : // Software Name: NEML2 -- the New Engineering material Model Library, version 2
       4              : // By: Argonne National Laboratory
       5              : // OPEN SOURCE LICENSE (MIT)
       6              : //
       7              : // Permission is hereby granted, free of charge, to any person obtaining a copy
       8              : // of this software and associated documentation files (the "Software"), to deal
       9              : // in the Software without restriction, including without limitation the rights
      10              : // to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
      11              : // copies of the Software, and to permit persons to whom the Software is
      12              : // furnished to do so, subject to the following conditions:
      13              : //
      14              : // The above copyright notice and this permission notice shall be included in
      15              : // all copies or substantial portions of the Software.
      16              : //
      17              : // THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
      18              : // IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
      19              : // FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
      20              : // AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
      21              : // LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
      22              : // OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
      23              : // THE SOFTWARE.
      24              : 
      25              : #include "neml2/user_tensors/UserPrimitiveTensor.h"
      26              : 
      27              : #include "neml2/tensors/tensors.h"
      28              : #include "neml2/misc/assertions.h"
      29              : 
      30              : namespace neml2
      31              : {
      32              : template <typename T>
      33              : OptionSet
      34           44 : UserPrimitiveTensor<T>::expected_options()
      35              : {
      36              :   // This is the only way of getting tensor type in a static method like this...
      37              :   // Trim 6 chars to remove 'neml2::'
      38           44 :   auto tensor_type = utils::demangle(typeid(T).name()).substr(7);
      39              : 
      40           44 :   OptionSet options = UserTensorBase::expected_options();
      41           44 :   options.doc() =
      42              :       "Construct a " + tensor_type +
      43              :       " from a vector values. The vector will be reshaped according to the specified batch shape.";
      44              : 
      45           88 :   options.set<std::vector<double>>("values");
      46           44 :   options.set("values").doc() = "Values in this (flattened) tensor";
      47              : 
      48          132 :   options.set<TensorShape>("batch_shape") = {};
      49           44 :   options.set("batch_shape").doc() = "Batch shape";
      50              : 
      51           88 :   return options;
      52           44 : }
      53              : 
      54              : template <typename T>
      55          162 : UserPrimitiveTensor<T>::UserPrimitiveTensor(const OptionSet & options)
      56          162 :   : T(T::empty(options.get<TensorShape>("batch_shape"), default_tensor_options())),
      57          324 :     UserTensorBase(options)
      58              : {
      59          162 :   auto vals = options.get<std::vector<double>>("values");
      60          162 :   auto flat = Tensor::create(vals, default_tensor_options());
      61          162 :   if (vals.size() == size_t(this->base_storage()))
      62          198 :     this->index_put_({indexing::Ellipsis}, flat.reshape(this->base_sizes()));
      63           96 :   else if (vals.size() == size_t(utils::storage_size(this->sizes())))
      64          288 :     this->index_put_({indexing::Ellipsis}, flat.reshape(this->sizes()));
      65              :   else
      66            0 :     neml_assert(false,
      67              :                 "Number of values ",
      68            0 :                 vals.size(),
      69              :                 " must equal to either the base storage size ",
      70            0 :                 this->base_storage(),
      71              :                 " or the total storage size ",
      72            0 :                 utils::storage_size(this->sizes()));
      73          324 : }
      74              : 
      75              : #define USERPRIMITIVETENSOR_REGISTER(T)                                                            \
      76              :   using User##T = UserPrimitiveTensor<T>;                                                          \
      77              :   register_NEML2_object_alias(User##T, #T)
      78              : FOR_ALL_PRIMITIVETENSOR(USERPRIMITIVETENSOR_REGISTER);
      79              : } // namespace neml2