add fusion seq_concat_fc op test

python/paddle/fluid/tests/unittests/test_fusion_seq_concat_fc_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
+from op_test import OpTest
+from test_fusion_lstm_op import fc, ACTIVATION
+
+
+def fusion_seqexpand_concat_fc(xs, lod, w, b, fc_act):
+
+    T = sum(lod[0])
+    N = len(lod[0])
+    num_inputs = len(xs)
+    D = w.shape[1]
+
+    expanded_inputs = [xs[0]]
+    for i in range(num_inputs - 1):
+        x = xs[i + 1]
+        assert x.shape[0] == N
+        expanded = np.repeat(x, lod[0], axis=0)
+        assert expanded.shape[0] == T
+        assert expanded.shape[1] == x.shape[1]
+        expanded_inputs.append(expanded)
+
+    fc_input = np.concatenate(expanded_inputs, axis=1)
+    assert fc_input.shape[0] == T
+    assert fc_input.shape[1] == w.shape[0]
+    fc_out = fc(fc_input, w, b)
+    fc_out = fc_act(fc_out)
+    assert fc_out.shape[0] == T
+    assert fc_out.shape[1] == D
+    return fc_out
+
+
+class TestFusionSeqExpandConcatFCOp(OpTest):
+    def set_conf(self):
+        pass
+
+    def setUp(self):
+        self.op_type = 'fusion_seq_concat_fc'
+        self.lod = [[3, 5, 8, 2]]
+        self.inputs_M = [15, 10, 10]
+        self.D = 20
+        self.with_bias = True
+        self.fc_act = 'relu'
+        self.set_conf()
+
+        T = sum(self.lod[0])
+        bs = len(self.lod[0])
+        num_inputs = len(self.inputs_M)
+
+        x0 = np.random.normal(size=(T, self.inputs_M[0])).astype('float32')
+        xs = [x0]
+        for i in range(num_inputs - 1):
+            xi = np.random.normal(size=(bs,
+                                        self.inputs_M[i + 1])).astype('float32')
+            xs.append(xi)
+
+        # fc weight and bias
+        w = np.random.normal(size=(sum(self.inputs_M),
+                                   self.D)).astype('float32')
+        b = np.random.normal(size=(
+            1, self.D)).astype('float32') if self.with_bias else np.zeros(
+                (1, self.D)).astype('float32')
+
+        out = fusion_seqexpand_concat_fc(xs, self.lod, w, b,
+                                         ACTIVATION[self.fc_act])
+
+        self.inputs = {'X': [(x0, self.lod)], 'FCWeight': w}
+        normal_lod = [i for i in range(bs + 1)]
+        for i in range(num_inputs - 1):
+            self.inputs['X'].append((xs[i + 1], normal_lod))
+
+        if self.with_bias:
+            self.inputs['FCBias'] = b
+
+        self.outputs = {'Out': (out, self.lod)}
+        self.attrs = {'fc_activation': self.fc_act, }
+
+    def test_check_output(self):
+        self.check_output()
+
+
+class TestFusionSECFCOpNonBias(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.with_bias = False
+
+
+class TestFusionSECFCOpNonAct(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.fc_act = 'identity'
+
+
+class TestFusionSECFCOpMD1(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.inputs_M = [3, 4, 2, 1, 5]
+        self.D = 8
+
+
+class TestFusionSECFCOpMD2(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.lod = [[5, 6]]
+        self.inputs_M = [1, 1]
+
+
+class TestFusionSECFCOpBS1_1(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.lod = [[1]]
+        self.inputs_M = [3, 4, 2]
+
+
+class TestFusionSECFCOpBS1_2(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.lod = [[1]]
+        self.inputs_M = [3, 4]
+
+
+class TestFusionSECFCOpBS1_3(TestFusionSeqExpandConcatFCOp):
+    def set_conf(self):
+        self.lod = [[5]]
+        self.inputs_M = [6, 3]
+
+
+if __name__ == '__main__':
+    unittest.main()