提交 109b5aed 编写于 作者: M mozga-intel 提交者: tensor-tang

[NGraph] Enable reshape operator test=develop (#17512)

上级 9bb6a421
...@@ -15,6 +15,7 @@ limitations under the License. */ ...@@ -15,6 +15,7 @@ limitations under the License. */
#include <algorithm> #include <algorithm>
#include <functional> #include <functional>
#include <memory> #include <memory>
#include <unordered_set>
#include <vector> #include <vector>
#include "ngraph/ngraph.hpp" #include "ngraph/ngraph.hpp"
...@@ -24,6 +25,8 @@ limitations under the License. */ ...@@ -24,6 +25,8 @@ limitations under the License. */
#include "paddle/fluid/platform/enforce.h" #include "paddle/fluid/platform/enforce.h"
#include "paddle/fluid/platform/ngraph_helper.h" #include "paddle/fluid/platform/ngraph_helper.h"
constexpr int64_t kNoPadding = -1;
namespace paddle { namespace paddle {
namespace operators { namespace operators {
...@@ -31,6 +34,34 @@ bool NgraphBridge::isRegister(const std::string& str) { ...@@ -31,6 +34,34 @@ bool NgraphBridge::isRegister(const std::string& str) {
return ops::NgraphSingleton::Lookup(str); return ops::NgraphSingleton::Lookup(str);
} }
bool NgraphBridge::isSupported(
const std::unique_ptr<framework::OperatorBase>& op) {
static std::unordered_set<std::string> skip_op_list{"reshape", "reshape2",
"lookup_table"};
bool result = true;
auto& op_type = op->Type();
auto op_attrs = paddle::framework::AttrReader(op->Attrs());
if (!isRegister(op_type)) {
if (skip_op_list.count(op_type)) {
if (op_type == "lookup_table") {
if (op_attrs.Get<bool>("is_sparse") ||
(op_attrs.Get<int64_t>("padding_idx") != kNoPadding)) {
result = false;
}
} else if ((op_type == "reshape") || (op_type == "reshape2")) {
if (op->Input("Shape") != paddle::framework::kEmptyVarName) {
result = false;
}
} else {
result = false;
}
}
} else {
result = false;
}
return result;
}
void NgraphBridge::BuildNgNode( void NgraphBridge::BuildNgNode(
const std::shared_ptr<framework::OperatorBase>& op) { const std::shared_ptr<framework::OperatorBase>& op) {
auto& op_type = op->Type(); auto& op_type = op->Type();
......
...@@ -39,6 +39,8 @@ class NgraphBridge { ...@@ -39,6 +39,8 @@ class NgraphBridge {
static bool isRegister(const std::string& str); static bool isRegister(const std::string& str);
static bool isSupported(const std::unique_ptr<framework::OperatorBase>& op);
private: private:
std::shared_ptr< std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>> std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
......
...@@ -134,12 +134,11 @@ static std::vector<std::vector<int>> NgraphOpIntervals( ...@@ -134,12 +134,11 @@ static std::vector<std::vector<int>> NgraphOpIntervals(
int pivot = left; int pivot = left;
while (pivot < right) { while (pivot < right) {
auto op_type = ops->at(pivot)->Type(); auto op_type = ops->at(pivot)->Type();
if (NgraphBridge::isRegister(op_type)) { if (!NgraphBridge::isSupported(ops->at(pivot))) {
++pivot; ++pivot;
} else { } else {
int start = pivot, end = start; int start = pivot, end = start;
while (pivot < right && while (pivot < right && (NgraphBridge::isSupported(ops->at(pivot)))) {
(!NgraphBridge::isRegister(ops->at(pivot)->Type()))) {
++pivot; ++pivot;
++end; ++end;
} }
......
/*Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
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. */
#pragma once
#include <functional>
#include <memory>
#include <string>
#include <unordered_map>
#include <vector>
#include "ngraph/ngraph.hpp"
#include "paddle/fluid/operators/ngraph/ops/op_bridge.h"
#include "paddle/fluid/platform/ngraph_helper.h"
namespace paddle {
namespace operators {
namespace ngraphs {
ngraph::Shape calc_output_shape(const ngraph::Shape& input_shape,
const std::vector<int>& v_shape) {
auto out_shape = v_shape;
for (size_t i = 0; i < v_shape.size(); ++i) {
if (v_shape[i] == 0) {
out_shape[i] = input_shape[i];
}
}
int size_input = ngraph::shape_size(input_shape);
int size_out = 1;
for (auto o : out_shape) {
if (o > 0) size_out *= o;
}
for (auto& o : out_shape) {
if (o == -1) o = size_input / size_out;
}
return ngraph::Shape(out_shape.begin(), out_shape.end());
}
template <bool is_v2>
static void BuildReshapeNode(
const std::shared_ptr<framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
std::shared_ptr<ngraph::Node> input =
platform::GetInputNode(op, "X", ngb_node_map);
auto input_shape = input->get_shape();
// TODO(mozga-intel) The vector of shape is not supported yet, that's
// asDispensable() operator"
std::shared_ptr<ngraph::Node> shape =
platform::GetInputNode(op, "Shape", ngb_node_map);
auto op_attrs = framework::AttrReader(op->Attrs());
std::vector<int> v_shape = op_attrs.Get<std::vector<int>>("shape");
auto out = input;
if (shape != nullptr) {
ngraph::Shape new_shape;
for (auto& it : shape->get_shape()) {
new_shape.push_back(it);
}
out = platform::NgReshaper(input, shape->get_shape());
} else {
auto out_shape = calc_output_shape(input_shape, v_shape);
out = platform::NgReshaper(input, out_shape);
}
if (is_v2) {
platform::SetOutputNode(op, "XShape", input, ngb_node_map);
}
platform::SetOutputNode(op, "Out", out, ngb_node_map);
}
template <bool is_v2>
void BuildReshapeGradNode(
const std::shared_ptr<paddle::framework::OperatorBase>& op,
std::shared_ptr<
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) {
auto dout = paddle::platform::GetInputNode(op, "Out@GRAD", ngb_node_map);
std::shared_ptr<ngraph::Node> input;
if (is_v2) {
input = paddle::platform::GetInputNode(op, "XShape", ngb_node_map);
} else {
input = paddle::platform::GetInputNode(op, "X", ngb_node_map);
}
auto dx = platform::NgReshaper(dout, input->get_shape());
paddle::platform::SetOutputNode(op, "X@GRAD", dx, ngb_node_map);
}
} // namespace ngraphs
} // namespace operators
} // namespace paddle
REGISTER_NG_OP(reshape, BuildReshapeNode<false>);
REGISTER_NG_OP(reshape2, BuildReshapeNode<true>);
REGISTER_NG_OP(reshape_grad, BuildReshapeGradNode<false>);
REGISTER_NG_OP(reshape2_grad, BuildReshapeGradNode<true>);
...@@ -77,9 +77,7 @@ std::shared_ptr<ngraph::Node> GetNode( ...@@ -77,9 +77,7 @@ std::shared_ptr<ngraph::Node> GetNode(
std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>> std::unordered_map<std::string, std::shared_ptr<ngraph::Node>>>
ngb_node_map) { ngb_node_map) {
auto& var_names = var_map.at(name); auto& var_names = var_map.at(name);
PADDLE_ENFORCE_EQ(var_names.size(), 1, if (var_names.size() == 0) return nullptr;
"op %s name %s expects one associated var", op->Type(),
name);
if (ngb_node_map->find(var_names[0]) != ngb_node_map->end()) { if (ngb_node_map->find(var_names[0]) != ngb_node_map->end()) {
return (*ngb_node_map)[var_names[0]]; return (*ngb_node_map)[var_names[0]];
} else { } else {
...@@ -189,6 +187,22 @@ inline void TrimTrailingSingularDims(ngraph::Shape* shape) { ...@@ -189,6 +187,22 @@ inline void TrimTrailingSingularDims(ngraph::Shape* shape) {
} }
} }
} }
ngraph::element::Type GetNgType(paddle::framework::proto::VarType::Type dtype) {
ngraph::element::Type ng_dtype;
if (dtype == paddle::framework::proto::VarType::FP32) {
ng_dtype = ngraph::element::f32;
} else if (dtype == paddle::framework::proto::VarType::FP64) {
ng_dtype = ngraph::element::f64;
} else if (dtype == paddle::framework::proto::VarType::INT64) {
ng_dtype = ngraph::element::i64;
} else if (dtype == paddle::framework::proto::VarType::INT32) {
ng_dtype = ngraph::element::i32;
} else {
PADDLE_THROW("unsupported data type: %s", dtype);
}
return ng_dtype;
}
} // namespace platform } // namespace platform
} // namespace paddle } // namespace paddle
......
# Copyright (c) 2019 PaddlePaddle Authors. All Rights Reserved.
#
# 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.
from __future__ import print_function
import unittest, sys
sys.path.append("../")
from test_reshape_op import TestReshapeOp, TestReshapeOpDimInfer1, TestReshapeOpDimInfer2, TestReshapeOpWithInputShape
if __name__ == '__main__':
unittest.main()
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