# Copyright 2018 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 RegexFullMatch op from string_ops."""

from __future__ import absolute_import
from __future__ import division
from __future__ import print_function

from absl.testing import parameterized

from tensorflow.python.compat import compat
from tensorflow.python.framework import constant_op
from tensorflow.python.framework import dtypes
from tensorflow.python.ops import gen_string_ops
from tensorflow.python.ops import string_ops
from tensorflow.python.platform import test


@parameterized.parameters(
    (gen_string_ops.regex_full_match),
    (gen_string_ops.static_regex_full_match))
class RegexFullMatchOpVariantsTest(test.TestCase, parameterized.TestCase):

  def testRegexFullMatch(self, op):
    values = ["abaaba", "abcdabcde"]
    with self.cached_session():
      input_tensor = constant_op.constant(values, dtypes.string)
      matched = op(input_tensor, "a.*a").eval()
      self.assertAllEqual([True, False], matched)

  def testRegexFullMatchTwoDims(self, op):
    values = [["abaaba", "abcdabcde"], ["acdcba", "ebcda"]]
    with self.cached_session():
      input_tensor = constant_op.constant(values, dtypes.string)
      matched = op(input_tensor, "a.*a").eval()
      self.assertAllEqual([[True, False], [True, False]], matched)

  def testEmptyMatch(self, op):
    values = ["abc", "1"]
    with self.cached_session():
      input_tensor = constant_op.constant(values, dtypes.string)
      matched = op(input_tensor, "").eval()
      self.assertAllEqual([False, False], matched)

  def testInvalidPattern(self, op):
    values = ["abc", "1"]
    with self.cached_session():
      input_tensor = constant_op.constant(values, dtypes.string)
      invalid_pattern = "A["
      matched = op(input_tensor, invalid_pattern)
      with self.assertRaisesOpError("Invalid pattern"):
        matched.eval()


class RegexFullMatchOpTest(test.TestCase):

  def testRegexFullMatchDelegation(self):
    with compat.forward_compatibility_horizon(2018, 11, 1):
      with self.cached_session():
        input_tensor = constant_op.constant("foo", dtypes.string)
        pattern = "[a-z]"
        op = string_ops.regex_full_match(input_tensor, pattern)
        self.assertTrue(op.name.startswith("RegexFullMatch"), op.name)

        pattern_tensor = constant_op.constant("[a-z]*", dtypes.string)
        op_tensor = string_ops.regex_full_match(input_tensor, pattern_tensor)
        self.assertTrue(op_tensor.name.startswith("RegexFullMatch"), op.name)

  def testStaticRegexFullMatchDelegation(self):
    with compat.forward_compatibility_horizon(2018, 11, 20):
      with self.cached_session():
        input_tensor = constant_op.constant("foo", dtypes.string)
        pattern = "[a-z]*"
        op = string_ops.regex_full_match(input_tensor, pattern)
        self.assertTrue(op.name.startswith("StaticRegexFullMatch"), op.name)

        pattern_tensor = constant_op.constant("[a-z]*", dtypes.string)
        op_vec = string_ops.regex_full_match(input_tensor, pattern_tensor)
        self.assertTrue(op_vec.name.startswith("RegexFullMatch"), op.name)

if __name__ == "__main__":
  test.main()