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@ -280,7 +280,8 @@ class TestDygraphPtbRnn(unittest.TestCase):
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num_steps=num_steps,
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init_scale=init_scale)
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exe = fluid.Executor(fluid.CPUPlace())
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exe = fluid.Executor(fluid.CPUPlace(
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) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
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sgd = SGDOptimizer(learning_rate=1e-3)
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x = fluid.layers.data(name="x", shape=[-1, 3, 1], dtype='int64')
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y = fluid.layers.data(name="y", shape=[-1, 1], dtype='float32')
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@ -333,20 +334,15 @@ class TestDygraphPtbRnn(unittest.TestCase):
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static_param_updated[static_param_name_list[k -
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3]] = out[k]
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self.assertTrue(np.allclose(static_loss_value, dy_loss._numpy()))
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self.assertTrue(np.allclose(static_last_cell_value, last_cell._numpy()))
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self.assertTrue(np.array_equal(static_loss_value, dy_loss._numpy()))
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self.assertTrue(
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np.allclose(static_last_hidden_value, last_hidden._numpy()))
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np.array_equal(static_last_cell_value, last_cell._numpy()))
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self.assertTrue(
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np.array_equal(static_last_hidden_value, last_hidden._numpy()))
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for key, value in six.iteritems(static_param_init):
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# print("static_init name: {}, value {}".format(key, value))
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# print("dy_init name: {}, value {}".format(key, dy_param_init[key]))
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self.assertTrue(np.allclose(value, dy_param_init[key], atol=1e-5))
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self.assertTrue(np.array_equal(value, dy_param_init[key]))
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for key, value in six.iteritems(static_param_updated):
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# print("static name: {}, value {}".format(key, value))
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# print("dy name: {}, value {}".format(key, dy_param_updated[key]))
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self.assertTrue(
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np.allclose(
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value, dy_param_updated[key], atol=1e-5))
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self.assertTrue(np.array_equal(value, dy_param_updated[key]))
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if __name__ == '__main__':
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