test=develop, ptb_rnn fix op (#16573)

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

@@ -200,8 +200,6 @@ class PtbModel(fluid.dygraph.Layer):
             rnn_out, shape=[-1, self.num_steps, self.hidden_size])
         projection = fluid.layers.matmul(rnn_out, self.softmax_weight)
         projection = fluid.layers.elementwise_add(projection, self.softmax_bias)
-        projection = fluid.layers.reshape(
-            projection, shape=[-1, self.vocab_size])
         projection = fluid.layers.reshape(
             projection, shape=[-1, self.vocab_size])
         loss = fluid.layers.softmax_with_cross_entropy(
@@ -223,6 +221,7 @@ class TestDygraphPtbRnn(unittest.TestCase):
         num_steps = 3
         init_scale = 0.1
         batch_size = 4
+        batch_num = 200
 
         with fluid.dygraph.guard():
             fluid.default_startup_program().random_seed = seed
@@ -242,7 +241,6 @@ class TestDygraphPtbRnn(unittest.TestCase):
             dy_loss = None
             last_hidden = None
             last_cell = None
-            batch_num = 200
 
             for i in range(batch_num):
                 x_data = np.arange(12).reshape(4, 3).astype('int64')
@@ -282,7 +280,8 @@ class TestDygraphPtbRnn(unittest.TestCase):
 
             exe = fluid.Executor(fluid.CPUPlace())
             sgd = SGDOptimizer(learning_rate=1e-3)
-            x = fluid.layers.data(name="x", shape=[-1, 3, 1], dtype='int64')
+            x = fluid.layers.data(
+                name="x", shape=[-1, num_steps, 1], dtype='int64')
             y = fluid.layers.data(name="y", shape=[-1, 1], dtype='float32')
             init_hidden = fluid.layers.data(
                 name="init_hidden", shape=[1], dtype='float32')
@@ -332,7 +331,6 @@ class TestDygraphPtbRnn(unittest.TestCase):
                     for k in range(3, len(out)):
                         static_param_updated[static_param_name_list[k -
                                                                     3]] = out[k]
-
         self.assertTrue(np.allclose(static_loss_value, dy_loss._numpy()))
         self.assertTrue(np.allclose(static_last_cell_value, last_cell._numpy()))
         self.assertTrue(
@@ -340,13 +338,11 @@ class TestDygraphPtbRnn(unittest.TestCase):
         for key, value in six.iteritems(static_param_init):
             # print("static_init name: {}, value {}".format(key, value))
             # print("dy_init name: {}, value {}".format(key, dy_param_init[key]))
-            self.assertTrue(np.allclose(value, dy_param_init[key], atol=1e-5))
+            self.assertTrue(np.allclose(value, dy_param_init[key]))
         for key, value in six.iteritems(static_param_updated):
             # print("static name: {}, value {}".format(key, value))
             # print("dy name: {}, value {}".format(key, dy_param_updated[key]))
-            self.assertTrue(
-                np.allclose(
-                    value, dy_param_updated[key], atol=1e-5))
+            self.assertTrue(np.allclose(value, dy_param_updated[key]))
 
 
 if __name__ == '__main__':