/*************************************************************************
 * Copyright (c) 2022-2025, NVIDIA CORPORATION & AFFILIATES. All rights reserved.
 *
 * See LICENSE for license information.
 ************************************************************************/

#include "common.h"

#include "transformer_engine/transformer_engine.h"

transformer_engine::DType getTransformerEngineFP8Type(bool e4m3_if_hybrid,
                                                      const std::string& fp8_recipe) {
  // if e4m3 or hybrid + forward
  if ((fp8_recipe == "E4M3") || ((fp8_recipe == "HYBRID") && e4m3_if_hybrid)) {
    return transformer_engine::DType::kFloat8E4M3;
  }
  return transformer_engine::DType::kFloat8E5M2;
}

transformer_engine::TensorWrapper makeTransformerEngineTensor(
    void* data_ptr, const NVTEShape& shape, const transformer_engine::DType type) {
  return transformer_engine::TensorWrapper(data_ptr, shape, type);
}

transformer_engine::TensorWrapper makeTransformerEngineTensor(
    void* data_ptr, const std::vector<size_t>& shape, const transformer_engine::DType type) {
  return transformer_engine::TensorWrapper(data_ptr, shape, type);
}

transformer_engine::TensorWrapper makeTransformerEngineTensor(at::Tensor tensor) {
  transformer_engine::DType dtype = GetTransformerEngineDType(tensor.scalar_type());
  std::vector<size_t> shape;

  for (auto s : tensor.sizes()) {
    shape.push_back(s);
  }
  return makeTransformerEngineTensor(tensor.data_ptr(), shape, dtype);
}

transformer_engine::TensorWrapper makeTransformerEngineTensor(void* data_ptr,
                                                              const std::vector<size_t>& shape,
                                                              const transformer_engine::DType type,
                                                              void* amax_ptr, void* scale_ptr,
                                                              void* scale_inv_ptr) {
  return transformer_engine::TensorWrapper(
      data_ptr, shape, type, reinterpret_cast<float*>(amax_ptr),
      reinterpret_cast<float*>(scale_ptr), reinterpret_cast<float*>(scale_inv_ptr));
}

transformer_engine::TensorWrapper makeTransformerEngineTensor(at::Tensor tensor, at::Tensor amax,
                                                              const at::Tensor scale,
                                                              at::Tensor scale_inv) {
  transformer_engine::DType dtype = GetTransformerEngineDType(tensor.scalar_type());
  std::vector<size_t> shape;

  for (auto s : tensor.sizes()) {
    shape.push_back(s);
  }
  NVTE_CHECK(amax.scalar_type() == at::kFloat);
  NVTE_CHECK(scale.scalar_type() == at::kFloat);
  NVTE_CHECK(scale_inv.scalar_type() == at::kFloat);

  return makeTransformerEngineTensor(tensor.data_ptr(), shape, dtype, amax.data_ptr(),
                                     scale.data_ptr(), scale_inv.data_ptr());
}

size_t product(const std::vector<size_t>& shape) {
  size_t ret = 1;
  for (auto s : shape) {
    ret *= s;
  }
  return ret;
}

at::Tensor allocateSpace(const std::vector<size_t>& shape, const transformer_engine::DType type,
                         bool init_to_zeros) {
  std::vector<int64_t> shape_int64(shape.begin(), shape.end());
  c10::IntArrayRef ar_shape(shape_int64);
  if (init_to_zeros) {
    return at::zeros(ar_shape, at::CUDA(GetATenDType(type)));
  } else {
    return at::empty(ar_shape, at::CUDA(GetATenDType(type)));
  }
}

at::Tensor allocateSpace(const NVTEShape& shape, const transformer_engine::DType type,
                         bool init_to_zeros) {
  auto size = shape.ndim;
  if (size == 2 && init_to_zeros) {
    return at::zeros({static_cast<int64_t>(shape.data[0]), static_cast<int64_t>(shape.data[1])},
                     at::CUDA(GetATenDType(type)));
  } else if (size == 2) {
    return at::empty({static_cast<int64_t>(shape.data[0]), static_cast<int64_t>(shape.data[1])},
                     at::CUDA(GetATenDType(type)));
  } else if (size == 1 && init_to_zeros) {
    return at::zeros({static_cast<int64_t>(shape.data[0])}, at::CUDA(GetATenDType(type)));
  } else if (size == 1) {
    return at::empty({static_cast<int64_t>(shape.data[0])}, at::CUDA(GetATenDType(type)));
  }
  NVTE_CHECK(false, "Should never reach here! func: allocateSpace");
}

at::Tensor allocateTorchTensor(int M, int N, transformer_engine::DType dtype) {
  return at::empty({static_cast<int64_t>(M), static_cast<int64_t>(N)},
                   at::CUDA(GetATenDType(dtype)));
}

at::Tensor allocateTorchTensor(int M, transformer_engine::DType dtype) {
  return at::empty({static_cast<int64_t>(M)}, at::CUDA(GetATenDType(dtype)));
}

void* getDataPtr(at::Tensor tensor, int offset) {
  void* dptr = nullptr;
  if (tensor.numel() > 0) {
    dptr = tensor.data_ptr();
  }
  if (dptr != nullptr && offset != 0) {
    char* char_ptr = reinterpret_cast<char*>(dptr);
    char_ptr += offset * tensor.element_size();
    dptr = reinterpret_cast<void*>(char_ptr);
  }
  return dptr;
}
