






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


snake_case    				=		None
snake_case    				=		"""<""" 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
snake_case    				=		[
    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  SCREAMING_SNAKE_CASE			:
     '''simple docstring'''


     UpperCamelCase_							:		bool			=	True
     UpperCamelCase_							:		Optional[str]			=	None
     # Automatically constructed
     UpperCamelCase_							:		ClassVar[str]			=	"PIL.Image.Image"
     UpperCamelCase_							:		ClassVar[Any]			=	pa.struct({'''bytes''': pa.binary(), '''path''': pa.string()}					)
     UpperCamelCase_							:		str			=	field(default='''Image'''      ,		init=lowerCAmelCase      ,		repr=lowerCAmelCase					)


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


     def 				_A       (				self       :	str					, UpperCAmelCase_       :	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(UpperCAmelCase_					, UpperCAmelCase_      ):
         SCREAMING_SNAKE_CASE       :      Optional[Any]							=    np.array(UpperCAmelCase_      )

       if isinstance(UpperCAmelCase_					, UpperCAmelCase_      ):
         return {"path": value, "bytes": None}
       elif isinstance(UpperCAmelCase_					, UpperCAmelCase_      ):
         return {"path": None, "bytes": value}
       elif isinstance(UpperCAmelCase_					, np.ndarray      ):
         # convert the image array to PNG/TIFF bytes
         return encode_np_array(UpperCAmelCase_      )
       elif isinstance(UpperCAmelCase_					, PIL.Image.Image      ):
         # convert the PIL image to bytes (default format is PNG/TIFF)
         return encode_pil_image(UpperCAmelCase_      )
       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 				_A       (				self       :	Tuple					, UpperCAmelCase_       :	dict					, UpperCAmelCase_       :	Tuple=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:
         SCREAMING_SNAKE_CASE       :      Tuple							=    {}

       SCREAMING_SNAKE_CASE						,  SCREAMING_SNAKE_CASE       :      Optional[int]							=    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(UpperCAmelCase_      ):
             SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    PIL.Image.open(UpperCAmelCase_      )
           else:
             SCREAMING_SNAKE_CASE       :      Tuple							=    path.split("::"      )[-1]
             try:
               SCREAMING_SNAKE_CASE       :      List[str]							=    string_to_dict(UpperCAmelCase_					, config.HUB_DATASETS_URL      )["repo_id"]
               SCREAMING_SNAKE_CASE       :      int							=    token_per_repo_id.get(UpperCAmelCase_      )
             except ValueError:
               SCREAMING_SNAKE_CASE       :      Optional[Any]							=    None
             with xopen(UpperCAmelCase_					, "rb"					, use_auth_token=UpperCAmelCase_      ) as f:
               SCREAMING_SNAKE_CASE       :      int							=    BytesIO(f.read()      )
             SCREAMING_SNAKE_CASE       :      List[str]							=    PIL.Image.open(bytes_      )
       else:
         SCREAMING_SNAKE_CASE       :      Optional[int]							=    PIL.Image.open(BytesIO(bytes_      )      )
       image.load()  # to avoid "Too many open files" errors
       return image


     def 				_A       (				self       :	int      ):
       from .features import Value

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


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






     def 				_A       (				self       :	int					, UpperCAmelCase_       :	pa.StructArray      ):

       @no_op_if_value_is_null
       def path_to_bytes(UpperCAmelCase_       :	List[Any]      ):
         with xopen(UpperCAmelCase_					, "rb"      ) as f:
           SCREAMING_SNAKE_CASE       :      Tuple							=    f.read()
         return bytes_

       SCREAMING_SNAKE_CASE       :      List[Any]							=    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()					, )
       SCREAMING_SNAKE_CASE       :      Dict							=    pa.array(
           [os.path.basename(UpperCAmelCase_      ) if path is not None else None for path in storage.field("path"      ).to_pylist()]					, type=pa.string()					, )
       SCREAMING_SNAKE_CASE       :      Dict							=    pa.StructArray.from_arrays([bytes_array, path_array]					, ["bytes", "path"]					, mask=bytes_array.is_null()      )
       return array_cast(UpperCAmelCase_					, self.pa_type      )





def   lowerCamelCase__			(     ):

  """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()
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    list(set(PIL.Image.OPEN.keys()				) & set(PIL.Image.SAVE.keys()				)				)
  return _IMAGE_COMPRESSION_FORMATS


def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






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


def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






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


def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






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

  SCREAMING_SNAKE_CASE       :      Optional[Any]							=    array.dtype
  SCREAMING_SNAKE_CASE       :      List[Any]							=    dtype.byteorder if dtype.byteorder != "=" else _NATIVE_BYTEORDER
  SCREAMING_SNAKE_CASE       :      Optional[Any]							=    dtype.kind
  SCREAMING_SNAKE_CASE       :      Tuple							=    dtype.itemsize

  SCREAMING_SNAKE_CASE       :      Optional[int]							=    None

  # Multi-channel array case (only np.dtype("|u1") is allowed)
  if array.shape[2:]:
    SCREAMING_SNAKE_CASE       :      Optional[Any]							=    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:
    SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    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:
      SCREAMING_SNAKE_CASE       :      Optional[Any]							=    dtype_byteorder + dtype_kind + str(lowercase				)
      SCREAMING_SNAKE_CASE       :      Any							=    np.dtype(lowercase				)
      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}'''				)
  SCREAMING_SNAKE_CASE       :      Optional[Any]							=    PIL.Image.fromarray(array.astype(lowercase				)				)
  return {"path": None, "bytes": image_to_bytes(lowercase				)}


def   lowerCamelCase__			(     lowercase				):

  """simple docstring"""






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

  if objs:
    SCREAMING_SNAKE_CASE						,  SCREAMING_SNAKE_CASE       :      str							=    first_non_null_value(lowercase				)
    if isinstance(lowercase						,     lowercase				):
      return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
    if isinstance(lowercase						,     np.ndarray				):
      SCREAMING_SNAKE_CASE       :      Optional[int]							=    no_op_if_value_is_null(lowercase				)
      return [obj_to_image_dict_func(lowercase				) for obj in objs]
    elif isinstance(lowercase						,     PIL.Image.Image				):
      SCREAMING_SNAKE_CASE       :      Union[str, Any]							=    no_op_if_value_is_null(lowercase				)
      return [obj_to_image_dict_func(lowercase				) for obj in objs]
    else:
      return objs
  else:
    return objs














# Copyright 2022 The HuggingFace Team and The OpenBMB 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_tokenizers_available, is_torch_available


snake_case    				=		{
    """configuration_cpmant""": ["""CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CpmAntConfig"""],
    """tokenization_cpmant""": ["""CpmAntTokenizer"""],
}

try:
   if not is_torch_available():
      raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
   pass
else:
   snake_case    				=		[
       """CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST""",
       """CpmAntForCausalLM""",
       """CpmAntModel""",
       """CpmAntPreTrainedModel""",
   ]


if TYPE_CHECKING:
   from .configuration_cpmant import CPMANT_PRETRAINED_CONFIG_ARCHIVE_MAP, CpmAntConfig
   from .tokenization_cpmant import CpmAntTokenizer

   try:
      if not is_torch_available():
         raise OptionalDependencyNotAvailable()
   except OptionalDependencyNotAvailable:
      pass
   else:
      from .modeling_cpmant import (
          CPMANT_PRETRAINED_MODEL_ARCHIVE_LIST,
          CpmAntForCausalLM,
          CpmAntModel,
          CpmAntPreTrainedModel,
      )


else:
   import sys

   snake_case    				=		_LazyModule(__name__, globals()["""__file__"""], _import_structure, module_spec=__spec__)






