






'''simple docstring'''





# Copyright 2021 The HuggingFace Inc. 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 packaging import version

from .. import __version__
from .constants import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD, IMAGENET_STANDARD_MEAN, IMAGENET_STANDARD_STD
from .doc import (
    add_code_sample_docstrings,
    add_end_docstrings,
    add_start_docstrings,
    add_start_docstrings_to_model_forward,
    copy_func,
    replace_return_docstrings,
)
from .generic import (
    ContextManagers,
    ExplicitEnum,
    ModelOutput,
    PaddingStrategy,
    TensorType,
    add_model_info_to_auto_map,
    cached_property,
    can_return_loss,
    expand_dims,
    find_labels,
    flatten_dict,
    infer_framework,
    is_jax_tensor,
    is_numpy_array,
    is_tensor,
    is_tf_symbolic_tensor,
    is_tf_tensor,
    is_torch_device,
    is_torch_dtype,
    is_torch_tensor,
    reshape,
    squeeze,
    strtobool,
    tensor_size,
    to_numpy,
    to_py_obj,
    transpose,
    working_or_temp_dir,
)
from .hub import (
    CLOUDFRONT_DISTRIB_PREFIX,
    DISABLE_TELEMETRY,
    HF_MODULES_CACHE,
    HUGGINGFACE_CO_PREFIX,
    HUGGINGFACE_CO_RESOLVE_ENDPOINT,
    PYTORCH_PRETRAINED_BERT_CACHE,
    PYTORCH_TRANSFORMERS_CACHE,
    S3_BUCKET_PREFIX,
    TRANSFORMERS_CACHE,
    TRANSFORMERS_DYNAMIC_MODULE_NAME,
    EntryNotFoundError,
    PushToHubMixin,
    RepositoryNotFoundError,
    RevisionNotFoundError,
    cached_file,
    default_cache_path,
    define_sagemaker_information,
    download_url,
    extract_commit_hash,
    get_cached_models,
    get_file_from_repo,
    get_full_repo_name,
    has_file,
    http_user_agent,
    is_offline_mode,
    is_remote_url,
    move_cache,
    send_example_telemetry,
    try_to_load_from_cache,
)
from .import_utils import (
    ENV_VARS_TRUE_AND_AUTO_VALUES,
    ENV_VARS_TRUE_VALUES,
    TORCH_FX_REQUIRED_VERSION,
    USE_JAX,
    USE_TF,
    USE_TORCH,
    DummyObject,
    OptionalDependencyNotAvailable,
    _LazyModule,
    ccl_version,
    direct_transformers_import,
    get_torch_version,
    is_accelerate_available,
    is_apex_available,
    is_bitsandbytes_available,
    is_bsa_available,
    is_coloredlogs_available,
    is_cython_available,
    is_datasets_available,
    is_decord_available,
    is_detectrona_available,
    is_faiss_available,
    is_flax_available,
    is_ftfy_available,
    is_in_notebook,
    is_ipex_available,
    is_jieba_available,
    is_jumanpp_available,
    is_kenlm_available,
    is_keras_nlp_available,
    is_librosa_available,
    is_natten_available,
    is_ninja_available,
    is_onnx_available,
    is_openai_available,
    is_optimum_available,
    is_pandas_available,
    is_peft_available,
    is_phonemizer_available,
    is_protobuf_available,
    is_psutil_available,
    is_pyanvml_available,
    is_pyctcdecode_available,
    is_pytesseract_available,
    is_pytest_available,
    is_pytorch_quantization_available,
    is_rjieba_available,
    is_sacremoses_available,
    is_safetensors_available,
    is_sagemaker_dp_enabled,
    is_sagemaker_mp_enabled,
    is_scipy_available,
    is_sentencepiece_available,
    is_seqio_available,
    is_sklearn_available,
    is_soundfile_availble,
    is_spacy_available,
    is_speech_available,
    is_sudachi_available,
    is_tensorflow_probability_available,
    is_tensorflow_text_available,
    is_tfaonnx_available,
    is_tf_available,
    is_timm_available,
    is_tokenizers_available,
    is_torch_available,
    is_torch_bfaa_available,
    is_torch_bfaa_cpu_available,
    is_torch_bfaa_gpu_available,
    is_torch_compile_available,
    is_torch_cuda_available,
    is_torch_fx_available,
    is_torch_fx_proxy,
    is_torch_mps_available,
    is_torch_neuroncore_available,
    is_torch_tensorrt_fx_available,
    is_torch_tfaa_available,
    is_torch_tpu_available,
    is_torchaudio_available,
    is_torchdistx_available,
    is_torchdynamo_available,
    is_torchvision_available,
    is_training_run_on_sagemaker,
    is_vision_available,
    requires_backends,
    torch_only_method,
)


__A							:							Any  							=		'pytorch_model.bin'
__A							:							List[str]  							=		'pytorch_model.bin.index.json'
__A							:							List[Any]  							=		'adapter_config.json'
__A							:							str  							=		'adapter_model.bin'
__A							:							List[str]  							=		'adapter_model.safetensors'
__A							:							Any  							=		'tf_model.h5'
__A							:							str  							=		'tf_model.h5.index.json'
__A							:							Any  							=		'model.ckpt'
__A							:							Optional[int]  							=		'flax_model.msgpack'
__A							:							Dict  							=		'flax_model.msgpack.index.json'
__A							:							Dict  							=		'model.safetensors'
__A							:							Dict  							=		'model.safetensors.index.json'
__A							:							Union[str, Any]  							=		'config.json'
__A							:							Tuple  							=		'preprocessor_config.json'
__A							:							Tuple  							=		FEATURE_EXTRACTOR_NAME
__A							:							Dict  							=		'generation_config.json'
__A							:							Dict  							=		'modelcard.json'

__A							:							Optional[int]  							=		'▁'
__A							:							Any  							=		SENTENCEPIECE_UNDERLINE  # Kept for backward compatibility

__A							:							List[Any]  							=		[
    [[0, 1, 0, 1], [1, 0, 0, 1]]
] * 2  # Needs to have 0s and 1s only since XLM uses it for langs too.
__A							:							Tuple  							=		[[7, 6, 0, 0, 1], [1, 2, 3, 0, 0], [0, 0, 0, 4, 5]]
__A							:							Any  							=		[[1, 1, 1, 1, 1], [1, 1, 1, 0, 0], [0, 0, 0, 1, 1]]






def    lowerCamelCase_     (    lowercase__):





	if version.parse(_lowerCamelCase) < version.parse(_lowerCamelCase):
		if "dev" in min_version:
			lowerCamelCase__  =     (
			    "This example requires a source install from HuggingFace Transformers (see "
			    "`https://huggingface.co/docs/transformers/installation#install-from-source`),"
			)
		else:
			lowerCamelCase__  =     F'''This example requires a minimum version of {min_version},'''
		error_message += F''' but the version found is {__version__}.\n'''
		raise ImportError(
		    error_message
		    + "Check out https://github.com/huggingface/transformers/tree/main/examples#important-note for the examples corresponding to other "
		    "versions of HuggingFace Transformers.")









'''simple docstring'''





class 				lowercase       :


    '''simple docstring'''

    def __init__(					self     :     Union[str, Any]     )							->							None:

     '''simple docstring'''




     lowerCamelCase__  =     {}  # Mapping from char to TrieNode
     lowerCamelCase__  =     False

    def    a__				(					self     :     List[Any]				,     __lowerCamelCase     :     list[str]     )							->							None:

     '''simple docstring'''




     for word in words:
      self.insert(__lowerCamelCase     )

    def    a__				(					self     :     int				,     __lowerCamelCase     :     str     )							->							None:

     '''simple docstring'''




     lowerCamelCase__  =     self
     for char in word:
      if char not in curr.nodes:
       lowerCamelCase__  =     TrieNode()
      lowerCamelCase__  =     curr.nodes[char]
     lowerCamelCase__  =     True

    def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     str     )							->							bool:

     '''simple docstring'''




     lowerCamelCase__  =     self
     for char in word:
      if char not in curr.nodes:
       return False
      lowerCamelCase__  =     curr.nodes[char]
     return curr.is_leaf




    def    a__				(					self     :     Optional[Any]				,     __lowerCamelCase     :     str     )							->							None:

     '''simple docstring'''




     def _delete(__lowerCamelCase     :     TrieNode				,     __lowerCamelCase     :     str				,     __lowerCamelCase     :     int     ) -> bool:
      if index == len(__lowerCamelCase     ):
       # If word does not exist
       if not curr.is_leaf:
        return False
       lowerCamelCase__  =     False
       return len(curr.nodes     ) == 0
      lowerCamelCase__  =     word[index]
      lowerCamelCase__  =     curr.nodes.get(__lowerCamelCase     )
      # If char not in current trie node
      if not char_node:
       return False
      # Flag to check if node can be deleted
      lowerCamelCase__  =     _delete(__lowerCamelCase				,     __lowerCamelCase				,     index + 1     )
      if delete_curr:
       del curr.nodes[char]
       return len(curr.nodes     ) == 0
      return delete_curr

     _delete(self				,     __lowerCamelCase				,     0     )






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 if node.is_leaf:
  print(lowercase__				,     end=" ")

 for key, value in node.nodes.items():
  print_words(lowercase__				,     word + key)






def    lowerCamelCase_     (    ):
 lowerCamelCase__  =     "banana bananas bandana band apple all beast".split()
 lowerCamelCase__  =     TrieNode()
 root.insert_many(lowercase__)
 # print_words(root, "")
 assert all(root.find(lowercase__) for word in words)
 assert root.find("banana")
 assert not root.find("bandanas")
 assert not root.find("apps")
 assert root.find("apple")
 assert root.find("all")
 root.delete("all")
 assert not root.find("all")
 root.delete("banana")
 assert not root.find("banana")
 assert root.find("bananas")
 return True






def    lowerCamelCase_     (    lowercase__				,     lowercase__):
 print(str(lowercase__)				,     "works!" if passes else "doesn't work :(")






def    lowerCamelCase_     (    ):
 assert test_trie()






def    lowerCamelCase_     (    ):
 print_results("Testing trie functionality"				,     test_trie())


if __name__ == "__main__":
 main()

