Merge pull request #4837 from QiJune/pybind_feed_fetch_method
export feed/fetch variable method to Pythonrevert-4814-Add_sequence_project_op
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/* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve.
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Licensed under the Apache License, Version 2.0 (the "License");
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you may not use this file except in compliance with the License.
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You may obtain a copy of the License at
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http://www.apache.org/licenses/LICENSE-2.0
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Unless required by applicable law or agreed to in writing, software
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distributed under the License is distributed on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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See the License for the specific language governing permissions and
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limitations under the License. */
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#pragma once
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#include "paddle/framework/scope.h"
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#include "paddle/framework/variable.h"
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namespace paddle {
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namespace framework {
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template <typename T>
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void SetFeedVariable(const LoDTensor& input, const std::string& var_name,
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size_t index) {
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// If var_name Variable is not found in GlobalScope, a new variable will
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// be created.
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Variable* g_feed_value = GetGlobalScope().Var(var_name);
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auto& feed_inputs =
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*(g_feed_value->GetMutable<std::vector<paddle::framework::LoDTensor>>());
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if (index >= feed_inputs.size()) {
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feed_inputs.resize(index + 1);
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}
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// shared data with input tensor
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feed_inputs[index].ShareDataWith<T>(input);
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// set lod
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feed_inputs[index].set_lod(input.lod());
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}
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LoDTensor& GetFetchVariable(const std::string& var_name, size_t index) {
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// Since we want to fetch LodTensor from a variable, the variable must
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// be created alreadly.
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Variable* g_fetch_value = GetGlobalScope().FindVar(var_name);
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auto& fetch_outputs =
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*(g_fetch_value->GetMutable<std::vector<paddle::framework::LoDTensor>>());
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PADDLE_ENFORCE_LT(index, fetch_outputs.size());
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return fetch_outputs[index];
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}
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} // namespace framework
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} // namespace paddle
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import paddle.v2.framework.core as core
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import unittest
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import numpy as np
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class TestFeedFetch(unittest.TestCase):
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def test_feed_fetch(self):
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place = core.CPUPlace()
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input_array = np.ones((4, 4, 6)).astype("float32")
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input_array[0, 0, 0] = 3
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input_array[3, 3, 5] = 10
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input_tensor = core.LoDTensor([[0, 2, 4]])
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input_tensor.set(input_array, place)
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core.set_feed_variable_float(input_tensor, "feed", 0)
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output_tensor = core.get_fetch_variable("feed", 0)
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output_lod = output_tensor.lod()
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self.assertEqual(0, output_lod[0][0])
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self.assertEqual(2, output_lod[0][1])
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self.assertEqual(4, output_lod[0][2])
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output_array = np.array(output_tensor)
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self.assertEqual(3, output_array[0, 0, 0])
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self.assertEqual(10, output_array[3, 3, 5])
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if __name__ == "__main__":
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unittest.main()
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