phivenv/Lib/site-packages/torch/include/ATen/miopen/Descriptors.h

#pragma once

#include <ATen/miopen/Exceptions.h>

#include <ATen/miopen/miopen-wrapper.h>
#include <ATen/core/Tensor.h>
#include <ATen/TensorUtils.h>
#include <c10/macros/Export.h>

namespace at { namespace native {

inline int dataSize(miopenDataType_t dataType)
{
  switch (dataType) {
    case miopenHalf: return 2;
    case miopenFloat: return 4;
    case miopenBFloat16: return 2;
    default: return 8;
  }
}

template <typename T, miopenStatus_t (*dtor)(T*)>
struct DescriptorDeleter {
  void operator()(T* x) {
    if (x != nullptr) {
      MIOPEN_CHECK(dtor(x));
    }
  }
};

// A generic class for wrapping MIOpen descriptor types.  All you need
// is to give the underlying type the Descriptor_t points to (usually,
// if it's miopenTensorDescriptor_t it points to miopenTensorStruct),
// the constructor and the destructor.  Subclasses are responsible
// for defining a set() function to actually set the descriptor.
//
// Descriptors default construct to a nullptr, and have a descriptor
// initialized the first time you call set() or any other initializing
// function.
template <typename T, miopenStatus_t (*ctor)(T**), miopenStatus_t (*dtor)(T*)>
// NOLINTNEXTLINE(bugprone-exception-escape)
class TORCH_CUDA_CPP_API Descriptor {
 public:
  // Use desc() to access the underlying descriptor pointer in
  // a read-only fashion.  Most client code should use this.
  // If the descriptor was never initialized, this will return
  // nullptr.
  T* desc() const { return desc_.get(); }
  T* desc() { return desc_.get(); }

  // Use mut_desc() to access the underlying descriptor pointer
  // if you intend to modify what it points to (e.g., using
  // miopenSetFooDescriptor).  This will ensure that the descriptor
  // is initialized.  Code in this file will use this function.
  T* mut_desc() { init(); return desc_.get(); }
protected:
  void init() {
    if (desc_ == nullptr) {
      T* raw_desc = nullptr;
      MIOPEN_CHECK(ctor(&raw_desc));
      desc_.reset(raw_desc);
    }
  }
private:
  std::unique_ptr<T, DescriptorDeleter<T, dtor>> desc_;
};

class TORCH_CUDA_CPP_API TensorDescriptor : public Descriptor<
                                               miopenTensorDescriptor,
                                               &miopenCreateTensorDescriptor,
                                               &miopenDestroyTensorDescriptor> {
 public:
  TensorDescriptor() = default;
  explicit TensorDescriptor(const at::Tensor &t, size_t pad = 0) {
    set(t, pad);
  }

  void set(const at::Tensor &t, size_t pad = 0);
  void set(miopenDataType_t dataType, IntArrayRef sizes, IntArrayRef strides, size_t pad = 0);

  void print();

private:
  void set(miopenDataType_t dataType, int dim, int* size, int* stride) {
    MIOPEN_CHECK(miopenSetTensorDescriptor(mut_desc(), dataType, dim, size, stride));
  }
};

std::ostream& operator<<(std::ostream & out, const TensorDescriptor& d);

class TORCH_CUDA_CPP_API FilterDescriptor : public Descriptor<
                                               miopenTensorDescriptor,
                                               &miopenCreateTensorDescriptor,
                                               &miopenDestroyTensorDescriptor> {
 public:
  void set(const at::Tensor &t, int64_t pad = 0) {
    set(t, at::MemoryFormat::Contiguous, pad);
  }

  void set(const at::Tensor &t, const at::MemoryFormat memory_format, int64_t pad = 0);

private:
  void set(miopenDataType_t dataType, int dim, int* size, int* stride) {
    MIOPEN_CHECK(miopenSetTensorDescriptor(mut_desc(), dataType, dim, size, stride));
  }
};

struct TORCH_CUDA_CPP_API ConvolutionDescriptor
    : public Descriptor<
          miopenConvolutionDescriptor,
          &miopenCreateConvolutionDescriptor,
          &miopenDestroyConvolutionDescriptor> {
  void set(miopenDataType_t dataType, miopenConvolutionMode_t c_mode,  int dim, int* pad, int* stride, int * upscale /* aka dilation */, int groups, bool benchmark, bool deterministic) {
    MIOPEN_CHECK(miopenInitConvolutionNdDescriptor(mut_desc(), dim, pad, stride, upscale, c_mode));
    MIOPEN_CHECK(miopenSetConvolutionGroupCount(mut_desc(), groups));
    MIOPEN_CHECK(miopenSetConvolutionAttribute(mut_desc(), MIOPEN_CONVOLUTION_ATTRIB_DETERMINISTIC, deterministic ? 1 : 0));
    if (benchmark) {
      MIOPEN_CHECK(miopenSetConvolutionFindMode(mut_desc(), miopenConvolutionFindModeNormal));
    }
  }
};

// NOLINTNEXTLINE(bugprone-exception-escape)
struct TORCH_CUDA_CPP_API DropoutDescriptor
    : public Descriptor<
          miopenDropoutDescriptor,
          &miopenCreateDropoutDescriptor,
          &miopenDestroyDropoutDescriptor> {
    void set(miopenHandle_t handle, float dropout, void* states, size_t stateSizeInBytes,
             unsigned long long seed, bool use_mask, bool state_evo, miopenRNGType_t rng_mode) {
      MIOPEN_CHECK(miopenSetDropoutDescriptor(mut_desc(), handle, dropout, states, stateSizeInBytes, seed, use_mask, state_evo, rng_mode));
    }

    void restore(miopenHandle_t handle, float dropout, void* states, size_t stateSizeInBytes,
      unsigned long long seed, bool use_mask, bool state_evo, miopenRNGType_t rng_mode) {
      MIOPEN_CHECK(miopenRestoreDropoutDescriptor(mut_desc(), handle, dropout, states, stateSizeInBytes, seed, use_mask, state_evo, rng_mode));
    }
};

struct TORCH_CUDA_CPP_API RNNDescriptor
  : public Descriptor<miopenRNNDescriptor,
                      &miopenCreateRNNDescriptor,
                      &miopenDestroyRNNDescriptor>
{
    void set(int64_t hidden_size, int64_t num_layers, miopenRNNInputMode_t input_mode, miopenRNNDirectionMode_t direction, miopenRNNMode_t rnn_mode,
             miopenRNNBiasMode_t bias_mode, miopenRNNAlgo_t algorithm, miopenDataType_t datatype) {
      MIOPEN_CHECK(miopenSetRNNDescriptor(mut_desc(), hidden_size, num_layers, input_mode, direction, rnn_mode, bias_mode, algorithm, datatype));
    }

    void setWithDropout(DropoutDescriptor& dropout_desc, int64_t hidden_size, int64_t num_layers, miopenRNNInputMode_t input_mode, miopenRNNDirectionMode_t direction,
                        miopenRNNMode_t rnn_mode, miopenRNNBiasMode_t bias_mode, miopenRNNAlgo_t algorithm, miopenDataType_t datatype) {
      MIOPEN_CHECK(miopenSetRNNDescriptor_V2(mut_desc(), hidden_size, num_layers, dropout_desc.mut_desc(), input_mode, direction, rnn_mode, bias_mode, algorithm, datatype));
    }
};

union Constant
{
  float f;
  double d;
  Constant(miopenDataType_t dataType, double value) {
    if (dataType == miopenHalf || dataType == miopenFloat || dataType == miopenBFloat16) {
      f = static_cast<float>(value);
    } else {
      d = value;
    }
  }
};

}}  // namespace