src/operator/quantization/dnnl/dnnl_quantized_act.cc

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 * to you under the Apache License, Version 2.0 (the
 * "License"); you may not use this file except in compliance
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/*!
 * \file dnnl_quantized_act.cc
 * \brief DNNL(Quantized) Activation operator based on subgraph
 * /author Zhiyuan Huang
 */
#if MXNET_USE_ONEDNN == 1

#include "operator/nn/activation-inl.h"
#include "operator/nn/dnnl/dnnl_act-inl.h"
#include "operator/quantization/quantization_utils.h"

namespace mxnet {
namespace op {

static void DNNLQuantizedActForward(const nnvm::NodeAttrs& attrs,
                                    const OpContext& ctx,
                                    const std::vector<NDArray>& in_data,
                                    const std::vector<OpReqType>& req,
                                    const std::vector<NDArray>& out_data) {
  CHECK(in_data[0].dtype() == mshadow::kUint8 || in_data[0].dtype() == mshadow::kInt8)
      << "_contrib_quantized_act op only supports uint8 and int8 as input "
         "type";

  DNNLRun(DNNLActivationForward, attrs, ctx, in_data[0], req[0], out_data[0]);
  out_data[1].data().dptr<float>()[0] = in_data[1].data().dptr<float>()[0];
  out_data[2].data().dptr<float>()[0] = in_data[2].data().dptr<float>()[0];
}

NNVM_REGISTER_OP(_contrib_quantized_act)
    .set_attr<bool>("TIsDNNL", true)
    .set_attr<FComputeEx>("FComputeEx<cpu>", DNNLQuantizedActForward);

}  // namespace op
}  // namespace mxnet

#endif  // MXNET_USE_ONEDNN == 1