EVOLUTION-MANAGER

Edit File: scatter_functor_gpu.cu.h

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
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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,
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See the License for the specific language governing permissions and
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==============================================================================*/

#ifndef TENSORFLOW_CORE_KERNELS_SCATTER_FUNCTOR_GPU_CU_H_
#define TENSORFLOW_CORE_KERNELS_SCATTER_FUNCTOR_GPU_CU_H_

#if GOOGLE_CUDA || TENSORFLOW_USE_ROCM

#define EIGEN_USE_GPU

#include "tensorflow/core/framework/tensor_types.h"
#include "tensorflow/core/kernels/scatter_functor.h"
#include "tensorflow/core/platform/types.h"
#include "tensorflow/core/util/gpu_kernel_helper.h"

namespace tensorflow {

typedef Eigen::GpuDevice GPUDevice;

namespace scatter_op_gpu {

template <typename T, scatter_op::UpdateOp op>
struct ScatterOpKernelBody;

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::ASSIGN> {
  __device__ void operator()(T* __restrict__ dest, T src) const { *dest = src; }
};

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::ADD> {
  __device__ void operator()(T* __restrict__ dest, T src) const {
    GpuAtomicAdd(dest, src);
  }
};

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::SUB> {
  __device__ void operator()(T* __restrict__ dest, T src) const {
    GpuAtomicSub(dest, src);
  }
};

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::MUL> {
  __device__ void operator()(T* __restrict__ dest, T src) const {
    GpuAtomicMul(dest, src);
  }
};

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::DIV> {
  __device__ void operator()(T* __restrict__ dest, T src) const {
    GpuAtomicDiv(dest, src);
  }
};

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::MIN> {
  __device__ void operator()(T* __restrict__ dest, T src) const {
    GpuAtomicMin(dest, src);
  }
};

template <typename T>
struct ScatterOpKernelBody<T, scatter_op::UpdateOp::MAX> {
  __device__ void operator()(T* __restrict__ dest, T src) const {
    GpuAtomicMax(dest, src);
  }
};

template <typename T, typename Index, scatter_op::UpdateOp op>
__global__ void ScatterOpCustomKernel(T* __restrict__ params,
                                      const T* __restrict__ updates,
                                      const Index* __restrict__ indices,
                                      Index first_dim_size, Index updates_size,
                                      Index indices_size) {
  Index update_block = updates_size / indices_size;
  ScatterOpKernelBody<T, op> body;
  GPU_1D_KERNEL_LOOP(i, updates_size) {
    int indices_i = i / update_block;
    int updates_i = i;
    int param_first_index = indices[indices_i];
    if (!(param_first_index >= 0 && param_first_index < first_dim_size)) {
      // Ignore indices that are out of range.
      continue;
    }
    int params_i = param_first_index * update_block + (i % update_block);
    body(&params[params_i], ldg(updates + updates_i));
  }
}

template <typename T, typename Index, scatter_op::UpdateOp op>
__global__ void ScatterScalarOpCustomKernel(T* __restrict__ params,
                                            const T* __restrict__ update,
                                            const Index* __restrict__ indices,
                                            Index first_dim_size,
                                            Index indices_size,
                                            Index synthesized_updates_size) {
  Index update_block = synthesized_updates_size / indices_size;
  ScatterOpKernelBody<T, op> body;
  GPU_1D_KERNEL_LOOP(i, synthesized_updates_size) {
    int indices_i = i / update_block;
    int param_first_index = indices[indices_i];
    const T update_val = *update;
    if (!(param_first_index >= 0 && param_first_index < first_dim_size)) {
      // Ignore indices that are out of range.
      continue;
    }
    int params_i = param_first_index * update_block + (i % update_block);
    body(&params[params_i], update_val);
  }
}

}  // namespace scatter_op_gpu

namespace functor {
// Specialization for a GPU device.
template <typename T, typename Index, scatter_op::UpdateOp op>
struct ScatterFunctor<GPUDevice, T, Index, op> {
  Index operator()(OpKernelContext* c, const GPUDevice& d,
                   typename TTypes<T>::Matrix params,
                   typename TTypes<T>::ConstMatrix updates,
                   typename TTypes<Index>::ConstFlat indices) {
    // TODO(b/31801742): Implement indices range check. The hardest part is
    // with returning a value after the range check, as we do not want to do
    // device to host memcpy during a stream.
    const Index first_dim_size = params.dimension(0);
    const Index indices_size = indices.size();
    const Index updates_size = updates.size();
    GpuLaunchConfig config = GetGpuLaunchConfig(updates_size, d);
    TF_CHECK_OK(GpuLaunchKernel(
        scatter_op_gpu::ScatterOpCustomKernel<T, Index, op>, config.block_count,
        config.thread_per_block, 0, d.stream(), params.data(), updates.data(),
        indices.data(), first_dim_size, updates_size, indices_size));
    return -1;
  }
};

template <typename T, typename Index, scatter_op::UpdateOp op>
struct ScatterScalarFunctor<GPUDevice, T, Index, op> {
  Index operator()(OpKernelContext* c, const GPUDevice& d,
                   typename TTypes<T>::Matrix params,
                   const typename TTypes<T>::ConstScalar update,
                   typename TTypes<Index>::ConstFlat indices) {
    // TODO(b/31801742): Implement indices range check. The hardest part is
    // with returning a value after the range check, as we do not want to do
    // device to host memcpy during a stream.
    const Index first_dim_size = params.dimension(0);
    const Index indices_size = indices.size();
    const Index synthesized_updates_size = indices_size * params.dimension(1);
    GpuLaunchConfig config = GetGpuLaunchConfig(synthesized_updates_size, d);
    TF_CHECK_OK(GpuLaunchKernel(
        scatter_op_gpu::ScatterScalarOpCustomKernel<T, Index, op>,
        config.block_count, config.thread_per_block, 0, d.stream(),
        params.data(), update.data(), indices.data(), first_dim_size,
        indices_size, synthesized_updates_size));
    return -1;
  }
};

}  // namespace functor
}  // namespace tensorflow

#endif  // GOOGLE_CUDA || TENSORFLOW_USE_ROCM

#endif  // TENSORFLOW_CORE_KERNELS_SCATTER_FUNCTOR_GPU_CU_H_