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77 lines
2.2 KiB
77 lines
2.2 KiB
# Copyright (c) 2018 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 print_function
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import unittest
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import numpy
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import paddle.fluid as fluid
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import paddle.fluid.core as core
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from paddle.fluid.op import Operator
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from paddle.fluid.executor import Executor
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class TestGaussianRandomOp(unittest.TestCase):
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def setUp(self):
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self.op_type = "gaussian_random"
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self.inputs = {}
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self.use_mkldnn = False
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self.init_kernel_type()
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self.attrs = {
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"shape": [1000, 784],
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"mean": .0,
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"std": 1.,
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"seed": 10,
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"use_mkldnn": self.use_mkldnn
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}
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self.outputs = ["Out"]
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def test_cpu(self):
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self.gaussian_random_test(place=fluid.CPUPlace())
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def test_gpu(self):
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if core.is_compiled_with_cuda():
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self.gaussian_random_test(place=fluid.CUDAPlace(0))
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def gaussian_random_test(self, place):
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program = fluid.Program()
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block = program.global_block()
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vout = block.create_var(name="Out")
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op = block.append_op(
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type=self.op_type, outputs={"Out": vout}, attrs=self.attrs)
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op.desc.infer_var_type(block.desc)
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op.desc.infer_shape(block.desc)
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fetch_list = []
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for var_name in self.outputs:
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fetch_list.append(block.var(var_name))
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exe = Executor(place)
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outs = exe.run(program, fetch_list=fetch_list)
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tensor = outs[0]
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self.assertAlmostEqual(numpy.mean(tensor), .0, delta=0.1)
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self.assertAlmostEqual(numpy.std(tensor), 1., delta=0.1)
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def init_kernel_type(self):
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pass
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if __name__ == "__main__":
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unittest.main()
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