


'''simple docstring'''






import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil






class        __snake_case	(       __lowercase):







    """simple docstring"""



    def __lowercase       (       self   :  str		)       ->  List[str]:
      lowerCAmelCase_      :				Dict      =       pa.array(TypedSequence([1, 2, 3]		)		)
      self.assertEqual(arr.type   ,						pa.intaa()		)

    def __lowercase       (       self   :  Dict		)       ->  int:
      with self.assertRaises(_a		):
        lowerCAmelCase_      :				Tuple      =       pa.array(TypedSequence([1, 2, 3]		)   ,						type=pa.intaa()		)

    def __lowercase       (       self   :  List[str]		)       ->  Optional[int]:
      with self.assertRaises(_a		):
        lowerCAmelCase_      :				Optional[int]      =       pa.array(TypedSequence([1, 2, 3]   ,						try_type=Value("""bool"""		)   ,						type=Value("""int64"""		)		)		)

    def __lowercase       (       self   :  str		)       ->  Any:
      lowerCAmelCase_      :				Any      =       pa.array(TypedSequence([1, 2, 3]   ,						type=Value("""int32"""		)		)		)
      self.assertEqual(arr.type   ,						pa.intaa()		)

    def __lowercase       (       self   :  Union[str, Any]		)       ->  Optional[int]:
      with self.assertRaises((TypeError, pa.lib.ArrowInvalid)		):
        lowerCAmelCase_      :				str      =       pa.array(TypedSequence(["""foo""", """bar"""]   ,						type=Value("""int64"""		)		)		)

    def __lowercase       (       self   :  Tuple		)       ->  Dict:
      lowerCAmelCase_      :				List[str]      =       pa.array(TypedSequence([1, 2, 3]   ,						try_type=Value("""int32"""		)		)		)
      self.assertEqual(arr.type   ,						pa.intaa()		)

    def __lowercase       (       self   :  Optional[int]		)       ->  int:
      lowerCAmelCase_      :				str      =       pa.array(TypedSequence(["""foo""", """bar"""]   ,						try_type=Value("""int64"""		)		)		)
      self.assertEqual(arr.type   ,						pa.string()		)

    def __lowercase       (       self   :  Optional[int]		)       ->  Tuple:
      lowerCAmelCase_      :				Tuple      =       pa.array(TypedSequence([[[1, 2, 3]]]   ,						type=ArrayaD((1, 3)   ,						"""int64"""		)		)		)
      self.assertEqual(arr.type   ,						ArrayaDExtensionType((1, 3)   ,						"""int64"""		)		)

    def __lowercase       (       self   :  Any		)       ->  Optional[Any]:
      with self.assertRaises((TypeError, pa.lib.ArrowInvalid)		):
        lowerCAmelCase_      :				Union[str, Any]      =       pa.array(TypedSequence(["""foo""", """bar"""]   ,						type=ArrayaD((1, 3)   ,						"""int64"""		)		)		)

    def __lowercase       (       self   :  int		)       ->  Union[str, Any]:
      lowerCAmelCase_      :				List[Any]      =       pa.array(TypedSequence([[[1, 2, 3]]]   ,						try_type=ArrayaD((1, 3)   ,						"""int64"""		)		)		)
      self.assertEqual(arr.type   ,						ArrayaDExtensionType((1, 3)   ,						"""int64"""		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  List[str]:
      lowerCAmelCase_      :				Optional[Any]      =       pa.array(TypedSequence(["""foo""", """bar"""]   ,						try_type=ArrayaD((1, 3)   ,						"""int64"""		)		)		)
      self.assertEqual(arr.type   ,						pa.string()		)





    @require_pil
    def __lowercase       (       self   :  Any		)       ->  int:
      import PIL.Image

      lowerCAmelCase_      :				int      =       PIL.Image.fromarray(np.arange(10   ,						dtype=np.uinta		).reshape(2   ,						5		)		)
      with patch(
          """datasets.arrow_writer.cast_to_python_objects"""   ,						side_effect=_a		) as mock_cast_to_python_objects:
        lowerCAmelCase_      :				Optional[int]      =       pa.array(TypedSequence([{"""path""": None, """bytes""": B"""image_bytes"""}, pil_image]   ,						type=Image()		)		)
        lowerCAmelCase_,							lowerCAmelCase_      :				str      =       mock_cast_to_python_objects.call_args_list[-1]
        self.assertIn("""optimize_list_casting"""   ,						_a		)
        self.assertFalse(kwargs["""optimize_list_casting"""]		)







def     UpperCamelCase_      (   A__ :       Optional[Any]							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[str]      =       pa.BufferReader(__a ) if isinstance(__a							,   pa.Buffer ) else pa.memory_map(__a )
  lowerCAmelCase_      :				int      =       pa.ipc.open_stream(__a )
  lowerCAmelCase_      :				Optional[int]      =       f.read_all()
  assert len(pa_table.to_batches() ) == expected_num_chunks
  assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
  del pa_table







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 1, 10] )
@pytest.mark.parametrize(
    """fields"""							,   [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}] )
def     UpperCamelCase_      (   A__ :       int							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				Optional[Any]      =       pa.BufferOutputStream()
  lowerCAmelCase_      :				Dict      =       pa.schema(__a ) if fields else None
  with ArrowWriter(stream=__a							,   schema=__a							,   writer_batch_size=__a ) as writer:
    writer.write({"""col_1""": """foo""", """col_2""": 1} )
    writer.write({"""col_1""": """bar""", """col_2""": 2} )
    lowerCAmelCase_,							lowerCAmelCase_      :				Dict      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCAmelCase_      :				List[Any]      =       {"""col_1""": pa.string(), """col_2""": pa.intaa()}
  assert writer._schema == pa.schema(__a							,   metadata=writer._schema.metadata )
  _check_output(output.getvalue()							,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )







def     UpperCamelCase_      (   ):
  '''simple docstring'''





  lowerCAmelCase_      :				Union[str, Any]      =       pa.BufferOutputStream()
  lowerCAmelCase_      :				str      =       Features({"""labels""": ClassLabel(names=["""neg""", """pos"""] )} )
  with ArrowWriter(stream=__a							,   features=__a ) as writer:
    writer.write({"""labels""": 0} )
    writer.write({"""labels""": 1} )
    lowerCAmelCase_,							lowerCAmelCase_      :				Optional[Any]      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  assert writer._schema == features.arrow_schema
  assert writer._schema.metadata == features.arrow_schema.metadata
  lowerCAmelCase_      :				Union[str, Any]      =       pa.BufferReader(output.getvalue() )
  lowerCAmelCase_      :				Tuple      =       pa.ipc.open_stream(__a )
  lowerCAmelCase_      :				Tuple      =       f.read_all()
  lowerCAmelCase_      :				List[str]      =       pa_table.schema
  assert pa_table.num_rows == 2
  assert schema == features.arrow_schema
  assert schema.metadata == features.arrow_schema.metadata
  assert features == Features.from_arrow_schema(__a )







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 1, 10] )
def     UpperCamelCase_      (   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				Dict      =       pa.BufferOutputStream()
  with ArrowWriter(
      stream=__a							,   writer_batch_size=__a							,   hash_salt="""split_name"""							,   check_duplicates=__a							,   ) as writer:
    with pytest.raises(__a ):
      writer.write({"""col_1""": """foo""", """col_2""": 1}							,   key=[1, 2] )
      lowerCAmelCase_,							lowerCAmelCase_      :				Optional[Any]      =       writer.finalize()







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 2, 10] )
def     UpperCamelCase_      (   A__ :       Any ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[Any]      =       pa.BufferOutputStream()
  with ArrowWriter(
      stream=__a							,   writer_batch_size=__a							,   hash_salt="""split_name"""							,   check_duplicates=__a							,   ) as writer:
    with pytest.raises(__a ):
      writer.write({"""col_1""": """foo""", """col_2""": 1}							,   key=10 )
      writer.write({"""col_1""": """bar""", """col_2""": 2}							,   key=10 )
      lowerCAmelCase_,							lowerCAmelCase_      :				int      =       writer.finalize()







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 2, 10] )
def     UpperCamelCase_      (   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				Union[str, Any]      =       pa.BufferOutputStream()
  with ArrowWriter(
      stream=__a							,   writer_batch_size=__a							,   hash_salt="""split_name"""							,   check_duplicates=__a							,   ) as writer:
    writer.write({"""col_1""": """foo""", """col_2""": 1}							,   key=1 )
    writer.write({"""col_1""": """bar""", """col_2""": 2}							,   key=2 )
    lowerCAmelCase_,							lowerCAmelCase_      :				Dict      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  _check_output(output.getvalue()							,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 1, 10] )
@pytest.mark.parametrize(
    """fields"""							,   [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}] )
def     UpperCamelCase_      (   A__ :       List[str]							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[str]      =       pa.BufferOutputStream()
  lowerCAmelCase_      :				Optional[int]      =       pa.schema(__a ) if fields else None
  with ArrowWriter(stream=__a							,   schema=__a							,   writer_batch_size=__a ) as writer:
    writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]} )
    writer.write_batch({"""col_1""": [], """col_2""": []} )
    lowerCAmelCase_,							lowerCAmelCase_      :				List[str]      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCAmelCase_      :				Dict      =       {"""col_1""": pa.string(), """col_2""": pa.intaa()}
  assert writer._schema == pa.schema(__a							,   metadata=writer._schema.metadata )
  _check_output(output.getvalue()							,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 1, 10] )
@pytest.mark.parametrize(
    """fields"""							,   [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}] )
def     UpperCamelCase_      (   A__ :       Union[str, Any]							,   A__ :       List[Any] ):
  '''simple docstring'''





  lowerCAmelCase_      :				Optional[int]      =       pa.BufferOutputStream()
  lowerCAmelCase_      :				str      =       pa.schema(__a ) if fields else None
  with ArrowWriter(stream=__a							,   schema=__a							,   writer_batch_size=__a ) as writer:
    writer.write_table(pa.Table.from_pydict({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]} ) )
    lowerCAmelCase_,							lowerCAmelCase_      :				Optional[Any]      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCAmelCase_      :				int      =       {"""col_1""": pa.string(), """col_2""": pa.intaa()}
  assert writer._schema == pa.schema(__a							,   metadata=writer._schema.metadata )
  _check_output(output.getvalue()							,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )







@pytest.mark.parametrize("""writer_batch_size"""							,   [None, 1, 10] )
@pytest.mark.parametrize(
    """fields"""							,   [None, {"""col_1""": pa.string(), """col_2""": pa.intaa()}, {"""col_1""": pa.string(), """col_2""": pa.intaa()}] )
def     UpperCamelCase_      (   A__ :       Dict							,   A__ :       Dict ):
  '''simple docstring'''





  lowerCAmelCase_      :				str      =       pa.BufferOutputStream()
  lowerCAmelCase_      :				Tuple      =       pa.schema(__a ) if fields else None
  with ArrowWriter(stream=__a							,   schema=__a							,   writer_batch_size=__a ) as writer:
    writer.write_row(pa.Table.from_pydict({"""col_1""": ["""foo"""], """col_2""": [1]} ) )
    writer.write_row(pa.Table.from_pydict({"""col_1""": ["""bar"""], """col_2""": [2]} ) )
    lowerCAmelCase_,							lowerCAmelCase_      :				Dict      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  if not fields:
    lowerCAmelCase_      :				Any      =       {"""col_1""": pa.string(), """col_2""": pa.intaa()}
  assert writer._schema == pa.schema(__a							,   metadata=writer._schema.metadata )
  _check_output(output.getvalue()							,   expected_num_chunks=num_examples if writer_batch_size == 1 else 1 )







def     UpperCamelCase_      (   ):
  '''simple docstring'''





  with tempfile.TemporaryDirectory() as tmp_dir:
    lowerCAmelCase_      :				Optional[int]      =       {"""col_1""": pa.string(), """col_2""": pa.intaa()}
    lowerCAmelCase_      :				Dict      =       os.path.join(__a							,   """test.arrow""" )
    with ArrowWriter(path=__a							,   schema=pa.schema(__a ) ) as writer:
      writer.write_batch({"""col_1""": ["""foo""", """bar"""], """col_2""": [1, 2]} )
      lowerCAmelCase_,							lowerCAmelCase_      :				Optional[Any]      =       writer.finalize()
    assert num_examples == 2
    assert num_bytes > 0
    assert writer._schema == pa.schema(__a							,   metadata=writer._schema.metadata )
    _check_output(__a							,   1 )







def     UpperCamelCase_      (   A__ :       str ):
  '''simple docstring'''





  if pa.types.is_list(__a ):
    return get_base_dtype(arr_type.value_type )
  else:
    return arr_type







def     UpperCamelCase_      (   A__ :       Tuple							,   A__ :       Any ):
  '''simple docstring'''





  if isinstance(lst[0]							,   __a ):
    change_first_primitive_element_in_list(lst[0]							,   __a )
  else:
    lowerCAmelCase_      :				Dict      =       value







@pytest.mark.parametrize("""optimized_int_type, expected_dtype"""							,   [(None, pa.intaa()), (Value("""int32""" ), pa.intaa())] )
@pytest.mark.parametrize("""sequence"""							,   [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]] )
def     UpperCamelCase_      (   A__ :       Any							,   A__ :       str							,   A__ :       int ):
  '''simple docstring'''





  lowerCAmelCase_      :				Dict      =       pa.array(TypedSequence(__a							,   optimized_int_type=__a ) )
  assert get_base_dtype(arr.type ) == expected_dtype







@pytest.mark.parametrize(
    """col, expected_dtype"""							,   [
        ("""attention_mask""", pa.inta()),
        ("""special_tokens_mask""", pa.inta()),
        ("""token_type_ids""", pa.inta()),
        ("""input_ids""", pa.intaa()),
        ("""other""", pa.intaa()),
    ]							,   )
@pytest.mark.parametrize("""sequence"""							,   [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]] )
def     UpperCamelCase_      (   A__ :       Tuple							,   A__ :       str							,   A__ :       Optional[int] ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[str]      =       pa.array(OptimizedTypedSequence(__a							,   col=__a ) )
  assert get_base_dtype(arr.type ) == expected_dtype

  # not in range
  if col != "other":
    # avoids errors due to in-place modifications
    lowerCAmelCase_      :				List[Any]      =       copy.deepcopy(__a )
    lowerCAmelCase_      :				int      =       np.iinfo(expected_dtype.to_pandas_dtype() ).max + 1
    change_first_primitive_element_in_list(__a							,   __a )
    lowerCAmelCase_      :				Any      =       pa.array(OptimizedTypedSequence(__a							,   col=__a ) )
    assert get_base_dtype(arr.type ) == pa.intaa()







@pytest.mark.parametrize("""raise_exception"""							,   [False, True] )
def     UpperCamelCase_      (   A__ :       Dict							,   A__ :       List[str] ):
  '''simple docstring'''





  lowerCAmelCase_      :				Optional[int]      =       str(tmp_path / """dataset-train.arrow""" )
  try:
    with ArrowWriter(path=__a ) as writer:
      if raise_exception:
        raise pa.lib.ArrowInvalid()
      else:
        writer.stream.close()
  except pa.lib.ArrowInvalid:
    pass
  finally:
    assert writer.stream.closed







def     UpperCamelCase_      (   A__ :       Union[str, Any] ):
  '''simple docstring'''





  lowerCAmelCase_      :				List[str]      =       """mock://dataset-train.arrow"""
  with ArrowWriter(path=__a							,   storage_options=mockfs.storage_options ) as writer:
    assert isinstance(writer._fs							,   type(__a ) )
    assert writer._fs.storage_options == mockfs.storage_options
    writer.write({"""col_1""": """foo""", """col_2""": 1} )
    writer.write({"""col_1""": """bar""", """col_2""": 2} )
    lowerCAmelCase_,							lowerCAmelCase_      :				List[str]      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  assert mockfs.exists(__a )







def     UpperCamelCase_      (   ):
  '''simple docstring'''





  lowerCAmelCase_      :				Dict      =       pa.BufferOutputStream()
  with ParquetWriter(stream=__a ) as writer:
    writer.write({"""col_1""": """foo""", """col_2""": 1} )
    writer.write({"""col_1""": """bar""", """col_2""": 2} )
    lowerCAmelCase_,							lowerCAmelCase_      :				str      =       writer.finalize()
  assert num_examples == 2
  assert num_bytes > 0
  lowerCAmelCase_      :				List[str]      =       pa.BufferReader(output.getvalue() )
  lowerCAmelCase_      :				List[str]      =       pq.read_table(__a )
  assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}







@require_pil
@pytest.mark.parametrize("""embed_local_files"""							,   [False, True] )
def     UpperCamelCase_      (   A__ :       Tuple							,   A__ :       Dict ):
  '''simple docstring'''





  import PIL.Image

  lowerCAmelCase_      :				str      =       str(tmp_path / """test_image_rgb.jpg""" )
  PIL.Image.fromarray(np.zeros((5, 5)							,   dtype=np.uinta ) ).save(__a							,   format="""png""" )
  lowerCAmelCase_      :				List[Any]      =       pa.BufferOutputStream()
  with ParquetWriter(
      stream=__a							,   features=Features({"""image""": Image()} )							,   embed_local_files=__a ) as writer:
    writer.write({"""image""": image_path} )
    writer.finalize()
  lowerCAmelCase_      :				Optional[int]      =       pa.BufferReader(output.getvalue() )
  lowerCAmelCase_      :				Union[str, Any]      =       pq.read_table(__a )
  lowerCAmelCase_      :				Optional[int]      =       pa_table.to_pydict()
  if embed_local_files:
    assert isinstance(out["""image"""][0]["""path"""]							,   __a )
    with open(__a							,   """rb""" ) as f:
      assert out["image"][0]["bytes"] == f.read()
  else:
    assert out["image"][0]["path"] == image_path
    assert out["image"][0]["bytes"] is None







def     UpperCamelCase_      (   ):
  '''simple docstring'''





  lowerCAmelCase_      :				str      =       pa.schema([pa.field("""col_1"""							,   pa.string()							,   nullable=__a )] )
  lowerCAmelCase_      :				List[str]      =       pa.BufferOutputStream()
  with ArrowWriter(stream=__a ) as writer:
    writer._build_writer(inferred_schema=__a )
    assert writer._schema == pa.schema([pa.field("""col_1"""							,   pa.string() )] )










'''simple docstring'''






import unittest

from diffusers.pipelines.pipeline_utils import is_safetensors_compatible






class        __snake_case	(       unittest.TestCase):







    """simple docstring"""



    def __lowercase       (       self   :  Tuple		)       ->  Dict:
      lowerCAmelCase_      :				str      =       [
          """safety_checker/pytorch_model.bin""",
          """safety_checker/model.safetensors""",
          """vae/diffusion_pytorch_model.bin""",
          """vae/diffusion_pytorch_model.safetensors""",
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      self.assertTrue(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  int:
      lowerCAmelCase_      :				Tuple      =       [
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      self.assertTrue(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  Optional[int]		)       ->  Optional[Any]:
      lowerCAmelCase_      :				int      =       [
          """safety_checker/pytorch_model.bin""",
          """safety_checker/model.safetensors""",
          """vae/diffusion_pytorch_model.bin""",
          """vae/diffusion_pytorch_model.safetensors""",
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
          """unet/diffusion_pytorch_model.bin""",
          # Removed: 'unet/diffusion_pytorch_model.safetensors',
      ]
      self.assertFalse(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  int		)       ->  List[Any]:
      lowerCAmelCase_      :				Dict      =       [
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
      ]
      self.assertTrue(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  str		)       ->  List[str]:
      lowerCAmelCase_      :				Union[str, Any]      =       [
          """safety_checker/pytorch_model.bin""",
          """safety_checker/model.safetensors""",
          """vae/diffusion_pytorch_model.bin""",
          """vae/diffusion_pytorch_model.safetensors""",
          """text_encoder/pytorch_model.bin""",
          # Removed: 'text_encoder/model.safetensors',
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      self.assertFalse(is_safetensors_compatible(lowerCamelCase		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  Tuple:
      lowerCAmelCase_      :				Union[str, Any]      =       [
          """safety_checker/pytorch_model.fp16.bin""",
          """safety_checker/model.fp16.safetensors""",
          """vae/diffusion_pytorch_model.fp16.bin""",
          """vae/diffusion_pytorch_model.fp16.safetensors""",
          """text_encoder/pytorch_model.fp16.bin""",
          """text_encoder/model.fp16.safetensors""",
          """unet/diffusion_pytorch_model.fp16.bin""",
          """unet/diffusion_pytorch_model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				Union[str, Any]      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Optional[Any]		)       ->  List[str]:
      lowerCAmelCase_      :				str      =       [
          """unet/diffusion_pytorch_model.fp16.bin""",
          """unet/diffusion_pytorch_model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				Optional[int]      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Tuple		)       ->  Optional[Any]:
      # pass variant but use the non-variant filenames
      lowerCAmelCase_      :				Dict      =       [
          """unet/diffusion_pytorch_model.bin""",
          """unet/diffusion_pytorch_model.safetensors""",
      ]
      lowerCAmelCase_      :				str      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Optional[int]		)       ->  List[str]:
      lowerCAmelCase_      :				str      =       [
          """safety_checker/pytorch_model.fp16.bin""",
          """safety_checker/model.fp16.safetensors""",
          """vae/diffusion_pytorch_model.fp16.bin""",
          """vae/diffusion_pytorch_model.fp16.safetensors""",
          """text_encoder/pytorch_model.fp16.bin""",
          """text_encoder/model.fp16.safetensors""",
          """unet/diffusion_pytorch_model.fp16.bin""",
          # Removed: 'unet/diffusion_pytorch_model.fp16.safetensors',
      ]
      lowerCAmelCase_      :				List[str]      =       """fp16"""
      self.assertFalse(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  Union[str, Any]		)       ->  Optional[int]:
      lowerCAmelCase_      :				str      =       [
          """text_encoder/pytorch_model.fp16.bin""",
          """text_encoder/model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				Optional[Any]      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)

    def __lowercase       (       self   :  List[Any]		)       ->  List[Any]:
      # pass variant but use the non-variant filenames
      lowerCAmelCase_      :				Dict      =       [
          """text_encoder/pytorch_model.bin""",
          """text_encoder/model.safetensors""",
      ]
      lowerCAmelCase_      :				Any      =       """fp16"""
      self.assertTrue(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)





    def __lowercase       (       self   :  Dict		)       ->  Any:
      lowerCAmelCase_      :				Optional[int]      =       [
          """safety_checker/pytorch_model.fp16.bin""",
          """safety_checker/model.fp16.safetensors""",
          """vae/diffusion_pytorch_model.fp16.bin""",
          """vae/diffusion_pytorch_model.fp16.safetensors""",
          """text_encoder/pytorch_model.fp16.bin""",
          # 'text_encoder/model.fp16.safetensors',
          """unet/diffusion_pytorch_model.fp16.bin""",
          """unet/diffusion_pytorch_model.fp16.safetensors""",
      ]
      lowerCAmelCase_      :				int      =       """fp16"""
      self.assertFalse(is_safetensors_compatible(lowerCamelCase   ,						variant=lowerCamelCase		)		)



