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# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import numpy as np
from op_test import OpTest
class TestTopkOp(OpTest):
def setUp(self):
self.op_type = "top_k"
k = 1
input = np.random.random((32, 84)).astype("float32")
output = np.ndarray((32, k))
indices = np.ndarray((32, k)).astype("int64")
self.inputs = {'X': input}
self.attrs = {'k': k}
for rowid in range(32):
row = input[rowid]
output[rowid] = np.sort(row)[-k:]
indices[rowid] = row.argsort()[-k:]
self.outputs = {'Out': output, 'Indices': indices}
def test_check_output(self):
self.check_output()
class TestTopkOp3d(OpTest):
def setUp(self):
self.op_type = "top_k"
k = 1
input = np.random.random((32, 2, 84)).astype("float32")
input_flat_2d = input.reshape(64, 84)
output = np.ndarray((64, k))
indices = np.ndarray((64, k)).astype("int64")
# FIXME: should use 'X': input for a 3d input
self.inputs = {'X': input_flat_2d}
self.attrs = {'k': k}
for rowid in range(64):
row = input_flat_2d[rowid]
output[rowid] = np.sort(row)[-k:]
indices[rowid] = row.argsort()[-k:]
self.outputs = {'Out': output, 'Indices': indices}
def test_check_output(self):
self.check_output()
if __name__ == "__main__":
unittest.main()