diff --git a/python/paddle/fluid/tests/unittests/test_fusion_gru_op.py b/python/paddle/fluid/tests/unittests/test_fusion_gru_op.py new file mode 100644 index 0000000000000000000000000000000000000000..764f83b534c8a183dbf21511f0b05741c13c9528 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_fusion_gru_op.py @@ -0,0 +1,133 @@ +# Copyright (c) 2018 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 +import numpy as np +import math +from op_test import OpTest +from test_gru_op import gru +from test_fusion_lstm_op import fc, ACTIVATION + + +def fusion_gru( + x, # T x M + lod, # 1 x N + h0, # N x D + wx, # M x 3D + wh, # D x 3D + bias, # 1 x 3D + is_reverse, + act_state, + act_gate): + return gru(fc(x, wx, bias), + lod, + h0, + wh, + np.zeros( + (1, wh.shape[1]), dtype='float64'), + is_reverse, + act_state, + act_gate) + + +class TestFusionGRUOp(OpTest): + def set_confs(self): + pass + + def setUp(self): + self.op_type = "fusion_gru" + self.lod = [[2, 4, 3]] + self.M = 3 + self.D = 5 + self.is_reverse = False + self.with_h0 = True + self.with_bias = True + self.act_state = 'tanh' + self.act_gate = 'sigmoid' + self.set_confs() + + T = sum(self.lod[0]) + N = len(self.lod[0]) + + x = np.random.rand(T, self.M).astype('float64') + wx = np.random.rand(self.M, 3 * self.D).astype('float64') + wh = np.random.rand(self.D, 3 * self.D).astype('float64') + bias = np.random.rand( + 1, 3 * self.D).astype('float64') if self.with_bias else np.zeros( + (1, 3 * self.D), dtype='float64') + h0 = np.random.rand( + N, self.D).astype('float64') if self.with_h0 else np.zeros( + (N, self.D), dtype='float64') + + _, _, _, hidden = fusion_gru( + x, self.lod, h0, wx, wh, bias, self.is_reverse, + ACTIVATION[self.act_state], ACTIVATION[self.act_gate]) + + self.inputs = {'X': (x, self.lod), 'WeightX': wx, 'WeightH': wh} + + if self.with_bias: + self.inputs['Bias'] = bias + + if self.with_h0: + self.inputs['H0'] = h0 + + self.outputs = {'Hidden': (hidden, self.lod)} + + self.attrs = { + 'activation': self.act_state, + 'gate_activation': self.act_gate, + 'is_reverse': self.is_reverse + } + + def test_check_output(self): + self.check_output(atol=1e-8) + + +class TestFusionGRUOpNoInitial(TestFusionGRUOp): + def set_confs(self): + self.with_h0 = False + + +class TestFusionGRUOpNoBias(TestFusionGRUOp): + def set_confs(self): + self.with_bias = False + + +class TestFusionGRUOpReverse(TestFusionGRUOp): + def set_confs(self): + self.is_reverse = True + + +class TestFusionGRUOpMD1(TestFusionGRUOp): + def set_confs(self): + self.M = 36 + self.D = 8 + + +class TestFusionGRUOpMD2(TestFusionGRUOp): + def set_confs(self): + self.M = 8 + self.D = 8 + + +class TestFusionGRUOpBS1(TestFusionGRUOp): + def set_confs(self): + self.lod = [[3]] + self.D = 16 + + +if __name__ == "__main__": + unittest.main()