/* Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

    http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License. */

#include "paddle/phi/kernels/dequantize_abs_max_kernel.h"

#include "paddle/common/hostdevice.h"
#include "paddle/phi/backends/gpu/gpu_context.h"
#include "paddle/phi/backends/gpu/gpu_primitives.h"
#include "paddle/phi/core/kernel_registry.h"
#include "paddle/phi/kernels/funcs/math.h"

namespace phi {

template <typename T>
__global__ void KeDequantize(
    const T* in, const float* scale, float max_range, int num, float* out) {
  const int idx = threadIdx.x + blockIdx.x * blockDim.x;
  if (idx < num) {
    out[idx] = in[idx] * scale[0] / max_range;
  }
}

template <typename T, typename Context>
void DequantizeAbsMaxKernel(const Context& dev_ctx,
                            const DenseTensor& x,
                            const DenseTensor& scale,
                            float max_range,
                            DenseTensor* out) {
  const T* in_data = x.data<T>();
  const float* scale_factor = scale.data<float>();
  float* out_data = dev_ctx.template Alloc<float>(out);

  int64_t num = x.numel();

  // big tensor currently not supported
  PADDLE_ENFORCE_LE(num,
                    (1LL << 31) - 1,
                    ::common::errors::PreconditionNotMet(
                        "x's numel too large, allowed size is 2 ^ 31 - 1 "
                        "elements, but got %lld",
                        num));
  int block = 512;
  int grid = (num + block - 1) / block;

  KeDequantize<T><<<grid, block, 0, dev_ctx.stream()>>>(
      in_data, scale_factor, max_range, num, out_data);
}

}  // namespace phi

PD_REGISTER_KERNEL(dequantize_abs_max,
                   GPU,
                   ALL_LAYOUT,
                   phi::DequantizeAbsMaxKernel,
                   int8_t,
                   int16_t) {}