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test_bucketize_api.py
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test_bucketize_api.py
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# Copyright (c) 2022 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.
from __future__ import print_function
from re import X
import unittest
import numpy as np
import paddle
import paddle.fluid as fluid
import paddle.fluid.core as core
from paddle.fluid import Program, program_guard
np.random.seed(10)
class TestBucketizeAPI(unittest.TestCase):
# test paddle.tensor.math.nanmean
def setUp(self):
self.sorted_sequence = np.array([2, 4, 8, 16]).astype("float64")
self.x = np.array([[0, 8, 4, 16], [-1, 2, 8, 4]]).astype("float64")
self.place = [paddle.CPUPlace()]
if core.is_compiled_with_cuda():
self.place.append(paddle.CUDAPlace(0))
def test_api_static(self):
paddle.enable_static()
def run(place):
with paddle.static.program_guard(paddle.static.Program()):
sorted_sequence = paddle.static.data(
'SortedSequence',
shape=self.sorted_sequence.shape,
dtype="float64")
x = paddle.static.data('x', shape=self.x.shape, dtype="float64")
out1 = paddle.bucketize(x, sorted_sequence)
out2 = paddle.bucketize(x, sorted_sequence, right=True)
exe = paddle.static.Executor(place)
res = exe.run(feed={
'SortedSequence': self.sorted_sequence,
'x': self.x
},
fetch_list=[out1, out2])
out_ref = np.searchsorted(self.sorted_sequence, self.x)
out_ref1 = np.searchsorted(self.sorted_sequence,
self.x,
side='right')
self.assertTrue(np.allclose(out_ref, res[0]))
self.assertTrue(np.allclose(out_ref1, res[1]))
for place in self.place:
run(place)
def test_api_dygraph(self):
def run(place):
paddle.disable_static(place)
sorted_sequence = paddle.to_tensor(self.sorted_sequence)
x = paddle.to_tensor(self.x)
out1 = paddle.bucketize(x, sorted_sequence)
out2 = paddle.bucketize(x, sorted_sequence, right=True)
out_ref1 = np.searchsorted(self.sorted_sequence, self.x)
out_ref2 = np.searchsorted(self.sorted_sequence,
self.x,
side='right')
self.assertEqual(np.allclose(out_ref1, out1.numpy()), True)
self.assertEqual(np.allclose(out_ref2, out2.numpy()), True)
paddle.enable_static()
for place in self.place:
run(place)
def test_out_int32(self):
paddle.disable_static()
sorted_sequence = paddle.to_tensor(self.sorted_sequence)
x = paddle.to_tensor(self.x)
out = paddle.bucketize(x, sorted_sequence, out_int32=True)
self.assertTrue(out.type, 'int32')
def test_bucketize_dims_error(self):
with paddle.static.program_guard(paddle.static.Program()):
sorted_sequence = paddle.static.data('SortedSequence',
shape=[2, 2],
dtype="float64")
x = paddle.static.data('x', shape=[2, 5], dtype="float64")
self.assertRaises(ValueError, paddle.bucketize, x, sorted_sequence)
def test_input_error(self):
for place in self.place:
paddle.disable_static(place)
sorted_sequence = paddle.to_tensor(self.sorted_sequence)
self.assertRaises(ValueError, paddle.bucketize, self.x,
sorted_sequence)
def test_empty_input_error(self):
for place in self.place:
paddle.disable_static(place)
sorted_sequence = paddle.to_tensor(self.sorted_sequence)
x = paddle.to_tensor(self.x)
self.assertRaises(ValueError, paddle.bucketize, None,
sorted_sequence)
self.assertRaises(AttributeError, paddle.bucketize, x, None)
if __name__ == "__main__":
unittest.main()