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Paddle/python/paddle/fluid/tests/unittests/test_sampling_id_op.py

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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
import paddle.fluid.core as core
import paddle.fluid as fluid
from paddle.fluid.op import Operator
class TestSamplingIdOp(OpTest):
def setUp(self):
self.op_type = "sampling_id"
self.use_mkldnn = False
self.init_kernel_type()
self.X = np.random.random((100, 10)).astype('float32')
self.inputs = {"X": self.X}
self.Y = np.random.random(100).astype('int64')
self.outputs = {'Out': self.Y}
self.attrs = {'max': 1.0, 'min': 0.0, 'seed': 1}
def test_check_output(self):
self.check_output_customized(self.verify_output)
y1 = self.out
self.check_output_customized(self.verify_output)
y2 = self.out
# check dtype
assert y1.dtype == np.int64
assert y2.dtype == np.int64
# check output is index ids of inputs
inputs_ids = np.arange(self.X.shape[1])
assert np.isin(y1, inputs_ids).all()
assert np.isin(y2, inputs_ids).all()
self.assertTrue(np.array_equal(y1, y2))
self.assertEqual(len(y1), len(self.Y))
def verify_output(self, outs):
out = np.array(outs[0])
self.out = out
def init_kernel_type(self):
pass
class TestSamplingIdShape(unittest.TestCase):
def test_shape(self):
x = fluid.layers.data(name='x', shape=[3], dtype='float32')
output = fluid.layers.sampling_id(x)
place = fluid.CPUPlace()
exe = fluid.Executor(place=place)
exe.run(fluid.default_startup_program())
feed = {
'x': np.array(
[[0.2, 0.3, 0.5], [0.2, 0.3, 0.4]], dtype='float32')
}
output_np = exe.run(feed=feed, fetch_list=[output])[0]
self.assertEqual(output.shape[0], -1)
self.assertEqual(len(output.shape), 1)
self.assertEqual(output_np.shape[0], 2)
self.assertEqual(len(output_np.shape), 1)
if __name__ == "__main__":
unittest.main()