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66 lines
2.3 KiB
66 lines
2.3 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import print_function
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import unittest
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from op_test import OpTest
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import paddle
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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import numpy as np
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class TestBilinearAPI(unittest.TestCase):
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def test_api(self):
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with fluid.program_guard(fluid.default_startup_program(),
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fluid.default_main_program()):
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if core.is_compiled_with_cuda():
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place = core.CUDAPlace(0)
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else:
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place = core.CPUPlace()
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exe = fluid.Executor(place)
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data1 = fluid.data(name='X1', shape=[5, 5], dtype='float32')
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data2 = fluid.data(name='X2', shape=[5, 4], dtype='float32')
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layer1 = np.random.random((5, 5)).astype('float32')
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layer2 = np.random.random((5, 4)).astype('float32')
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bilinear = paddle.nn.Bilinear(
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in1_features=5, in2_features=4, out_features=1000)
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ret = bilinear(data1, data2)
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exe.run(fluid.default_startup_program())
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ret_fetch = exe.run(feed={'X1': layer1,
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'X2': layer2},
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fetch_list=[ret.name])
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self.assertEqual(ret_fetch[0].shape, (5, 1000))
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class TestBilinearAPIDygraph(unittest.TestCase):
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def test_api(self):
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paddle.disable_static()
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layer1 = np.random.random((5, 5)).astype('float32')
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layer2 = np.random.random((5, 4)).astype('float32')
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bilinear = paddle.nn.Bilinear(
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in1_features=5, in2_features=4, out_features=1000)
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ret = bilinear(paddle.to_tensor(layer1), paddle.to_tensor(layer2))
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self.assertEqual(ret.shape, [5, 1000])
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if __name__ == "__main__":
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unittest.main()
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