提交 4237d333 编写于 作者: M mindspore-ci-bot 提交者: Gitee

!5604 add caffe slice parser

Merge pull request !5604 from yeyunpeng2020/master_caffe_slice
......@@ -50,6 +50,14 @@ int DoSplit(float *in_data, float **out_data, const int *input_shape, int offset
split_which = i % num_split;
split_times = i / num_split;
int split_size = split_sizes[split_which];
// support split size is -1 in the end.
if (split_size == -1) {
int split_dim_i = input_shape[split_dim];
for (int j = 0; j < num_split - 1; ++j) {
split_dim_i -= split_sizes[j];
}
split_size = split_dim_i;
}
float *dst = out_data[split_which] + split_times * in_stride * split_size;
(void)memcpy(dst, src, split_size * in_stride_bytes);
src += split_size * in_stride;
......
......@@ -88,7 +88,7 @@ int Split::InferShape(std::vector<tensor::Tensor *> inputs_, std::vector<tensor:
if (!GetInferFlag()) {
return RET_OK;
}
int split_dim = GetSplitDim();
size_t split_dim = GetSplitDim() == -1 ? input->shape().size() - 1 : GetSplitDim();
std::vector<int> input_shape = input->shape();
std::vector<int> size_split;
for (size_t i = 0; i < GetSizeSplits().size(); ++i) {
......@@ -97,7 +97,15 @@ int Split::InferShape(std::vector<tensor::Tensor *> inputs_, std::vector<tensor:
for (int i = 0; i < number_split; ++i) {
std::vector<int> output_shape;
output_shape.insert(output_shape.begin(), input_shape.begin(), input_shape.end());
auto split_dim_i = size_split.empty() ? input_shape[split_dim] / number_split : size_split[i];
int split_dim_i = input_shape[split_dim];
// support split size is -1 in the end.
if (i == number_split - 1 && size_split[i] == -1) {
for (size_t j = 0; j < size_split.size() - 1; ++j) {
split_dim_i -= size_split[j];
}
} else {
split_dim_i = size_split.empty() ? input_shape[split_dim] / number_split : size_split[i];
}
output_shape[split_dim] = split_dim_i;
outputs_[i]->set_shape(output_shape);
outputs_[i]->set_data_type(input->data_type());
......
......@@ -29,4 +29,6 @@ add_library(caffe_parser_mid OBJECT
${CMAKE_CURRENT_SOURCE_DIR}/caffe_permute_parser.cc
${CMAKE_CURRENT_SOURCE_DIR}/caffe_tile_parser.cc
${CMAKE_CURRENT_SOURCE_DIR}/caffe_tanh_parser.cc
${CMAKE_CURRENT_SOURCE_DIR}/caffe_exp_parser.cc)
${CMAKE_CURRENT_SOURCE_DIR}/caffe_exp_parser.cc
${CMAKE_CURRENT_SOURCE_DIR}/caffe_slice_parser.cc
)
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* 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 "tools/converter/parser/caffe/caffe_slice_parser.h"
#include <memory>
namespace mindspore {
namespace lite {
STATUS CaffeSliceParser::Parse(const caffe::LayerParameter &proto, const caffe::LayerParameter &weight,
schema::CNodeT *op, std::vector<schema::TensorT *> *weightVec) {
MS_LOG(DEBUG) << "parse CaffeSliceParser";
if (op == nullptr) {
MS_LOG(ERROR) << "op is null";
return RET_NULL_PTR;
}
op->primitive = std::make_unique<schema::PrimitiveT>();
if (op->primitive == nullptr) {
MS_LOG(ERROR) << "op->primitive is null";
return RET_NULL_PTR;
}
std::unique_ptr<schema::SplitT> attr = std::make_unique<schema::SplitT>();
if (attr == nullptr) {
MS_LOG(ERROR) << "new op failed";
return RET_NULL_PTR;
}
const caffe::SliceParameter &slice_param = proto.slice_param();
if (!slice_param.slice_point().empty()) {
attr->numberSplit = slice_param.slice_point_size() + 1;
std::vector<int32_t> size_splits;
for (int i = 0; i < slice_param.slice_point_size(); ++i) {
if (i == 0) {
size_splits.push_back(slice_param.slice_point(i));
} else {
size_splits.push_back(slice_param.slice_point(i) - slice_param.slice_point(i - 1));
}
}
size_splits.push_back(-1);
attr->sizeSplits = size_splits;
}
// The axis along which to slice -- may be negative to index from the end (e.g., -1 for the last axis).
if (slice_param.has_axis()) {
attr->splitDim = slice_param.axis();
} else if (slice_param.has_slice_dim()) {
attr->splitDim = slice_param.slice_dim();
}
op->name = proto.name();
op->primitive->value.type = schema::PrimitiveType_Split;
op->primitive->value.value = attr.release();
return RET_OK;
}
CaffeNodeRegistrar g_caffeSliceParser("Slice", new CaffeSliceParser());
} // namespace lite
} // namespace mindspore
/**
* Copyright 2020 Huawei Technologies Co., Ltd
*
* 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.
*/
#ifndef MMINDSPORE_LITE_TOOLS_CONVERTER_PARSER_CAFFE_CAFFE_SLICE_PARSER_H_
#define MINDSPORE_LITE_TOOLS_CONVERTER_PARSER_CAFFE_CAFFE_SLICE_PARSER_H_
#include <vector>
#include "mindspore/lite/tools/converter/parser/caffe/caffe_node_parser.h"
#include "mindspore/lite/tools/converter/parser/caffe/caffe_node_parser_registry.h"
namespace mindspore {
namespace lite {
class CaffeSliceParser : public CaffeNodeParser {
public:
CaffeSliceParser() : CaffeNodeParser("slice") {}
STATUS Parse(const caffe::LayerParameter &proto, const caffe::LayerParameter &weight, schema::CNodeT *op,
std::vector<schema::TensorT *> *weightVec) override;
};
} // namespace lite
} // namespace mindspore
#endif // MINDSPORE_LITE_TOOLS_CONVERTER_PARSER_CAFFE_CAFFE_SLICE_PARSER_H_
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