code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
f... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 329 | 1 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 329 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 1 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils impo... | 329 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 329 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 1 |
def lowerCAmelCase__ ( a__: int ) -> list:
'''simple docstring'''
if bit_count < 0:
raise ValueError('The given input must be positive' )
# get the generated string sequence
_UpperCAmelCase = gray_code_sequence_string(a__ )
#
... | 329 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import os... | 329 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 1 |
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def lowerCAmelCase__ ( a__: np.ndarray , a__: np.ndarray ) -> float:
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ) for a, b in zip(a__ , a__ ) ... | 329 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 1 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_available():
from trans... | 329 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 1 |
from collections.abc import Callable
def lowerCAmelCase__ ( a__: Callable[[float], float] , a__: float , a__: float ) -> float:
'''simple docstring'''
_UpperCAmelCase = a
_UpperCAmelCase = b
if function(a__ ) == 0: # one of the a or b is a ... | 329 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 1 |
class __a :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> Dict:
"""simple docstring"""
_UpperCAmelCase = arr.split(',' )
def UpperCAmelCase__ ( self ) -> Optional[int]:
"""simple docstring"""
_UpperCA... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 1 |
def lowerCAmelCase__ ( a__: int , a__: int ) -> str:
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
_UpperCAmelCase = str(bin(a__ ) )[2:] # remove the leading "0b"
... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 1 |
def lowerCAmelCase__ ( a__: int = 5_0_0_0_0_0_0_0 ) -> int:
'''simple docstring'''
_UpperCAmelCase = set()
_UpperCAmelCase = int((limit - 2_4) ** (1 / 2) )
_UpperCAmelCase = set(range(3 , prime_square_limit + 1 , 2 ) )
p... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 1 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('repo_id' , ['canonical_dataset_name', 'org-name/dataset-name'] )
@pytest.mark.parametrize('path' , ['filename.csv', 'filename with blanks.csv'] )
@pytest.mark.parametrize('revision' ... | 329 | 1 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {
'''huggingface/time-series-transformer-tourism-monthly''': (
'''ht... | 329 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 1 |
from collections import defaultdict
def lowerCAmelCase__ ( a__: str , a__: str ) -> bool:
'''simple docstring'''
_UpperCAmelCase = first_str.lower().strip()
_UpperCAmelCase = second_str.lower().strip()
# Remove whitespace
_UpperCAmelCase = ... | 329 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor,... | 329 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 1 |
import requests
lowerCAmelCase__ :Union[str, Any] = '''''' # <-- Put your OpenWeatherMap appid here!
lowerCAmelCase__ :Tuple = '''https://api.openweathermap.org/data/2.5/'''
def lowerCAmelCase__ ( a__: str = "Chicago" , a__: str = APPID ) -> dict:
'''simple d... | 329 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 1 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common im... | 329 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 1 |
from random import shuffle
import tensorflow as tf
from numpy import array
def lowerCAmelCase__ ( a__: int , a__: List[Any] ) -> Dict:
'''simple docstring'''
_UpperCAmelCase = int(a__ )
assert noofclusters < len(a__ )
# Find out the dimensio... | 329 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 1 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: int , a__: int ) -> tuple[int, int]:
'''simple docstring'''
if b == 0:
return (1, 0)
((_UpperCAmelCase) , (_UpperCAmelCase)) = extended_euclid(a__ , a % b )
_Uppe... | 329 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ :Any = logging.get_logger(__name__)
lowerCAmelCase__ :List[str] = {
'''vocab_file''': '''vocab.... | 329 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 1 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __a ( UpperCAmelCase ):
@staticmethod
@abstractmethod
def UpperCAmelCase__ ( _SCREAMING_SNAKE_CASE ) -> List[str]:
"""simple docstring"""
raise NotImplementedError()
@a... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ :List[str] = {
'''configuration_efficientformer''': [
'''EFFICIENTFORMER_PRETRAINED_CONFIG_A... | 329 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 329 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def lowerCAmelCase__ ( a__: int = 1_0_0_0_0_0_0 , a__: int = 1_0 ) -> int:
'''simple docstring'''
_UpperCAmelCase = defaultdict(a__ )
for outer_width in range(3 , (t_limit // 4) + 2 ... | 329 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 1 |
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 329 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 1 |
import math
def lowerCAmelCase__ ( a__: int ) -> str:
'''simple docstring'''
_UpperCAmelCase = 0
_UpperCAmelCase = 0
while num > 0:
_UpperCAmelCase = num % 8
_UpperCAmelCase = octal + (remainder * math.floor(math.pow(1_... | 329 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 1 |
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .transformer_engine import c... | 329 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 1 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_mem... | 329 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 1 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor,... | 329 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 1 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_utils... | 329 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 1 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import T... | 329 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 1 |
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Tuple = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt ... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 1 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
lowerCAmelCase__ :str = logging.get_logger(__name__)
def lowerCAmelCase__ ( a__: Any ... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 1 |
import tensorflow as tf
from ...tf_utils import shape_list
class __a ( tf.keras.layers.Layer ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE=1 , _SCREAMING_SNAKE_CASE=False ... | 329 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('repo_id' , ['canonical_dataset_name', 'org-name/dataset-name'] )
@pytest.mark.parametrize('path' , ['filename.csv', 'filename with blanks.csv'] )
@pytest.mark.parametrize('revision' ... | 329 | 1 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmelCase__ :List[str] = get_tests_dir('''fixture... | 329 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 1 |
import operator as op
def lowerCAmelCase__ ( a__: str ) -> List[str]:
'''simple docstring'''
_UpperCAmelCase = []
_UpperCAmelCase = lambda a__ , a__ : int(x / y ) # noqa: E731 integer division operation
_UpperCAmelCase = {
'... | 329 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 1 |
from __future__ import annotations
from collections import deque
class __a :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
"""simple docstring"""
_UpperCAmelCase = []
self.adlist.append(
{'value': '', 'next_states': ... | 329 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 1 |
from string import ascii_uppercase
lowerCAmelCase__ :Any = {char: i for i, char in enumerate(ascii_uppercase)}
lowerCAmelCase__ :Optional[int] = dict(enumerate(ascii_uppercase))
def lowerCAmelCase__ ( a__: str , a__: str ) -> str:
'''simple docstring'''
... | 329 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 1 |
from typing import List
import numpy as np
def lowerCAmelCase__ ( a__: dict ) -> int:
'''simple docstring'''
_UpperCAmelCase = {key: len(a__ ) for key, value in gen_kwargs.items() if isinstance(a__ , a__ )}
if len(set(lists_lengths.values() ) ... | 329 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 1 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_auto import TF_MODEL... | 329 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 1 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowerCAmelCase__ :List[str] = logging.get_logger(__name__)
class __a ( UpperCAmelCase ):
def __init__( self , *_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_CASE ) ... | 329 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 1 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester... | 329 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 1 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenizer... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 1 |
import math
def lowerCAmelCase__ ( a__: int ) -> bool:
'''simple docstring'''
_UpperCAmelCase = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(a__ )
def lowerCAmelCase__ ( a__: float = 1 / 1_2_3_4_5 ... | 329 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 329 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __a ( UpperCAmelCase ):
_a : Optional[Any] = ['image_processor', 'tokenizer']
_a : Tuple = 'ChineseCLIPImageProcessor'
_a : Optional[int] = ('BertTokenizer', 'Bert... | 329 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 1 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
l... | 329 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = ... | 329 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 1 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS... | 329 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 1 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 1 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 329 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ :List[Any] = {
'''configuration_longformer''': [
'''LONGFORMER_PRETRAINED_CONFIG_ARCHIVE... | 329 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 1 |
lowerCAmelCase__ :str = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''': '... | 329 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 1 |
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors import TemplateProcessing
cl... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Any = {
'''uw-madison/mra-base-512-4''': '''https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json''',
}
... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ :Any = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FunnelConfi... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('repo_id' , ['canonical_dataset_name', 'org-name/dataset-name'] )
@pytest.mark.parametrize('path' , ['filename.csv', 'filename with blanks.csv'] )
@pytest.mark.parametrize('revision' ... | 329 | 1 |
import math
import qiskit
def lowerCAmelCase__ ( a__: int = 1 , a__: int = 1 , a__: int = 1 ) -> qiskit.result.counts.Counts:
'''simple docstring'''
if (
isinstance(a__ , a__ )
or isinstance(a__ , a__ )
or isinstance(... | 329 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
BertTokenizer,
ViltConfig,
ViltForImageAndTextRetrieval,
ViltForImagesAndTextClassification,
ViltForMaskedLM,
ViltFo... | 329 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 1 |
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.util... | 329 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 1 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
lowerCAmelCase__ :Optional[Any] ... | 329 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 1 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequenceClas... | 329 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 1 |
from math import isqrt
def lowerCAmelCase__ ( a__: int ) -> list[int]:
'''simple docstring'''
_UpperCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2... | 329 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :int = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/... | 329 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 1 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 1 |
import numpy as np
def lowerCAmelCase__ ( a__: Tuple , a__: Dict , a__: Tuple , a__: Optional[Any] , a__: List[str] ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = int(np.ceil((x_end - xa) / h ) )
_UpperCAmelCase = np.zeros((n + ... | 329 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 329 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 1 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 1 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( a__: List[str] , a__: float = 0.0 , a__: float = 1.0 ) -> int:
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import ... | 329 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 1 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
te... | 329 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 1 |
def lowerCAmelCase__ ( a__: list[list[float]] ) -> list[list[float]]:
'''simple docstring'''
_UpperCAmelCase = []
for data in source_data:
for i, el in enumerate(a__ ):
if len(a__ ) < i + 1:
d... | 329 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 1 |
def lowerCAmelCase__ ( a__: str ) -> list:
'''simple docstring'''
_UpperCAmelCase = [0] * len(a__ )
for i in range(1 , len(a__ ) ):
# use last results for better performance - dynamic programming
_UpperCAmelCase = ... | 329 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 1 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase__ :Optional[Any] = '''sshleifer/bart-tiny-r... | 329 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 1 |
from __future__ import annotations
from typing import TypedDict
class __a ( UpperCAmelCase ):
_a : str
_a : int
def lowerCAmelCase__ ( a__: str ) -> list[str]:
'''simple docstring'''
if not isinstance(a__ , a__ ):
raise TypeError('T... | 329 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase )
class __a ( UpperCAmelCase ):
_a : str = field(default='language-modeling' , metadata={'include_in_asdict_e... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 1 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class __a ( UpperCAmelCase ):
def __lt__( self , _SCREAMING_SNAKE_CASE ) -> Any:
"""simple docstring"""
return se... | 329 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Dict = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[int] = {'''openai-gpt''': '''https://huggingface.co/openai-gpt/resolve/main/config.json'''}
class __a ( UpperCAmelCas... | 329 | 1 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def _a ( *a :List[str] ) -> Dict:
if not isinstance(a , a ):
a = list(a )
for i in range(len(a ) ):
a = None
gc.collect()
if is_... | 0 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('repo_id' , ['canonical_dataset_name', 'org-name/dataset-name'] )
@pytest.mark.parametrize('path' , ['filename.csv', 'filename with blanks.csv'] )
@pytest.mark.parametrize('revision' ... | 329 | 0 |
'''simple docstring'''
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelera... | 1 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
lower... | 329 | 0 |
'''simple docstring'''
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def _SCREAMING_SNAKE_CASE (A ) -> bool:
"""simple docstring"""
lowercase__ = int(number**0.5 )
return number == sq * sq
def _S... | 2 |
from __future__ import annotations
def lowerCAmelCase__ ( a__: dict , a__: str ) -> set[str]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = set(a__ ), [start]
while stack:
_UpperCAmelCase = stack.pop()
e... | 329 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
'''simple docstring'''
while b:
A, A : List[Any] = b, a % b
return a
def lowerCAmelCase_ ( snake_case__ , snake_case__ ):
... | 3 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils import sh... | 329 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
__snake_case =logging.get_logger(__name__)
class UpperCAmelCase_ ( __lowercase ):
def __init__( self : List[Any] , ... | 4 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import loa... | 329 | 0 |
import argparse
from collections import defaultdict
import yaml
UpperCAmelCase__ = '''docs/source/en/_toctree.yml'''
def UpperCAmelCase_ ( __snake_case ) -> Dict:
"""simple docstring"""
_lowercase =defaultdict(__snake_case )
for doc in model_doc:
co... | 5 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowerCAmelCase__ ( *a__: str , a__: Optional[Union[Dict, Any]] = None , a__: Dict=True , a__: Any=2 ) -> Union[str, Any]:
'''simple docstring'''
from .. ... | 329 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class __A( nn.Module ):
def __init__( self , _snake_case = 16 , _snake_case = 88 , _snake_case = None , _snake_case = 1 , _snake_case = 0.0 , ... | 6 |
import math
lowerCAmelCase__ :Optional[int] = 1_0
lowerCAmelCase__ :Optional[Any] = 7
lowerCAmelCase__ :Union[str, Any] = BALLS_PER_COLOUR * NUM_COLOURS
def lowerCAmelCase__ ( a__: int = 2_0 ) -> str:
'''simple docstring'''
_UpperCAmelCase ... | 329 | 0 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _snake_case( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : Union[str, Any] , SCREAMING_SNAKE_CASE__ ... | 7 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ :str = {
'''configuration_megatron_bert''': ['''MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegatronBertConfig'''],
}
try:
if not is_torch_available():
... | 329 | 0 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase_ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
# Mark tests as "unit" by d... | 8 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
from __future__ import annotations
from statistics import mean
def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ):
__SCREAMING_SNAKE_CASE : List[str] = [0] * no_of_processes
__SCREAMING_SNAKE_CASE : Tuple = [0] * no_of_p... | 9 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :List[Any] = logging.get_logger(__name__)
lowerCAmelCase__ :Tuple = {'''ctrl''': '''https://huggingface.co/ctrl/resolve/main/config.json'''}
class __a ( UpperCAmelCase ):
_a : ... | 329 | 0 |
import os
import unittest
from transformers import BatchEncoding
from transformers.models.bert.tokenization_bert import (
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.models.prophetnet.tokenization_prophetnet import VOCAB_FILES_NAMES, P... | 10 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 329 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'xlm-mlm-en-2048': 'https://huggingface.co/xlm-mlm-... | 11 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __a ( unittest.TestCase ):
_a : List[str] = JukeboxTokenizer
_a : List[Any] = {
'artist': 'Zac Brown Band',
'genres': 'Country',
'lyrics': 'I met a travelle... | 329 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json'
),
}
c... | 12 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase__ :Optional[int] = logging.getLogger(__name__)
def lowerCAmelCase__ ( ) -> Tuple:
'''simple docstring'''
_UpperCAmelCase = argpar... | 329 | 0 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_scheduler""")
class __lowercase :
"""simp... | 13 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
get_constant_sche... | 329 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> str:
"""simple docstring"""
A__ = ''''''
for word_or_phrase in separated:
if not isinstance(lowercase_ , lowercase_ ):
raise Exception('''join() accepts only... | 14 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils impor... | 329 | 0 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
... | 15 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __a ( UpperCAmelCase ):
def __init__( self , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Any:
"""... | 329 | 0 |
"""simple docstring"""
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
... | 16 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ :int = logging.get_logger(__name__)
lowerCAmelCase__ :Optional[Any] = {
'''facebook/data2vec-... | 329 | 0 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Padding... | 17 |
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_backbone_common import Back... | 329 | 0 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_MO... | 18 |
from collections.abc import Generator
def lowerCAmelCase__ ( ) -> Generator[int, None, None]:
'''simple docstring'''
_UpperCAmelCase , _UpperCAmelCase = 0, 1
while True:
_UpperCAmelCase , _UpperCAmelCase = b, a + b
yield b
def... | 329 | 0 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterM... | 19 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 329 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
i... | 20 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 329 | 0 |
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