wehub-resource-sync
84 lines
3.0 KiB
Python
84 lines
3.0 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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from fused_pass.pass_test import PassTest
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import paddle
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import paddle.nn.functional as F
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from paddle.base import core
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from paddle.pir.core import create_parameter
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paddle.enable_static()
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@unittest.skipIf(
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not core.is_compiled_with_cuda() or core.is_compiled_with_rocm(),
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"DepthwiseConv2ConvPattern requires CUDA",
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)
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class TestDepthwiseConv2ConvPattern(PassTest):
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r""" """
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def is_program_valid(self, program=None):
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return True
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def sample_program(self):
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with paddle.pir_utils.IrGuard():
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main_prog = paddle.static.Program()
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start_prog = paddle.static.Program()
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for x_shape in [[3, 32, 150, 150]]:
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for conv2d_filter_shape in [[32, 1, 3, 3]]:
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with paddle.pir.core.program_guard(main_prog, start_prog):
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x = paddle.static.data(
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name='x', shape=x_shape, dtype='float32'
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)
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initializer = paddle.nn.initializer.Assign(
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np.random.rand(32, 1, 3, 3)
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)
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conv2d_filter = create_parameter(
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shape=conv2d_filter_shape,
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dtype='float32',
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initializer=initializer,
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padding="SAME",
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dilation=[1, 1],
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stride=[1, 1],
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)
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depthwise_conv2d_out = F.conv2d(
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x, conv2d_filter, groups=32, data_format="NCHW"
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)
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out = paddle.assign(depthwise_conv2d_out)
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self.pass_attr_list = [{'map_op_to_another_pass': {}}]
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self.feeds = {
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"x": np.random.random(x_shape).astype("float32"),
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}
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self.fetch_list = [out]
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self.valid_op_map = {
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"pd_op.depthwise_conv2d": 0,
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"pd_op.conv2d": 1,
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}
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yield [main_prog, start_prog], False
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def setUp(self):
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if core.is_compiled_with_cuda():
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self.places.append(paddle.CUDAPlace(0))
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def test_check_output(self):
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self.check_pass_correct()
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if __name__ == "__main__":
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unittest.main()
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