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[Dy2Stat]Support Python3 type hint #33745
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124 changes: 124 additions & 0 deletions
124
python/paddle/fluid/tests/unittests/dygraph_to_static/test_typing.py
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# Copyright (c) 2021 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 paddle | ||
import unittest | ||
import numpy as np | ||
from typing import Tuple, List, Dict, TypeVar | ||
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class BaseLayer(paddle.nn.Layer): | ||
def __init__(self, in_size, out_size): | ||
super(BaseLayer, self).__init__() | ||
self._linear = paddle.nn.Linear(in_size, out_size) | ||
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def build(self, x): | ||
out1 = self._linear(x) | ||
out2 = paddle.mean(out1) | ||
return out1, out2 | ||
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class LinearNetWithTuple(BaseLayer): | ||
def __init__(self, in_size, out_size): | ||
super(LinearNetWithTuple, self).__init__(in_size, out_size) | ||
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def forward(self, x) -> Tuple[paddle.Tensor, str]: | ||
out1, out2 = self.build(x) | ||
return (out2, 'str') | ||
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class LinearNetWithTuple2(BaseLayer): | ||
def __init__(self, in_size, out_size): | ||
super(LinearNetWithTuple2, self).__init__(in_size, out_size) | ||
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def forward(self, x) -> Tuple[paddle.Tensor, np.array]: | ||
out1, out2 = self.build(x) | ||
return (out2, np.ones([4, 16])) | ||
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class LinearNetWithList(BaseLayer): | ||
def __init__(self, in_size, out_size): | ||
super(LinearNetWithList, self).__init__(in_size, out_size) | ||
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def forward(self, x) -> List[paddle.Tensor]: | ||
out1, out2 = self.build(x) | ||
return [out2] | ||
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class LinearNetWithDict(BaseLayer): | ||
def __init__(self, in_size, out_size): | ||
super(LinearNetWithDict, self).__init__(in_size, out_size) | ||
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def forward(self, x) -> Dict[str, paddle.Tensor]: | ||
out1, out2 = self.build(x) | ||
return {'out': out2} | ||
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class TestTyping(unittest.TestCase): | ||
def setUp(self): | ||
self.in_num = 16 | ||
self.out_num = 16 | ||
self.x = paddle.randn([4, 16]) | ||
self.spec = [paddle.static.InputSpec(shape=[None, 16], dtype='float32')] | ||
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def build_net(self): | ||
return LinearNetWithTuple(self.in_num, self.out_num) | ||
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def save_and_load(self, suffix=''): | ||
path = './layer_typing_' + suffix | ||
paddle.jit.save(self.net, path, input_spec=self.spec) | ||
return paddle.jit.load(path) | ||
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def run_dy(self): | ||
out, _ = self.net(self.x) | ||
return out | ||
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def test_type(self): | ||
self.net = self.build_net() | ||
out = self.run_dy() | ||
load_net = self.save_and_load('tuple') | ||
load_out = load_net(self.x) | ||
self.assertTrue(np.allclose(out, load_out)) | ||
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class TestTypingTuple(TestTyping): | ||
def build_net(self): | ||
return LinearNetWithTuple2(self.in_num, self.out_num) | ||
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def run_dy(self): | ||
out, np_data = self.net(self.x) | ||
self.assertTrue(np.equal(np_data, np.ones_like(np_data)).all()) | ||
return out | ||
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class TestTypingList(TestTyping): | ||
def build_net(self): | ||
return LinearNetWithList(self.in_num, self.out_num) | ||
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def run_dy(self): | ||
out = self.net(self.x)[0] | ||
return out | ||
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class TestTypingDict(TestTyping): | ||
def build_net(self): | ||
return LinearNetWithDict(self.in_num, self.out_num) | ||
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def run_dy(self): | ||
out = self.net(self.x)['out'] | ||
return out | ||
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if __name__ == '__main__': | ||
unittest.main() |
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Because we add two
import
statement, so here we adjust line infos by +2