code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
cla... | 158 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : list[list[int]] ) -> int:
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
... | 325 | 0 |
"""simple docstring"""
import qiskit
def _A ( UpperCamelCase_ : int = 2) -> qiskit.result.counts.Counts:
'''simple docstring'''
__lowercase = qubits
# Using Aer's simulator
__lowercase = qiskit.Aer.get_backend("aer_simulator")
# Creating a Quantum... | 17 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
class A__ ( enum.Enum ):
lowerCAmelCase__ : Dict = "all_checks"
lowerCAmelCase__ : ... | 325 | 0 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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_configuration_common import ConfigTester
from ...test... | 195 |
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> bool:
assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are prime... | 325 | 0 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
_lowerCamelCase : Tuple = [
['''atte... | 282 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision_a... | 325 | 0 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_available, is_torch_avai... | 340 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass... | 325 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResamplin... | 327 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class A__ ( lowerCAmelCase... | 325 | 0 |
from __future__ import annotations
import requests
lowerCAmelCase_ = set(
'''approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc downs... | 279 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVe... | 325 | 0 |
"""simple docstring"""
import unittest
from transformers import BertGenerationConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_com... | 289 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : Optional[Any] , SCREAMING_SNAKE_CASE : List[Any] ) -> List[str]:
__lowercase = [0 for i in range(r + 1 )]
# nc0 = 1
__lowercase = 1
for i in range(1 , n + 1 ):
... | 325 | 0 |
def UpperCAmelCase_( a__ , a__ ):
"""simple docstring"""
if number < 0 or shift_amount < 0:
raise ValueError('''both inputs must be positive integers''' )
SCREAMING_SNAKE_CASE : str = str(bin(a__ ) )
binary_number += "0" * shift_amoun... | 313 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, B... | 325 | 0 |
import math
def _A ( SCREAMING_SNAKE_CASE__ : int ):
return math.sqrt(SCREAMING_SNAKE_CASE__ ) * math.sqrt(SCREAMING_SNAKE_CASE__ ) == num
def _A ( SCREAMING_SNAKE_CASE__ : int ):
UpperCamelCase :List[str] = 0
UpperCamelCase :Optional[A... | 259 |
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.
SCREAMING_SNAKE_CASE__ = 10
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_S... | 325 | 0 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowercase__ ( ):
__UpperCAmelCase = [randint(-1_000 , 1_000 ) for i in range(10 )]
__UpperCAmelCase = ... | 332 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from transformers.testing... | 325 | 0 |
'''simple docstring'''
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipelin... | 158 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 325 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a = logging.get_logger(__name__)
_a = {
'junnyu/roformer_chinese_small': 'https://... | 17 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_scheduler""")
class A__ :
def __init__( se... | 325 | 0 |
from math import isqrt, loga
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
lowercase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ... | 195 |
import collections
import importlib.util
import os
import re
from pathlib import Path
SCREAMING_SNAKE_CASE__ = """src/transformers"""
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE__ = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
SCREAMING_SNAKE_CASE... | 325 | 0 |
def a_ ( __lowercase : int = 1_000 ) -> int:
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution()) | 282 |
import logging
import os
from .state import PartialState
class A__ ( logging.LoggerAdapter ):
@staticmethod
def a__ ( _UpperCAmelCase : str ) -> Optional[Any]:
"""simple docstring"""
__lowercase = PartialState()
return not m... | 325 | 0 |
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, SchedulerOutput
def _a ( UpperCa... | 340 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET... | 325 | 0 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_availabl... | 327 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https://huggingface.co/facebook/mask2former... | 325 | 0 |
from ...processing_utils import ProcessorMixin
class __lowerCAmelCase ( lowerCAmelCase__ ):
lowerCamelCase_ : List[Any] = "WhisperFeatureExtractor"
lowerCamelCase_ : List[str] = "WhisperTokenizer"
def __init__(self , __magic_... | 279 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {name: getattr(transformers, name + """Fast""") for n... | 325 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def __UpperCAmelCase ( lowercase="ro" ,lowercase="en" ,lowercase="wmt16" ,lowercase=None ):
"""simple docstring"""
try:
import datasets
except (ModuleNotFoundError, ImportError):
rai... | 289 |
from math import isqrt, loga
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> list[int]:
__lowercase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j in range(i**2 , ... | 325 | 0 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def UpperCAmelCase_( a__ , a__=() , a__=None , a__="no" , a__="29500" ):
"""simple docstring"... | 313 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
from tr... | 325 | 0 |
# Copyright 2023 The HuggingFace Inc. 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
#
# Unless required ... | 259 |
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
if TYPE_CHECKING:
... | 325 | 0 |
"""simple docstring"""
def lowercase__ ( snake_case_ :list , snake_case_ :list , snake_case_ :int ):
if len(snake_case_ ) != len(snake_case_ ):
raise ValueError('''The length of profit and weight must be same.''' )
if max_weight <= 0:
raise ValueError(''... | 332 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
fro... | 325 | 0 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __a(SCREAMING_SNAKE_CASE_ : List[Any] )... | 158 |
from __future__ import annotations
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : list[list[int]] ) -> int:
# preprocessing the first row
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
... | 325 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_a = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFo... | 17 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
class A__ ( enum.Enum ):
lowerCAmelCase__ : Dict = "all_checks"
lowerCAmelCase__ : ... | 325 | 0 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRetriev... | 195 |
import math
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int ) -> bool:
assert isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are prime... | 325 | 0 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings('''ignore''', category=UserWarning, module='''torch.optim.lr_scheduler''')
class SCREAMING_SNAKE_CASE__ :
... | 282 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision_a... | 325 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'''edbeeching/decision-transformer-gym-hopper-medium''': (
'''https://huggingface.co/edbeeching/decision-transformer-gym-hopper-medium/resolve/main/config.json'... | 340 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
SCREAMING_SNAKE_CASE__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass... | 325 | 0 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'kwargs, expected' , [
({'num_shards': 0, 'max_num_jobs': 1}, []),
({'num_shards': 10, 'max_num_jobs': 1}, [range(10 ... | 327 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
class A__ ( lowerCAmelCase... | 325 | 0 |
import math
def lowerCamelCase_ ( _UpperCamelCase ) -> bool:
"""simple docstring"""
assert isinstance(_UpperCamelCase , _UpperCamelCase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
... | 279 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVe... | 325 | 0 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
UpperCAmelCase__ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
from .s... | 289 |
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : Optional[Any] , SCREAMING_SNAKE_CASE : List[Any] ) -> List[str]:
__lowercase = [0 for i in range(r + 1 )]
# nc0 = 1
__lowercase = 1
for i in range(1 , n + 1 ):
... | 325 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Any = logging.get_logger(__name__)
a__ : int = {
'''facebook/timesformer''': '''https://huggingface.co/facebook/timesformer/resolve/main/config.json''',
}
class a_ ( lowerCAmelCa... | 313 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, B... | 325 | 0 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class UpperCAmelCase_ ( lowerC... | 259 |
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.
SCREAMING_SNAKE_CASE__ = 10
def __SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE : int , SCREAMING_S... | 325 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
_lowercase : Union[str, Any] = logging.get_logger(__name__)
class _UpperCAmelCase ( lowerCAmelCase__ ):
def __init__( self : Optional[... | 332 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from transformers.testing... | 325 | 0 |
'''simple docstring'''
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require... | 158 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 325 | 0 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
fro... | 17 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_scheduler""")
class A__ :
def __init__( se... | 325 | 0 |
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = len(__SCREAMING_SNAKE_CASE )
lowercase = [[0] * n for i in range(__SCREAMING_SNAKE_CASE )]
for i in range(__SCREAMING_SNAKE_CASE ):
lowe... | 195 |
import collections
import importlib.util
import os
import re
from pathlib import Path
SCREAMING_SNAKE_CASE__ = """src/transformers"""
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE__ = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
SCREAMING_SNAKE_CASE... | 325 | 0 |
import os
import unicodedata
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__)
_lowerCamelCa... | 282 |
import logging
import os
from .state import PartialState
class A__ ( logging.LoggerAdapter ):
@staticmethod
def a__ ( _UpperCAmelCase : str ) -> Optional[Any]:
"""simple docstring"""
__lowercase = PartialState()
return not m... | 325 | 0 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from t... | 340 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET... | 325 | 0 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
_SCREAMING_SNAKE_CASE = """
import os
"""
_SCREAMING_SNAKE_CASE = """
def foo():
import os
return False
"""
_SCREAMING_SNAKE_CASE = """
def foo():
def bar():
... | 327 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ = {
"""facebook/mask2former-swin-small-coco-instance""": (
"""https://huggingface.co/facebook/mask2former... | 325 | 0 |
import mpmath # for roots of unity
import numpy as np
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , UpperCAmelCase=None , UpperCAmelCase=None ) -> int:
'''simple docstring'''
__snake_case : Tuple = ... | 326 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenize... | 326 | 1 |
import requests
_UpperCamelCase = '''YOUR API KEY'''
def lowerCAmelCase__( lowercase : str , lowercase : str = giphy_api_key ) -> list:
__snake_case : List[str] = "+".join(query.split() )
__snake_case : Optional[int] = f"""https://api.g... | 326 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
class _lowerCamelCase ( a ):
... | 326 | 1 |
import math
def lowerCAmelCase__( lowercase : int ) -> str:
__snake_case : List[str] = 0
__snake_case : Union[str, Any] = 0
while num > 0:
__snake_case : Union[str, Any] = num % 8
__snake_case : List[str] = octal + (remain... | 326 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvail... | 326 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class _lowerCamelCase :
"""simple docstring"""
UpperCAmelCase_ : Optional[int] =None
def UpperCAmelCase ( self ) -> T... | 326 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.s... | 326 | 1 |
def lowerCAmelCase__( lowercase : list ) -> list:
if len(lowercase ) < 2:
return collection
def circle_sort_util(lowercase : list , lowercase : int , lowercase : int ) -> bool:
__snake_case : Optional[int] = False
if low == high:
... | 326 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
_UpperCamelCase = logging.getLogg... | 326 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
... | 326 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowerCamelCase ( unittest.TestCase ):
"""simple docstring"""
UpperCAmelCase_ : str =JukeboxTokenizer
UpperCAmelCase_ : Tuple ={... | 326 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class _lowerCamelCase ( unittest.TestCase ):... | 326 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
defau... | 326 | 1 |
import string
import numpy
def lowerCAmelCase__( lowercase : int , lowercase : int ) -> int:
return b if a == 0 else greatest_common_divisor(b % a , lowercase )
class _lowerCamelCase :
"""simple docstring"""
UpperCAmelCase_ : Any... | 326 |
import math
def lowerCAmelCase__( lowercase : list , lowercase : int = 0 , lowercase : int = 0 ) -> list:
__snake_case : Any = end or len(lowercase )
for i in range(lowercase , lowercase ):
__snake_case : List[str] = i
... | 326 | 1 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCAmelCase__( lowercase : Dict ) -> str: # picklable for multip... | 326 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCAmelCase__( lowercase : Dict ) -> str: # picklable for multip... | 326 | 1 |
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 require_keras_nlp, require_t... | 326 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCAmelCase__( lowercase : Dict , lowercase : bool = True , lowercase : float = math.inf , lowercase : float = -math.inf , lowercase : float = math.in... | 326 | 1 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def lowerCAmelCase__( lowercase : List[str] , lowercase : Optional[Any] , lowercase : List[str] ) -> Optional[int]:
__snake_case : Option... | 326 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _lowerCa... | 326 | 1 |
def lowerCAmelCase__( lowercase : int = 1000 ) -> int:
__snake_case , __snake_case : Optional[int] = 1, 1
__snake_case : List[str] = 2
while True:
__snake_case : Optional[Any] = 0
__snake_case : Any = fa + fa
__snake_c... | 326 |
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 = {'''vocab_fil... | 326 | 1 |
from __future__ import annotations
from collections import deque
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , UpperCAmelCase ) -> Optional[int]:
'''simple docstring'''
__snake_case : list[dict] = [... | 326 |
def lowerCAmelCase__( lowercase : list[int] , lowercase : int ) -> bool:
__snake_case : List[str] = len(lowercase )
__snake_case : int = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed ... | 326 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {
'''configuration_albert''': ['''ALBERT... | 326 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_UpperCamelCase = 4
_UpperCamelCase = 3
class _lowerCamelCase ( a ):
"""s... | 326 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCas... | 326 |
def lowerCAmelCase__( lowercase : int = 100_0000 ) -> int:
__snake_case : List[Any] = limit + 1
__snake_case : List[str] = [0] * limit
for first_term in range(1 , lowercase ):
for n in range(lowercase , lowercase , lowercase ):
__sn... | 326 | 1 |
# Copyright 2021 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
#
# Unless required by app... | 326 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : str , lowercase : list[str] | None = None ) -> list[list[str]]:
__snake_case : List[str] = word_bank or []
# create a table
__snake_case : int = len(lowercase ) + 1
__snake... | 326 | 1 |
import datasets
_UpperCamelCase = '''\
@InProceedings{conneau2018xnli,
author = "Conneau, Alexis
and Rinott, Ruty
and Lample, Guillaume
and Williams, Adina
and Bowman, Samuel R.
and Schwenk, Holger
a... | 326 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.m... | 326 | 1 |
def lowerCAmelCase__( lowercase : int , lowercase : int ) -> str:
return "\n".join(
f"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__":
print(multiplication_table(number=5, number_of_terms=10))
| 326 |
import argparse
import datetime
def lowerCAmelCase__( lowercase : str ) -> str:
__snake_case : int = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturday",
}
__snake_... | 326 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_UpperCamelCase = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2VecAudioConfig'''],
'''configuration_data2... | 326 |
def lowerCAmelCase__( lowercase : List[Any] , lowercase : Optional[Any] , lowercase : Optional[int] , lowercase : str , lowercase : List[Any] , lowercase : List[str] ) -> int:
if index == r:
for j in range(lowercase ):
prin... | 326 | 1 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import re... | 326 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging... | 326 | 1 |
def lowerCAmelCase__( lowercase : int = 100_0000 ) -> int:
__snake_case : List[Any] = limit + 1
__snake_case : List[str] = [0] * limit
for first_term in range(1 , lowercase ):
for n in range(lowercase , lowercase , lowercase ):
__sn... | 326 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase__( lowercase : Option... | 326 | 1 |
def lowerCAmelCase__( lowercase : list[int] , lowercase : int ) -> bool:
__snake_case : List[str] = len(lowercase )
__snake_case : int = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed ... | 326 |
from maths.prime_factors import prime_factors
def lowerCAmelCase__( lowercase : int ) -> int:
if not isinstance(lowercase , lowercase ):
__snake_case : Optional[int] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase )
i... | 326 | 1 |
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_UpperCamelCase = logging.get_logger(__name_... | 326 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenize... | 326 | 1 |
import gc
import importlib.metadata
import tempfile
import unittest
from packaging import version
from transformers import (
AutoModel,
AutoModelForCausalLM,
AutoModelForSeqaSeqLM,
AutoModelForSequenceClassification,
AutoTokenizer,
BitsAndBytesConfig,
pipeline,
)
from transformers.te... | 326 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
class _lowerCamelCase ( a ):
... | 326 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 326 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvail... | 326 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_UpperCamelCase = {
'''configuration_gpt_neo''': ['''GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoConfig''', '''GPTNeoOnnxConfig'''],
}
try:
if not i... | 326 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.s... | 326 | 1 |
import argparse
import datetime
def lowerCAmelCase__( lowercase : str ) -> str:
__snake_case : int = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturday",
}
__snake_... | 326 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
_UpperCamelCase = logging.getLogg... | 326 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 326 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowerCamelCase ( unittest.TestCase ):
"""simple docstring"""
UpperCAmelCase_ : str =JukeboxTokenizer
UpperCAmelCase_ : Tuple ={... | 326 | 1 |
import json
import os
import shutil
import tempfile
from unittest import TestCase
from transformers import BartTokenizer, BartTokenizerFast, DPRQuestionEncoderTokenizer, DPRQuestionEncoderTokenizerFast
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bert.tokenization_b... | 326 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
defau... | 326 | 1 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : str , lowercase : list[str] | None = None ) -> list[list[str]]:
__snake_case : List[str] = word_bank or []
# create a table
__snake_case : int = len(lowercase ) + 1
__snake... | 326 |
import math
def lowerCAmelCase__( lowercase : list , lowercase : int = 0 , lowercase : int = 0 ) -> list:
__snake_case : Any = end or len(lowercase )
for i in range(lowercase , lowercase ):
__snake_case : List[str] = i
... | 326 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
from transformers.util... | 326 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCAmelCase__( lowercase : Dict ) -> str: # picklable for multip... | 326 | 1 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar('''KEY''')
_UpperCamelCase = TypeVar('''VAL''')
@dataclass(frozen=a , slots=a )
class _lowerCamelCase ( Generic[KEY, VAL... | 326 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCAmelCase__( lowercase : Dict , lowercase : bool = True , lowercase : float = math.inf , lowercase : float = -math.inf , lowercase : float = math.in... | 326 | 1 |
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
clas... | 326 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _lowerCa... | 326 | 1 |
from __future__ import annotations
_UpperCamelCase = list[list[int]]
# assigning initial values to the grid
_UpperCamelCase = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5],
... | 326 |
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 = {'''vocab_fil... | 326 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
loggi... | 326 |
def lowerCAmelCase__( lowercase : list[int] , lowercase : int ) -> bool:
__snake_case : List[str] = len(lowercase )
__snake_case : int = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed ... | 326 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase__( lowercase : Option... | 326 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_UpperCamelCase = 4
_UpperCamelCase = 3
class _lowerCamelCase ( a ):
"""s... | 326 | 1 |
from datetime import datetime
import requests
def lowerCAmelCase__( lowercase : str ) -> bytes:
__snake_case : Union[str, Any] = "https://downloadgram.net/wp-json/wppress/video-downloader/video?url="
__snake_case : str = requests.get(base_url + url ).json()... | 326 |
def lowerCAmelCase__( lowercase : int = 100_0000 ) -> int:
__snake_case : List[Any] = limit + 1
__snake_case : List[str] = [0] * limit
for first_term in range(1 , lowercase ):
for n in range(lowercase , lowercase , lowercase ):
__sn... | 326 | 1 |
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, BlipaProcessor, BlipImagePr... | 326 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : str , lowercase : list[str] | None = None ) -> list[list[str]]:
__snake_case : List[str] = word_bank or []
# create a table
__snake_case : int = len(lowercase ) + 1
__snake... | 326 | 1 |
def lowerCAmelCase__( lowercase : int = 50 ) -> int:
__snake_case : Union[str, Any] = [1] * (length + 1)
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
ways_number[row_len... | 326 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.m... | 326 | 1 |
class _lowerCamelCase ( a ):
"""simple docstring"""
pass
class _lowerCamelCase ( a ):
"""simple docstring"""
pass
class _lowerCamelCase :
"""simple docstring"""
def __init__( self ) -> Union[str,... | 326 |
import argparse
import datetime
def lowerCAmelCase__( lowercase : str ) -> str:
__snake_case : int = {
"0": "Sunday",
"1": "Monday",
"2": "Tuesday",
"3": "Wednesday",
"4": "Thursday",
"5": "Friday",
"6": "Saturday",
}
__snake_... | 326 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_UpperCamelCase = {
'''configuration_altclip''': [
'''ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''AltCLIPConfig''',
'''AltCLIPText... | 326 |
def lowerCAmelCase__( lowercase : List[Any] , lowercase : Optional[Any] , lowercase : Optional[int] , lowercase : str , lowercase : List[Any] , lowercase : List[str] ) -> int:
if index == r:
for j in range(lowercase ):
prin... | 326 | 1 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , UpperCAmelCase ) -> Union[str, Any]:
'''simple docstring'''
__snake_case : Lis... | 326 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging... | 326 | 1 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vis... | 326 |
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCAmelCase__( lowercase : Option... | 326 | 1 |
import csv
import tweepy
# Twitter API credentials
_UpperCamelCase = ''''''
_UpperCamelCase = ''''''
_UpperCamelCase = ''''''
_UpperCamelCase = ''''''
def lowerCAmelCase__( lowercase : str ) -> None:
# authorize twitter, initialize tweepy
__snake... | 326 |
from maths.prime_factors import prime_factors
def lowerCAmelCase__( lowercase : int ) -> int:
if not isinstance(lowercase , lowercase ):
__snake_case : Optional[int] = f"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase )
i... | 326 | 1 |
import functools
def lowerCAmelCase__( lowercase : list[int] , lowercase : list[int] ) -> int:
# Validation
if not isinstance(lowercase , lowercase ) or not all(isinstance(lowercase , lowercase ) for day in days ):
raise ValueError("The parameter days s... | 326 |
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers import AutoTokenize... | 326 | 1 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
TrainingArgum... | 326 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
class _lowerCamelCase ( a ):
... | 326 | 1 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
_UpperCamelCase = ''''''
_UpperCamelCase = ''''''
_UpperCamelCase = ''''''
_UpperCamelCase = 1 # (0 is vertical, 1 is horizontal)
def lowerCAmelCase__( ) -> None:
... | 326 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvail... | 326 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = '''▁'''
_UpperCamelCase ... | 326 |
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 (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils import logging
logging.s... | 326 | 1 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_availab... | 326 |
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging.INFO,
)
_UpperCamelCase = logging.getLogg... | 326 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConfig... | 326 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowerCamelCase ( unittest.TestCase ):
"""simple docstring"""
UpperCAmelCase_ : str =JukeboxTokenizer
UpperCAmelCase_ : Tuple ={... | 326 | 1 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class _lowerCamelCase ( unittest.TestCase ):
"""simple docstring"""
UpperCAmelCase_ : str =JukeboxTokenizer
UpperCAmelCase_ : Tuple ={... | 326 |
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default_hp_space_optuna,
defau... | 326 | 1 |
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers import GradientAccumulator, cre... | 326 |
import math
def lowerCAmelCase__( lowercase : list , lowercase : int = 0 , lowercase : int = 0 ) -> list:
__snake_case : Any = end or len(lowercase )
for i in range(lowercase , lowercase ):
__snake_case : List[str] = i
... | 326 | 1 |
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch_available():
imp... | 326 |
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def lowerCAmelCase__( lowercase : Dict ) -> str: # picklable for multip... | 326 | 1 |
_UpperCamelCase = 256
# Modulus to hash a string
_UpperCamelCase = 100_0003
def lowerCAmelCase__( lowercase : str , lowercase : str ) -> bool:
__snake_case : Tuple = len(lowercase )
__snake_case : List[Any] = len(lowercase )
i... | 326 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCAmelCase__( lowercase : Dict , lowercase : bool = True , lowercase : float = math.inf , lowercase : float = -math.inf , lowercase : float = math.in... | 326 | 1 |
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import SPIECE_UNDERLINE, is_sentencepiece_available
from transformers.models.speech_to_text import SpeechaTextTokenizer
from transformers.models.speech_to_text.tokenization_speech_to_text import VOCAB_FILES_NAMES, save_json
fr... | 326 |
import warnings
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _lowerCa... | 326 | 1 |
def lowerCAmelCase__( lowercase : int = 100 ) -> int:
__snake_case : Dict = set()
__snake_case : List[Any] = 0
__snake_case : Optional[Any] = n + 1 # maximum limit
for a in range(2 , lowercase ):
for b in range(2 , lowercase )... | 326 |
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 = {'''vocab_fil... | 326 | 1 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : float , lowercase : float , lowercase : float , ) -> tuple:
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more or less than 2 valu... | 326 |
def lowerCAmelCase__( lowercase : list[int] , lowercase : int ) -> bool:
__snake_case : List[str] = len(lowercase )
__snake_case : int = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed ... | 326 | 1 |
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , UpperCAmelCase ) -> None:
'''simple docstring'''
__snake_case : Optional[int] = len(UpperCAmelCase )
__snake_case : Any = [0] * len... | 326 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
_UpperCamelCase = 4
_UpperCamelCase = 3
class _lowerCamelCase ( a ):
"""s... | 326 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple reposit... | 326 |
def lowerCAmelCase__( lowercase : int = 100_0000 ) -> int:
__snake_case : List[Any] = limit + 1
__snake_case : List[str] = [0] * limit
for first_term in range(1 , lowercase ):
for n in range(lowercase , lowercase , lowercase ):
__sn... | 326 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.mod... | 326 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : str , lowercase : list[str] | None = None ) -> list[list[str]]:
__snake_case : List[str] = word_bank or []
# create a table
__snake_case : int = len(lowercase ) + 1
__snake... | 326 | 1 |
from __future__ import annotations
def lowerCAmelCase__( lowercase : tuple[int, int] , lowercase : int ) -> list[tuple[int, int]]:
__snake_case , __snake_case : Optional[Any] = position
__snake_case : List[str] = [
(y + 1, x + 2),
... | 326 |
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transformers.models.big_bird.m... | 326 | 1 |
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