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138 lines
4.9 KiB
138 lines
4.9 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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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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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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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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from __future__ import print_function
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import unittest
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from paddle.fluid.framework import Program, default_main_program, program_guard, grad_var_name
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import paddle.fluid.layers as layers
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import paddle.fluid as fluid
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main_program = default_main_program()
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class TestProgram(unittest.TestCase):
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def test_program(self):
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b = main_program.current_block()
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self.assertEqual(-1, b.parent_idx)
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self.assertEqual(0, b.idx)
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b = main_program._create_block()
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self.assertEqual(1, b.idx)
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self.assertEqual(0, b.parent_idx)
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b = main_program._create_block()
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self.assertEqual(2, b.idx)
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self.assertEqual(1, b.parent_idx)
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main_program._rollback()
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b = main_program.current_block()
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self.assertEqual(1, b.idx)
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self.assertEqual(0, b.parent_idx)
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b = main_program._create_block()
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self.assertEqual(3, b.idx)
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self.assertEqual(1, b.parent_idx)
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main_program._rollback()
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b = main_program.current_block()
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self.assertEqual(1, b.idx)
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self.assertEqual(0, b.parent_idx)
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def test_program_clone(self):
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prog = Program()
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x = prog.global_block().create_var(
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name='X', shape=[1000, 784], dtype='float32')
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y = prog.global_block().create_var(
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name='Y', shape=[784, 100], dtype='float32')
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out = prog.global_block().create_var(name='Out', dtype='float32')
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prog.global_block().append_op(
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type="mul", inputs={'X': [x],
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'Y': [y]}, outputs={'Out': [out]})
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# FIXME(yuyang18): We manual compare the output string, since the order
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# of variable could be changed.
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print(prog)
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print(prog.clone())
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def test_parse_program_from_string(self):
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prog = Program()
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x = prog.global_block().create_var(
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name='X', shape=[1000, 784], dtype='float32')
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y = prog.global_block().create_var(
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name='Y', shape=[784, 100], dtype='float32')
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out = prog.global_block().create_var(name='Out', dtype='float32')
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prog.global_block().append_op(
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type="mul", inputs={'X': [x],
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'Y': [y]}, outputs={'Out': [out]})
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binary_str = prog.desc.serialize_to_string()
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prog_restored = Program.parse_from_string(binary_str)
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print(prog)
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print(prog_restored)
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def test_program_clone_with_parameter(self):
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main_program = Program()
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startup_program = Program()
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with program_guard(main_program, startup_program):
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d = layers.data(name='x', shape=[784], dtype='float32')
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hidden = layers.fc(input=d, size=100)
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layers.fc(input=hidden, size=100)
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new_program = main_program.clone()
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self.assertNotEqual(0, len(new_program.blocks[0].all_parameters()))
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def test_program_inference_optimize(self):
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def net():
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reader = fluid.layers.py_reader(
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capacity=10,
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shapes=[[-1, 10], [-1, 1]],
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lod_levels=[0, 0],
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dtypes=['float32', 'int64'],
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use_double_buffer=True)
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in_data, label = fluid.layers.read_file(reader)
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predict_label = fluid.layers.fc(in_data, size=2, act='softmax')
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loss = fluid.layers.mean(
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fluid.layers.cross_entropy(
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input=predict_label, label=label))
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optimizer = fluid.optimizer.Adam()
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optimizer.minimize(loss)
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startup_program = fluid.Program()
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main_program = fluid.Program()
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with fluid.program_guard(main_program, startup_program):
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net()
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no_read_program = main_program._inference_optimize()
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keep_read_program = main_program._inference_optimize(
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prune_read_op=False)
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no_read_ops = no_read_program.global_block().ops
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keep_read_ops = keep_read_program.global_block().ops
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self.assertEqual(len(keep_read_ops) - len(no_read_ops), 2)
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self.assertEqual(keep_read_ops[0].type, 'create_double_buffer_reader')
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self.assertEqual(keep_read_ops[1].type, 'read')
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for i in range(len(no_read_ops)):
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self.assertEqual(no_read_ops[i].type, keep_read_ops[i + 2].type)
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if __name__ == '__main__':
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unittest.main()
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