import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
  import PIL.Image

  from .features import FeatureType


SCREAMING_SNAKE_CASE			:						Optional[List[str]]				  =		None
SCREAMING_SNAKE_CASE			:						str				  =		"""<""" if sys.byteorder == """little""" else """>"""
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
SCREAMING_SNAKE_CASE			:						str				  =		[
    np.dtype("""|b1"""),
    np.dtype("""|u1"""),
    np.dtype("""<u2"""),
    np.dtype(""">u2"""),
    np.dtype("""<i2"""),
    np.dtype(""">i2"""),
    np.dtype("""<u4"""),
    np.dtype(""">u4"""),
    np.dtype("""<i4"""),
    np.dtype(""">i4"""),
    np.dtype("""<f4"""),
    np.dtype(""">f4"""),
    np.dtype("""<f8"""),
    np.dtype(""">f8"""),
]
@dataclass
class  A_			:
  _SCREAMING_SNAKE_CASE     					=      True
  _SCREAMING_SNAKE_CASE     					=      None
  # Automatically constructed
  _SCREAMING_SNAKE_CASE     					=      "PIL.Image.Image"
  _SCREAMING_SNAKE_CASE     					=      pa.struct({"""bytes""": pa.binary(), """path""": pa.string()}			)
  _SCREAMING_SNAKE_CASE     					=      field(default="""Image"""      ,							init=a_      ,							repr=a_			)

  def __call__(		self			:   Any							):
   return self.pa_type

  def 		_UpperCAmelCase (		self			:   Any  ,				__SCREAMING_SNAKE_CASE			:   Union[str, bytes, dict, np.ndarray, "PIL.Image.Image"]							):
   if config.PIL_AVAILABLE:
    import PIL.Image
   else:
    raise ImportError("To support encoding images, please install 'Pillow'."							)

   if isinstance(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							):
    __a							=	np.array(__SCREAMING_SNAKE_CASE							)

   if isinstance(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							):
    return {"path": value, "bytes": None}
   elif isinstance(__SCREAMING_SNAKE_CASE  ,				__SCREAMING_SNAKE_CASE							):
    return {"path": None, "bytes": value}
   elif isinstance(__SCREAMING_SNAKE_CASE  ,				np.ndarray							):
    # convert the image array to PNG/TIFF bytes
    return encode_np_array(__SCREAMING_SNAKE_CASE							)
   elif isinstance(__SCREAMING_SNAKE_CASE  ,				PIL.Image.Image							):
    # convert the PIL image to bytes (default format is PNG/TIFF)
    return encode_pil_image(__SCREAMING_SNAKE_CASE							)
   elif value.get("path"							) is not None and os.path.isfile(value["path"]							):
    # we set "bytes": None to not duplicate the data if they're already available locally
    return {"bytes": None, "path": value.get("path"							)}
   elif value.get("bytes"							) is not None or value.get("path"							) is not None:
    # store the image bytes, and path is used to infer the image format using the file extension
    return {"bytes": value.get("bytes"							), "path": value.get("path"							)}
   else:
    raise ValueError(
        f"""An image sample should have one of 'path' or 'bytes' but they are missing or None in {value}."""							)

  def 		_UpperCAmelCase (		self			:   str  ,				__SCREAMING_SNAKE_CASE			:   dict  ,				__SCREAMING_SNAKE_CASE			:   Union[str, Any]=None							):
   if not self.decode:
    raise RuntimeError("Decoding is disabled for this feature. Please use Image(decode=True) instead."							)

   if config.PIL_AVAILABLE:
    import PIL.Image
   else:
    raise ImportError("To support decoding images, please install 'Pillow'."							)

   if token_per_repo_id is None:
    __a							=	{}

   __a							,  __a							=	value["path"], value["bytes"]
   if bytes_ is None:
    if path is None:
     raise ValueError(f"""An image should have one of 'path' or 'bytes' but both are None in {value}."""							)
    else:
     if is_local_path(__SCREAMING_SNAKE_CASE							):
      __a							=	PIL.Image.open(__SCREAMING_SNAKE_CASE							)
     else:
      __a							=	path.split("::"							)[-1]
      try:
       __a							=	string_to_dict(__SCREAMING_SNAKE_CASE  ,				config.HUB_DATASETS_URL							)["repo_id"]
       __a							=	token_per_repo_id.get(__SCREAMING_SNAKE_CASE							)
      except ValueError:
       __a							=	None
      with xopen(__SCREAMING_SNAKE_CASE  ,				"rb"  ,				use_auth_token=__SCREAMING_SNAKE_CASE							) as f:
       __a							=	BytesIO(f.read()							)
      __a							=	PIL.Image.open(bytes_							)
   else:
    __a							=	PIL.Image.open(BytesIO(bytes_							)							)
   image.load()  # to avoid "Too many open files" errors
   return image

  def 		_UpperCAmelCase (		self			:   Union[str, Any]							):
   from .features import Value

   return (
       self
       if self.decode
       else {
           "bytes": Value("binary"							),
           "path": Value("string"							),
       }
   )

  def 		_UpperCAmelCase (		self			:   str  ,				__SCREAMING_SNAKE_CASE			:   Union[pa.StringArray, pa.StructArray, pa.ListArray]							):
   if pa.types.is_string(storage.type							):
    __a							=	pa.array([None] * len(__SCREAMING_SNAKE_CASE							)  ,				type=pa.binary()							)
    __a							=	pa.StructArray.from_arrays([bytes_array, storage]  ,				["bytes", "path"]  ,				mask=storage.is_null()							)
   elif pa.types.is_binary(storage.type							):
    __a							=	pa.array([None] * len(__SCREAMING_SNAKE_CASE							)  ,				type=pa.string()							)
    __a							=	pa.StructArray.from_arrays([storage, path_array]  ,				["bytes", "path"]  ,				mask=storage.is_null()							)
   elif pa.types.is_struct(storage.type							):
    if storage.type.get_field_index("bytes"							) >= 0:
     __a							=	storage.field("bytes"							)
    else:
     __a							=	pa.array([None] * len(__SCREAMING_SNAKE_CASE							)  ,				type=pa.binary()							)
    if storage.type.get_field_index("path"							) >= 0:
     __a							=	storage.field("path"							)
    else:
     __a							=	pa.array([None] * len(__SCREAMING_SNAKE_CASE							)  ,				type=pa.string()							)
    __a							=	pa.StructArray.from_arrays([bytes_array, path_array]  ,				["bytes", "path"]  ,				mask=storage.is_null()							)
   elif pa.types.is_list(storage.type							):
    __a							=	pa.array(
        [encode_np_array(np.array(__SCREAMING_SNAKE_CASE							)							)["bytes"] if arr is not None else None for arr in storage.to_pylist()]  ,				type=pa.binary()  ,				)
    __a							=	pa.array([None] * len(__SCREAMING_SNAKE_CASE							)  ,				type=pa.string()							)
    __a							=	pa.StructArray.from_arrays(
        [bytes_array, path_array]  ,				["bytes", "path"]  ,				mask=bytes_array.is_null()							)
   return array_cast(__SCREAMING_SNAKE_CASE  ,				self.pa_type							)

  def 		_UpperCAmelCase (		self			:   int  ,				__SCREAMING_SNAKE_CASE			:   pa.StructArray							):

   @no_op_if_value_is_null
   def path_to_bytes(__SCREAMING_SNAKE_CASE			:   Optional[int]							):
    with xopen(__SCREAMING_SNAKE_CASE  ,				"rb"							) as f:
     __a							=	f.read()
    return bytes_

   __a							=	pa.array(
       [
           (path_to_bytes(x["path"]							) if x["bytes"] is None else x["bytes"]) if x is not None else None
           for x in storage.to_pylist()
       ]  ,				type=pa.binary()  ,				)
   __a							=	pa.array(
       [os.path.basename(__SCREAMING_SNAKE_CASE							) if path is not None else None for path in storage.field("path"							).to_pylist()]  ,				type=pa.string()  ,				)
   __a							=	pa.StructArray.from_arrays([bytes_array, path_array]  ,				["bytes", "path"]  ,				mask=bytes_array.is_null()							)
   return array_cast(__SCREAMING_SNAKE_CASE  ,				self.pa_type							)



def 	__A		(      ):



 """simple docstring"""


 if config.PIL_AVAILABLE:
  import PIL.Image
 else:
  raise ImportError("To support encoding images, please install 'Pillow'."       )

 global _IMAGE_COMPRESSION_FORMATS
 if _IMAGE_COMPRESSION_FORMATS is None:
  PIL.Image.init()
  __a							=	list(set(PIL.Image.OPEN.keys()       ) & set(PIL.Image.SAVE.keys()       )       )
 return _IMAGE_COMPRESSION_FORMATS



def 	__A		(      _A       ):



 """simple docstring"""


 __a							=	BytesIO()
 if image.format in list_image_compression_formats():
  __a							=	image.format
 else:
  __a							=	"PNG" if image.mode in ["1", "L", "LA", "RGB", "RGBA"] else "TIFF"
 image.save(_A				,					format=_A       )
 return buffer.getvalue()



def 	__A		(      _A       ):



 """simple docstring"""


 if hasattr(_A				,					"filename"       ) and image.filename != "":
  return {"path": image.filename, "bytes": None}
 else:
  return {"path": None, "bytes": image_to_bytes(_A       )}



def 	__A		(      _A       ):



 """simple docstring"""


 if config.PIL_AVAILABLE:
  import PIL.Image
 else:
  raise ImportError("To support encoding images, please install 'Pillow'."       )

 __a							=	array.dtype
 __a							=	dtype.byteorder if dtype.byteorder != "=" else _NATIVE_BYTEORDER
 __a							=	dtype.kind
 __a							=	dtype.itemsize

 __a							=	None

 # Multi-channel array case (only np.dtype("|u1") is allowed)
 if array.shape[2:]:
  __a							=	np.dtype("|u1"       )
  if dtype_kind not in ["u", "i"]:
   raise TypeError(
       f"""Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays."""       )
  if dtype is not dest_dtype:
   warnings.warn(f"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"""       )
    # Exact match
 elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
  __a							=	dtype
 else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
  while dtype_itemsize >= 1:
   __a							=	dtype_byteorder + dtype_kind + str(_A       )
   __a							=	np.dtype(_A       )
   if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
    warnings.warn(f"""Downcasting array dtype {dtype} to {dest_dtype} to be compatible with 'Pillow'"""       )
    break
   else:
    dtype_itemsize //= 2

 if dest_dtype is None:
  raise TypeError(
      f"""Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}"""       )
 __a							=	PIL.Image.fromarray(array.astype(_A       )       )
 return {"path": None, "bytes": image_to_bytes(_A       )}






def 	__A		(      _A       ):



 """simple docstring"""


 if config.PIL_AVAILABLE:
  import PIL.Image
 else:
  raise ImportError("To support encoding images, please install 'Pillow'."       )

 if objs:
  __a							,  __a							=	first_non_null_value(_A       )
  if isinstance(_A				,					_A       ):
   return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
  if isinstance(_A				,					np.ndarray       ):
   __a							=	no_op_if_value_is_null(_A       )
   return [obj_to_image_dict_func(_A       ) for obj in objs]
  elif isinstance(_A				,					PIL.Image.Image       ):
   __a							=	no_op_if_value_is_null(_A       )
   return [obj_to_image_dict_func(_A       ) for obj in objs]
  else:
   return objs
 else:
  return objs



# Copyright 2021 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 argparse import ArgumentParser

from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.commands.tpu import tpu_command_parser



def 	__A		(      ):



 """simple docstring"""


 __a							=	ArgumentParser("Accelerate CLI tool"				,					usage="accelerate <command> [<args>]"				,					allow_abbrev=_A       )
 __a							=	parser.add_subparsers(help="accelerate command helpers"       )

 # Register commands
 get_config_parser(subparsers=_A       )
 env_command_parser(subparsers=_A       )
 launch_command_parser(subparsers=_A       )
 tpu_command_parser(subparsers=_A       )
 test_command_parser(subparsers=_A       )

 # Let's go
 __a							=	parser.parse_args()

 if not hasattr(_A				,					"func"       ):
  parser.print_help()
  exit(1       )

 # Run
 args.func(_A       )


if __name__ == "__main__":
  main()


