



# Copyright 2023 The HuggingFace Team. 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 typing import TYPE_CHECKING

# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available


_lowerCamelCase    :		str		      =    {
    """configuration_vivit""": ["""VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VivitConfig"""],
}
try:
			if not is_vision_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_lowerCamelCase    :		List[str]		      =    ["""VivitImageProcessor"""]


try:
			if not is_torch_available():
						raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
			pass
else:
			_lowerCamelCase    :		Tuple		      =    [
			    """VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST""",
			    """VivitModel""",
			    """VivitPreTrainedModel""",
			    """VivitForVideoClassification""",
			]


if TYPE_CHECKING:
			from .configuration_vivit import VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP, VivitConfig

			try:
						if not is_vision_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .image_processing_vivit import VivitImageProcessor

			try:
						if not is_torch_available():
									raise OptionalDependencyNotAvailable()
			except OptionalDependencyNotAvailable:
						pass
			else:
						from .modeling_vivit import (
						    VIVIT_PRETRAINED_MODEL_ARCHIVE_LIST,
						    VivitForVideoClassification,
						    VivitModel,
						    VivitPreTrainedModel,
						)


else:
			import sys

			_lowerCamelCase    :		List[Any]		      =    _LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)




_lowerCamelCase    :		Optional[Any]		      =    256
# Modulus to hash a string
_lowerCamelCase    :		Optional[Any]		      =    1_000_003

def        __a			(   __lowerCAmelCase      ,	__lowerCAmelCase   )     ->     bool:
					SCREAMING_SNAKE_CASE							:     Tuple						=				len(__lowerCAmelCase   )
					SCREAMING_SNAKE_CASE							:     Tuple						=				len(__lowerCAmelCase   )
					if p_len > t_len:
										return False

					SCREAMING_SNAKE_CASE							:     Dict						=				0
					SCREAMING_SNAKE_CASE							:     Tuple						=				0
					SCREAMING_SNAKE_CASE							:     Optional[Any]						=				1

					# Calculating the hash of pattern and substring of text
					for i in range(__lowerCAmelCase   ):
										SCREAMING_SNAKE_CASE							:     Tuple						=				(ord(pattern[i]   ) + p_hash * alphabet_size) % modulus
										SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				(ord(text[i]   ) + text_hash * alphabet_size) % modulus
										if i == p_len - 1:
															continue
										SCREAMING_SNAKE_CASE							:     Optional[Any]						=				(modulus_power * alphabet_size) % modulus

					for i in range(0      ,	t_len - p_len + 1   ):
										if text_hash == p_hash and text[i : i + p_len] == pattern:
															return True
										if i == t_len - p_len:
															continue
										# Calculate the https://en.wikipedia.org/wiki/Rolling_hash
										SCREAMING_SNAKE_CASE							:     int						=				(
										    (text_hash - ord(text[i]   ) * modulus_power) * alphabet_size
										    + ord(text[i + p_len]   )
										) % modulus
					return False

def        __a			(   )     ->     None:
					SCREAMING_SNAKE_CASE							:     Any						=				'abc1abc12'
					SCREAMING_SNAKE_CASE							:     str						=				'alskfjaldsabc1abc1abc12k23adsfabcabc'
					SCREAMING_SNAKE_CASE							:     List[str]						=				'alskfjaldsk23adsfabcabc'
					assert rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   ) and not rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   )

					# Test 2)
					SCREAMING_SNAKE_CASE							:     List[str]						=				'ABABX'
					SCREAMING_SNAKE_CASE							:     int						=				'ABABZABABYABABX'
					assert rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   )

					# Test 3)
					SCREAMING_SNAKE_CASE							:     int						=				'AAAB'
					SCREAMING_SNAKE_CASE							:     Tuple						=				'ABAAAAAB'
					assert rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   )

					# Test 4)
					SCREAMING_SNAKE_CASE							:     Tuple						=				'abcdabcy'
					SCREAMING_SNAKE_CASE							:     Optional[Any]						=				'abcxabcdabxabcdabcdabcy'
					assert rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   )

					# Test 5)
					SCREAMING_SNAKE_CASE							:     List[Any]						=				'Lü'
					SCREAMING_SNAKE_CASE							:     Optional[Any]						=				'Lüsai'
					assert rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   )
					SCREAMING_SNAKE_CASE							:     Union[str, Any]						=				'Lue'
					assert not rabin_karp(__lowerCAmelCase      ,	__lowerCAmelCase   )
					print('Success.'   )


if __name__ == "__main__":
			test_rabin_karp()