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/*
* Licensed to the Apache Software Foundation (ASF) under one
* or more contributor license agreements. See the NOTICE file
* distributed with this work for additional information
* regarding copyright ownership. The ASF licenses this file
* to you 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.
*/
/*!
* Copyright (c) 2017 by Contributors
* \file quantized_flatten-inl.h
* \brief implementation of quantized flatten operation
*/
#ifndef MXNET_OPERATOR_QUANTIZATION_QUANTIZED_FLATTEN_INL_H_
#define MXNET_OPERATOR_QUANTIZATION_QUANTIZED_FLATTEN_INL_H_
#include <mxnet/operator_util.h>
#include <vector>
#include <limits>
#include "../elemwise_op_common.h"
#include "../mshadow_op.h"
#include "../mxnet_op.h"
#include "./quantization_utils.h"
namespace mxnet {
namespace op {
// keep zero-center
struct quantized_flatten {
template<typename DstDType, typename SrcDType>
MSHADOW_XINLINE static void Map(int i, DstDType *out, float *omin_range,
float *omax_range, const SrcDType *in,
const float *imin_range, const float *imax_range) {
out[i] = in[i];
omin_range[0] = imin_range[0];
omax_range[0] = imax_range[0];
}
};
template<typename xpu>
void QuantizedFlattenCompute(const nnvm::NodeAttrs& attrs,
const OpContext& ctx,
const std::vector<TBlob>& inputs,
const std::vector<OpReqType>& req,
const std::vector<TBlob>& outputs) {
CHECK_EQ(inputs.size(), 3U);
CHECK_EQ(outputs.size(), 3U);
CHECK_EQ(req.size(), 3U);
if (req[0] == kWriteInplace && req[1] == kWriteInplace && req[2] == kWriteInplace) return;
using namespace mshadow;
using namespace mxnet_op;
Stream<xpu> *s = ctx.get_stream<xpu>();
if (inputs[0].type_flag_ == mshadow::kUint8) {
typedef uint8_t SrcDType;
typedef uint8_t DstDType;
Kernel<quantized_flatten, xpu>::Launch(s, outputs[0].Size(),
outputs[0].dptr<DstDType>(), outputs[1].dptr<float>(), outputs[2].dptr<float>(),
inputs[0].dptr<SrcDType>(), inputs[1].dptr<float>(), inputs[2].dptr<float>());
} else if (inputs[0].type_flag_ == mshadow::kInt8) {
typedef int8_t SrcDType;
typedef int8_t DstDType;
Kernel<quantized_flatten, xpu>::Launch(s, outputs[0].Size(),
outputs[0].dptr<DstDType>(), outputs[1].dptr<float>(), outputs[2].dptr<float>(),
inputs[0].dptr<SrcDType>(), inputs[1].dptr<float>(), inputs[2].dptr<float>());
} else {
LOG(FATAL) << "quantized_flatten op only supports int8 and uint8 as input and output type";
}
}
inline bool QuantizedFlattenShape(const nnvm::NodeAttrs& attrs,
mxnet::ShapeVector *in_attrs,
mxnet::ShapeVector *out_attrs) {
CHECK_EQ(in_attrs->size(), 3U);
CHECK_EQ(out_attrs->size(), 3U);
const mxnet::TShape &dshape = (*in_attrs)[0];
if (shape_is_none(dshape)) return false;
uint32_t target_dim = 1;
for (uint32_t i = 1; i < dshape.ndim(); ++i) {
target_dim *= dshape[i];
}
SHAPE_ASSIGN_CHECK(*in_attrs, 1, mxnet::TShape{1});
SHAPE_ASSIGN_CHECK(*in_attrs, 2, mxnet::TShape{1});
SHAPE_ASSIGN_CHECK(*out_attrs, 0, mshadow::Shape2(dshape[0], target_dim));
SHAPE_ASSIGN_CHECK(*out_attrs, 1, mxnet::TShape{1});
SHAPE_ASSIGN_CHECK(*out_attrs, 2, mxnet::TShape{1});
return true;
}
inline bool QuantizedFlattenType(const nnvm::NodeAttrs& attrs,
std::vector<int> *in_attrs,
std::vector<int> *out_attrs) {
CHECK_EQ(in_attrs->size(), 3U);
CHECK_EQ(out_attrs->size(), 3U);
TYPE_ASSIGN_CHECK(*in_attrs, 1, mshadow::kFloat32);
TYPE_ASSIGN_CHECK(*in_attrs, 2, mshadow::kFloat32);
TYPE_ASSIGN_CHECK(*out_attrs, 0, (*in_attrs)[0]);
TYPE_ASSIGN_CHECK(*out_attrs, 1, mshadow::kFloat32);
TYPE_ASSIGN_CHECK(*out_attrs, 2, mshadow::kFloat32);
return (*in_attrs)[0] != -1;
}
} // namespace op
} // namespace mxnet
#endif // MXNET_OPERATOR_QUANTIZATION_QUANTIZED_FLATTEN_INL_H_