wehub-resource-sync
76 lines
2.1 KiB
Python
76 lines
2.1 KiB
Python
# 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.
|
|
|
|
import unittest
|
|
|
|
import numpy as np
|
|
|
|
import paddle
|
|
|
|
|
|
class LinearNet(paddle.nn.Layer):
|
|
def __init__(self):
|
|
super().__init__()
|
|
self._linear = paddle.nn.Linear(128, 10)
|
|
|
|
def forward(self, x):
|
|
return self._linear(x)
|
|
|
|
|
|
class Logic(paddle.nn.Layer):
|
|
def __init__(self):
|
|
super().__init__()
|
|
|
|
def forward(self, x, y, z):
|
|
if z:
|
|
return x
|
|
else:
|
|
return y
|
|
|
|
|
|
class TestExportWithTensor(unittest.TestCase):
|
|
def test_with_tensor(self):
|
|
self.x_spec = paddle.static.InputSpec(
|
|
shape=[None, 128], dtype='float32'
|
|
)
|
|
model = LinearNet()
|
|
paddle.onnx.export(model, 'linear_net', input_spec=[self.x_spec])
|
|
|
|
|
|
class TestExportWithTensor1(unittest.TestCase):
|
|
def test_with_tensor(self):
|
|
self.x = paddle.to_tensor(np.random.random((1, 128)))
|
|
model = LinearNet()
|
|
paddle.onnx.export(model, 'linear_net', input_spec=[self.x])
|
|
|
|
|
|
class TestExportPrunedGraph(unittest.TestCase):
|
|
def test_prune_graph(self):
|
|
model = Logic()
|
|
self.x = paddle.to_tensor(np.array([1]))
|
|
self.y = paddle.to_tensor(np.array([-1]))
|
|
paddle.jit.to_static(model, full_graph=True)
|
|
out = model(self.x, self.y, z=True)
|
|
paddle.onnx.export(
|
|
model,
|
|
'pruned',
|
|
input_spec=[self.x, self.y, True],
|
|
output_spec=[out],
|
|
input_names_after_prune=[self.x.name],
|
|
)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|