
# Copyright 2022 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.

import argparse
import os
import subprocess

from packaging.version import Version, parse

from accelerate.commands.config.config_args import default_config_file, load_config_from_file


_lowerCamelCase					   ="""Run commands across TPU VMs for initial setup before running `accelerate launch`."""





def     _a					(						lowerCamelCase=None							):
 if subparsers is not None:
  lowerCamelCase		:	Optional[Any]							=      subparsers.add_parser("""tpu-config""",	description=_description							)
 else:
  lowerCamelCase		:	Tuple							=      argparse.ArgumentParser("""Accelerate tpu-config command""",	description=_description							)
 # Core arguments
 lowerCamelCase		:	Tuple							=      parser.add_argument_group(
     """Config Arguments""",	"""Arguments that can be configured through `accelerate config`."""							)
 config_args.add_argument(
     """--config_file""",	type=lowerCamelCase,	default=lowerCamelCase,	help="""Path to the config file to use for accelerate.""",	)
 config_args.add_argument(
     """--tpu_name""",	default=lowerCamelCase,	help="""The name of the TPU to use. If not specified, will use the TPU specified in the config file.""",	)
 config_args.add_argument(
     """--tpu_zone""",	default=lowerCamelCase,	help="""The zone of the TPU to use. If not specified, will use the zone specified in the config file.""",	)
 lowerCamelCase		:	List[str]							=      parser.add_argument_group("""TPU Arguments""",	"""Arguments for options ran inside the TPU."""							)
 pod_args.add_argument(
     """--use_alpha""",	action="""store_true""",	help="""Whether to use `gcloud alpha` when running the TPU training script instead of `gcloud`.""",	)
 pod_args.add_argument(
     """--command_file""",	default=lowerCamelCase,	help="""The path to the file containing the commands to run on the pod on startup.""",	)
 pod_args.add_argument(
     """--command""",	action="""append""",	nargs="""+""",	help="""A command to run on the pod. Can be passed multiple times.""",	)
 pod_args.add_argument(
     """--install_accelerate""",	action="""store_true""",	help="""Whether to install accelerate on the pod. Defaults to False.""",	)
 pod_args.add_argument(
     """--accelerate_version""",	default="""latest""",	help="""The version of accelerate to install on the pod. If not specified, will use the latest pypi version. Specify 'dev' to install from GitHub.""",	)
 pod_args.add_argument(
     """--debug""",	action="""store_true""",	help="""If set, will print the command that would be run instead of running it."""							)

 if subparsers is not None:
  parser.set_defaults(func=lowerCamelCase							)
 return parser





def     _a					(						lowerCamelCase							):
 lowerCamelCase		:	Any							=      None

 # Get the default from the config file if it exists.
 if args.config_file is not None or os.path.isfile(lowerCamelCase							):
  lowerCamelCase		:	List[Any]							=      load_config_from_file(args.config_file							)
  if not args.command_file and defaults.command_file is not None and not args.command:
   lowerCamelCase		:	int							=      defaults.command_file
  if not args.command and defaults.commands is not None:
   lowerCamelCase		:	Optional[int]							=      defaults.commands
  if not args.tpu_name:
   lowerCamelCase		:	List[str]							=      defaults.tpu_name
  if not args.tpu_zone:
   lowerCamelCase		:	int							=      defaults.tpu_zone
 if args.accelerate_version == "dev":
  lowerCamelCase		:	Dict							=      """git+https://github.com/huggingface/accelerate.git"""
 elif args.accelerate_version == "latest":
  lowerCamelCase		:	int							=      """accelerate -U"""
 elif isinstance(parse(args.accelerate_version							),	lowerCamelCase							):
  lowerCamelCase		:	Tuple							=      F'''accelerate=={args.accelerate_version}'''

 if not args.command_file and not args.command:
  raise ValueError("""You must specify either a command file or a command to run on the pod."""							)

 if args.command_file:
  with open(args.command_file,	"""r"""							) as f:
   lowerCamelCase		:	Dict							=      [f.read().splitlines()]

    # To turn list of lists into list of strings
 if isinstance(args.command[0],	lowerCamelCase							):
  lowerCamelCase		:	Optional[Any]							=      [line for cmd in args.command for line in cmd]
 # Default to the shared folder and install accelerate
 lowerCamelCase		:	Tuple							=      ["""cd /usr/share"""]
 if args.install_accelerate:
  new_cmd += [F'''pip install {args.accelerate_version}''']
 new_cmd += args.command
 lowerCamelCase		:	Optional[int]							=      """; """.join(lowerCamelCase							)

 # Then send it to gcloud
 # Eventually try to use google-api-core to do this instead of subprocess
 lowerCamelCase		:	str							=      ["""gcloud"""]
 if args.use_alpha:
  cmd += ["alpha"]
 cmd += [
     "compute",
     "tpus",
     "tpu-vm",
     "ssh",
     args.tpu_name,
     "--zone",
     args.tpu_zone,
     "--command",
     args.command,
     "--worker",
     "all",
 ]
 if args.debug:
  print(F'''Running {" ".join(lowerCamelCase							)}'''							)
  return
 subprocess.run(lowerCamelCase							)
 print("""Successfully setup pod."""							)





def     _a					(						):
 lowerCamelCase		:	int							=      tpu_command_parser()
 lowerCamelCase		:	int							=      parser.parse_args()

 tpu_command_launcher(lowerCamelCase							)






# 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,
)


_lowerCamelCase					   ="""pytorch_model.bin"""
_lowerCamelCase					   ="""pytorch_model.bin.index.json"""
_lowerCamelCase					   ="""adapter_config.json"""
_lowerCamelCase					   ="""adapter_model.bin"""
_lowerCamelCase					   ="""adapter_model.safetensors"""
_lowerCamelCase					   ="""tf_model.h5"""
_lowerCamelCase					   ="""tf_model.h5.index.json"""
_lowerCamelCase					   ="""model.ckpt"""
_lowerCamelCase					   ="""flax_model.msgpack"""
_lowerCamelCase					   ="""flax_model.msgpack.index.json"""
_lowerCamelCase					   ="""model.safetensors"""
_lowerCamelCase					   ="""model.safetensors.index.json"""
_lowerCamelCase					   ="""config.json"""
_lowerCamelCase					   ="""preprocessor_config.json"""
_lowerCamelCase					   =FEATURE_EXTRACTOR_NAME
_lowerCamelCase					   ="""generation_config.json"""
_lowerCamelCase					   ="""modelcard.json"""

_lowerCamelCase					   ="""▁"""
_lowerCamelCase					   =SENTENCEPIECE_UNDERLINE  # Kept for backward compatibility

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





def     _a					(						lowerCamelCase							):
 if version.parse(lowerCamelCase							) < version.parse(lowerCamelCase							):
  if "dev" in min_version:
   lowerCamelCase		:	Optional[int]							=      (
       """This example requires a source install from HuggingFace Transformers (see """
       """`https://huggingface.co/docs/transformers/installation#install-from-source`),"""
   )
  else:
   lowerCamelCase		:	int							=      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."""							)




