


import math





def   _UpperCAmelCase       (     UpperCAmelCase      :			int      ):
      """simple docstring"""




      assert isinstance(UpperCAmelCase						,	UpperCAmelCase      ) and (
          number >= 0
      ), "'number' must been an int and positive"

      if 1 < number < 4:
            # 2 and 3 are primes
            return True
      elif number < 2 or not number % 2:
            # Negatives, 0, 1 and all even numbers are not primes
            return False

      __lowerCamelCase     :      Union[str, Any]       						=						range(3						,	int(math.sqrt(UpperCAmelCase      ) + 1      )						,	2      )
      return not any(not number % i for i in odd_numbers      )





def   _UpperCAmelCase       (     UpperCAmelCase      :			Union[str, Any]						,	UpperCAmelCase      :			int=1						,	**UpperCAmelCase      :			int      ):
      """simple docstring"""




      __lowerCamelCase     :      str       						=						factor * value
      __lowerCamelCase     :      int       						=						value

      while not is_prime(UpperCAmelCase      ):
            value += 1 if not ("desc" in kwargs and kwargs["desc"] is True) else -1

      if value == first_value_val:
            return next_prime(value + 1						,	**UpperCAmelCase      )
      return value







# 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

from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available


__UpperCamelCase    :						Any     =							{
    'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
    'processing_mgp_str': ['MgpstrProcessor'],
    'tokenization_mgp_str': ['MgpstrTokenizer'],
}

try:
    if not is_torch_available():
        raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
    pass
else:
    __UpperCamelCase    :						Tuple     =							[
        'MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST',
        'MgpstrModel',
        'MgpstrPreTrainedModel',
        'MgpstrForSceneTextRecognition',
    ]

if TYPE_CHECKING:
    from .configuration_mgp_str import MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP, MgpstrConfig
    from .processing_mgp_str import MgpstrProcessor
    from .tokenization_mgp_str import MgpstrTokenizer

    try:
        if not is_torch_available():
            raise OptionalDependencyNotAvailable()
    except OptionalDependencyNotAvailable:
        pass
    else:
        from .modeling_mgp_str import (
            MGP_STR_PRETRAINED_MODEL_ARCHIVE_LIST,
            MgpstrForSceneTextRecognition,
            MgpstrModel,
            MgpstrPreTrainedModel,
        )
else:
    import sys

    __UpperCamelCase    :						Optional[Any]     =							_LazyModule(__name__, globals()['__file__'], _import_structure, module_spec=__spec__)



