wehub-resource-sync
68 lines
2.2 KiB
Python
68 lines
2.2 KiB
Python
# Copyright (c) 2023 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 re
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import unittest
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import numpy as np
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from op_test import is_custom_device
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import paddle
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from paddle.base import core
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class TestElementwiseOp(unittest.TestCase):
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def setUp(self):
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self.op_type = "elementwise_sub"
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self.python_api = paddle.subtract
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self.public_python_api = paddle.subtract
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self.prim_op_type = "prim"
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def test_float16_sub(self):
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if not (core.is_compiled_with_cuda() or is_custom_device()):
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return
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gpu_info = paddle.device.get_device_properties()
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gpu_name = gpu_info.name
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try:
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re_result = re.split(r'[ , -]', gpu_name)
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memory = int(re_result[-1][:-2])
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except:
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memory = int(gpu_info.total_memory) // (1000**3)
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if memory < 37: # 37GB
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return
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paddle.disable_static()
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tensor_a = paddle.rand(shape=[5120, 4, 384, 384], dtype="float16")
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tensor_b = paddle.rand(shape=[5120, 1, 384, 384], dtype="float16")
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tensor_z = paddle.subtract(tensor_a, tensor_b)
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in0, in1 = paddle.split(tensor_a, num_or_sections=2, axis=1)
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(
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out0,
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out1,
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) = paddle.split(tensor_z, num_or_sections=2, axis=1)
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split_add0 = paddle.subtract(tensor_b, in0)
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split_add1 = paddle.subtract(tensor_b, in1)
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result1 = paddle.any(paddle.equal(out0, split_add0), [0, 1, 2, 3])
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result2 = paddle.any(paddle.equal(out1, split_add1), [0, 1, 2, 3])
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np.testing.assert_equal(result1.numpy(), True)
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np.testing.assert_equal(result2.numpy(), True)
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if __name__ == '__main__':
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unittest.main()
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