// Original TunableOp is from onnxruntime.
// https://github.com/microsoft/onnxruntime/blob/main/onnxruntime/core/framework/tunable.h
// https://github.com/microsoft/onnxruntime/tree/main/onnxruntime/core/providers/rocm/tunable
// Copyright (c) Microsoft Corporation.
// Licensed under the MIT license.
//
// Adapting TunableOp into PyTorch
// Copyright (c) Advanced Micro Devices, Inc.
//
#pragma once

#include <string>

#include <ATen/cuda/tunable/TunableOp.h>
#include <ATen/cuda/Exceptions.h>
#include <c10/util/StringUtil.h>

#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/Functions.h>
#include <ATen/NativeFunctions.h>
#else
#include <ATen/ops/allclose.h>
#include <ATen/ops/from_blob.h>
#endif

namespace at::cuda::tunable {

enum class BlasOp {
  N = 0,
  T = 1
};

inline std::string BlasOpToString(BlasOp op) {
  switch (op) {
    case BlasOp::N:
      return "N";
    case BlasOp::T:
      return "T";
  }
  TORCH_CHECK(false, "unrecognized BlasOp");
  return "N";
}

namespace detail {

static bool NumericalCheck(ScalarType dtype, void* c, void* other_c, int64_t size) {
  auto options = at::TensorOptions().dtype(dtype).device(at::kCUDA);
  // comparison done as 1D tensor
  at::Tensor ref = at::from_blob(c,       {size}, options);
  at::Tensor oth = at::from_blob(other_c, {size}, options);
  at::Tensor ref_float = ref.to(at::kFloat);
  at::Tensor oth_float = oth.to(at::kFloat);
  std::vector<double> atols{1e-1, 1e-2, 1e-3, 1e-4, 1e-5};
  std::vector<double> rtols{1e-1, 1e-2, 1e-3, 1e-4, 1e-5};
  double last_succeed_atol = 1;
  double last_succeed_rtol = 1;
  for (auto& atol : atols) {
    for (auto& rtol : rtols) {
      if (at::allclose(ref_float, oth_float, rtol, atol)) {
        last_succeed_atol = atol;
        last_succeed_rtol = rtol;
      }
    }
  }
  if (last_succeed_atol == 1) {
    return false;
  }
  else {
    TUNABLE_LOG3("├──verify numerics: atol=", last_succeed_atol, ", rtol=", last_succeed_rtol);
  }

  return true;
}

}

template <typename T>
struct GemmParams : OpParams {
  GemmParams() {
    duplicate_inputs_ = false;
  }

  std::string Signature() const override {
    return c10::str(transa, transb, "_", m, "_", n, "_", k);
  }

  size_t GetSize(bool duplicate_inputs) const {
    size_t size = sizeof(T) * ldc * n;
    if (duplicate_inputs) {
      size += sizeof(T) * lda * ((transa == 'n' || transa == 'N') ? k : m);
      size += sizeof(T) * ldb * ((transb == 'n' || transb == 'N') ? n : k);
    }
    return size;
  }

  GemmParams* DeepCopy(bool duplicate_inputs) const {
    GemmParams* copy = new GemmParams;
    *copy = *this;
    c10::DeviceIndex device = 0;
    AT_CUDA_CHECK(c10::cuda::GetDevice(&device));
    size_t c_size = ldc * n * sizeof(T);
    copy->c = static_cast<T*>(c10::cuda::CUDACachingAllocator::raw_alloc(c_size));
    AT_CUDA_CHECK(c10::cuda::CUDACachingAllocator::memcpyAsync(
        copy->c, device, c, device, c_size, getCurrentCUDAStream(device), true));
    if (duplicate_inputs) {
      size_t a_size = sizeof(T) * lda * ((transa == 'n' || transa == 'N') ? k : m);
      size_t b_size = sizeof(T) * ldb * ((transb == 'n' || transb == 'N') ? n : k);
      copy->a = static_cast<const T*>(c10::cuda::CUDACachingAllocator::raw_alloc(a_size));
      copy->b = static_cast<const T*>(c10::cuda::CUDACachingAllocator::raw_alloc(b_size));
      copy->duplicate_inputs_ = true;
    }
    return copy;
  }

  // only call on object returned by DeepCopy
  void Delete() {
    c10::cuda::CUDACachingAllocator::raw_delete(c);
    if (duplicate_inputs_) {
      c10::cuda::CUDACachingAllocator::raw_delete(const_cast<T*>(a));
      c10::cuda::CUDACachingAllocator::raw_delete(const_cast<T*>(b));
    }
  }

  TuningStatus NumericalCheck(GemmParams<T> *other) {
    auto c_dtype = c10::CppTypeToScalarType<T>::value;
    return detail::NumericalCheck(c_dtype, c, other->c, ldc*n) ? OK : FAIL;
  }

  char transa;
  char transb;
  int64_t m;
  int64_t n;
  int64_t k;
  at::opmath_type<T> alpha;
  const T* a;
  int64_t lda;
  const T* b;
  int64_t ldb;
  at::opmath_type<T> beta;
  T* c;
  int64_t ldc;
private:
  bool duplicate_inputs_;
};

template <typename T>
struct GemmStridedBatchedParams : OpParams {
  GemmStridedBatchedParams() {
    duplicate_inputs_ = false;
  }

  std::string Signature() const override {
    return c10::str(transa, transb, "_", m, "_", n, "_", k, "_B_", batch);
  }

  size_t GetSize(bool duplicate_inputs) const {
    size_t size = sizeof(T) * stride_c * batch;
    if (duplicate_inputs) {
      size += sizeof(T) * stride_a * batch;
      size += sizeof(T) * stride_b * batch;
    }
    return size;
  }

  GemmStridedBatchedParams* DeepCopy(bool duplicate_inputs) const {
    GemmStridedBatchedParams* copy = new GemmStridedBatchedParams;
    *copy = *this;
    c10::DeviceIndex device = 0;
    AT_CUDA_CHECK(c10::cuda::GetDevice(&device));
    size_t c_size = batch * stride_c * sizeof(T);
    copy->c = static_cast<T*>(c10::cuda::CUDACachingAllocator::raw_alloc(c_size));
    AT_CUDA_CHECK(c10::cuda::CUDACachingAllocator::memcpyAsync(
        copy->c, device, c, device, c_size, getCurrentCUDAStream(device), true));
    if (duplicate_inputs) {
      size_t a_size = sizeof(T) * stride_a * batch;
      size_t b_size = sizeof(T) * stride_b * batch;
      copy->a = static_cast<const T*>(c10::cuda::CUDACachingAllocator::raw_alloc(a_size));
      copy->b = static_cast<const T*>(c10::cuda::CUDACachingAllocator::raw_alloc(b_size));
      copy->duplicate_inputs_ = true;
    }
    return copy;
  }

  // only call on object returned by DeepCopy
  void Delete() {
    c10::cuda::CUDACachingAllocator::raw_delete(c);
    if (duplicate_inputs_) {
      c10::cuda::CUDACachingAllocator::raw_delete(const_cast<T*>(a));
      c10::cuda::CUDACachingAllocator::raw_delete(const_cast<T*>(b));
    }
  }

  TuningStatus NumericalCheck(GemmStridedBatchedParams<T> *other) {
    auto c_dtype = c10::CppTypeToScalarType<T>::value;
    return detail::NumericalCheck(c_dtype, c, other->c, batch*stride_c) ? OK : FAIL;
  }

  char transa;
  char transb;
  int64_t m;
  int64_t n;
  int64_t k;
  at::opmath_type<T> alpha;
  const T* a;
  int64_t lda;
  int64_t stride_a;
  const T* b;
  int64_t ldb;
  int64_t stride_b;
  at::opmath_type<T> beta;
  T* c;
  int64_t ldc;
  int64_t stride_c;
  int64_t batch;
private:
  bool duplicate_inputs_;
};

template <typename T>
struct ScaledGemmParams : OpParams {
  ScaledGemmParams() {
    duplicate_inputs_ = false;
  }

  std::string Signature() const override {
    return c10::str(transa, transb, "_", m, "_", n, "_", k);
  }

  size_t GetSize(bool duplicate_inputs) const {
    size_t size = sizeof(T) * ldc * n;
    if (duplicate_inputs) {
      size += sizeof(T) * lda * ((transa == 'n' || transa == 'N') ? k : m);
      size += sizeof(T) * ldb * ((transb == 'n' || transb == 'N') ? n : k);
    }
    return size;
  }

  ScaledGemmParams* DeepCopy(bool duplicate_inputs) const {
    ScaledGemmParams* copy = new ScaledGemmParams;
    *copy = *this;
    c10::DeviceIndex device = 0;
    AT_CUDA_CHECK(c10::cuda::GetDevice(&device));
    size_t c_size = ldc * n * sizeof(T);
    copy->c = c10::cuda::CUDACachingAllocator::raw_alloc(c_size);
    AT_CUDA_CHECK(c10::cuda::CUDACachingAllocator::memcpyAsync(
        copy->c, device, c, device, c_size, getCurrentCUDAStream(device), true));
    if (duplicate_inputs) {
      size_t a_size = sizeof(T) * lda * ((transa == 'n' || transa == 'N') ? k : m);
      size_t b_size = sizeof(T) * ldb * ((transb == 'n' || transb == 'N') ? n : k);
      copy->a = c10::cuda::CUDACachingAllocator::raw_alloc(a_size);
      copy->b = c10::cuda::CUDACachingAllocator::raw_alloc(b_size);
      copy->duplicate_inputs_ = true;
    }
    return copy;
  }

  // only call on object returned by DeepCopy
  void Delete() {
    c10::cuda::CUDACachingAllocator::raw_delete(c);
    if (duplicate_inputs_) {
      c10::cuda::CUDACachingAllocator::raw_delete(const_cast<void*>(a));
      c10::cuda::CUDACachingAllocator::raw_delete(const_cast<void*>(b));
    }
  }

  TuningStatus NumericalCheck(ScaledGemmParams<T> *other) {
    return detail::NumericalCheck(c_dtype, c, other->c, ldc*n) ? OK : FAIL;
  }

  char transa;
  char transb;
  int64_t m;
  int64_t n;
  int64_t k;
  const void* a;
  const void* a_scale_ptr;
  int64_t lda;
  ScalarType a_dtype;
  const void* b;
  const void* b_scale_ptr;
  int64_t ldb;
  ScalarType b_dtype;
  const void* bias_ptr;
  ScalarType bias_dtype;
  void* c;
  const void* c_scale_ptr;
  int64_t ldc;
  ScalarType c_dtype;
  void* amax_ptr;
  bool use_fast_accum;
private:
  bool duplicate_inputs_;
};

} // namespace at::cuda::tunable
