wehub-resource-sync
93 lines
2.7 KiB
Python
93 lines
2.7 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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from __future__ import annotations
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import unittest
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from typing import TYPE_CHECKING, Any
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import numpy as np
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from dygraph_to_static_utils import (
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Dy2StTestBase,
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test_ast_only,
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)
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import paddle
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from paddle.static.input import InputSpec
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if TYPE_CHECKING:
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from collections.abc import Callable, Sequence
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class TestDynamicShapeInfermeta(Dy2StTestBase):
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def check_dynamic_shape(
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self,
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fn: Callable[..., Any],
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inputs: Sequence[paddle.Tensor],
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input_specs: list[InputSpec],
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):
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static_fn = paddle.jit.to_static(
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fn,
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full_graph=True,
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input_spec=input_specs,
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)
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np.testing.assert_allclose(static_fn(*inputs), fn(*inputs), rtol=1e-05)
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@test_ast_only
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def test_conv2d(self):
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self.check_dynamic_shape(
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paddle.nn.Conv2D(3, 3, 3),
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[paddle.randn([1, 3, 32, 32])],
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[InputSpec(shape=[None, None, None, None], dtype='float32')],
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)
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@test_ast_only
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def test_bn(self):
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self.check_dynamic_shape(
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paddle.nn.BatchNorm2D(3),
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[paddle.randn([1, 3, 32, 32])],
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[InputSpec(shape=[None, None, None, None], dtype='float32')],
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)
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@test_ast_only
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def test_depthwise_conv2d(self):
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self.check_dynamic_shape(
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paddle.nn.Conv2D(3, 3, 3, groups=3),
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[paddle.randn([1, 3, 32, 32])],
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[InputSpec(shape=[None, None, None, None], dtype='float32')],
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)
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@test_ast_only
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def test_group_norm(self):
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self.check_dynamic_shape(
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paddle.nn.GroupNorm(3, 3),
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[paddle.randn([1, 3, 32, 32])],
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[InputSpec(shape=[None, None, None, None], dtype='float32')],
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)
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@test_ast_only
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def test_functional_conv(self):
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self.check_dynamic_shape(
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paddle.nn.functional.conv2d,
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[paddle.randn([1, 3, 32, 32]), paddle.randn([3, 3, 3, 3])],
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[
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InputSpec(shape=[None, None, None, None], dtype='float32'),
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InputSpec(shape=[None, None, None, None], dtype='float32'),
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],
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)
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if __name__ == '__main__':
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unittest.main()
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