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112 lines
4.0 KiB
112 lines
4.0 KiB
# Copyright (c) 2020 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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import numpy
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import paddle.fluid as fluid
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import paddle.fluid.layers as layers
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import paddle.fluid.core as core
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from paddle.fluid.contrib.layers import basic_gru, basic_lstm
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from paddle.fluid.executor import Executor
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from paddle.fluid import framework
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from test_imperative_base import new_program_scope
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import numpy as np
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class TestBasicGRUApiName(unittest.TestCase):
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def setUp(self):
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self.name_set = set([
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"test1_fw_w_0_gate", "test1_fw_w_0_candidate", "test1_fw_b_0_gate",
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"test1_fw_b_0_candidate", "test1_bw_w_0_gate",
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"test1_bw_w_0_candidate", "test1_bw_b_0_gate",
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"test1_bw_b_0_candidate"
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])
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def test_name(self):
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batch_size = 20
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input_size = 128
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hidden_size = 256
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num_layers = 1
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dropout = 0.5
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bidirectional = True
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batch_first = False
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with new_program_scope():
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input = layers.data(
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name="input",
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shape=[-1, batch_size, input_size],
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dtype='float32')
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pre_hidden = layers.data(
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name="pre_hidden", shape=[-1, hidden_size], dtype='float32')
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sequence_length = layers.data(
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name="sequence_length", shape=[-1], dtype='int32')
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rnn_out, last_hidden = basic_gru( input, pre_hidden, hidden_size, num_layers = num_layers, \
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sequence_length = sequence_length, dropout_prob=dropout, bidirectional = bidirectional, \
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batch_first = batch_first, param_attr=fluid.ParamAttr( name ="test1"), bias_attr=fluid.ParamAttr( name="test1"), name="basic_gru")
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var_list = fluid.io.get_program_parameter(
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fluid.default_main_program())
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for var in var_list:
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self.assertTrue(var.name in self.name_set)
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class TestBasicLSTMApiName(unittest.TestCase):
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def setUp(self):
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self.name_set = set([
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"test1_fw_w_0", "test1_fw_b_0", "test1_fw_w_1", "test1_fw_b_1",
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"test1_bw_w_0", "test1_bw_b_0", "test1_bw_w_1", "test1_bw_b_1"
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])
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def test_name(self):
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batch_size = 20
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input_size = 128
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hidden_size = 256
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num_layers = 2
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dropout = 0.5
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bidirectional = True
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batch_first = False
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with new_program_scope():
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input = layers.data(
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name="input",
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shape=[-1, batch_size, input_size],
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dtype='float32')
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pre_hidden = layers.data(
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name="pre_hidden", shape=[-1, hidden_size], dtype='float32')
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pre_cell = layers.data(
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name="pre_cell", shape=[-1, hidden_size], dtype='float32')
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sequence_length = layers.data(
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name="sequence_length", shape=[-1], dtype='int32')
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rnn_out, last_hidden, last_cell = basic_lstm( input, pre_hidden, pre_cell, \
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hidden_size, num_layers = num_layers, \
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sequence_length = sequence_length, dropout_prob=dropout, bidirectional = bidirectional, \
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param_attr=fluid.ParamAttr( name ="test1"), bias_attr=fluid.ParamAttr( name = "test1"), \
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batch_first = batch_first)
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var_list = fluid.io.get_program_parameter(
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fluid.default_main_program())
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for var in var_list:
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self.assertTrue(var.name in self.name_set)
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if __name__ == '__main__':
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unittest.main()
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