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TracedLayer Error Message Enhancement (PaddlePaddle#25734)
Enhance TracedLayer Error Message Note: this PR uses assert to check type somewhere and check_type somewhere, the reason is that the check_type skips checking when it is under dygraph mode.
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python/paddle/fluid/tests/unittests/test_traced_layer_err_msg.py
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| # Copyright (c) 2020 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. | ||
|
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| import numpy as np | ||
| import paddle.fluid as fluid | ||
| import six | ||
| import unittest | ||
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| class SimpleFCLayer(fluid.dygraph.Layer): | ||
| def __init__(self, feature_size, batch_size, fc_size): | ||
| super(SimpleFCLayer, self).__init__() | ||
| self._linear = fluid.dygraph.Linear(feature_size, fc_size) | ||
| self._offset = fluid.dygraph.to_variable( | ||
| np.random.random((batch_size, fc_size)).astype('float32')) | ||
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| def forward(self, x): | ||
| fc = self._linear(x) | ||
| return fc + self._offset | ||
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| class TestTracedLayerErrMsg(unittest.TestCase): | ||
| def setUp(self): | ||
| self.batch_size = 4 | ||
| self.feature_size = 3 | ||
| self.fc_size = 2 | ||
| self.layer = self._train_simple_net() | ||
| if six.PY2: | ||
| self.type_str = 'type' | ||
| else: | ||
| self.type_str = 'class' | ||
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| def test_trace_err(self): | ||
| with fluid.dygraph.guard(): | ||
| in_x = fluid.dygraph.to_variable( | ||
| np.random.random((self.batch_size, self.feature_size)).astype( | ||
| 'float32')) | ||
|
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| with self.assertRaises(AssertionError) as e: | ||
| dygraph_out, traced_layer = fluid.dygraph.TracedLayer.trace( | ||
| None, [in_x]) | ||
| self.assertEqual( | ||
| "The type of 'layer' in fluid.dygraph.jit.TracedLayer.trace must be fluid.dygraph.Layer, but received <{} 'NoneType'>.". | ||
| format(self.type_str), str(e.exception)) | ||
| with self.assertRaises(TypeError) as e: | ||
| dygraph_out, traced_layer = fluid.dygraph.TracedLayer.trace( | ||
| self.layer, 3) | ||
| self.assertEqual( | ||
| "The type of 'each element of inputs' in fluid.dygraph.jit.TracedLayer.trace must be fluid.Variable, but received <{} 'int'>.". | ||
| format(self.type_str, self.type_str), str(e.exception)) | ||
| with self.assertRaises(TypeError) as e: | ||
| dygraph_out, traced_layer = fluid.dygraph.TracedLayer.trace( | ||
| self.layer, [True, 1]) | ||
| self.assertEqual( | ||
| "The type of 'each element of inputs' in fluid.dygraph.jit.TracedLayer.trace must be fluid.Variable, but received <{} 'bool'>.". | ||
| format(self.type_str), str(e.exception)) | ||
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| dygraph_out, traced_layer = fluid.dygraph.TracedLayer.trace( | ||
| self.layer, [in_x]) | ||
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| def test_set_strategy_err(self): | ||
| with fluid.dygraph.guard(): | ||
| in_x = fluid.dygraph.to_variable( | ||
| np.random.random((self.batch_size, self.feature_size)).astype( | ||
| 'float32')) | ||
| dygraph_out, traced_layer = fluid.dygraph.TracedLayer.trace( | ||
| self.layer, [in_x]) | ||
|
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| with self.assertRaises(AssertionError) as e: | ||
| traced_layer.set_strategy(1, fluid.ExecutionStrategy()) | ||
| self.assertEqual( | ||
| "The type of 'build_strategy' in fluid.dygraph.jit.TracedLayer.set_strategy must be fluid.BuildStrategy, but received <{} 'int'>.". | ||
| format(self.type_str), str(e.exception)) | ||
|
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||
| with self.assertRaises(AssertionError) as e: | ||
| traced_layer.set_strategy(fluid.BuildStrategy(), False) | ||
| self.assertEqual( | ||
| "The type of 'exec_strategy' in fluid.dygraph.jit.TracedLayer.set_strategy must be fluid.ExecutionStrategy, but received <{} 'bool'>.". | ||
| format(self.type_str), str(e.exception)) | ||
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| traced_layer.set_strategy(build_strategy=fluid.BuildStrategy()) | ||
| traced_layer.set_strategy(exec_strategy=fluid.ExecutionStrategy()) | ||
| traced_layer.set_strategy(fluid.BuildStrategy(), | ||
| fluid.ExecutionStrategy()) | ||
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| def test_save_inference_model_err(self): | ||
| with fluid.dygraph.guard(): | ||
| in_x = fluid.dygraph.to_variable( | ||
| np.random.random((self.batch_size, self.feature_size)).astype( | ||
| 'float32')) | ||
| dygraph_out, traced_layer = fluid.dygraph.TracedLayer.trace( | ||
| self.layer, [in_x]) | ||
|
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| dirname = './traced_layer_err_msg' | ||
| with self.assertRaises(TypeError) as e: | ||
| traced_layer.save_inference_model([0]) | ||
| self.assertEqual( | ||
| "The type of 'dirname' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'str'>, but received <{} 'list'>. ". | ||
| format(self.type_str, self.type_str), str(e.exception)) | ||
| with self.assertRaises(TypeError) as e: | ||
| traced_layer.save_inference_model(dirname, [0], [None]) | ||
| self.assertEqual( | ||
| "The type of 'each element of fetch' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'int'>, but received <{} 'NoneType'>. ". | ||
| format(self.type_str, self.type_str), str(e.exception)) | ||
| with self.assertRaises(TypeError) as e: | ||
| traced_layer.save_inference_model(dirname, [0], False) | ||
| self.assertEqual( | ||
| "The type of 'fetch' in fluid.dygraph.jit.TracedLayer.save_inference_model must be (<{} 'NoneType'>, <{} 'list'>), but received <{} 'bool'>. ". | ||
| format(self.type_str, self.type_str, self.type_str), | ||
| str(e.exception)) | ||
| with self.assertRaises(TypeError) as e: | ||
| traced_layer.save_inference_model(dirname, [None], [0]) | ||
| self.assertEqual( | ||
| "The type of 'each element of feed' in fluid.dygraph.jit.TracedLayer.save_inference_model must be <{} 'int'>, but received <{} 'NoneType'>. ". | ||
| format(self.type_str, self.type_str), str(e.exception)) | ||
| with self.assertRaises(TypeError) as e: | ||
| traced_layer.save_inference_model(dirname, True, [0]) | ||
| self.assertEqual( | ||
| "The type of 'feed' in fluid.dygraph.jit.TracedLayer.save_inference_model must be (<{} 'NoneType'>, <{} 'list'>), but received <{} 'bool'>. ". | ||
| format(self.type_str, self.type_str, self.type_str), | ||
| str(e.exception)) | ||
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| traced_layer.save_inference_model(dirname) | ||
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| def _train_simple_net(self): | ||
| layer = None | ||
| with fluid.dygraph.guard(): | ||
| layer = SimpleFCLayer(self.feature_size, self.batch_size, | ||
| self.fc_size) | ||
| optimizer = fluid.optimizer.SGD(learning_rate=1e-3, | ||
| parameter_list=layer.parameters()) | ||
|
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| for i in range(5): | ||
| in_x = fluid.dygraph.to_variable( | ||
| np.random.random((self.batch_size, self.feature_size)) | ||
| .astype('float32')) | ||
| dygraph_out = layer(in_x) | ||
| loss = fluid.layers.reduce_mean(dygraph_out) | ||
| loss.backward() | ||
| optimizer.minimize(loss) | ||
| return layer | ||
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| if __name__ == '__main__': | ||
| unittest.main() |