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# Copyright 2016 The TensorFlow 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.
# ==============================================================================
"""Tests for Substr op from string_ops."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import numpy as np
from tensorflow.python.framework import errors_impl
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test
class SubstrOpTest(test.TestCase):
def _testScalarString(self, dtype):
test_string = b"Hello"
position = np.array(1, dtype)
length = np.array(3, dtype)
expected_value = b"ell"
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
def _testVectorStrings(self, dtype):
test_string = [b"Hello", b"World"]
position = np.array(1, dtype)
length = np.array(3, dtype)
expected_value = [b"ell", b"orl"]
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
def _testMatrixStrings(self, dtype):
test_string = [[b"ten", b"eleven", b"twelve"],
[b"thirteen", b"fourteen", b"fifteen"],
[b"sixteen", b"seventeen", b"eighteen"]]
position = np.array(1, dtype)
length = np.array(4, dtype)
expected_value = [[b"en", b"leve", b"welv"], [b"hirt", b"ourt", b"ifte"],
[b"ixte", b"even", b"ight"]]
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
def _testElementWisePosLen(self, dtype):
test_string = [[b"ten", b"eleven", b"twelve"],
[b"thirteen", b"fourteen", b"fifteen"],
[b"sixteen", b"seventeen", b"eighteen"]]
position = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3]], dtype)
length = np.array([[2, 3, 4], [4, 3, 2], [5, 5, 5]], dtype)
expected_value = [[b"en", b"eve", b"lve"], [b"hirt", b"urt", b"te"],
[b"ixtee", b"vente", b"hteen"]]
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
def _testBroadcast(self, dtype):
# Broadcast pos/len onto input string
test_string = [[b"ten", b"eleven", b"twelve"],
[b"thirteen", b"fourteen", b"fifteen"],
[b"sixteen", b"seventeen", b"eighteen"],
[b"nineteen", b"twenty", b"twentyone"]]
position = np.array([1, 2, 3], dtype)
length = np.array([1, 2, 3], dtype)
expected_value = [[b"e", b"ev", b"lve"], [b"h", b"ur", b"tee"],
[b"i", b"ve", b"hte"], [b"i", b"en", b"nty"]]
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
# Broadcast input string onto pos/len
test_string = [b"thirteen", b"fourteen", b"fifteen"]
position = np.array([[1, 2, 3], [3, 2, 1], [5, 5, 5]], dtype)
length = np.array([[3, 2, 1], [1, 2, 3], [2, 2, 2]], dtype)
expected_value = [[b"hir", b"ur", b"t"], [b"r", b"ur", b"ift"],
[b"ee", b"ee", b"en"]]
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
# Test 1D broadcast
test_string = b"thirteen"
position = np.array([1, 5, 7], dtype)
length = np.array([3, 2, 1], dtype)
expected_value = [b"hir", b"ee", b"n"]
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
substr = substr_op.eval()
self.assertAllEqual(substr, expected_value)
def _testBadBroadcast(self, dtype):
test_string = [[b"ten", b"eleven", b"twelve"],
[b"thirteen", b"fourteen", b"fifteen"],
[b"sixteen", b"seventeen", b"eighteen"]]
position = np.array([1, 2, 3, 4], dtype)
length = np.array([1, 2, 3, 4], dtype)
expected_value = [[b"e", b"ev", b"lve"], [b"h", b"ur", b"tee"],
[b"i", b"ve", b"hte"]]
with self.assertRaises(ValueError):
substr_op = string_ops.substr(test_string, position, length)
def _testOutOfRangeError(self, dtype):
# Scalar/Scalar
test_string = b"Hello"
position = np.array(7, dtype)
length = np.array(3, dtype)
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
with self.assertRaises(errors_impl.InvalidArgumentError):
substr = substr_op.eval()
# Vector/Scalar
test_string = [b"good", b"good", b"bad", b"good"]
position = np.array(3, dtype)
length = np.array(1, dtype)
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
with self.assertRaises(errors_impl.InvalidArgumentError):
substr = substr_op.eval()
# Negative pos
test_string = b"Hello"
position = np.array(-1, dtype)
length = np.array(3, dtype)
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
with self.assertRaises(errors_impl.InvalidArgumentError):
substr = substr_op.eval()
# Matrix/Matrix
test_string = [[b"good", b"good", b"good"], [b"good", b"good", b"bad"],
[b"good", b"good", b"good"]]
position = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3]], dtype)
length = np.array([[3, 2, 1], [1, 2, 3], [2, 2, 2]], dtype)
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
with self.assertRaises(errors_impl.InvalidArgumentError):
substr = substr_op.eval()
# Broadcast
test_string = [[b"good", b"good", b"good"], [b"good", b"good", b"bad"]]
position = np.array([1, 2, 3], dtype)
length = np.array([1, 2, 3], dtype)
substr_op = string_ops.substr(test_string, position, length)
with self.test_session():
with self.assertRaises(errors_impl.InvalidArgumentError):
substr = substr_op.eval()
def _testMismatchPosLenShapes(self, dtype):
test_string = [[b"ten", b"eleven", b"twelve"],
[b"thirteen", b"fourteen", b"fifteen"],
[b"sixteen", b"seventeen", b"eighteen"]]
position = np.array([[1, 2, 3]], dtype)
length = np.array([2, 3, 4], dtype)
# Should fail: position/length have different rank
with self.assertRaises(ValueError):
substr_op = string_ops.substr(test_string, position, length)
position = np.array([[1, 2, 3], [1, 2, 3], [1, 2, 3]], dtype)
length = np.array([[2, 3, 4]], dtype)
# Should fail: postion/length have different dimensionality
with self.assertRaises(ValueError):
substr_op = string_ops.substr(test_string, position, length)
def _testAll(self, dtype):
self._testScalarString(dtype)
self._testVectorStrings(dtype)
self._testMatrixStrings(dtype)
self._testElementWisePosLen(dtype)
self._testBroadcast(dtype)
self._testBadBroadcast(dtype)
self._testOutOfRangeError(dtype)
self._testMismatchPosLenShapes(dtype)
def testInt32(self):
self._testAll(np.int32)
def testInt64(self):
self._testAll(np.int64)
def testWrongDtype(self):
with self.test_session():
with self.assertRaises(TypeError):
string_ops.substr(b"test", 3.0, 1)
with self.assertRaises(TypeError):
string_ops.substr(b"test", 3, 1.0)
if __name__ == "__main__":
test.main()
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