Tensor.h

// Copyright 2024, UChicago Argonne, LLC
// All Rights Reserved
// Software Name: NEML2 -- the New Engineering material Model Library, version 2
// By: Argonne National Laboratory
// OPEN SOURCE LICENSE (MIT)
//
// Permission is hereby granted, free of charge, to any person obtaining a copy
// of this software and associated documentation files (the "Software"), to deal
// in the Software without restriction, including without limitation the rights
// to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the Software is
// furnished to do so, subject to the following conditions:
//
// The above copyright notice and this permission notice shall be included in
// all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
// IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
// FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
// AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
// LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
// OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
// THE SOFTWARE.
 
#pragma once
 
#include "neml2/tensors/TensorBase.h"
 
namespace neml2
{
class Tensor;
 
namespace utils
{
TraceableTensorShape broadcast_batch_sizes(const std::vector<Tensor> & tensors);
 
torch::Dtype same_dtype(const std::vector<Tensor> & tensors);
 
torch::Device same_device(const std::vector<Tensor> & tensors);
} // namespace utils
 
class Tensor : public TensorBase<Tensor>
{
public:
  Tensor() = default;
 
  Tensor(const torch::Tensor & tensor, Size batch_dim);
 
  Tensor(const torch::Tensor & tensor, const TraceableTensorShape & batch_shape);
 
  template <class Derived2>
  Tensor(const TensorBase<Derived2> & tensor)
    : TensorBase<Tensor>(tensor)
  {
  }
 
  [[nodiscard]] static Tensor
  empty(TensorShapeRef base_shape, const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor
  empty(const TraceableTensorShape & batch_shape,
        TensorShapeRef base_shape,
        const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor
  zeros(TensorShapeRef base_shape, const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor
  zeros(const TraceableTensorShape & batch_shape,
        TensorShapeRef base_shape,
        const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor ones(TensorShapeRef base_shape,
                                   const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor ones(const TraceableTensorShape & batch_shape,
                                   TensorShapeRef base_shape,
                                   const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor full(TensorShapeRef base_shape,
                                   Real init,
                                   const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor full(const TraceableTensorShape & batch_shape,
                                   TensorShapeRef base_shape,
                                   Real init,
                                   const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor
  identity(Size n, const torch::TensorOptions & options = default_tensor_options());
  [[nodiscard]] static Tensor
  identity(const TraceableTensorShape & batch_shape,
           Size n,
           const torch::TensorOptions & options = default_tensor_options());
};
 
namespace math
{
Tensor bmm(const Tensor & a, const Tensor & b);
 
Tensor bmv(const Tensor & a, const Tensor & v);
 
Tensor bvv(const Tensor & a, const Tensor & b);
}
 
Tensor operator*(const Tensor & a, const Tensor & b);
}