code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
def UpperCamelCase_( lowerCamelCase_ ) -> list:
_lowercase : Optional[Any] = len(lowerCamelCase_ )
for i in range(1 , lowerCamelCase_ ):
_lowercase : Tuple = collection[i]
_lowercase : str = 0
_lowercase ... | 89 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64... | 688 | 0 |
import string
import numpy
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ ) -> int:
return b if a == 0 else greatest_common_divisor(b % a , lowerCamelCase_ )
class _lowerCamelCase:
lowercase_ : Tuple = string.ascii_uppercase + string.... | 354 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class _lowerCamelCase( _a ):
@require_torch
def UpperCamelCase ( self) -> int:
"""simple docst... | 354 | 1 |
class A : # Public class to implement a graph
def __init__( self: int , _lowerCAmelCase: int , _lowerCAmelCase: int , _lowerCAmelCase: list[list[bool]] ) -> None:
'''simple docstring'''
UpperCAmelCase_ =row
Uppe... | 54 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( __magic_name__ ):
"""simple docst... | 282 | 0 |
'''simple docstring'''
import argparse
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... | 665 |
'''simple docstring'''
from math import isqrt
def _a( UpperCamelCase__ : int ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : int =[True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
... | 665 | 1 |
"""simple docstring"""
from itertools import count
def a_ ( lowercase__ :int = 50 ):
__lowerCamelCase = [1] * min_block_length
for n in count(__lowerCamelCase ):
fill_count_functions.append(1 )
for block_length in range(__lowerCamelCase... | 281 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
_SCREAMING_SNAKE_CASE : Any = """sshleifer/bart-tiny... | 344 | 0 |
class __lowercase :
def __init__( self , A_ ) ->None:
'''simple docstring'''
__lowerCAmelCase : Dict = len(A_ )
__lowerCAmelCase : int = [0] * len_array
if len_array > 0:
__lowerCAmelCase : Un... | 583 |
def _lowercase ( lowercase__ , lowercase__ ):
__lowerCAmelCase : Union[str, Any] = len(lowercase__ )
__lowerCAmelCase : Any = len(lowercase__ )
__lowerCAmelCase : str = [[False for _ in range(m + 1 )] for _ in range(n + 1 )]
__low... | 583 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
A_ = {"configuration_beit": ["BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "BeitConfig", "BeitOnnxConfig"]}
try... | 42 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def _lowerCamelCase (__lowerCamelCase : str ) -> None:
a__ , a__ = analyze_text(__lowerCamelCase )
a__ = list(" " + asci... | 489 | 0 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import Gradient... | 700 |
a =[
"""Audio""",
"""Array2D""",
"""Array3D""",
"""Array4D""",
"""Array5D""",
"""ClassLabel""",
"""Features""",
"""Sequence""",
"""Value""",
"""Image""",
"""Translation""",
"""TranslationVariableLanguages""",
]
from .audio import Audio
from .features im... | 337 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=_a ):
'''simple docstring'''
lowerCamelCase__ = ['''keras_nlp''']
def __init__( self , *__SCREAMING_SNAKE_CASE , **__SCREAMING_SNAKE_CASE ... | 38 |
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,
BertTokeni... | 181 | 0 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
... | 182 |
from collections.abc import Callable
import numpy as np
def snake_case__ ( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase ) -> np.array:
"""simple docstring"""
A__ : Any = int(np.ceil((x_end - xa) / s... | 182 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
from diffusers.utils import floa... | 36 |
'''simple docstring'''
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_attent... | 694 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ : str = {
'configuration_longformer': [
... | 464 |
'''simple docstring'''
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase ( A : Union[str, Any] , A : Optional[int] ... | 464 | 1 |
"""simple docstring"""
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCamelCase = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and... | 82 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return x if y == 0 else greatest_common_divisor(lowerCAmelCase__ , x % y )
def a__ ( lowerCAmelCase__ , lowerCAmelCase__ ):
return (x * y) // greatest_common_divisor(lowerCA... | 82 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, V... | 709 | from __future__ import annotations
from collections.abc import Callable
def a__ ( a , a , a , a = 1_0_0 , ) -> float:
A_ : Any = x_start
A_ : int = fnc(a )
A_ : int = 0.0
for _ ... | 236 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __UpperCamelCase ( _a ):
'''simple docstring'''
@require_torch
def _UpperCAmelCase ( self ):
... | 113 |
_lowerCAmelCase : int ="""
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.g... | 113 | 1 |
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowercase_ (A : Any ):
snake_case__ : Dict = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementation only works for 2x2 matrices
... | 707 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
a_ :Dict = {
"configuration_gpt_neox_japanese": ["GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP", "GPTNeoXJapaneseConfig"],
"tokenization_gpt_neox... | 243 | 0 |
'''simple docstring'''
lowerCAmelCase__ : Any = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
lowerCAmelCase__ : List[str] = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def _a ( __lowerCAmelCase : dict[int, list[int]] , __lowerCAmelCase : ... | 347 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, 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 import ModelTes... | 347 | 1 |
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 lowerCamelCase_ ( lowerCAmelCase__ : List[Any] ) -> ... | 224 |
def lowerCamelCase_ ( lowerCAmelCase__ : Dict , lowerCAmelCase__ : List[Any] ) -> Optional[int]:
'''simple docstring'''
A = ''
for i in table:
res += inp[i - 1]
return res
def lowerCamelCase_ ( lowerCAmelCase__ : List[... | 224 | 1 |
def _A ( ) -> list[list[int]]:
"""simple docstring"""
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
__snake_case = generate_large_matrix()
__snake_case = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, ... | 1 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _UpperCamelCase (*_lowerCamelCase : str , _lowerCamelCase : Optional[Union[Dict, Any]] = None , _lowerCamelCase : List[Any]=True , _low... | 24 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase : Dict = {
"configuration_mobilevit": ["MOBILEVIT_PRETRAINE... | 718 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simpli... | 343 | 0 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerC... | 678 |
import collections
import os
import re
from pathlib import Path
lowerCAmelCase_ = """src/transformers"""
# Matches is_xxx_available()
lowerCAmelCase_ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase_ = re.compile(R"... | 678 | 1 |
'''simple docstring'''
import argparse
import os
# New Code #
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
f... | 705 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization impor... | 276 | 0 |
"""simple docstring"""
import inspect
import unittest
class SCREAMING_SNAKE_CASE ( unittest.TestCase ):
"""simple docstring"""
def __lowerCAmelCase ( self : Optional[int] ):
try:
import diffusers # noqa: F401
except ImportError... | 450 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class SCREAMING_SNAKE_CASE ( ... | 450 | 1 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ , UpperCAmelCase_ ):
return int((input_a, input_a).count(0 ) != 0 )
def UpperCamelCase( ):
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 , 0 ) == 1
assert nand_ga... | 695 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ = 10_00 ):
UpperCAmelCase : List[Any] = 2**power
UpperCAmelCase : List[Any] = 0
while n:
UpperCAmelCase , UpperCAmelCase : Optional[Any] = r + n % 10, n // 10
return r
if __name__ == "__ma... | 695 | 1 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
... | 52 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def __A ( a_ :Union[str, Any] , a_ :Union[str, Any] , a_ :Optional[Any] , a_ :Optional[int]=5) -> List[Any]:
# Adapted from https://github... | 52 | 1 |
import inspect
import unittest
class A_ ( unittest.TestCase ):
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( self ):
try:
import diffusers # noqa: F401
except ImportError:
assert False
def SCREAMING_SNAKE_CASE__ ( self ):
import diffusers
from diffusers.dep... | 713 |
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 import logging
loggi... | 565 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : Union[str, Any] = {
'''configuration_mobilebert''': [
'''M... | 589 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torc... | 280 | 0 |
"""simple docstring"""
import cva
import numpy as np
class _lowercase :
"""simple docstring"""
def __init__( self : Dict , UpperCamelCase__ : float , UpperCamelCase__ : int ) -> Union[str, Any]:
... | 296 | """simple docstring"""
def lowerCAmelCase (__UpperCamelCase : int = 1_0_0_0_0_0_0 ):
"""simple docstring"""
__UpperCamelCase =1
__UpperCamelCase =1
__UpperCamelCase ={1: 1}
for inputa in range(2 , __UpperCamelCase ):
__Upper... | 296 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = ""... | 451 | '''simple docstring'''
import math
def A_ ( SCREAMING_SNAKE_CASE_ ) ->int:
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
lowercase_ = f"""Input value of [number={number}] must be an integer"""
raise TypeError(SCREAMING_SNAKE_CASE_ )
if number... | 451 | 1 |
'''simple docstring'''
lowercase_ = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_0000)]
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =0
while number:
# Increased Speed Slightly by checking every 5 digits tog... | 717 | '''simple docstring'''
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
def UpperCamelCase__ ( self ) -> Optional[Any]:
_lowerCAmelCase =0
_lowerCAmelCase =[0]
... | 58 | 0 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
lowercase_ : Dict = logging.get_lo... | 64 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowercase_ ( _lowercase : list[int] ):
'''simple docstring'''
UpperCAmelCase : str = len(_lowercase ) // 2
# choose the middle 3 elements
UpperCAmelCase : str = lst[m - 1 : m + 2]
... | 292 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case_ : Dict = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfi... | 292 | 1 |
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
snake_case__ : Optional[int] = Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
import io ... | 408 |
class SCREAMING_SNAKE_CASE_ :
'''simple docstring'''
def __init__( self : List[Any] ) ->Tuple:
lowerCamelCase_ : Optional[Any] = """"""
lowerCamelCase_ : Dict = """"""
lowerCamelCase_ : Optional[Any] = []
de... | 278 | 0 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __magic_name__ ( UpperCAmelCas... | 718 |
'''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: Dict = logging.get_logger(__name__)
A: Optional[Any] ... | 7 | 0 |
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_uti... | 45 |
# 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 by app... | 219 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
_A : Optional[Any] =logging.get_... | 704 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Dict =logging.get_logger(__name__)
_A : Dict ={
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class lowerCamelCase__ ( A... | 4 | 0 |
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class SCREAMING_SNAKE_CASE ( __snake_case , __snake_case ):
... | 187 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
A = logging.get_logger(__name__)
A ... | 187 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase : Optional[Any] = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLIPConfig",
... | 284 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformer... | 284 | 1 |
'''simple docstring'''
import torch
from diffusers import KDPMaDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class snake_case__ ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCamelCase ... | 638 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig... | 638 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
lowercase_ = tuple[int, int]
class SCREAMING_SNAKE_CASE :
def __init__( self : Tuple , a : set[int] , a : Mapping[EdgeT, int] )-> Dict:
... | 707 |
from __future__ import annotations
import math
from collections.abc import Callable
def __UpperCamelCase (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 100 , ) -> float:
lowercase__ = x_start
lowercase__ ... | 45 | 0 |
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class _A( datasets.BuilderConfig ):
"""simple docstring"""
UpperCamelCase : Optional[datasets.Fe... | 239 |
from ..utils import DummyObject, requires_backends
class _A( metaclass=snake_case__ ):
"""simple docstring"""
UpperCamelCase : Tuple = ['''torch''', '''scipy''']
def __init__( self , *_A , **_A ):
requires_backends(self , ['torch', 'scipy'] )
... | 239 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, loa... | 480 |
"""simple docstring"""
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,
)
_lowerCAmelCase = ... | 480 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : int ):
"""simple docstring"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_lowerCamelCase : Union[str, Any] = 1
_lowerCamelCase : Optional[int] = 1
while repunit:
... | 88 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowerCamelCase =(3, 9, -1_1, 0, 7, 5, 1, -1)
lowerCamelCase =(4, 6, 2, 0, 8, 1_0, 3, -2)
@dataclass
class _lowerCamelCase :
"""simple docstring"""
SCREAMING_SNAKE_CAS... | 285 | 0 |
"""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 OptionalDependencyNotA... | 395 |
"""simple docstring"""
def A_ ( __lowercase = 10 ):
if not isinstance(__lowercase , __lowercase ) or n < 0:
raise ValueError('Invalid input' )
UpperCamelCase_ : int =10**n
UpperCamelCase_ : List[str] =2_84_33 * (pow(2 , 7_83_04_57 , __lowercase )) + 1
return st... | 395 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase__ ( A : List[str] , A : Dict , A : Tuple , A : Union[str, Any] ): # noqa: E741
'''simple docstring'''
while r - l > 1:
UpperCAmelCase = (l + r) // 2
i... | 210 |
from importlib import import_module
from .logging import get_logger
UpperCAmelCase : Union[str, Any] = get_logger(__name__)
class _A:
"""simple docstring"""
def __init__( self , _A , _A=None ):
__A : Union[str, Any] = attrs or []
if mod... | 239 | 0 |
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
__lowercase = input('''Enter image url: ''').strip()
print(F'Downloading image from {url} ...')
__lowercase = BeautifulSoup(requests.get(url).content, '''html.parser''')
... | 452 | from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowercase = datasets.load_iris()
__lowercase = np.array(data['''data'''])
__lowercase = np.array(data['''target'''])
__lowercase ... | 452 | 1 |
__snake_case = '''
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
__snake_case = [{'''type''': '''code''', '''content''': INSTALL_CONTENT}]
__snak... | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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 im... | 582 | 0 |
"""simple docstring"""
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_a... | 718 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case ( __lowercase , unittest.TestCase ):
UpperCAmelCase__... | 628 | 0 |
from __future__ import annotations
import math
def __A ( _A , _A , _A , _A , _A ):
"""simple docstring"""
if depth < 0:
raise ValueError("Depth cannot be less than 0" )
if not scores:
raise ValueError("Scores cannot be empty" )
i... | 197 | from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : Optional[int] = {
"""configuration_mctct""": ["""MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MCTCTConfig"""],
"""feature_extraction_mctct""": ["""MC... | 197 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase : List[Any] = logging.get_logger(_... | 703 |
'''simple docstring'''
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class snake_case ( __low... | 694 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attention_m... | 271 | import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.... | 271 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ : Optional[int] = logging.get_logger(__name__)
__magic_name__ : Optional[Any] = ... | 701 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class lowerCamelCase ( __snake_case ):
"""simple docstring"""
lo... | 608 | 0 |
'''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 ..packaged_module... | 356 |
'''simple docstring'''
def lowerCamelCase__ ( a ):
__snake_case = [0] * len(a )
__snake_case = []
__snake_case = []
__snake_case = 0
for values in graph.values():
for i in values:
indegree[i] += 1
... | 356 | 1 |
import numpy as np
import torch
from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class __magic_name__ ( __lowerCAmelCase):
A: Any... | 713 |
from math import factorial, radians
def _a ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : int = 18 , SCREAMING_SNAKE_CASE : int = 10 ):
"""simple docstring"""
UpperCamelCase__ : Dict = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Conve... | 106 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name_... | 9 |
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_comm... | 9 | 1 |
# 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 by ap... | 700 |
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 Interp... | 184 | 0 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise ValueError("check_bouncy() accepts only integer arguments" )
_lowerCamelCase : Optional[int] ... | 44 |
import random
from typing import Any
def UpperCAmelCase_ ( snake_case__ ) -> list[Any]:
"""simple docstring"""
for _ in range(len(snake_case__ ) ):
lowerCAmelCase__ = random.randint(0 , len(snake_case__ ) - 1 )
lowerCAmelCase__ = r... | 193 | 0 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def __a(SCREAMING_SNAKE_CASE_ : int ):
'''simple docstring'''
def is_in_circle(SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_... | 720 |
'''simple docstring'''
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class lowerCAmelCase_ :
def _snake_case ( self , _lowerCAmelCase ) -> Tuple:
raise NotImplementedError()
def ... | 489 | 0 |
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,
requ... | 371 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case_ : str = {
'''configuration_table_transformer''': [
'''TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TableTransformerConfig''',
''... | 691 | 0 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""kakaobrain/align-base""": """https://hugging... | 207 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Tra... | 207 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-... | 94 |
def _lowercase ( UpperCAmelCase_):
"""simple docstring"""
snake_case__ : Any = int(UpperCAmelCase_)
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCAmelCase_)
snake_case__ , snake_case__ : Optional[Any] = div... | 648 | 0 |
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 ... | 689 |
from __future__ import annotations
import math
def UpperCamelCase_ ( a_ , a_ ) ->float:
A =u
for i in range(1 , a_ ):
A =temp * (u - i)
return temp
def UpperCamelCase_ ( ) ->None:
A =int(input("enter the numbers of values: " ) )
A =[]
for _ in ... | 689 | 1 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 73 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
im... | 678 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class SCREAMING_SNAKE_CASE:
snake_case_ : int
snake_case_ : Node | None... | 700 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
A : List[str] = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE( __A ):
def __init__( self , *lowerCamelCa... | 163 | 0 |
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
@... | 254 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...tes... | 254 | 1 |
def a__ ( A_, A_ ):
'''simple docstring'''
if not (isinstance(A_, A_ ) and isinstance(A_, A_ )):
raise ValueError("""longest_common_substring() takes two strings for inputs""" )
__magic_name__ = len(A_ )
__magic_name__ = len(A_ ... | 76 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCAmelCase : Tuple = logging.get_logger(__name__)
__lowerCAmelCase : Tuple = {
'SCUT-DLVCLab/lilt-roberta-en-base': (
'https://huggingface.co/SCUT-DLVCLab/lilt-roberta-en-base/resolv... | 76 | 1 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __snake_case (unittest.TestCase ):
def SCREAMING_SNAKE_CASE ( self : Any ) -> List[Any]:
'''simple docstring'''... | 429 |
# using dfs for finding eulerian path traversal
def _UpperCAmelCase (UpperCamelCase_ : Tuple , UpperCamelCase_ : Optional[int] , UpperCamelCase_ : int , UpperCamelCase_ : Optional[int]=None ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] ... | 429 | 1 |
"""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.
UpperCAmelCase = 10
def lowerCamelCase (a_ :int , a_ :int , a_ ... | 475 |
"""simple docstring"""
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import Base... | 475 | 1 |
import math
def _A ( lowerCamelCase , lowerCamelCase ):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(lowerCamelCase__ )
else:
if x == 0: # 0 raised to any number is 0
return 0
elif y == 0:
r... | 112 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case : Optional[int] = logging.get_logger(__name__)
__snake_case : int = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",... | 131 | 0 |
'''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... | 713 | from ..utils import DummyObject, requires_backends
class UpperCAmelCase__ ( metaclass=snake_case ):
"""simple docstring"""
lowerCAmelCase__ : List[str] = ['transformers', 'torch', 'note_seq']
def __init__( self: List[str] , *__lowerCAmelCase: Optional[int] , **... | 286 | 0 |
"""simple docstring"""
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def A_ ( ):
'''simple docstring'''
UpperCamelCase : Any = ArgumentParser(
descrip... | 499 |
"""simple docstring"""
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
fro... | 499 | 1 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__A : Optional[Any] = [
'good first issue',
'feature request',
'wip',
]
def lowerCAmelCase_ ( ):
a__ = Github(os.environ['GITHUB_TOKEN'] )
a__ ... | 126 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
__A : str = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), 5: (... | 126 | 1 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
UpperCamelCase__ = pytest.mark.integration
@pytest.mark.parametrize("path"... | 620 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from ... import Pr... | 36 | 0 |
"""simple docstring"""
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
... | 707 | """simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common import... | 595 | 0 |
"""simple docstring"""
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, rand... | 58 |
a__: str = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_firs... | 190 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avail... | 641 |
import unittest
from transformers import XLMConfig, 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 ModelTesterM... | 641 | 1 |
'''simple docstring'''
_UpperCamelCase = {str(digit): digit**5 for digit in range(10)}
def _lowercase (SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(SCREAMING_SNAKE_CASE ) )
def _lower... | 111 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
_UpperCamelCase = {"""configuration_vit""": ["""VIT_PRETRAI... | 111 | 1 |
import math
from datetime import datetime, timedelta
def snake_case_ ( SCREAMING_SNAKE_CASE_ ) -> datetime:
lowercase__ : List[Any] = year % 19
lowercase__ : Union[str, Any] = year % 4
lowercase__ : List[str] ... | 298 |
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
__a : str = argparse.ArgumentParser()
parser.add_argument('''--dump_path''', default=N... | 298 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __A ( nn.Module ):
UpperCAmelCase__ = 42
Uppe... | 96 |
'''simple docstring'''
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
snake_case = get_tests_dir("""fixtures/... | 378 | 0 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowercase (snake_case__ : str ) -> Union[str, Any]:
'''simple docstring'''
return x + 2
class SCREAMI... | 529 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_... | 529 | 1 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
class snake_case__ ( a_ ):
_SCREAMING_SNAKE_CASE ... | 666 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS... | 328 | 0 |
from functools import reduce
__lowercase = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""668966489504... | 563 |
import datasets
from .evaluate import evaluate
__lowercase = """\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268},
... | 563 | 1 |
from __future__ import annotations
def snake_case__ ( lowercase ):
if len(lowercase ) == 0:
return []
lowerCAmelCase_ , lowerCAmelCase_: Union[str, Any] = min(lowercase ), max(lowercase )
lowerCAmelCase_: str = int(max_value - min_value ) + 1
lowerCAmelC... | 613 | import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vis... | 613 | 1 |
# 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 required by applicabl... | 710 | def snake_case (__lowercase , __lowercase ) -> int:
'''simple docstring'''
return int((input_a, input_a).count(1 ) != 0 )
def snake_case () -> None:
'''simple docstring'''
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
asser... | 580 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
_lowercase = logging.get_logger(__name_... | 157 |
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 ..pipeline_params import (
TEXT_G... | 157 | 1 |
"""simple docstring"""
import math
import os
import sys
def _snake_case ( lowercase__ ):
_lowerCamelCase : Optional[int] = ""
try:
with open(lowerCAmelCase_ , 'rb' ) as binary_file:
_lowerCamelCase : Any = ... | 707 |
"""simple docstring"""
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProce... | 492 | 0 |
'''simple docstring'''
from pathlib import Path
import cva
import numpy as np
from matplotlib import pyplot as plt
def _snake_case ( A_ : np.ndarray , A_ : np.ndarray , A_ : np.ndarray , A_ : int , A_ : int ):
"""simple docst... | 577 | """simple docstring"""
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
... | 516 | 0 |
'''simple docstring'''
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
_SCREAMING_SNAKE_CASE : Union[str, Any] ... | 716 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class __lowercase :
'''simple docstring'''
def __init__(self ,_lowerCamelCase ) -> None:
'''simple docstring'''
__lowerca... | 56 | 0 |
from __future__ import annotations
def _A ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
a__ : list[list[int]] =[]
create_all_state(1 , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , [] , SCREAMING_SNAKE... | 563 |
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( UpperCamelCase__):
_lowercase : Dict = (EulerDiscreteScheduler,)
... | 563 | 1 |
"""simple docstring"""
import sys
lowerCAmelCase_ = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
... | 710 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timestep... | 494 | 0 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class SCREAMING_SNAKE_CASE_ ( unittest.TestCase ):
"""simple docstring"""
def ... | 155 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase__ ( ):
_SCREAMING_SNAKE_CASE : dict[int, int] = {}
_SCREAMING_SNAKE_CASE : List[Any] = 2
while True:
_SCREAMING_SNAKE_CASE : List[Any] ... | 621 | 0 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
_lowerCAmelCase = ... | 711 |
from typing import List
from .keymap import KEYMAP, get_character
def _lowerCAmelCase ( _lowerCAmelCase ):
'''simple docstring'''
def decorator(_lowerCAmelCase ):
A_ : List[Any] = getattr(_lowerCAmelCase ,"""handle_key""" ,[] )
handle += [key]
setat... | 481 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : List[str] = 'encoder-decoder'
A_ : Dict =... | 106 |
__UpperCamelCase : Optional[int] = 'Input must be a string of 8 numbers plus letter'
__UpperCamelCase : Optional[Any] = 'TRWAGMYFPDXBNJZSQVHLCKE'
def _UpperCAmelCase ( UpperCAmelCase : str ):
"""simple docstring"""
if not isinstance(UpperCAm... | 519 | 0 |
"""simple docstring"""
import tensorflow as tf
from ...tf_utils import shape_list
class A_ ( tf.keras.layers.Layer ):
def __init__( self : int , __lowerCamelCase : Optional[Any] , __lowerCamelCase : Any ... | 468 |
"""simple docstring"""
def _lowerCAmelCase ( __lowerCamelCase:int ):
'''simple docstring'''
__magic_name__ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 468 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A = {
"configuration_ctrl": ["CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP", "CTRLConfig"],
"tokenization_ctrl": ["CTRLTokenizer"]... | 134 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import DDIMScheduler, KandinskyVaaPipeline, KandinskyVaaPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.utils import floats_tensor, load_numpy, slow, torch_device
from diff... | 320 | 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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logg... | 179 | '''simple docstring'''
from __future__ import annotations
import unittest
from transformers import LEDConfig, 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... | 179 | 1 |
"""simple docstring"""
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_lowerCAmelCase : List[Any] = "src/transformer... | 289 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import... | 430 | 0 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import data... | 464 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ : str = {
'configuration_llam... | 464 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_A = TypeVar("T")
class _lowerCAmelCase ( Generic[T] ):
def __init__( self , _UpperCamelCase ) -> Dict:
lowerCAmelCase_ = data
lowerC... | 290 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A = {"configuration_sew": ["SEW_PRETRAINED_CONFIG_ARCHIVE_MAP", "SEWConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 290 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...... | 704 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __UpperCAmelCase ( __UpperCamelCase ):
for param in module.parameters():
__lowercase : Tuple = False
def __UpperCAmelCase ( ... | 523 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.