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"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
"facebook/data2vec-base-960h": "https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/m... | 232 |
"""simple docstring"""
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_ef... | 104 | 0 |
"""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... | 155 |
"""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 OptionalDepen... | 104 | 0 |
"""simple docstring"""
from __future__ import annotations
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = str(UpperCAmelCase_ )
return n == n[::-1]
def __UpperCAmelCase ( __UpperCamelCase = 1_00_00_00 ):
__lowe... | 76 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase = {"""vocab_file""": """vocab.txt"... | 104 | 0 |
import numpy as np
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :np.array ) -> np.array:
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod() | 504 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_, UpperCAmelCase_ ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, yo... | 104 | 0 |
'''simple docstring'''
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, flo... | 119 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = ... | 308 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
f... | 104 | 0 |
def A ( _SCREAMING_SNAKE_CASE ) -> int:
if not isinstance(UpperCAmelCase_ ,UpperCAmelCase_ ):
raise TypeError("Input value must be an 'int' type" )
lowerCamelCase : Optional[Any] = 0
while number:
pos... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : Optional[Any] ) -> Dict:
"""simple docstring"""
A__ = []
A__ = set({"(", "[", "{"} )
A__ = set({")", "]", "}"} )
A__ ... | 104 | 0 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
UpperCAmelCase__ = loggin... | 277 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 104 | 0 |
def lowerCamelCase__ ( snake_case_ : list[int] , snake_case_ : list[int] , snake_case_ : int ) -> bool:
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(UpperCAmelCase_ ) )
def lowe... | 592 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ = "" , SCREAMING_SNAKE_CASE__ = False ) -> None:
# Mapping from the first character of the prefix of the node
A__ = ... | 104 | 0 |
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__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''facebook/levit-1... | 496 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstri... | 104 | 0 |
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tok... | 113 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase__ ( _lowerCAmelCase ):
"""simple docstring"""
d... | 104 | 0 |
"""simple docstring"""
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDat... | 232 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeach... | 104 | 0 |
"""simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ = "x" , UpperCamelCase_ = 10**-10 , UpperCamelCase_ = 1 , ):
__SCRE... | 155 |
"""simple docstring"""
from statistics import mean
import numpy as np
def _lowerCamelCase ( UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : int ) -> list:
"""simple docstring"""
A_... | 104 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
a_ = logging.get_logger(__name__)
class UpperCAmelCase_ ( _lowerCAmelCase ):
def __init__( self , *UpperCamelCase_ , ... | 76 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-... | 104 | 0 |
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require_torchaudio
@req... | 504 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__na... | 104 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
class lowerCAmelCase :
def __init__( self : Dict , __lowercase : List[str] ):
"""simple docstring"""
__lowercase =value
__... | 119 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers... | 104 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transfo... | 308 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_a... | 104 | 0 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : bytes ) -> str:
"""simple docstring"""
return "".join([hex(UpperCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(UpperCAmelCase_ )] )
def _lowerCamelCase ... | 104 | 0 |
"""simple docstring"""
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_as... | 277 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_uti... | 104 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case_ = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResNetConfig',... | 592 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMix... | 104 | 0 |
class snake_case__(_lowerCAmelCase ):
"""simple docstring"""
pass
class snake_case__(_lowerCAmelCase ):
"""simple docstring"""
pass
class snake_case__:
"""simple docstring"""
def __init__( self : List[str] ):
lowercase__ : ... | 496 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( UpperCAmelCase_ : float, UpperCAmelCase_ : float, UpperCAmelCase_ : float, ) -> tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc)... | 104 | 0 |
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
_lowerCAmelCase : Dict =(
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
_lowerCAmelCase : List[Any] =[ord(letter) for letter in string.ascii_lowercas... | 113 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
"""configuration_perceiver""": ["""PE... | 104 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
"configuration_autoformer": [
"AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Autofor... | 232 |
"""simple docstring"""
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_ef... | 104 | 0 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 155 |
"""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 OptionalDepen... | 104 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : Union[str, Any] = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __UpperCAm... | 76 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase = {"""vocab_file""": """vocab.txt"... | 104 | 0 |
from statistics import mean
import numpy as np
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :list , SCREAMING_SNAKE_CASE :list , SCREAMING_SNAKE_CASE :list , SCREAMING_SNAKE_CASE :int ) -> list:
__lowerCAmelCase : st... | 504 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_, UpperCAmelCase_ ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, yo... | 104 | 0 |
'''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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = '''... | 119 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"asapp/sew-tiny-100k": "https://huggingface.co/asapp/sew-... | 308 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
f... | 104 | 0 |
import math
def A ( _SCREAMING_SNAKE_CASE ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are ... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : Optional[Any] ) -> Dict:
"""simple docstring"""
A__ = []
A__ = set({"(", "[", "{"} )
A__ = set({")", "]", "}"} )
A__ ... | 104 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, re... | 277 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 104 | 0 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpo... | 592 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ = "" , SCREAMING_SNAKE_CASE__ = False ) -> None:
# Mapping from the first character of the prefix of the node
A__ = ... | 104 | 0 |
import math
import tensorflow as tf
from packaging import version
def __lowerCamelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowercase__ : Optional[int] = tf.convert_to_tensor(UpperCAmelCase_ )
lowercase__ : Optional[Any] = 0.5 * (1.0 + tf.math.erf(x / tf.cast(... | 496 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstri... | 104 | 0 |
import os
import sys
import unittest
_lowerCAmelCase : Optional[Any] =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object,... | 113 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase__ ( _lowerCAmelCase ):
"""simple docstring"""
d... | 104 | 0 |
"""simple docstring"""
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE ( _lowerCAmelCase ):
"""simple docstring"""
a_ : Tuple ="SpeechT5FeatureExtractor"
a_ : List[Any] ="SpeechT5Tokenizer"
def __init__( self : List[Any] ,... | 232 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeach... | 104 | 0 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = 0):
__SCREAMING_SNAKE_CASE ,__SCREAMING_SNAKE_CASE = ... | 155 |
"""simple docstring"""
from statistics import mean
import numpy as np
def _lowerCamelCase ( UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : int ) -> list:
"""simple docstring"""
A_... | 104 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a_ = {'vocab_file': 'vocab.txt', 'tokenizer_file':... | 76 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-... | 104 | 0 |
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class snake_case_ ( _low... | 504 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__na... | 104 | 0 |
'''simple docstring'''
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
UpperCAmelCase = logging.get_logger(__name__)
def __UpperCamelCase ( lowercase__ ... | 119 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers... | 104 | 0 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowercase_ ( _lowerCAmelCase ):
@staticmethod
@abstractmethod
def _lowerCAmelCase ( _lowercase : str ):
raise NotImplemented... | 308 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_a... | 104 | 0 |
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class UpperCamelCase__ :
'''simple docstring'''
lowerCamelCase_ : ... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : bytes ) -> str:
"""simple docstring"""
return "".join([hex(UpperCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(UpperCAmelCase_ )] )
def _lowerCamelCase ... | 104 | 0 |
"""simple docstring"""
from random import randint, random
def __UpperCAmelCase ( lowercase ,lowercase ,lowercase ,lowercase = False ,lowercase = False ,lowercase = 5 ,):
"""simple docstring"""
_UpperCAmelCase = [[-1] * number_of_cells] # Create a highway without any car
_Up... | 277 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_uti... | 104 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
fr... | 592 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMix... | 104 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class snake_case__(_lowerCAmelCase ):
"""simple docstring"""
@require_torch
def snake_case ( self : Tupl... | 496 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( UpperCAmelCase_ : float, UpperCAmelCase_ : float, UpperCAmelCase_ : float, ) -> tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc)... | 104 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slow
@require_torch_gpu
class __UpperCam... | 113 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
"""configuration_perceiver""": ["""PE... | 104 | 0 |
"""simple docstring"""
import numpy as np
from PIL import Image
def _lowerCamelCase ( UpperCAmelCase__,UpperCAmelCase__,UpperCAmelCase__ ) -> np.ndarray:
'''simple docstring'''
a__ = np.array(UpperCAmelCase_ )
if arr.shape[0] != arr.shape[1]:
raise ValueError('The ... | 232 |
"""simple docstring"""
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_ef... | 104 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class SCREAMING_SNAKE_CASE_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ = None):
if components is None:
__SC... | 155 |
"""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 OptionalDepen... | 104 | 0 |
"""simple docstring"""
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, S... | 76 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase = {"""vocab_file""": """vocab.txt"... | 104 | 0 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :str ) -> list:
if n_term == "":
return []
__lowerCAmelCase : Tuple = []
for temp in range(int(UpperCAmelCase_ ) ):
series.append(F'''1/{temp + 1}''' if series else """1""" )
return series
... | 504 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_, UpperCAmelCase_ ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, yo... | 104 | 0 |
'''simple docstring'''
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
fro... | 119 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Poo... | 308 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
f... | 104 | 0 |
def A ( _SCREAMING_SNAKE_CASE = 10 ,_SCREAMING_SNAKE_CASE = 22 ) -> int:
lowerCamelCase : Union[str, Any] = range(1 ,UpperCAmelCase_ )
lowerCamelCase : List[Any] = range(1 ,UpperCAmelCase_ )
return sum(
1 for p... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : Optional[Any] ) -> Dict:
"""simple docstring"""
A__ = []
A__ = set({"(", "[", "{"} )
A__ = set({")", "]", "}"} )
A__ ... | 104 | 0 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ..... | 277 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 104 | 0 |
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(_lowerCAmelCase ) , '... | 592 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ = "" , SCREAMING_SNAKE_CASE__ = False ) -> None:
# Mapping from the first character of the prefix of the node
A__ = ... | 104 | 0 |
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
'''The `inpainting.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionInpaintPipeline` instead.'''
)
| 496 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstri... | 104 | 0 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
_lowerCAmelCase : List[str] ={
"""E""": 12.70,
"""T""": 9.06,
"""A""": 8.17,
"""O""": 7.51,
"""I""": 6.97,
"""N""": 6.75,
"""S""": 6.33,
"""H""": 6.09,
"""R""": 5.99,
"""D""": 4.25,
... | 113 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase__ ( _lowerCAmelCase ):
"""simple docstring"""
d... | 104 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase__ ) -> str:
'''simple docstring'''
a__ = [0] * len(UpperCAmelCase_ )
a__ = []
a__ = [1] * len(UpperCAmelCase_ )
for values in graph.values():
for i in values:
indegree[i] += ... | 232 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeach... | 104 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, ... | 155 |
"""simple docstring"""
from statistics import mean
import numpy as np
def _lowerCamelCase ( UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : int ) -> list:
"""simple docstring"""
A_... | 104 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_lilt': ['LILT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LiltConfig'],
}
try:
if not is_torch_available():
... | 76 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-... | 104 | 0 |
import random
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :int , SCREAMING_SNAKE_CASE :float , SCREAMING_SNAKE_CASE :bool = False ) -> dict:
__lowerCAmelCase : Any = {i: [] for i in range(UpperCAmelCase_ )}
# if prob... | 504 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__na... | 104 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test... | 119 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers... | 104 | 0 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def lowercase__ ( lowerCamelCase : Optional[int] , lowerCamelCase : Tuple , lowerCamelCase : str , lowerC... | 308 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_a... | 104 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...utils import logging
i... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : bytes ) -> str:
"""simple docstring"""
return "".join([hex(UpperCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(UpperCAmelCase_ )] )
def _lowerCamelCase ... | 104 | 0 |
"""simple docstring"""
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def __UpperCAmelCase ( lowercase = True ,*lowercase ,**lowercase ):
"""simple docstring"""
if not is_tqdm_available()... | 277 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_uti... | 104 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def lowerCamelCase__ ( snake_case_ : str , snake_case_ : List[str] ) -> Tuple:
__snake_case = Mock... | 592 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMix... | 104 | 0 |
from typing import List
from .keymap import KEYMAP, get_character
def __lowerCamelCase ( lowerCamelCase__ ):
"""simple docstring"""
def decorator(lowerCamelCase__ ):
lowercase__ : Dict = getattr(UpperCAmelCase_ , "handle_key" , [] )
handle += [key]
s... | 496 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( UpperCAmelCase_ : float, UpperCAmelCase_ : float, UpperCAmelCase_ : float, ) -> tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc)... | 104 | 0 |
def _A ( SCREAMING_SNAKE_CASE ):
assert (
isinstance(UpperCAmelCase_ ,UpperCAmelCase_ ) and number_of_steps > 0
), f"number_of_steps needs to be positive integer, your input {number_of_steps}"
if number_of_steps == 1:
return 1
UpperCAmelCase__ , UpperCAmelCase__: Optional[Any] ... | 113 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
"""configuration_perceiver""": ["""PE... | 104 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase__ ) -> list:
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(UpperCAmelCase_ ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
__import__("doct... | 232 |
"""simple docstring"""
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_ef... | 104 | 0 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
__magic_name__ = logging.get_logger(__name__)
_... | 155 |
"""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 OptionalDepen... | 104 | 0 |
"""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, s... | 76 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase = {"""vocab_file""": """vocab.txt"... | 104 | 0 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_UpperCAmelCase = logging.get_logger(__name__)
class snake_case_ ( _lowerCAmelCase ):
def __init__( self : Union[str, Any] , *_snake_case : Dict , ... | 504 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_, UpperCAmelCase_ ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, yo... | 104 | 0 |
'''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
UpperCAmelCase = '''<<<<<<< This should probably be modified because it mentions: '''
UpperCAmelCase ... | 119 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 | 0 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( _lowerCAmelCase ):
__magic_name__ : Optional[int] = (IPNDMScheduler,)
__magic_name__ : str ... | 308 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
f... | 104 | 0 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_dat... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : Optional[Any] ) -> Dict:
"""simple docstring"""
A__ = []
A__ = set({"(", "[", "{"} )
A__ = set({")", "]", "}"} )
A__ ... | 104 | 0 |
"""simple docstring"""
import requests
from bsa import BeautifulSoup
def __UpperCAmelCase ( lowercase ,lowercase ):
"""simple docstring"""
_UpperCAmelCase = BeautifulSoup(requests.get(UpperCAmelCase_ ,params=UpperCAmelCase_ ).content ,"""html.parser""" )
_UpperCAmelCase ... | 277 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 104 | 0 |
import enum
import shutil
import sys
snake_case_ , snake_case_ = shutil.get_terminal_size()
snake_case_ = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class SCREAMING_SNAKE_CASE__ ( enum.Enum ):
A_ : List[Any] = ... | 592 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ = "" , SCREAMING_SNAKE_CASE__ = False ) -> None:
# Mapping from the first character of the prefix of the node
A__ = ... | 104 | 0 |
class snake_case__:
"""simple docstring"""
def __init__( self : str , SCREAMING_SNAKE_CASE : Optional[int] = "" , SCREAMING_SNAKE_CASE : Any = False ):
# Mapping from the first character of the prefix of the node
lowercase__ : Dict = {}
... | 496 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstri... | 104 | 0 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Config... | 113 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase__ ( _lowerCAmelCase ):
"""simple docstring"""
d... | 104 | 0 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
a_ : List[str] =None
def _lowerCAmelCase ( self : List[Any] ) -> Unio... | 232 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeach... | 104 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
... | 155 |
"""simple docstring"""
from statistics import mean
import numpy as np
def _lowerCamelCase ( UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : list, UpperCAmelCase_ : int ) -> list:
"""simple docstring"""
A_... | 104 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'tiiuae/falcon-40b': 'https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json',
'tiiuae/falcon-7b': '... | 76 |
"""simple docstring"""
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-... | 104 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase = {'configuration_wavlm': ['WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP', 'WavLMConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvaila... | 504 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase = logging.get_logger(__na... | 104 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
... | 119 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers... | 104 | 0 |
"""simple docstring"""
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_d... | 308 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_a... | 104 | 0 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
SCREAMING_SNAKE_CASE__ : str = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : bytes ) -> str:
"""simple docstring"""
return "".join([hex(UpperCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(UpperCAmelCase_ )] )
def _lowerCamelCase ... | 104 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( lowercase ):
"""simple docstring"""
return "".join([hex(UpperCAmelCase_ )[2:].zfill(2 ).upper() for byte in list(UpperCAmelCase_ )] )
def __UpperCAmelCase ( lowercase ):
"""simple docstring"""
if (len(... | 277 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_uti... | 104 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case_ = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenization... | 592 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMix... | 104 | 0 |
import math
def __lowerCamelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
if initial_intensity < 0:
raise ValueError("The value of intensity cannot be negative" )
# handling of negative values of initial intensity
if angle < 0 or angle > 360:
... | 496 |
"""simple docstring"""
from __future__ import annotations
def _lowerCamelCase ( UpperCAmelCase_ : float, UpperCAmelCase_ : float, UpperCAmelCase_ : float, ) -> tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc)... | 104 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : Any =logging.get_logger(__name__)
_lowerCAmelCase : Dict ={
"""google/realm-cc-news-pretrained-embedder""": (
"""https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/m... | 113 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
"""configuration_perceiver""": ["""PE... | 104 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase__,UpperCAmelCase__ ) -> str:
'''simple docstring'''
if not (isinstance(UpperCAmelCase_,UpperCAmelCase_ ) and isinstance(UpperCAmelCase_,UpperCAmelCase_ )):
raise ValueError('longest_common_substring() takes two str... | 232 |
"""simple docstring"""
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_ef... | 104 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDepende... | 155 |
"""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 OptionalDepen... | 104 | 0 |
"""simple docstring"""
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
... | 76 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
UpperCamelCase = {"""vocab_file""": """vocab.txt"... | 104 | 0 |
import logging
from transformers import PretrainedConfig
_UpperCAmelCase = logging.getLogger(__name__)
_UpperCAmelCase = {
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}
class snak... | 504 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
assert (
isinstance(UpperCAmelCase_, UpperCAmelCase_ ) and number_of_steps > 0
), F"""number_of_steps needs to be positive integer, yo... | 104 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase = {
'''configuration_mega''': ['''MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MegaConfig''', '''MegaOnnxConfig'''],
}
try:
if ... | 119 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 | 0 |
"""simple docstring"""
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_... | 308 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
f... | 104 | 0 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
f... | 311 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : Optional[Any] ) -> Dict:
"""simple docstring"""
A__ = []
A__ = set({"(", "[", "{"} )
A__ = set({")", "]", "}"} )
A__ ... | 104 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( lowercase = 1_00_00_00 ):
"""simple docstring"""
_UpperCAmelCase = set(range(3 ,UpperCAmelCase_ ,2 ) )
primes.add(2 )
for p in range(3 ,UpperCAmelCase_ ,2 ):
if p not in primes:
continue
primes.difference_update(se... | 277 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 104 | 0 |
from collections import deque
from math import floor
from random import random
from time import time
class SCREAMING_SNAKE_CASE__ :
def __init__(self : Optional[int] ):
"""simple docstring"""
__snake_case = {}
def a (... | 592 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self , SCREAMING_SNAKE_CASE__ = "" , SCREAMING_SNAKE_CASE__ = False ) -> None:
# Mapping from the first character of the prefix of the node
A__ = ... | 104 | 0 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class snake_case__(unittest.TestCase ):
"""simple docstring"""
def snake_case ( self : Optional[int] ):
... | 496 |
"""simple docstring"""
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstri... | 104 | 0 |
from collections import defaultdict
from math import ceil, sqrt
def _A ( SCREAMING_SNAKE_CASE = 1_0_0_0_0_0_0 ,SCREAMING_SNAKE_CASE = 1_0 ):
UpperCAmelCase__: Union[str, Any] = defaultdict(UpperCAmelCase_ )
for outer_width in range(3 ,(t_limit // 4) + 2 ):
if outer_width * outer... | 113 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
UpperCamelCase = logging.get_logger(__name__)
class UpperCamelCase__ ( _lowerCAmelCase ):
"""simple docstring"""
d... | 104 | 0 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : Any , _snake_case : List[str]=None , _snake_case : List[str]=None ) -> Optional[Any]:
'''simple docstring'''
... | 232 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeach... | 104 | 0 |
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