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112 lines
3.0 KiB
112 lines
3.0 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 as np
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from op_test import OpTest
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class TestTopkOp(OpTest):
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def setUp(self):
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self.set_args()
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self.op_type = "top_k"
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k = self.top_k
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input = np.random.random((self.row, k)).astype("float32")
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output = np.ndarray((self.row, k))
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indices = np.ndarray((self.row, k)).astype("int64")
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self.inputs = {'X': input}
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self.attrs = {'k': k}
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for rowid in range(self.row):
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row = input[rowid]
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output[rowid] = np.sort(row)[::-1][:k]
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indices[rowid] = row.argsort()[::-1][:k]
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self.outputs = {'Out': output, 'Indices': indices}
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def set_args(self):
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self.row = 32
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self.top_k = 1
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def test_check_output(self):
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self.check_output()
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class TestTopkOp3d(OpTest):
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def setUp(self):
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self.op_type = "top_k"
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k = 1
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input = np.random.random((32, 2, 84)).astype("float32")
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input_flat_2d = input.reshape(64, 84)
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output = np.ndarray((64, k))
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indices = np.ndarray((64, k)).astype("int64")
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self.inputs = {'X': input}
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self.attrs = {'k': k}
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for rowid in range(64):
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row = input_flat_2d[rowid]
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output[rowid] = np.sort(row)[::-1][:k]
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indices[rowid] = row.argsort()[::-1][:k]
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self.outputs = {
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'Out': output.reshape((32, 2, k)),
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'Indices': indices.reshape((32, 2, k))
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}
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def test_check_output(self):
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self.check_output()
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class TestTopkOp2(OpTest):
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def setUp(self):
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self.op_type = "top_k"
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k = 1
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m = 2056
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input = np.random.random((m, 84)).astype("float32")
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output = np.ndarray((m, k))
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indices = np.ndarray((m, k)).astype("int64")
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self.inputs = {'X': input}
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self.attrs = {'k': k}
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for rowid in range(m):
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row = input[rowid]
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output[rowid] = -np.sort(-row)[:k]
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indices[rowid] = (-row).argsort()[:k]
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self.outputs = {'Out': output, 'Indices': indices}
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def test_check_output(self):
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self.check_output()
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class TestTopkOp3(TestTopkOp):
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def set_args(self):
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self.row = 2056
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self.top_k = 3
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class TestTopkOp4(TestTopkOp):
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def set_args(self):
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self.row = 40000
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self.top_k = 1
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if __name__ == "__main__":
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unittest.main()
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