wehub-resource-sync
100 lines
3.2 KiB
Python
100 lines
3.2 KiB
Python
# Copyright (c) 2020 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 inspect
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle
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from paddle import base
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from paddle.base import core
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class TestDiagEmbedOp(OpTest):
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def setUp(self):
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self.op_type = "diag_embed"
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self.python_api = paddle.diag_embed
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self.init_shape()
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self.init_config()
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self.outputs = {'Out': self.target}
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def test_check_output(self):
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self.check_output(check_pir=True)
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def init_shape(self):
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self.shape = (2, 3)
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def init_config(self):
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self.case = np.random.randn(*self.shape).astype('float32')
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self.inputs = {'Input': self.case}
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self.attrs = {'offset': 0, 'dim1': -2, 'dim2': -1}
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self.target = np.stack([np.diag(r, 0) for r in self.inputs['Input']], 0)
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class TestDiagEmbedOpCase1(TestDiagEmbedOp):
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def init_config(self):
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self.case = np.random.randn(2, 3).astype('float32')
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self.inputs = {'Input': self.case}
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self.attrs = {'offset': -1, 'dim1': 0, 'dim2': 2}
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self.target = np.stack(
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[np.diag(r, -1) for r in self.inputs['Input']], 1
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)
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class TestDiagEmbedOp_ZeroSize(TestDiagEmbedOp):
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def init_shape(self):
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self.shape = (2, 0)
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class TestDiagEmbedAPICase(unittest.TestCase):
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def test_case1(self):
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paddle.enable_static()
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main = paddle.static.Program()
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startup = paddle.static.Program()
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with paddle.static.program_guard(main, startup):
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diag_embed = np.random.randn(2, 3, 4).astype('float32')
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data1 = paddle.static.data(
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name='data1', shape=[2, 3, 4], dtype='float32'
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)
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out1 = paddle.diag_embed(data1)
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out2 = paddle.diag_embed(data1, offset=1, dim1=-2, dim2=3)
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place = core.CPUPlace()
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exe = base.Executor(place)
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results = exe.run(
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main,
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feed={"data1": diag_embed},
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fetch_list=[out1, out2],
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return_numpy=True,
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)
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target1 = np.stack(
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[np.stack([np.diag(s, 0) for s in r], 0) for r in diag_embed], 0
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)
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target2 = np.stack(
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[np.stack([np.diag(s, 1) for s in r], 0) for r in diag_embed], 0
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)
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np.testing.assert_allclose(results[0], target1, rtol=1e-05)
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np.testing.assert_allclose(results[1], target2, rtol=1e-05)
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def test_tensor_method(self):
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paddle.disable_static()
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x = paddle.arange(15).reshape((3, 5)).astype('float64')
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self.assertTrue(inspect.ismethod(x.diag_embed))
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if __name__ == "__main__":
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unittest.main()
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