

import csv
import os

import pytest

from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.csv import CsvDatasetReader, CsvDatasetWriter

from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases




def      UpperCAmelCase__							(     _A :					int      , _A :					str				):





  '''simple docstring'''







  assert isinstance(_A      , _A				)
  assert dataset.num_rows == 4
  assert dataset.num_columns == 3
  assert dataset.column_names == ["col_1", "col_2", "col_3"]
  for feature, expected_dtype in expected_features.items():
    assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('''keep_in_memory'''      , [False, True]				)
def      UpperCAmelCase__							(     _A :					str      , _A :					Dict      , _A :					Optional[Any]				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    a__    =CsvDatasetReader(_A      , cache_dir=_A      , keep_in_memory=_A				).read()
  _check_csv_dataset(_A      , _A				)




@pytest.mark.parametrize(
    '''features'''      , [
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ]      , )
def      UpperCAmelCase__							(     _A :					Dict      , _A :					Optional[int]      , _A :					Tuple				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  a__    =features.copy() if features else default_expected_features
  a__    =(
      Features({feature: Value(_A				) for feature, dtype in features.items()}				) if features is not None else None
  )
  a__    =CsvDatasetReader(_A      , features=_A      , cache_dir=_A				).read()
  _check_csv_dataset(_A      , _A				)




@pytest.mark.parametrize('''split'''      , [None, NamedSplit('''train'''				), '''train''', '''test''']				)
def      UpperCAmelCase__							(     _A :					List[str]      , _A :					List[str]      , _A :					Optional[int]				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  a__    =CsvDatasetReader(_A      , cache_dir=_A      , split=_A				).read()
  _check_csv_dataset(_A      , _A				)
  assert dataset.split == split if split else "train"




@pytest.mark.parametrize('''path_type'''      , [str, list]				)
def      UpperCAmelCase__							(     _A :					Optional[int]      , _A :					int      , _A :					Union[str, Any]				):





  '''simple docstring'''







  if issubclass(_A      , _A				):
    a__    =csv_path
  elif issubclass(_A      , _A				):
    a__    =[csv_path]
  a__    =tmp_path / '''cache'''
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  a__    =CsvDatasetReader(_A      , cache_dir=_A				).read()
  _check_csv_dataset(_A      , _A				)




def      UpperCAmelCase__							(     _A :					Union[str, Any]      , _A :					List[str]      , _A :					str=("train",)				):





  '''simple docstring'''







  assert isinstance(_A      , _A				)
  for split in splits:
    a__    =dataset_dict[split]
    assert dataset.num_rows == 4
    assert dataset.num_columns == 3
    assert dataset.column_names == ["col_1", "col_2", "col_3"]
    for feature, expected_dtype in expected_features.items():
      assert dataset.features[feature].dtype == expected_dtype




@pytest.mark.parametrize('''keep_in_memory'''      , [False, True]				)
def      UpperCAmelCase__							(     _A :					str      , _A :					Optional[int]      , _A :					int				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  with assert_arrow_memory_increases() if keep_in_memory else assert_arrow_memory_doesnt_increase():
    a__    =CsvDatasetReader({'''train''': csv_path}      , cache_dir=_A      , keep_in_memory=_A				).read()
  _check_csv_datasetdict(_A      , _A				)




@pytest.mark.parametrize(
    '''features'''      , [
        None,
        {'''col_1''': '''string''', '''col_2''': '''int64''', '''col_3''': '''float64'''},
        {'''col_1''': '''string''', '''col_2''': '''string''', '''col_3''': '''string'''},
        {'''col_1''': '''int32''', '''col_2''': '''int32''', '''col_3''': '''int32'''},
        {'''col_1''': '''float32''', '''col_2''': '''float32''', '''col_3''': '''float32'''},
    ]      , )
def      UpperCAmelCase__							(     _A :					Optional[Any]      , _A :					Optional[Any]      , _A :					Optional[Any]				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  # CSV file loses col_1 string dtype information: default now is "int64" instead of "string"
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  a__    =features.copy() if features else default_expected_features
  a__    =(
      Features({feature: Value(_A				) for feature, dtype in features.items()}				) if features is not None else None
  )
  a__    =CsvDatasetReader({'''train''': csv_path}      , features=_A      , cache_dir=_A				).read()
  _check_csv_datasetdict(_A      , _A				)




@pytest.mark.parametrize('''split'''      , [None, NamedSplit('''train'''				), '''train''', '''test''']				)
def      UpperCAmelCase__							(     _A :					Union[str, Any]      , _A :					str      , _A :					List[Any]				):





  '''simple docstring'''







  if split:
    a__    ={split: csv_path}
  else:
    a__    ={'''train''': csv_path, '''test''': csv_path}
  a__    =tmp_path / '''cache'''
  a__    ={'''col_1''': '''int64''', '''col_2''': '''int64''', '''col_3''': '''float64'''}
  a__    =CsvDatasetReader(_A      , cache_dir=_A				).read()
  _check_csv_datasetdict(_A      , _A      , splits=list(path.keys()				)				)
  assert all(dataset[split].split == split for split in path.keys()				)




def      UpperCAmelCase__							(     _A :					Optional[Any]				):





  '''simple docstring'''







  with open(_A      , encoding='''utf-8'''				) as csvfile:
    yield from csv.reader(_A				)




def      UpperCAmelCase__							(     _A :					str      , _A :					Tuple				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  a__    =os.path.join(_A      , '''tmp.csv'''				)
  a__    =CsvDatasetReader({'''train''': csv_path}      , cache_dir=_A				).read()
  CsvDatasetWriter(dataset['''train''']      , _A      , num_proc=1				).write()

  a__    =iter_csv_file(_A				)
  a__    =iter_csv_file(_A				)

  for rowa, rowa in zip(_A      , _A				):
    assert rowa == rowa




def      UpperCAmelCase__							(     _A :					List[str]      , _A :					Any				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  a__    =os.path.join(_A      , '''tmp.csv'''				)
  a__    =CsvDatasetReader({'''train''': csv_path}      , cache_dir=_A				).read()
  CsvDatasetWriter(dataset['''train''']      , _A      , num_proc=2				).write()

  a__    =iter_csv_file(_A				)
  a__    =iter_csv_file(_A				)

  for rowa, rowa in zip(_A      , _A				):
    assert rowa == rowa




def      UpperCAmelCase__							(     _A :					Optional[Any]      , _A :					int				):





  '''simple docstring'''







  a__    =tmp_path / '''cache'''
  a__    =os.path.join(_A      , '''tmp.csv'''				)
  a__    =CsvDatasetReader({'''train''': csv_path}      , cache_dir=_A				).read()
  with pytest.raises(_A				):
    CsvDatasetWriter(dataset['''train''']      , _A      , num_proc=0				)



import copy

from ...configuration_utils import PretrainedConfig
from ...utils import logging


lowerCamelCase 	=   logging.get_logger(__name__)

lowerCamelCase 	=   {
    '''facebook/sam-vit-huge''': '''https://huggingface.co/facebook/sam-vit-huge/resolve/main/config.json''',
    '''facebook/sam-vit-large''': '''https://huggingface.co/facebook/sam-vit-large/resolve/main/config.json''',
    '''facebook/sam-vit-base''': '''https://huggingface.co/facebook/sam-vit-base/resolve/main/config.json''',
}







class 		__magic_name__     (				lowerCamelCase__				):

   '''simple docstring'''




   def __init__(							self,       lowercase_=256,       lowercase_=1024,       lowercase_=16,       lowercase_=16,       lowercase_=4,       lowercase_="gelu",       lowercase_=1E-6,       **lowercase_,       )				->       int:






     """simple docstring"""






     super().__init__(**lowercase_			)
     a__    =hidden_size
     a__    =image_size
     a__    =patch_size
     a__    =image_size // patch_size
     a__    =mask_input_channels
     a__    =num_point_embeddings
     a__    =hidden_act
     a__    =layer_norm_eps







class 		__magic_name__     (				lowerCamelCase__				):

   '''simple docstring'''




   def __init__(							self,       lowercase_=256,       lowercase_="relu",       lowercase_=2048,       lowercase_=2,       lowercase_=8,       lowercase_=2,       lowercase_=3,       lowercase_=3,       lowercase_=256,       lowercase_=1E-6,       **lowercase_,       )				->       int:






     """simple docstring"""






     super().__init__(**lowercase_			)
     a__    =hidden_size
     a__    =hidden_act
     a__    =mlp_dim
     a__    =num_hidden_layers
     a__    =num_attention_heads
     a__    =attention_downsample_rate
     a__    =num_multimask_outputs
     a__    =iou_head_depth
     a__    =iou_head_hidden_dim
     a__    =layer_norm_eps







class 		__magic_name__     (				lowerCamelCase__				):

   '''simple docstring'''




   def __init__(							self,       lowercase_=768,       lowercase_=256,       lowercase_=12,       lowercase_=12,       lowercase_=3,       lowercase_=1024,       lowercase_=16,       lowercase_="gelu",       lowercase_=1E-06,       lowercase_=0.0,       lowercase_=1E-10,       lowercase_=True,       lowercase_=4.0,       lowercase_=True,       lowercase_=True,       lowercase_=14,       lowercase_=[2, 5, 8, 11],       lowercase_=128,       lowercase_=None,       **lowercase_,       )				->       Union[str, Any]:






     """simple docstring"""






     super().__init__(**lowercase_			)

     a__    =hidden_size
     a__    =output_channels
     a__    =num_hidden_layers
     a__    =num_attention_heads
     a__    =num_channels
     a__    =image_size
     a__    =patch_size
     a__    =hidden_act
     a__    =layer_norm_eps
     a__    =attention_dropout
     a__    =initializer_range
     a__    =qkv_bias
     a__    =mlp_ratio
     a__    =use_abs_pos
     a__    =use_rel_pos
     a__    =window_size
     a__    =global_attn_indexes
     a__    =num_pos_feats
     a__    =int(hidden_size * mlp_ratio			) if mlp_dim is None else mlp_dim







class 		__magic_name__     (				lowerCamelCase__				):

   '''simple docstring'''




   lowerCamelCase__					:      Optional[int]        =  'sam'
   lowerCamelCase__					:      str        =  True



   def __init__(							self,       lowercase_=None,       lowercase_=None,       lowercase_=None,       lowercase_=0.02,       **lowercase_,       )				->       Tuple:






     """simple docstring"""






     super().__init__(**lowercase_			)
     a__    =vision_config if vision_config is not None else {}
     a__    =prompt_encoder_config if prompt_encoder_config is not None else {}
     a__    =mask_decoder_config if mask_decoder_config is not None else {}

     if isinstance(lowercase_,       lowercase_			):
       a__    =vision_config.to_dict()
     if isinstance(lowercase_,       lowercase_			):
       a__    =prompt_encoder_config.to_dict()
     if isinstance(lowercase_,       lowercase_			):
       a__    =mask_decoder_config.to_dict()

     a__    =SamVisionConfig(**lowercase_			)
     a__    =SamPromptEncoderConfig(**lowercase_			)
     a__    =SamMaskDecoderConfig(**lowercase_			)
     a__    =initializer_range



   def 					_UpperCAmelCase					(							self			)				->       List[str]:






     """simple docstring"""






     a__    =copy.deepcopy(self.__dict__			)
     a__    =self.vision_config.to_dict()
     a__    =self.prompt_encoder_config.to_dict()
     a__    =self.mask_decoder_config.to_dict()
     a__    =self.__class__.model_type
     return output
