wehub-resource-sync
163 lines
4.7 KiB
Python
163 lines
4.7 KiB
Python
# Copyright (c) 2024 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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import unittest
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import numpy as np
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import paddle
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class TestFallBackBase(unittest.TestCase):
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def setUp(self):
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self.func_api = None
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self.dtype = np.float32
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self.tol = 1e-6
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def custom_dropout(x, p):
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return paddle.nn.functional.dropout(x, p) + 2.0
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class TestDropOutFallBack(TestFallBackBase):
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def setUp(self):
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super().setUp()
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self.func_api = custom_dropout
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self.x = paddle.to_tensor([[1.0, -2], [3.0, 4]], dtype=self.dtype)
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self.p = paddle.to_tensor(0.0, dtype=self.dtype)
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def test_fallback(self):
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static_func = paddle.jit.to_static(
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self.func_api, full_graph=True, backend=None
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)
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dynamic_func = self.func_api
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out = static_func(self.x, self.p)
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ref_out = dynamic_func(self.x, self.p)
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for ref, actual in zip(ref_out, out):
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np.testing.assert_allclose(
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ref, actual, rtol=self.tol, atol=self.tol
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)
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def custom_full(shape, value):
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return paddle.full_like(shape, value) + 2.0
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class TestFullLikeFallBack(TestFallBackBase):
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def setUp(self):
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super().setUp()
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self.func_api = custom_full
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self.x = paddle.to_tensor([[1.0, -2], [3.0, 4]], dtype=self.dtype)
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self.value = paddle.to_tensor(2, dtype=self.dtype)
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def test_fallback(self):
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static_func = paddle.jit.to_static(
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self.func_api, full_graph=True, backend=None
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)
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dynamic_func = self.func_api
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out = static_func(self.x, self.value)
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ref_out = dynamic_func(self.x, self.value)
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for ref, actual in zip(ref_out, out):
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np.testing.assert_allclose(
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ref, actual, rtol=self.tol, atol=self.tol
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)
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def custom_squeeze(x, axis):
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return paddle.squeeze(x, axis) + 2.0
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class TestSqueezeFallBack(TestFallBackBase):
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def setUp(self):
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super().setUp()
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self.func_api = custom_squeeze
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self.x = paddle.rand([5, 1, 10], dtype=self.dtype)
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self.axis = paddle.to_tensor(1, dtype=paddle.int64)
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def test_fallback(self):
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static_func = paddle.jit.to_static(
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self.func_api, full_graph=True, backend=None
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)
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dynamic_func = self.func_api
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out = static_func(self.x, self.axis)
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ref_out = dynamic_func(self.x, self.axis)
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for ref, actual in zip(ref_out, out):
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np.testing.assert_allclose(
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ref, actual, rtol=self.tol, atol=self.tol
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)
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def custom_unsqueeze(x, axis):
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return paddle.unsqueeze(x, axis) + 2.0
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class TestUnsqueezeFallBack(TestFallBackBase):
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def setUp(self):
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super().setUp()
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self.func_api = custom_unsqueeze
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self.x = paddle.rand([5, 10], dtype=self.dtype)
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self.axis = paddle.to_tensor([0, 2], dtype=paddle.int64)
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def test_fallback(self):
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static_func = paddle.jit.to_static(
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self.func_api, full_graph=True, backend=None
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)
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dynamic_func = self.func_api
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out = static_func(self.x, self.axis)
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ref_out = dynamic_func(self.x, self.axis)
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for ref, actual in zip(ref_out, out):
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np.testing.assert_allclose(
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ref, actual, rtol=self.tol, atol=self.tol
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)
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def custom_any(x, axis):
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return paddle.any(x, axis)
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class TestAnyFallBack(TestFallBackBase):
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def setUp(self):
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super().setUp()
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self.func_api = custom_any
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self.x = paddle.to_tensor([[1, 0], [1, 1]], dtype='int32').cast('bool')
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# Axis cannot accept a list of tensors,
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# the framework will check the argument type before decomposition.
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self.axis = [0]
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def test_fallback(self):
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static_func = paddle.jit.to_static(
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self.func_api, full_graph=True, backend=None
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)
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dynamic_func = self.func_api
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out = static_func(self.x, self.axis)
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ref_out = dynamic_func(self.x, self.axis)
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for ref, actual in zip(ref_out, out):
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np.testing.assert_allclose(
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ref, actual, rtol=self.tol, atol=self.tol
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)
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if __name__ == '__main__':
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unittest.main()
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