
import os
from pathlib import Path
from unittest.mock import patch

import pytest
import zstandard as zstd

from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
    OfflineModeIsEnabled,
    cached_path,
    fsspec_get,
    fsspec_head,
    ftp_get,
    ftp_head,
    get_from_cache,
    http_get,
    http_head,
)


lowerCamelCase__     :		Dict        = """\
    Text data.
    Second line of data."""

lowerCamelCase__     :		List[Any]        = """file"""

@pytest.fixture(scope="""session""" )
def 		UpperCamelCase						(   lowercase_ )		->						Dict:


  '''simple docstring'''






  lowercase__	: List[Any]     		=   tmp_path_factory.mktemp("""data""" ) / (FILE_PATH + """.zstd""")
  lowercase__	: Optional[int]     		=   bytes(lowercase_			,			"""utf-8""" )
  with zstd.open(lowercase_			,			"""wb""" ) as f:
    f.write(lowercase_ )
  return path

@pytest.fixture
def 		UpperCamelCase						(   lowercase_ )		->						str:


  '''simple docstring'''






  with open(os.path.join(tmpfs.local_root_dir			,			lowercase_ )			,			"""w""" ) as f:
    f.write(lowercase_ )
  return FILE_PATH

@pytest.mark.parametrize("""compression_format"""			,			["""gzip""", """xz""", """zstd"""] )
def 		UpperCamelCase						(   lowercase_			,			lowercase_			,			lowercase_			,			lowercase_			,			lowercase_			,			lowercase_ )		->						Any:


  '''simple docstring'''






  lowercase__	: Dict     		=   {"""gzip""": gz_file, """xz""": xz_file, """zstd""": zstd_path}
  lowercase__	: Tuple     		=   input_paths[compression_format]
  lowercase__	: int     		=   tmp_path / """cache"""
  lowercase__	: int     		=   DownloadConfig(cache_dir=lowercase_			,			extract_compressed_file=lowercase_ )
  lowercase__	: Optional[int]     		=   cached_path(lowercase_			,			download_config=lowercase_ )
  with open(lowercase_ ) as f:
    lowercase__	: str     		=   f.read()
  with open(lowercase_ ) as f:
    lowercase__	: Dict     		=   f.read()
  assert extracted_file_content == expected_file_content

@pytest.mark.parametrize("""default_extracted"""			,			[True, False] )
@pytest.mark.parametrize("""default_cache_dir"""			,			[True, False] )
def 		UpperCamelCase						(   lowercase_			,			lowercase_			,			lowercase_			,			lowercase_			,			lowercase_ )		->						int:


  '''simple docstring'''






  lowercase__	: Optional[int]     		=   """custom_cache"""
  lowercase__	: Optional[Any]     		=   """custom_extracted_dir"""
  lowercase__	: List[str]     		=   tmp_path / """custom_extracted_path"""
  if default_extracted:
    lowercase__	: str     		=   ("""downloads""" if default_cache_dir else custom_cache_dir, """extracted""")
  else:
    monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_DIR"""			,			lowercase_ )
    monkeypatch.setattr("""datasets.config.EXTRACTED_DATASETS_PATH"""			,			str(lowercase_ ) )
    lowercase__	: Optional[int]     		=   custom_extracted_path.parts[-2:] if default_cache_dir else (custom_cache_dir, custom_extracted_dir)

  lowercase__	: Union[str, Any]     		=   xz_file
  lowercase__	: Union[str, Any]     		=   (
      DownloadConfig(extract_compressed_file=lowercase_ )
      if default_cache_dir
      else DownloadConfig(cache_dir=tmp_path / custom_cache_dir			,			extract_compressed_file=lowercase_ )
  )
  lowercase__	: Dict     		=   cached_path(lowercase_			,			download_config=lowercase_ )
  assert Path(lowercase_ ).parent.parts[-2:] == expected

def 		UpperCamelCase						(   lowercase_ )		->						Any:


  '''simple docstring'''






  lowercase__	: List[str]     		=   str(Path(lowercase_ ).resolve() )
  assert cached_path(lowercase_ ) == text_file
  # relative path
  lowercase__	: Optional[Any]     		=   str(Path(lowercase_ ).resolve().relative_to(Path(os.getcwd() ) ) )
  assert cached_path(lowercase_ ) == text_file

def 		UpperCamelCase						(   lowercase_ )		->						List[Any]:


  '''simple docstring'''






  lowercase__	: str     		=   str(tmp_path.resolve() / """__missing_file__.txt""" )
  with pytest.raises(lowercase_ ):
    cached_path(lowercase_ )
  # relative path
  lowercase__	: Optional[Any]     		=   """./__missing_file__.txt"""
  with pytest.raises(lowercase_ ):
    cached_path(lowercase_ )

def 		UpperCamelCase						(   lowercase_ )		->						Any:


  '''simple docstring'''






  lowercase__	: Optional[int]     		=   get_from_cache(F'tmp://{tmpfs_file}' )
  with open(lowercase_ ) as f:
    lowercase__	: Union[str, Any]     		=   f.read()
  assert output_file_content == FILE_CONTENT

@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,			lowercase_ )
def 		UpperCamelCase						(   )		->						Optional[Any]:


  '''simple docstring'''






  with pytest.raises(lowercase_ ):
    cached_path("""https://huggingface.co""" )

@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,			lowercase_ )
def 		UpperCamelCase						(   lowercase_ )		->						List[Any]:


  '''simple docstring'''






  lowercase__	: Optional[int]     		=   tmp_path_factory.mktemp("""data""" ) / """file.html"""
  with pytest.raises(lowercase_ ):
    http_get("""https://huggingface.co"""			,			temp_file=lowercase_ )
  with pytest.raises(lowercase_ ):
    http_head("""https://huggingface.co""" )

@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,			lowercase_ )
def 		UpperCamelCase						(   lowercase_ )		->						Optional[int]:


  '''simple docstring'''






  lowercase__	: Union[str, Any]     		=   tmp_path_factory.mktemp("""data""" ) / """file.html"""
  with pytest.raises(lowercase_ ):
    ftp_get("""ftp://huggingface.co"""			,			temp_file=lowercase_ )
  with pytest.raises(lowercase_ ):
    ftp_head("""ftp://huggingface.co""" )



@patch("""datasets.config.HF_DATASETS_OFFLINE"""			,			lowercase_ )
def 		UpperCamelCase						(   lowercase_ )		->						str:


  '''simple docstring'''






  lowercase__	: Dict     		=   tmp_path_factory.mktemp("""data""" ) / """file.html"""
  with pytest.raises(lowercase_ ):
    fsspec_get("""s3://huggingface.co"""			,			temp_file=lowercase_ )
  with pytest.raises(lowercase_ ):
    fsspec_head("""s3://huggingface.co""" )








from typing import Optional, Union

import numpy as np

from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_images
from ...utils import TensorType, logging


lowerCamelCase__     :		Union[str, Any]        = logging.get_logger(__name__)



class    _snake_case (						UpperCAmelCase_				):
 __lowerCAmelCase	:  Any	   =      ['pixel_values']


 def __init__(       self       ,	SCREAMING_SNAKE_CASE_ = True       ,	SCREAMING_SNAKE_CASE_ = 1 / 2_55       ,	SCREAMING_SNAKE_CASE_ = True       ,	SCREAMING_SNAKE_CASE_ = 8       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   super().__init__(**SCREAMING_SNAKE_CASE_)

   lowercase__	: List[str]     		=   do_rescale
   lowercase__	: List[Any]     		=   rescale_factor
   lowercase__	: Tuple     		=   do_pad
   lowercase__	: Optional[Any]     		=   pad_size


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = None       ,	**SCREAMING_SNAKE_CASE_):


   '''simple docstring'''




   return rescale(SCREAMING_SNAKE_CASE_       ,	scale=SCREAMING_SNAKE_CASE_       ,	data_format=SCREAMING_SNAKE_CASE_       ,	**SCREAMING_SNAKE_CASE_)


 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = None):


   '''simple docstring'''




   lowercase__		,     lowercase__	: Optional[int]     		=   get_image_size(SCREAMING_SNAKE_CASE_)
   lowercase__	: Optional[Any]     		=   (old_height // size + 1) * size - old_height
   lowercase__	: str     		=   (old_width // size + 1) * size - old_width

   return pad(SCREAMING_SNAKE_CASE_       ,	((0, pad_height), (0, pad_width))       ,	mode="""symmetric"""       ,	data_format=SCREAMING_SNAKE_CASE_)



 def   lowercase__  (       self       ,	SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = None       ,	SCREAMING_SNAKE_CASE_ = ChannelDimension.FIRST       ,	**SCREAMING_SNAKE_CASE_       ,	):


   '''simple docstring'''




   lowercase__	: Union[str, Any]     		=   do_rescale if do_rescale is not None else self.do_rescale
   lowercase__	: int     		=   rescale_factor if rescale_factor is not None else self.rescale_factor
   lowercase__	: Union[str, Any]     		=   do_pad if do_pad is not None else self.do_pad
   lowercase__	: Optional[Any]     		=   pad_size if pad_size is not None else self.pad_size

   lowercase__	: str     		=   make_list_of_images(SCREAMING_SNAKE_CASE_)

   if not valid_images(SCREAMING_SNAKE_CASE_):
     raise ValueError(
         """Invalid image type. Must be of type PIL.Image.Image, numpy.ndarray, """
         """torch.Tensor, tf.Tensor or jax.ndarray.""")

   if do_rescale and rescale_factor is None:
     raise ValueError("""Rescale factor must be specified if do_rescale is True.""")

   # All transformations expect numpy arrays.
   lowercase__	: List[Any]     		=   [to_numpy_array(SCREAMING_SNAKE_CASE_) for image in images]

   if do_rescale:
     lowercase__	: str     		=   [self.rescale(image=SCREAMING_SNAKE_CASE_       ,	scale=SCREAMING_SNAKE_CASE_) for image in images]

   if do_pad:
     lowercase__	: List[str]     		=   [self.pad(SCREAMING_SNAKE_CASE_       ,	size=SCREAMING_SNAKE_CASE_) for image in images]

   lowercase__	: Optional[Any]     		=   [to_channel_dimension_format(SCREAMING_SNAKE_CASE_       ,	SCREAMING_SNAKE_CASE_) for image in images]

   lowercase__	: Dict     		=   {"""pixel_values""": images}
   return BatchFeature(data=SCREAMING_SNAKE_CASE_       ,	tensor_type=SCREAMING_SNAKE_CASE_)






