code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone ... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/go... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
import requests
def lowerCamelCase_( _lowerCamelCase ) -> dict:
'''simple docstring'''
_lowerCamelCase : List[str] = F"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
... | 46 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 46 | 1 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class A_ :
def __init__( self: Union[str, Any] ):
'''simple docstring'''
_lowerCamelCase : Optional[int] = ""
_lowerCamelCas... | 46 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 46 | 1 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..u... | 46 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 | 1 |
"""simple docstring"""
from typing import Any
def lowerCamelCase_( _lowerCamelCase ) -> list[Any]:
'''simple docstring'''
if not input_list:
return []
_lowerCamelCase : Dict = [input_list.count(_lowerCamelCase ) for value in input_list]
_l... | 46 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_a... | 46 |
"""simple docstring"""
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowerCAmelCase : List[str] = 10
def lowerCamelCase_( _lowerCamelCase , _lo... | 46 | 1 |
"""simple docstring"""
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCamelCase_( _lowerCamelCase ) -> Tuple:
'''simple docstring'''
def is_in_circle(_lowerCamelCase , _lowerCamelCase ... | 46 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 100 ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = set()
_lowerCamelCase : Optional[Any] = 0
_lowerCamelCase : Optional[int] = n + 1 # maximum limi... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : int = {
'''configuration_roberta''': ['... | 46 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
# TODO Update this
_lowerCAmelCase : Option... | 46 | 1 |
"""simple docstring"""
_lowerCAmelCase : List[Any] = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transforme... | 46 |
"""simple docstring"""
import re
def lowerCamelCase_( _lowerCamelCase ) -> str:
'''simple docstring'''
if len(re.findall("[ATCG]" , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(... | 46 | 1 |
"""simple docstring"""
from math import sqrt
def lowerCamelCase_( _lowerCamelCase ) -> int:
'''simple docstring'''
_lowerCamelCase : int = 0
for i in range(1 , int(sqrt(_lowerCamelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(_lo... | 46 |
"""simple docstring"""
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
loggin... | 46 | 1 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_b... | 46 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MOD... | 46 | 1 |
"""simple docstring"""
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 TF... | 46 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 | 1 |
"""simple docstring"""
from PIL import Image
def lowerCamelCase_( _lowerCamelCase ) -> Image:
'''simple docstring'''
_lowerCamelCase, _lowerCamelCase : Optional[Any] = image.size
_lowerCamelCase : List[Any] = 0
_lowerCamelCase : ... | 46 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase = "cpu" , _lowerCamelCase = None ) -> None:
'''simple docstring'''
_lowerCamelCase : Any = torch.loa... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : List[Any] = {
'''configuration_electra'... | 46 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_b... | 46 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require... | 46 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 46 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiff... | 46 |
"""simple docstring"""
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,
... | 46 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 46 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> str | Literal[False]:
'''simple docstring'''
_lowerCamelCase : Optional[Any] ... | 46 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 46 |
"""simple docstring"""
from __future__ import annotations
from random import random
class A_ :
def __init__( self: List[str] ,__lowerCAmelCase: int | None = None ):
'''simple docstring'''
_lowerCamelCase : Any = value
_lowerC... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> list:
'''simple docstring'''
_lowerCamelCase : List[str] = len(_lowerCamelCase )
_lowerCamelCase : Any = [[0] * n for i in range(_low... | 46 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class A_ :
def __init__( self: Tuple ,__lowerCAmelCase: int = 6 ):
'''simple docstring'''
_lowerCamelCase : Node | None = None
_lowerCamelCase ... | 46 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..u... | 46 | 1 |
"""simple docstring"""
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,... | 46 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( _a ):
lowerCAmelCase__ = (DDIMParallelScheduler,)
lowerCAmelCase__ = (('eta', 0.0), ('num_inference_steps', 5_0))
def ... | 46 | 1 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import SwinvaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configur... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase : ... | 46 | 1 |
"""simple docstring"""
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils i... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/go... | 46 | 1 |
"""simple docstring"""
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 ..... | 46 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = ""
for i in table:
res += inp[i - 1]
return res
def lowerCamelCase_( _lowerCamelCase ) ... | 46 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 46 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .... | 46 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
_lowerCAmelCase : Union[str, Any] = {
'''configuration_audio_spectrogram_transformer''': [
'''AUDIO_SPECTROGRAM_TRANSF... | 46 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 | 1 |
"""simple docstring"""
from math import isqrt, loga
def lowerCamelCase_( _lowerCamelCase ) -> list[int]:
'''simple docstring'''
_lowerCamelCase : Dict = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime... | 46 |
"""simple docstring"""
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowerCAmelCase : List[str] = 10
def lowerCamelCase_( _lowerCamelCase , _lo... | 46 | 1 |
"""simple docstring"""
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import re... | 46 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 100 ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = set()
_lowerCamelCase : Optional[Any] = 0
_lowerCamelCase : Optional[int] = n + 1 # maximum limi... | 46 | 1 |
"""simple docstring"""
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# f... | 46 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
# TODO Update this
_lowerCAmelCase : Option... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import random
class A_ :
def __init__( self: List[str] ,__lowerCAmelCase: int | None = None ):
'''simple docstring'''
_lowerCamelCase : Any = value
_lowerC... | 46 |
"""simple docstring"""
import re
def lowerCamelCase_( _lowerCamelCase ) -> str:
'''simple docstring'''
if len(re.findall("[ATCG]" , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> float:
'''simple docstring'''
_lowerCamelCase : Optional[Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum... | 46 |
"""simple docstring"""
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
loggin... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : List[Any] = {
'''configuration_mobilebert''': [
'''MOB... | 46 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MOD... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf... | 46 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test impor... | 46 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase = "cpu" , _lowerCamelCase = None ) -> None:
'''simple docstring'''
_lowerCamelCase : Any = torch.loa... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 50 ) -> int:
'''simple docstring'''
_lowerCamelCase : Optional[int] = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ... | 46 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_b... | 46 | 1 |
"""simple docstring"""
import operator as op
def lowerCamelCase_( _lowerCamelCase ) -> Tuple:
'''simple docstring'''
_lowerCamelCase : Optional[int] = []
_lowerCamelCase : Union[str, Any] = lambda _lowerCamelCase , _lowerCamelCase ... | 46 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 46 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
_lowerCAmelCase : List[Any] = logging.get_logger(__name__) # pylint: disable=invalid-name
c... | 46 |
"""simple docstring"""
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,
... | 46 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
_lowerCAmelCase : Optional[Any] = '''examples/'''
_lowerCAmelCase : Optional[Any] = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_vers... | 46 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> str | Literal[False]:
'''simple docstring'''
_lowerCamelCase : Optional[Any] ... | 46 | 1 |
"""simple docstring"""
import math
import sys
def lowerCamelCase_( _lowerCamelCase ) -> int:
'''simple docstring'''
if number != int(_lowerCamelCase ):
raise ValueError("the value of input must be a natural number" )
if number < 0:
raise ValueEr... | 46 |
"""simple docstring"""
from __future__ import annotations
from random import random
class A_ :
def __init__( self: List[str] ,__lowerCAmelCase: int | None = None ):
'''simple docstring'''
_lowerCamelCase : Any = value
_lowerC... | 46 | 1 |
"""simple docstring"""
import math
class A_ :
def _lowercase ( self: Tuple ,__lowerCAmelCase: list[list[float]] ,__lowerCAmelCase: list[int] ):
'''simple docstring'''
_lowerCamelCase : List[str] = 0.0
_lo... | 46 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test... | 46 | 1 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase=5 ) -> Tuple:
'''simple docstring'''
assert masked_input.count("<mask... | 46 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..u... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 1000 ) -> int:
'''simple docstring'''
_lowerCamelCase, _lowerCamelCase : Dict = 1, 1
_lowerCamelCase : Optional[int] = []
for i in range(1 , n + 1 ):
_lowerCamelC... | 46 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( _a ):
lowerCAmelCase__ = (DDIMParallelScheduler,)
lowerCAmelCase__ = (('eta', 0.0), ('num_inference_steps', 5_0))
def ... | 46 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase : str = logging.get_logger(__name__)
_... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase : ... | 46 | 1 |
"""simple docstring"""
import sys
def lowerCamelCase_( _lowerCamelCase ) -> Optional[int]:
'''simple docstring'''
_lowerCamelCase : str = len(_lowerCamelCase )
_lowerCamelCase : str = [[0 for x in range(_lowerCamelCase )] for x... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/go... | 46 | 1 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 46 | 1 |
"""simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class A_ ( unittest.TestCase ):
def _lowercase ... | 46 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 10 , _lowerCamelCase = 22 ) -> int:
'''simple docstring'''
_lowerCamelCase : Dict = range(1 , _lowerCamelCase )
_lowerCamelCase : Optional[int] = range(1 , _lowerCamelCa... | 46 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_com... | 46 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 | 1 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_a... | 46 |
"""simple docstring"""
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowerCAmelCase : List[str] = 10
def lowerCamelCase_( _lowerCamelCase , _lo... | 46 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : Any = {
'''s-JoL/Open-Llama-V1''': '''https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/... | 46 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 100 ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = set()
_lowerCamelCase : Optional[Any] = 0
_lowerCamelCase : Optional[int] = n + 1 # maximum limi... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
_lowerCAmelCase : Tuple = {
'''configuration_trocr''': ['''TROCR_PRETRAIN... | 46 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
# TODO Update this
_lowerCAmelCase : Option... | 46 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tok... | 46 |
"""simple docstring"""
import re
def lowerCamelCase_( _lowerCamelCase ) -> str:
'''simple docstring'''
if len(re.findall("[ATCG]" , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(... | 46 | 1 |
"""simple docstring"""
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_lowerCAmelCase : Optional[int] ... | 46 |
"""simple docstring"""
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
loggin... | 46 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acce... | 46 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MOD... | 46 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available... | 46 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase : Any = {
'''configuration_whisper''': ['... | 46 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase = "cpu" , _lowerCamelCase = None ) -> None:
'''simple docstring'''
_lowerCamelCase : Any = torch.loa... | 46 | 1 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowerCAmelCase : Any = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
pa... | 46 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_b... | 46 | 1 |
"""simple docstring"""
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 che... | 46 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 46 | 1 |
"""simple docstring"""
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowerCAmelCase : str = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4... | 46 |
"""simple docstring"""
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,
... | 46 | 1 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
# TODO Update this
_lowerCAmelCase : Option... | 46 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> str | Literal[False]:
'''simple docstring'''
_lowerCamelCase : Optional[Any] ... | 46 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(_a ) ,... | 46 |
"""simple docstring"""
from __future__ import annotations
from random import random
class A_ :
def __init__( self: List[str] ,__lowerCAmelCase: int | None = None ):
'''simple docstring'''
_lowerCamelCase : Any = value
_lowerC... | 46 | 1 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
_lowerCAmelCase : List[str] = parse(importlib.metadata.version('''torch'''))
def lowerCamelCase_( _lowerCamelCas... | 46 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase ) -> list:
'''simple docstring'''
for i in range(len(_lowerCamelCase ) - 1 , 0 , -1 ):
_lowerCamelCase : Dict = False
for j in range(_lowerCamelCase , 0 , -1 ):
... | 46 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..u... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase : Union[str, Any] = list[list[float | int]]
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> Matrix:
'''simple docstring'''
_lowe... | 46 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( _a ):
lowerCAmelCase__ = (DDIMParallelScheduler,)
lowerCAmelCase__ = (('eta', 0.0), ('num_inference_steps', 5_0))
def ... | 46 | 1 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def lowerCamelCase_( ) -> List[Any]:
'''simple docstring'''
_lowerCamelCase : Optional[Any] ... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase : ... | 46 | 1 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/go... | 46 | 1 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached... | 46 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 46 | 1 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class A_ :
lowerCAmelCase__ = None
def _lowercase ( self: Optional[int] ):
'''simple docstring'''
_l... | 46 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 46 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 46 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> str | Literal[False]:
'''simple docstring'''
_lowerCamelCase : Optional[Any] ... | 46 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 | 1 |
"""simple docstring"""
from math import sqrt
def lowerCamelCase_( _lowerCamelCase = 1000000 ) -> int:
'''simple docstring'''
_lowerCamelCase : int = 0
_lowerCamelCase : int = 0
_lowerCamelCase : int
while num_cuboids <= limit:
... | 46 |
"""simple docstring"""
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowerCAmelCase : List[str] = 10
def lowerCamelCase_( _lowerCamelCase , _lo... | 46 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, l... | 46 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 100 ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = set()
_lowerCamelCase : Optional[Any] = 0
_lowerCamelCase : Optional[int] = n + 1 # maximum limi... | 46 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_ch... | 46 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
# TODO Update this
_lowerCAmelCase : Option... | 46 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 46 |
"""simple docstring"""
import re
def lowerCamelCase_( _lowerCamelCase ) -> str:
'''simple docstring'''
if len(re.findall("[ATCG]" , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(... | 46 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowerCamelCase_( _lowe... | 46 |
"""simple docstring"""
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
loggin... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase ) -> int:
'''simple docstring'''
_lowerCamelCase : list[list[int]] = [[0 for _ in range(_lowerCamelCase )] for _ in range(m + 1 )]
for i in range(m + 1 ):
_lowerCamelCase : ... | 46 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MOD... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> set[str]:
'''simple docstring'''
_lowerCamelCase, _lowerCamelCase : List[Any] = set(_lowerCamelCase ), [start]
while stack... | 46 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 | 1 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
_lowerCAmelCase : Optional[Any] = [
# tf -> hf
('''/''', '''.'''),
('''... | 46 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase = "cpu" , _lowerCamelCase = None ) -> None:
'''simple docstring'''
_lowerCamelCase : Any = torch.loa... | 46 | 1 |
"""simple docstring"""
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklea... | 46 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_b... | 46 | 1 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermar... | 46 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNot... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) -> list:
'''simple docstring'''
_lowerCamelCase : Tuple = []
_lowerCamelCase, _lowerCamelC... | 46 |
"""simple docstring"""
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,
... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_( _lowerCamelCase ) -> bool:
'''simple docstring'''
return len(set(_lowerCamelCase ) ) == len(_lowerCamelCase )
if __name__ == "__main__":
import doctest
doctest.testmod(... | 46 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> str | Literal[False]:
'''simple docstring'''
_lowerCamelCase : Optional[Any] ... | 46 | 1 |
"""simple docstring"""
class A_ :
def __init__( self: Dict ,__lowerCAmelCase: List[Any] ,__lowerCAmelCase: Union[str, Any] ):
'''simple docstring'''
_lowerCamelCase : int = name
_lowerCamelCase : int = va... | 46 |
"""simple docstring"""
from __future__ import annotations
from random import random
class A_ :
def __init__( self: List[str] ,__lowerCAmelCase: int | None = None ):
'''simple docstring'''
_lowerCamelCase : Any = value
_lowerC... | 46 | 1 |
"""simple docstring"""
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class A_ ( unittest.TestCase ):
def _lowercase ( self: List[str] ):
'''simple docstring'''
_lowerCamelCase : Optional[int]... | 46 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test... | 46 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> str:
'''simple docstring'''
if len(_lowerCamelCase ) <= 1 or n <= 1:
return
insert_next(_lowerCamelCase , n - 1 )
rec_inser... | 46 |
"""simple docstring"""
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..u... | 46 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=_a ):
lowerCAmelCase__ = ['transformers', 'torch', 'note_seq']
def __init__( self: Union[str, Any] ,*__lowerCAmelCase: List[str] ,**__lowerCAmelCase: L... | 46 |
"""simple docstring"""
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( _a ):
lowerCAmelCase__ = (DDIMParallelScheduler,)
lowerCAmelCase__ = (('eta', 0.0), ('num_inference_steps', 5_0))
def ... | 46 | 1 |
"""simple docstring"""
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... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
_lowerCAmelCase : ... | 46 | 1 |
"""simple docstring"""
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
_lowerCAmelCase : Optional[Any] = yaml.safe_load(
'''\
name: ""
allow_empty: false
allow_empty_... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/go... | 46 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : List[str] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/go... | 46 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requ... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Dict = {'''configuration_yolos''': ['''YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''YolosConfig''', '''YolosOnnxCo... | 46 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import... | 46 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_fu... | 46 |
"""simple docstring"""
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCamelCase_( ) -> None:
'''simple docstring'''
print("Making key files..." )
make_key_... | 46 | 1 |
"""simple docstring"""
import string
from math import logaa
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
_lowerCamelCase : Tuple = document.translate(
str.maketrans("" , "" , string.punctuation ... | 46 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 | 1 |
"""simple docstring"""
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
_lowerCAmelCase : Optional[int] = '''<<<<<<< This should probably be modified because it ... | 46 |
"""simple docstring"""
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowerCAmelCase : List[str] = 10
def lowerCamelCase_( _lowerCamelCase , _lo... | 46 | 1 |
"""simple docstring"""
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class A_ ( tf.keras.optimizers.schedules.LearningRat... | 46 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase = 100 ) -> int:
'''simple docstring'''
_lowerCamelCase : List[str] = set()
_lowerCamelCase : Optional[Any] = 0
_lowerCamelCase : Optional[int] = n + 1 # maximum limi... | 46 | 1 |
"""simple docstring"""
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import t... | 46 |
"""simple docstring"""
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
# TODO Update this
_lowerCAmelCase : Option... | 46 | 1 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_ava... | 46 |
"""simple docstring"""
import re
def lowerCamelCase_( _lowerCamelCase ) -> str:
'''simple docstring'''
if len(re.findall("[ATCG]" , _lowerCamelCase ) ) != len(_lowerCamelCase ):
raise ValueError("Invalid Strand" )
return dna.translate(... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
return x if y == 0 else greatest_common_divisor(_lowerCamelCase , x % y )
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) ... | 46 |
"""simple docstring"""
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
loggin... | 46 | 1 |
"""simple docstring"""
def lowerCamelCase_( _lowerCamelCase , _lowerCamelCase ) -> int:
'''simple docstring'''
while second != 0:
_lowerCamelCase : int = first & second
first ^= second
_lowerCamelCase : str = c << 1
return fi... | 46 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MOD... | 46 | 1 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 46 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
... | 46 | 1 |
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