code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def snake_case_ ( _lowerCAmelCase : Any ) -> Tuple:
if "model" in orig_key:
UpperCAmelCase : Dict = orig_key.replace('''mod... | 23 |
'''simple docstring'''
from __future__ import annotations
def snake_case_ ( _lowerCAmelCase : list[int | float] , _lowerCAmelCase : int , _lowerCAmelCase : int ) -> int | float:
if len(_lowerCAmelCase ) == 0:
raise ValueE... | 23 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from... | 355 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
return [
txt[:a] + txt[a].upper() + txt[a + 1 :]
for a in range(len(lowerCAmelCase ) )
if txt[a].isalpha()
]
if __name__ == "__main__":
_... | 248 | 0 |
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 a( A : Optional[Any] ) -> Optional[int]: # picklable for m... | 227 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase: str = logging.get_logger(__name__)
_lowercase: List[str] = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.json"
),
... | 227 | 1 |
'''simple docstring'''
def _lowerCAmelCase ( lowerCamelCase_ : Optional[int] ):
stooge(lowerCamelCase_ , 0 , len(lowerCamelCase_ ) - 1 )
return arr
def _lowerCAmelCase ( lowerCamelCase_ : Tuple , lowerCamelCase_ : Tu... | 364 |
'''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
_SCREAMING_SNAKE_CASE = {'''vocab_file''': '''vocab.txt'... | 217 | 0 |
def lowercase( UpperCamelCase_ , UpperCamelCase_ = " " ) -> list:
'''simple docstring'''
UpperCamelCase = []
UpperCamelCase = 0
for index, char in enumerate(UpperCamelCase_ ):
if char == separator:
split_words.append(string[last_index:index] )
UpperC... | 343 | from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common im... | 343 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[int] = logging.get_logger(__name__)
lowercase__ : List[str] = {
'BAAI/AltCLIP': 'https://huggingface.... | 352 |
"""simple docstring"""
import os
def __lowercase ( _a ):
snake_case_ : Tuple = len(grid[0] )
snake_case_ : Optional[int] = len(_a )
snake_case_ : Union[str, Any] = 0
snake_case_ : Union[str, Any] = 0
snake_case_ : L... | 155 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
... | 64 |
"""simple docstring"""
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def UpperCAmelCase__ (snake_case__ : Optional[int] , snake_case__ : Any=7 ):
"""simple docstring"""
_snake_case... | 64 | 1 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipelin... | 184 |
'''simple docstring'''
import os
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : List[str] = len(grid[0] )
lowerCAmelCase__ : int = len(UpperCamelCase )
lowerCAmelCase__ : Optional[int] ... | 184 | 1 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stable... | 333 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokeniz... | 70 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
import transformers
from transfor... | 110 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
@dataclass
class ... | 110 | 1 |
'''simple docstring'''
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
_UpperCAmelCase : List[Any] = logging.get_logger(__name__)
_UpperCAm... | 174 |
'''simple docstring'''
def __magic_name__( lowerCamelCase, lowerCamelCase):
assert x is not None
assert y is not None
__lowerCAmelCase = len(lowerCamelCase)
__lowerCAmelCase = len(lowerCamelCase)
# declaring the array for storing the dp values
... | 174 | 1 |
'''simple docstring'''
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,
)
... | 311 |
'''simple docstring'''
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class A ( __snake_cas... | 311 | 1 |
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
lowerCamelCase__ = TypeVar("""T""")
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
return (position - 1) // 2
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ) -> int:
... | 212 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, ClassLabel, Features
from .base import TaskTemplate
@dataclass(frozen=__magic_name__ )
class A__ ( __magic_name__ ):
lowercase = field(default='audio-cl... | 212 | 1 |
"""simple docstring"""
import requests
SCREAMING_SNAKE_CASE = "" # <-- Put your OpenWeatherMap appid here!
SCREAMING_SNAKE_CASE = "https://api.openweathermap.org/data/2.5/"
def _SCREAMING_SNAKE_CASE ( lowercase_ = "Chicago" , lowercase_ = APPID ) -> dict:
return r... | 230 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRober... | 230 | 1 |
import datasets
from .evaluate import evaluate
UpperCAmelCase_ : Optional[Any] = '\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n journal={a... | 32 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : Union[str, Any] ):
"""simple docstring"""
stooge(snake_case__ , 0 , len(snake_case__ ) - 1 )
return arr
def UpperCAmelCase__ (snake_case__ : List[Any] , snake_case__ ... | 64 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 353 | def __lowerCamelCase ( lowerCAmelCase__ ):
lowerCAmelCase__ = len(lowerCAmelCase__ )
for i in range(lowerCAmelCase__ ):
for j in range(i + 1 , lowerCAmelCase__ ):
if numbers[j] < numbers[i]:
lowerCAmelCa... | 119 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...fea... | 49 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Union[str, Any] = logging.get_logger(__name__)
__snake_case :Any = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class ... | 49 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
a_ = TypeVar("""T""")
a_ = TypeVar("""U""")
class __snake_case ( Generic[T, U] ):
"""simple docstring"""
def __init__( self , __lowerCa... | 291 |
"""simple docstring"""
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availab... | 291 | 1 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoModelWithLMHead,
A... | 76 |
"""simple docstring"""
def __magic_name__ ( lowercase , lowercase ):
SCREAMING_SNAKE_CASE_: Union[str, Any] =int(lowercase )
# Initialize Result
SCREAMING_SNAKE_CASE_: str =[]
# Traverse through all denomination
for denomination in reversed(l... | 173 | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def UpperCamelCase (lowercase_: int ) -> 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 ar... | 141 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def UpperCamelCase (lowercase_: int ) -> str:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class _a (__magic_name__ ):
'''simple docstring'''... | 141 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : Optional[int] ={
'configuration_squeezebert': [
'SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SqueezeBertConfig',
... | 129 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreT... | 129 | 1 |
'''simple docstring'''
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command,... | 355 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def a_ ( lowerCamelCase : str = "AAPL" ):
lowerCAmelCase = f'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
lowerCAmelCase = BeautifulSoup(requests.get(lowerCamelCase ... | 55 | 0 |
from __future__ import annotations
from typing import TypedDict
class A__ ( snake_case__ ):
"""simple docstring"""
__magic_name__ = 42
__magic_name__ = 42
def UpperCAmelCase__ (UpperCamelCase_ ):
"""simple docstring"""
... | 127 |
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ... | 127 | 1 |
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.file_download import REGEX_COMMIT_HASH
from huggingfac... | 117 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import Inter... | 117 | 1 |
"""simple docstring"""
import requests
_SCREAMING_SNAKE_CASE : Tuple = '' # <-- Put your OpenWeatherMap appid here!
_SCREAMING_SNAKE_CASE : Tuple = 'https://api.openweathermap.org/data/2.5/'
def lowerCamelCase__ ( _low... | 183 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelin... | 115 | 0 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class snake_case__ ( __lowercase ):
"""simple docstring"""
lowerCamelCase = (CMStochasticIterativeScheduler,)
lo... | 361 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class snake_case__ :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : int , UpperCamelCase__ : MutableSeque... | 83 | 0 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __UpperCAmelCase ( A__ ):
'''simple docstring'''
__lowerCAmelCase = ''''''
__lowerCAme... | 258 |
'''simple docstring'''
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowerCamelCase : int = 10
def __a ( UpperCAmelCase , UpperCAmelCase , UpperCAm... | 258 | 1 |
"""simple docstring"""
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .tr... | 259 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def _lowerCamelCase ( ):
'''simple docstring'''
__lowerCAmelCase = {}
__lowerCAmelCase = 2
while True:
__lowerCAmelCase = factor_map.pop(_UpperCamelCase ... | 259 | 1 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_sco... | 189 |
import functools
def lowerCamelCase__ ( _A , _A ):
'''simple docstring'''
if not isinstance(_A , _A ) or not all(isinstance(_A , _A ) for day in days ):
raise ValueError("The parameter days should be a list of integers" )
... | 187 | 0 |
def lowercase_ ( _lowerCamelCase : int = 10 , _lowerCamelCase : int = 1000 , _lowerCamelCase : bool = True):
assert (
isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerCamelCase , _lowerCamelCase)
and isinstance(_lowerC... | 333 | import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__A )
class snake_case_ ( __A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output f... | 333 | 1 |
import math
def lowerCAmelCase_ ( __A ) -> bool:
'''simple docstring'''
return math.sqrt(__A ) * math.sqrt(__A ) == num
def lowerCAmelCase_ ( __A ) -> bool:
'''simple docstring'''
UpperC... | 65 |
import unittest
from transformers import LiltConfig, 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_common import ModelTesterMixin, ... | 52 | 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__ : Optional[Any] =logging.get_logger(__name__)
lowerCAmelCase__ ... | 355 |
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 a__ ( A__, A__, ... | 162 | 0 |
def __magic_name__ ( A : int, A : int ):
'''simple docstring'''
if number < 0 or shift_amount < 0:
raise ValueError("both inputs must be positive integers" )
a = str(bin(A ) )
binary_number += "0" * shift_amount
return binary_number
def __magi... | 107 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixi... | 107 | 1 |
# Lint as: python3
# pylint: enable=line-too-long
# pylint: disable=g-import-not-at-top,g-bad-import-order,wrong-import-position
a__ : Union[str, Any] = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('''3.... | 19 |
import math
def UpperCAmelCase_( a__ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Any = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(a__ )
def UpperCAmelCase_( a__ = 1 / 12_345 ):
"""simple docs... | 19 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer, DPR... | 334 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
_lowerCamelCase =2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be sm... | 334 | 1 |
def lowerCamelCase_ ( _a : str ):
'''simple docstring'''
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def lowerCamelCase_ ( _a : str ):
'''simple docstring'''
UpperCAmelCase_ : List[Any... | 360 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
UpperCamelCase_ = TypeVar('''T''')
UpperCamelCase_ = TypeVar('''U''')
class _snake_case ( Generic[T, U] ):
'''simple docstring'''
def __init__( ... | 59 | 0 |
# 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 applicabl... | 18 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTok... | 135 | 0 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import patch_enviro... | 103 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
import j... | 103 | 1 |
'''simple docstring'''
_lowercase : Tuple = 8.3_1_4_4_6_2 # Unit - J mol-1 K-1
def snake_case_ ( __SCREAMING_SNAKE_CASE : float , __SCREAMING_SNAKE_CASE : float , __SCREAMING_SNAKE_CASE : float ):
"""simple docstring"""
... | 93 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
lowercase_ : Optional[int] = int(__SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
... | 93 | 1 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _SCREAMING_SNAKE_CASE ( ) -> ... | 363 |
import random
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : bool = False) -> dict:
'''simple docstring'''
__UpperCamelCase : dict = {i: [] for i in range(_low... | 151 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : str ) -> bool:
'''simple docstring'''
UpperCAmelCase_ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 1 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
from... | 262 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from di... | 32 | """simple docstring"""
import enum
import shutil
import sys
__lowerCAmelCase , __lowerCAmelCase : List[str] =shutil.get_terminal_size()
__lowerCAmelCase : Union[str, Any] ={"""UP""": """A""", """DOWN""": """B""", """RIGHT""": """C""", """LEFT""": """D"""}
class ... | 32 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) ->... | 67 |
'''simple docstring'''
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 j... | 83 | 0 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
a__: Optional[Any] = logging.get_logger(__name__)
a__: Tuple = {'vocab_file': 'vocab.json', 'me... | 368 |
def UpperCamelCase__( UpperCamelCase__ : int = 1_00 )->int:
A__ = (n * (n + 1) // 2) ** 2
A__ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(F"{solution() = }")
| 39 | 0 |
"""simple docstring"""
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
__A : Tuple = logging.get_logger(__name__)
... | 33 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..... | 260 | 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 SPIECE_UNDERLINE, logging
_UpperCAmelCase : Any = logging.get_logger(__name__... | 363 |
def UpperCAmelCase__ ( ):
lowercase :List[str] = 0
for i in range(1, 1001 ):
total += i**i
return str(lowerCamelCase )[-10:]
if __name__ == "__main__":
print(solution())
| 158 | 0 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def __A ( a_ :str) -> int:
__a : int = np.max(A__ , axis=-1 , keepdims=A__)
__a : Any = np.exp(outputs - maxes)
return shifted_exp / s... | 160 |
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class __lowe... | 205 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=__lowercase )
class lowercase_ ( __lowercase ):
UpperCamelCase_ : str = field(default="ima... | 278 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_video_inputs
if is_torch_available():
import torch
i... | 278 | 1 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : List[str] , __magic_name__ : str=False ) -> Union[str, Any]:
"""simple docstring"""
UpperCamelCase :Lis... | 38 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.config... | 125 | 0 |
"""simple docstring"""
import json
import sys
def lowerCamelCase__ ( __snake_case, __snake_case ) -> Union[str, Any]:
"""simple docstring"""
with open(__snake_case, encoding='''utf-8''' ) as f:
_UpperCamelCase = json.lo... | 100 |
"""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 = {
"""facebook/xlm-rober... | 100 | 1 |
'''simple docstring'''
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def a_ ( lowerCamelCase : Union[str, Any] , lowerCamelCase : Tuple , lowerCamelCase : Optional[Any] , lowerCamelCase : Any , low... | 4 |
def lowerCamelCase_ ( lowerCamelCase__ , lowerCamelCase__ ):
lowerCamelCase_ = [0 for i in range(r + 1 )]
# nc0 = 1
lowerCamelCase_ = 1
for i in range(1 , n + 1 ):
# to compute current row from previous row.
lowerCamelCase_ = min(lowerCamelCase__ , lo... | 19 | 0 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowercase__ ( UpperCamelCase_ , UpperCamelCase_):
@register_to_config
def __init__( sel... | 353 | import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def A ( _lowercase ):
return (data["data"], data["target"])
def ... | 258 | 0 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase ( lowercase_ ):
'''simple docstrin... | 121 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int, __snake_case : int, __snake_case : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(__snake_case : int, __snake_case : int ) -> in... | 134 | 0 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 363 |
"""simple docstring"""
from typing import Any
class a :
"""simple docstring"""
def __init__( self: List[Any] , UpperCamelCase: Any ):
"""simple docstring"""
A__ = data
A__ = None
... | 69 | 0 |
def _UpperCamelCase ( lowercase__ = 10 , lowercase__ = 1000 , lowercase__ = True ):
assert (
isinstance(lowercase__ , lowercase__ )
and isinstance(lowercase__ , lowercase__ )
and isinstance(lowercase__ , ... | 9 |
import random
from .binary_exp_mod import bin_exp_mod
def UpperCamelCase ( lowerCAmelCase__ , lowerCAmelCase__=1000 ):
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
lowercase = n - 1
... | 101 | 0 |
"""simple docstring"""
import os
import jsonlines
import numpy as np
from tqdm import tqdm
_A = 20_48
_A = 40_96
_A = 42
_A = os.environ.pop("""PROCESS_TRAIN""", """false""")
_A = {"""null""": 0, """short""": 1, """long""": 2, """yes""": 3, """no... | 363 |
"""simple docstring"""
_A = range(2, 20 + 1)
_A = [10**k for k in range(ks[-1] + 1)]
_A = {}
def a__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ) -> int:
UpperCAmelCase__ : List[str] = sum(a_i[j] for j in... | 166 | 0 |
import string
import numpy
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__) -> int:
return b if a == 0 else greatest_common_divisor(b % a , __UpperCAmelCase)
class __snake_case :
'''simple docstring'''
lowerCAmelCase__... | 111 |
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... | 201 | 0 |
def snake_case ( snake_case__ :str) -> list:
if n_term == "":
return []
_A = []
for temp in range(int(snake_case__)):
series.append(F'''1/{temp + 1}''' if series else """1""")
return series
if __name__ == "__main__":
... | 81 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE = {'configuration_fnet': ['FNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FNetCo... | 81 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
f... | 165 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMix... | 165 | 1 |
"""simple docstring"""
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 OptionalD... | 368 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf... | 30 | 0 |
a__: Tuple = 9.8_06_65
def UpperCamelCase__( UpperCamelCase__ : float , UpperCamelCase__ : float , UpperCamelCase__ : float = g )->Dict:
if fluid_density <= 0:
raise ValueError('''Impossible fluid density''' )
... | 193 |
'''simple docstring'''
from __future__ import annotations
from collections import Counter
from random import random
class lowerCAmelCase__ :
def __init__( self ):
"""simple docstring"""
lowercase_ : int = ... | 93 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import Autoencod... | 359 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators ... | 313 | 0 |
from functools import lru_cache
@lru_cache
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : int) -> int:
'''simple docstring'''
if num < 0:
raise ValueError("Number should not be negative.")
return 1 if num in (0, 1) else num * facto... | 232 |
from __future__ import annotations
import math
lowercase : Any = '2020.9.26'
lowercase : Union[str, Any] = 'xcodz-dot, cclaus, dhruvmanila'
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : float , _lowerCamelCase : float , _lowerCamelCas... | 232 | 1 |
'''simple docstring'''
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base impor... | 104 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
a_ : Optional[Any] = TypeVar("T")
def _A (lowerCAmelCase__ :int ) -> int:
'''simple docstring'''
r... | 104 | 1 |
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterM... | 19 |
"""simple docstring"""
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tok... | 64 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
snake_case : Optional[Any] = 6378137.0
snake_case : str = 6356752.314245
snake_case : int = 6_37_81_37
def __lowercase ( __lowerCAmelCase : float , __lowerCAmelCase ... | 109 |
def __lowercase ( __lowerCAmelCase : int ):
if num <= 0:
raise ValueError('Input must be a positive integer' )
a__ = [True] * (num + 1)
a__ = 2
while p * p <= num:
if primes[p]:
for i i... | 109 | 1 |
"""simple docstring"""
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class __lowerCAmelCase ( pl.LightningModule ):
'''simple docstring'''
def __init__( s... | 45 |
"""simple docstring"""
lowercase_ = "ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/"
def lowercase ( lowerCAmelCase__ : bytes ) -> bytes:
# Make sure the supplied data is a bytes-like object
if not isinstance(lowerCAmelCase__ , lowerCAmel... | 45 | 1 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( lowercase_ ) -> list[int]:
A__ = [True] * limit
A__ = False
A__ = False
A__ = True
for i in range(3 , int(limit**0.5 + 1 ) , 2 ):
A__ = i * 2
whi... | 230 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
"SCUT-DLVCLab/lilt-roberta-en-base": (
"https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolve/main/... | 230 | 1 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class a ( lowercase__ ):
__lowerCAmelCase : Dict = (DDPMScheduler,)
def __lowerCamelCase ( self :Tuple ,**__lowercase :Union[str, Any] ):
... | 230 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase_ : Optional[int] = {
'facebook/mask2former-swin-small-coco-instance': (
'https://huggingfa... | 32 | 0 |
'''simple docstring'''
import os
def UpperCAmelCase_ (__a : str = "input.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(__a ) , __a ) ) as input_file:
_a : List[str] = [
[int(__a ) for element in line.split(',' )... | 5 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoi... | 5 | 1 |
"""simple docstring"""
from __future__ import annotations
class lowerCAmelCase_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
snake_case = text, pattern
snake_cas... | 150 | """simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chan... | 213 | 0 |
'''simple docstring'''
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,
... | 190 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenize... | 190 | 1 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
re... | 170 |
from __future__ import annotations
import math
def lowerCAmelCase_ ( _lowercase : int) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negati... | 170 | 1 |
'''simple docstring'''
from graphs.minimum_spanning_tree_kruskal import kruskal
def _A ( ):
"""simple docstring"""
__lowercase =9
__lowercase =[
[0, 1, 4],
[0, 7, 8],
[1, 2, 8],
[7, 8, 7],
[7, 6, 1],
... | 48 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _A ( _lowerCAmelCase ):
"""simple docstring"""
__lowercase =SwinConfig(image_size=192 )
... | 48 | 1 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 268 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class UpperCamelCase_ :
def __init__( self : str ) -> Dict:
UpperCAmelCase_ : List[Any] = ""
UpperCAmelCase_ : int = ""... | 268 | 1 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase( UpperCamelCase... | 368 | from ....configuration_utils import PretrainedConfig
from ....utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
# TODO: upload to AWS
_SCREAMING_SNAKE_CASE = {
"""yjernite/retribert-base-uncased""": (
"""https://huggingface.co/yjernite/retribert-base-unca... | 165 | 0 |
'''simple docstring'''
from __future__ import annotations
def a_ ( _lowerCAmelCase ,_lowerCAmelCase ) -> list[str]:
if nth_term == "":
return [""]
__lowerCamelCase : Any = int(__UpperCamelCase )
__lowerCamelCase ... | 208 |
'''simple docstring'''
import datasets
from .evaluate import evaluate
SCREAMING_SNAKE_CASE__ = '\\n@article{hendrycks2021cuad,\n title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},\n author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},\n ... | 321 | 0 |
'''simple docstring'''
def _a ( _lowercase : list[int] ):
'''simple docstring'''
__UpperCAmelCase : Optional[int] = []
if len(_lowercase ) == 1:
return [nums.copy()]
for _ in range(len(_lowercase ) ):
... | 369 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
S... | 240 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Dict =logging.get_logger(__name__)
__lowerCAmelCase : str ={
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
... | 237 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str = "cpu" , lowerCAmelCase__ : Union[str, None] = None ) -> None:
... | 224 | 0 |
from manim import *
class UpperCamelCase__ ( __lowercase ):
def lowerCAmelCase (self : List[str] ):
__a : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
__a : Union[str, Any] = Rectangle(height=0.46 , width=0.46 ).set_stroke(width=0 )
... | 353 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 0 |
"""simple docstring"""
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_... | 45 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
a_ :Optional[Any] = logging.getLogger(__n... | 277 | 0 |
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.utils.data import Data... | 350 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
__a = logging.getLogger()
def lowerCamelCase__ ... | 235 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import float... | 109 |
"""simple docstring"""
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _snake_case ( *UpperCamelCase : str , UpperCamelCase : Optional[Union[Dict, Any]] = None , UpperCamelCase : Tuple=True , UpperCamelCase ... | 109 | 1 |
from __future__ import annotations
def UpperCamelCase_( _snake_case : list[int] , _snake_case : int , _snake_case : int , _snake_case : int ):
"""simple docstring"""
if (direction == 1 and array[indexa] > array[indexa]) or (... | 308 |
import os
def UpperCamelCase_( _snake_case : str = "input.txt" ):
"""simple docstring"""
with open(os.path.join(os.path.dirname(_snake_case ) , _snake_case ) ) as input_file:
__a =[
[int(_snake_case ) for element i... | 308 | 1 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
_lowerCamelCase : Optional[int] = Fal... | 167 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import ... | 167 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( a_: list[int] ):
if not numbers:
return 0
if not isinstance(a_, (list, tuple) ) or not all(
isinstance(a_, a_ ) for number in numbers ):
raise ValueError("numbers must be an iterable of integers" )
... | 17 | '''simple docstring'''
import baseaa
def __UpperCAmelCase ( a_: str ):
return baseaa.baaencode(string.encode("utf-8" ) )
def __UpperCAmelCase ( a_: bytes ):
return baseaa.baadecode(a_ ).decode("utf-8" )
if __name__ == "__main__":
... | 17 | 1 |
import os
def UpperCAmelCase_ ( __snake_case = "input.txt" ) -> int:
"""simple docstring"""
with open(os.path.join(os.path.dirname(__snake_case ) , __snake_case ) ) as input_file:
_lowercase =[
[int(__snake_case ) for element in lin... | 5 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProcessor,
)
from transfor... | 5 | 1 |
class snake_case__ :
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__=None , lowerCAmelCase__=None ) -> Tuple:
__magic_name__ : int = data
__magic_name__ : Dict = previous
__magic_name__ ... | 138 |
__magic_name__: List[Any] = "\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
__magic_name__: Dict = [{"type": "code", "content": INSTALL_CONTENT}... | 138 | 1 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _SCREAMING_SNAKE_CASE ( A__ ):
def __init__( self , __A ... | 84 |
'''simple docstring'''
a__ : Union[str, Any] = [sum(int(c, 1_0) ** 2 for c in i.__str__()) for i in range(1_0_0_0_0_0)]
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
UpperCamelCase__ = 0
while number:
# In... | 80 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, 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 ... | 360 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import f... | 337 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
_a = datasets.utils.logging.get_logger... | 322 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_a = '''.'''
# Internal TensorFlow ops that can be s... | 322 | 1 |
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 AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tes... | 36 |
def lowerCAmelCase__ ( _a : float , _a : float ):
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
if __name__ == "__main__":
... | 36 | 1 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def _lowerCAmelCase ( _UpperCamelCase : Optional[int] , _UpperCamelCase : List[Any] ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =math.sqrt(snake_case__ ... | 47 |
"""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
A_ : List[Any] = logging.get_logger(__na... | 165 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 276 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : Optional[Any] = logging.get_logger(__name__)
A : List[str] = {
'''huggingface/time-series-transformer-tourism-monthly''': (
'''https://hugging... | 276 | 1 |
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils import ca... | 48 |
'''simple docstring'''
import string
from math import logaa
def __snake_case( _lowerCAmelCase , _lowerCAmelCase ) -> int:
snake_case__ : List[str] = document.translate(
str.maketrans("""""" , """""" , string.punctuation ) ).replace("""\n""" ... | 35 | 0 |
import math
def lowerCAmelCase_ (lowerCAmelCase__: int ):
"""simple docstring"""
assert isinstance(lowerCAmelCase__ , lowerCAmelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
#... | 82 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
a : Optional[int] = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'se... | 82 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...... | 109 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
... | 111 | 0 |
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 DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils impo... | 152 |
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 OptionalDependencyNotAvailab... | 152 | 1 |
import argparse
import copy
def _A ( _lowercase ) -> List[Any]:
"""simple docstring"""
__UpperCamelCase = {}
with open(__snake_case ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
... | 310 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def __lowerCamelCase ( __snake_case : str, __snake_case : dict ) -> str:
"""simple docstring"""
A__ : Optional[Any] =BeautifulSoup(requests.get(__snake_case, params=__s... | 134 | 0 |
"""simple docstring"""
import unittest
from transformers import DonutProcessor
_UpperCamelCase: Any = 'naver-clova-ix/donut-base'
class a__ ( unittest.TestCase ):
def lowercase ( self : Optional[Any] ) -> Tuple:
... | 53 |
"""simple docstring"""
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if ... | 53 | 1 |
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