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#include "dequantize_dnnlowp_op.h"
#include "caffe2/core/tensor_int8.h"
#include "caffe2_dnnlowp_utils.h"
namespace caffe2 {
template <typename T>
DequantizeDNNLowPOp<T>::DequantizeDNNLowPOp(
const OperatorDef& operator_def,
Workspace* ws)
: Operator<CPUContext>(operator_def, ws),
qfactory_(dnnlowp::GetQuantizationFactoryOf(this)) {
if (this->debug_def().engine() == "DNNLOWP_16" ||
this->debug_def().engine() == "DNNLOWP_ROWWISE_16") {
LOG(WARNING)
<< this->debug_def().engine()
<< " is an experimental feature mostly for testing accuracy with "
"fixed-point precision higher than 8 and performance is very slow";
}
}
template <typename T>
bool DequantizeDNNLowPOp<T>::RunOnDevice() {
using namespace dnnlowp;
TensorQuantizationParams in_qparams =
GetInputTensorQuantizationParamsOf(this, 0, qfactory_.get());
const TensorCPU& input = InputIsType<int8::Int8TensorCPU>(0)
? this->template Input<int8::Int8TensorCPU>(0).t
: Input(0);
CAFFE_ENFORCE(input.template IsType<T>());
Output(0)->ResizeLike(input);
fbgemm::Dequantize<T>(
input.template data<T>(),
Output(0)->template mutable_data<float>(),
input.numel(),
in_qparams);
return true;
}
OPERATOR_SCHEMA(Dequantize)
.NumInputs(1)
.NumOutputs(1)
.IdenticalTypeAndShapeOfInput(0);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Dequantize,
DNNLOWP,
DequantizeDNNLowPOp<std::uint8_t>);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Dequantize,
DNNLOWP_ROWWISE,
DequantizeDNNLowPOp<std::uint8_t>);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Dequantize,
DNNLOWP_16,
DequantizeDNNLowPOp<std::uint16_t>);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Dequantize,
DNNLOWP_ROWWISE_16,
DequantizeDNNLowPOp<std::uint16_t>);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Int8Dequantize,
DNNLOWP,
DequantizeDNNLowPOp<std::uint8_t>);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Int8Dequantize,
DNNLOWP_ROWWISE,
DequantizeDNNLowPOp<std::uint8_t>);
REGISTER_CPU_OPERATOR_WITH_ENGINE(
Int8DequantizeRowWise,
DNNLOWP,
DequantizeDNNLowPOp<std::uint8_t>);
} // namespace caffe2
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