paddlepaddle--paddle
wehub-resource-sync
138 行
3.8 KiB
Python
138 行
3.8 KiB
Python
# Copyright (c) 2022 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 op_test_ipu import IPUOpTest
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import paddle
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import paddle.static
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class TestGreaterThan(IPUOpTest):
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def setUp(self):
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self.set_atol()
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self.set_training()
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self.set_test_op()
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def set_test_op(self):
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self.op = paddle.base.layers.greater_than
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def set_op_attrs(self):
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self.attrs = {}
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@IPUOpTest.static_graph
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def build_model(self):
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x = paddle.static.data(
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name=self.feed_list[0], shape=self.feed_shape[0], dtype='float32'
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)
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y = paddle.static.data(
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name=self.feed_list[1], shape=self.feed_shape[1], dtype='float32'
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)
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out = self.op(x, y, **self.attrs)
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self.fetch_list = [out.name]
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def run_model(self, exec_mode):
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self.run_op_test(exec_mode)
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def run_test_base(self):
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for m in IPUOpTest.ExecutionMode:
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if not self.skip_mode(m):
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self.build_model()
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self.run_model(m)
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self.check()
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def set_feed_attr(self):
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self.feed_shape = [x.shape for x in self.feed_fp32.values()]
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self.feed_list = list(self.feed_fp32.keys())
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def set_data_feed0(self):
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x = np.random.randn(3, 4, 5)
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y = np.random.randn(3, 4, 5)
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self.feed_fp32 = {
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"x": x.astype(np.float32),
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"y": y.astype(np.float32),
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}
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self.feed_fp16 = {
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"x": x.astype(np.float16),
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"y": y.astype(np.float16),
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}
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self.set_feed_attr()
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def set_data_feed1(self):
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x = np.ones([1, 10])
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y = np.ones([10])
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self.feed_fp32 = {"x": x.astype(np.float32), "y": y.astype(np.float32)}
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self.feed_fp16 = {"x": x.astype(np.float16), "y": y.astype(np.float16)}
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self.set_feed_attr()
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def set_data_feed2(self):
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x = np.ones([1, 10])
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y = np.zeros([1, 10])
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self.feed_fp32 = {"x": x.astype(np.float32), "y": y.astype(np.float32)}
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self.feed_fp16 = {"x": x.astype(np.float16), "y": y.astype(np.float16)}
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self.set_feed_attr()
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def set_data_feed3(self):
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x = np.zeros([1, 10])
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y = np.ones([1, 10])
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self.feed_fp32 = {"x": x.astype(np.float32), "y": y.astype(np.float32)}
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self.feed_fp16 = {"x": x.astype(np.float16), "y": y.astype(np.float16)}
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self.set_feed_attr()
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def test_case0(self):
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self.set_data_feed0()
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self.set_op_attrs()
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self.run_test_base()
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def test_case1(self):
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self.set_data_feed1()
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self.set_op_attrs()
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self.run_test_base()
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def test_case2(self):
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self.set_data_feed2()
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self.set_op_attrs()
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self.run_test_base()
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def test_case3(self):
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self.set_data_feed3()
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self.set_op_attrs()
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self.run_test_base()
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class TestLessThan(TestGreaterThan):
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def set_test_op(self):
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self.op = paddle.base.layers.less_than
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class TestEqual(TestGreaterThan):
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def set_test_op(self):
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self.op = paddle.base.layers.equal
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class TestGreaterEqual(TestGreaterThan):
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def set_test_op(self):
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self.op = paddle.base.layers.greater_equal
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class TestLessEqual(TestGreaterThan):
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def set_test_op(self):
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self.op = paddle.base.layers.less_equal
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if __name__ == "__main__":
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unittest.main()
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