add fusion gru op test

python/paddle/fluid/tests/unittests/test_fusion_gru_op.py

+#   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()