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 |
|---|---|---|---|---|
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def _a ( __UpperCamelCase : Optional[int] ):
lowerCAm... | 233 |
def __lowerCamelCase ( __a :int , __a :int ) -> Optional[Any]:
"""simple docstring"""
if b == 0:
return 1
if (b % 2) == 0:
return actual_power(__a , int(b / 2 ) ) * actual_power(__a , int(b / 2 ) )
else:
... | 176 | 0 |
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class _lowe... | 715 |
import os
import time
import numpy as np
import onnxruntime as ort
a_ = "1"
a_ = "0"
a_ = "1"
a_ = ort.SessionOptions()
a_ = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print("Create inference session...")
a_ = ["TensorrtExecutionProvider", "CUDAExecutionProvider"... | 375 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCamelCase : int = {
'''configuration_data2vec_audio''': ['''DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Data2Vec... | 4 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Co... | 304 | 0 |
"""simple docstring"""
def A_ ( __UpperCamelCase : str ):
lowercase : Any = 0
for ch in input_str:
lowercase : str = ord(__UpperCamelCase )
lowercase : str = pow(2 , __UpperCamelCase )
# If we alrea... | 709 |
"""simple docstring"""
def A_ ( __UpperCamelCase : str , __UpperCamelCase : str ):
lowercase = len(__UpperCamelCase )
lowercase = []
for i in range(len(__UpperCamelCase ) - pat_len + 1 ):
lowercase = True
... | 396 | 0 |
'''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_available, ... | 614 | '''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoModelFo... | 614 | 1 |
"""simple docstring"""
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
lowerCAmelCase ... | 713 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
lowerCAmelCase : List[Any] = """\
@inproceedings{popovic-2015-chrf,
title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",
author = \"... | 533 | 0 |
def _snake_case ( ):
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
_lowerCAmelCase = generate_large_matrix()
_lowerCAmelCase = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -2, -3]],
[[3, 2], [1, 0]],
[[7, 7, 6]],
... | 10 | import math
from typing import Dict, Iterable, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAGENET_STANDAR... | 10 | 1 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
lowerCAmelCase__ = HfArgumentParser(InitializationArguments)
lowerCAmelCase__ = parser.parse_args()
# Load codepar... | 624 |
'''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _A ( A__ ):
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class lowercase_ (lowerCa... | 624 | 1 |
"""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 require_vision
f... | 650 |
"""simple docstring"""
from math import ceil, sqrt
def SCREAMING_SNAKE_CASE_ ( snake_case : int = 1_000_000 )-> int:
_lowerCamelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
_lowe... | 650 | 1 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenization_c... | 704 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : Any = logging.get_logger(__name__)
lowercase : Optional[int] = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformabl... | 392 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( __SCREAMING_SNAKE_CASE):
"""simple docstring"""
lowercase = ['image_processor', 'tokenizer']
lo... | 275 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ : Any = {'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}
try:
if not is_torch... | 572 | 0 |
'''simple docstring'''
# 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/LICE... | 702 |
from collections.abc import Callable
import numpy as np
def A ( lowercase__ : Callable , lowercase__ : float , lowercase__ : float , lowercase__ : float , lowercase__ : float ) -> np.ndarray:
UpperCamelCase__ :List[str] = int... | 383 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.model... | 9 |
"""simple docstring"""
from manim import *
class lowercase_ ( __lowerCAmelCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Union[str, Any] ):
_A = Rectangle(height=0.5 , width=0.5 )
_A = Rectangle(height=0.46 , w... | 7 | 0 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( snake_case__ : list[int] ):
if len(snake_case__ ) == 0:
return array
A , A = min(snake_case__ ), max(snake_case__ )
# Compute the variables
A = _max - _min + 1
A , ... | 719 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _snake_case ( snake_case__ : Optional[int] ):
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class lowerCAmelCa... | 22 | 0 |
from copy import deepcopy
import torch
import torch.nn.functional as F
from torch.optim import AdamW
from torch.optim.lr_scheduler import LambdaLR
from torch.utils.data import DataLoader
from accelerate.accelerator import Accelerator
from accelerate.state import GradientState
from accelerate.test_utils ... | 693 |
from functools import lru_cache
def _A ( __snake_case :int ) -> set:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 2
__SCREAMING_SNAKE_CASE = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
... | 693 | 1 |
'''simple docstring'''
from math import ceil, sqrt
def _SCREAMING_SNAKE_CASE ( __snake_case = 1_0_0_0_0_0_0 ) -> int:
_UpperCAmelCase = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
_Uppe... | 719 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Confi... | 402 | 0 |
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,
StableDiffusionXLImgaImgPipeline,
... | 256 |
def _UpperCamelCase ( lowercase__ , lowercase__ ):
__SCREAMING_SNAKE_CASE : str = len(lowercase__ )
__SCREAMING_SNAKE_CASE : Optional[int] = len(lowercase__ )
__SCREAMING_SNAKE_CASE : List[str] = [[False for _ in range(m + 1 )] for _ in ... | 696 | 0 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class UpperCamelCase_ ( A ):
'''simple docstring'''... | 413 |
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
from transform... | 413 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NA... | 52 |
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 OptionalDepend... | 311 | 0 |
"""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 require_vision... | 498 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}
class __S... | 498 | 1 |
'''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 AutoTokenizer
from transformers.model... | 107 |
"""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... | 695 | 0 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class __SCREAMING_SNAKE_CASE :
SCREAMING_SNAKE_CASE__ =field(
default="""codeparrot/codeparrot""" , metadata={"""help""": """Model name or path of model to be trained."""} )
SCREAMING_SNAKE_CASE... | 214 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case : Any = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
SCREAMING_SNAKE_CASE__ ="""encoder-decoder"""
SCREAMING... | 214 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if i... | 426 |
"""simple docstring"""
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSche... | 426 | 1 |
def lowerCAmelCase__ ( UpperCamelCase_ : int )-> bool:
if num < 0:
return False
A__ = num
A__ = 0
while num > 0:
A__ = rev_num * 1_0 + (num % 1_0)
num //= 1_0
return num_copy == rev_num
if __name__ == "__main__":
import doctest
... | 526 |
def lowerCAmelCase__ ( UpperCamelCase_ : str , UpperCamelCase_ : str )-> float:
def get_matched_characters(UpperCamelCase_ : str , UpperCamelCase_ : str ) -> str:
A__ = []
A__ = min(len(_stra ) , len(_stra ) ) // 2
... | 526 | 1 |
'''simple docstring'''
def _UpperCamelCase ( __UpperCamelCase ) -> List[str]:
if length <= 0 or not isinstance(lowercase_ ,lowercase_ ):
raise ValueError('Length must be a positive integer.' )
return [n * (2 * n - 1) for n in range(lowercase_ )]
if __name__ == "__main__":
... | 42 |
'''simple docstring'''
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from tensorflow.python.eager import context
from tensorflow.python.framework import ops
from transformers impo... | 588 | 0 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .... | 398 |
'''simple docstring'''
# 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/... | 398 | 1 |
'''simple docstring'''
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase : Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( snake_case_ ):
UpperCA... | 310 |
'''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_check... | 330 | 0 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
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... | 182 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case : Optional[int] = logging.get_logger(__name__)
snake_case : Union[str, Any] = {
'facebook/data... | 182 | 1 |
"""simple docstring"""
import operator
def lowercase_ ( __UpperCAmelCase , __UpperCAmelCase = False , __UpperCAmelCase = None ) -> list:
lowerCAmelCase__ : int = operator.lt if reverse else operator.gt
lowerCAmelCase__ : int = sol... | 299 |
'''simple docstring'''
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTra... | 421 | 0 |
"""simple docstring"""
def a__ ( lowerCAmelCase__ = 1000 ):
UpperCAmelCase_ = 2**power
UpperCAmelCase_ = str(_UpperCamelCase )
UpperCAmelCase_ = list(_UpperCamelCase )
UpperCAmelCase_ = 0
for i in list_n... | 720 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase = {
"""configuration_swinv2""": ["""SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Swinv2Config"""],
}
try:
if not is_to... | 14 | 0 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedKVPro... | 285 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase ( SCREAMING_SNAKE_CASE ):
__UpperCamelCase =["image_processor", "tokenizer"]
__UpperCamelCase ="CLIPImageProcessor"
__UpperCamelCase =("CLIPTokenizer"... | 439 | 0 |
'''simple docstring'''
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
... | 700 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_SCREAMING_SNAKE_CASE = {
'configuration_jukebox': [
'JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP',
'JukeboxConfig',
'JukeboxPriorConfig',
'JukeboxV... | 83 | 0 |
from collections.abc import Callable
def __a ( A__ : Callable[[float], float] , A__ : float , A__ : float ):
SCREAMING_SNAKE_CASE = a
SCREAMING_SNAKE_CASE = b
if function(A__ ) == 0: # one of the a or b is a root for the function
... | 16 |
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 import BertTokenizer
__A : str = logging.get_logger(__name__)
_... | 16 | 1 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEnco... | 720 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase : Any = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
... | 514 | 0 |
from typing import Any
class lowerCamelCase__ :
def __init__( self : List[Any] , lowercase__ : Any ):
_lowerCAmelCase = data
_lowerCAmelCase = None
def __repr__( self : List[str] ):
return f'Node({self.data})'
... | 192 | import argparse
from collections import defaultdict
import yaml
_lowercase: List[Any] = '''docs/source/en/_toctree.yml'''
def _lowerCamelCase ( snake_case ):
_lowerCAmelCase = defaultdict(snake_case )
_lowerCAmelCase = []
_lowerCAmelCase = ... | 192 | 1 |
import copy
import re
class UpperCamelCase:
snake_case_ : Tuple = """hp"""
snake_case_ : List[Any] = {}
snake_case_ : Any = None
@classmethod
def SCREAMING_SNAKE_CASE_ ( cls : Optional[int] , SCREAMING_... | 701 |
import os
from datetime import datetime as dt
from github import Github
A : Union[str, Any] = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def _lowe... | 473 | 0 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
__A : int = logging.getLogger(__name__)
if __name__ =... | 394 |
'''simple docstring'''
import numpy
class _UpperCamelCase :
'''simple docstring'''
def __init__( self , _a , _a ):
"""simple docstring"""
a__ = input_array
# Random initial weights are assigned where ... | 394 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
lowerCAmelCase : int =logging.get_logger(__name__)
lowerCAmelCase : Any ={
'Intel/dpt-large': 'https://huggingface.co/Intel/dpt-large/resolve... | 693 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ,SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def _UpperCAmelCase ( ):
'''simple docstring'''
print("""Truth Table of NOR Gat... | 693 | 1 |
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 ... impor... | 105 |
# 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... | 318 | 0 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
# TODO Update this
UpperCamelCase = {
'facebook/esm-1b': 'https://huggingface.co/facebook/esm-1b/resolve... | 704 |
def _A ( lowerCAmelCase_ : int = 100_0000 ):
"""simple docstring"""
lowerCAmelCase__ = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1... | 125 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.activations import gelu_new, gelu_python, get_activation
@require_torch
class SCREAMING_SNA... | 685 |
'''simple docstring'''
import math
def __UpperCAmelCase (lowercase__ ) -> list:
'''simple docstring'''
a_ = [True] * n
a_ = False
a_ = False
a_ = True
for i in range(3 ,int(n**0.5 + 1 ) ,2 ):
... | 685 | 1 |
'''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_mod... | 506 |
'''simple docstring'''
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
A__: Dict = 5_0000
A__: Optional[int] = 5000
A__ , A__: Optional[int] = os.path.split(__file__)
A__: ... | 506 | 1 |
"""simple docstring"""
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTok... | 636 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
A : Optional[Any] = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 636 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : Tuple = logging.get_logger(__name__)
_UpperCAmelCase : Any = {
"""microsoft/unispeech-large-1500h-cv""": (... | 474 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_UpperCAmelCase : str = {
"""configuration_gpt_neox_japanese""": ["""GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MA... | 474 | 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 ):
'''simple docstring'''
SCREAM... | 293 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torch
class ... | 108 | 0 |
'''simple docstring'''
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __snake_cas... | 718 |
'''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_mobilebert import MobileBertTokenizer
A_ : Any = logging.get_logger(__nam... | 419 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def a__ (__lowercase :int ) -> str:
_A : Any = int(number**0.5 )
return number == sq * sq
def a__ (__lowercase :int , __lowercase :int , __l... | 206 |
a_ = {
0: """0""",
1: """1""",
2: """2""",
3: """3""",
4: """4""",
5: """5""",
6: """6""",
7: """7""",
8: """8""",
9: """9""",
10: """a""",
11: """b""",
12: """c""",
13: """d""",
14: """e""",
15: """f""",
}
def a__ ( _UpperCam... | 175 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.util... | 702 |
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__( self , UpperCAmelCase ) ... | 601 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class lowercase_ ( unittest.TestCas... | 7 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
lowercase : List[str] = logging.get_logger(__name__)
def snake_case__ ( lowerCamelCase_=None , lowe... | 542 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
UpperCamelCase__ = '''\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted a... | 705 |
import qiskit
def UpperCAmelCase__ ( _A , _A ):
"""simple docstring"""
a_ = qiskit.Aer.get_backend('''aer_simulator''' )
a_ = qiskit.QuantumCircuit(4 , 2 )
# encode inputs in qubits 0 and 1
if bita == 1:
qc_ha.x(... | 143 | 0 |
'''simple docstring'''
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_... | 577 |
'''simple docstring'''
__snake_case: Tuple = "Tobias Carryer"
from time import time
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_=int(time() ) ): # noqa: B00... | 577 | 1 |
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
... | 387 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
UpperCamelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at https://h... | 387 | 1 |
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowercase_ = logging.get_logger(__name__)
class _UpperCamelCase ( a__ ... | 562 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines... | 90 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __magic_name__ :
'''simple docstring'''
__UpperCamelCase = 42
__UpperCamelCase =... | 533 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowerCAmelCase : List[Any] = {"""UserAgent""": UserAgent().random}
def a__ ( snake_case__ ) -> dict:
... | 533 | 1 |
'''simple docstring'''
import os
from math import logaa
def _A ( A__ = "base_exp.txt" ):
"""simple docstring"""
__lowercase = 0
__lowercase = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(A__ ) , A__ ) ) ):
__lowercase , __lowercase... | 41 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowercase : Optional[Any] = """http://www.mocksite.com/... | 336 | 0 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interl... | 704 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
__magic_name__ = argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', default=None, type=str, required=True, help=''... | 530 | 0 |
'''simple docstring'''
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets impo... | 531 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoin... | 531 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
lowercase__ = list[tuple[int, int]]
lowercase__ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
... | 695 |
'''simple docstring'''
# 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-... | 695 | 1 |
'''simple docstring'''
class SCREAMING_SNAKE_CASE__ :
def __init__( self ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[Any] = {}
def __lowerCamelCase ( self ):
"""... | 421 |
'''simple docstring'''
class lowerCamelCase_ :
def __init__( self : str , _A : Union[str, Any] , _A : Optional[int] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = name
... | 75 | 0 |
from __future__ import annotations
def _a ( __SCREAMING_SNAKE_CASE : list[list[int]] ):
"""simple docstring"""
_lowerCAmelCase = len(_lowerCamelCase )
# We need to create solution object to save path.
_lowerCAmelCase = [[0 for _ in range(_lowerCamelCase )... | 704 |
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def _a ( __SCREAMING_SNAKE_CASE : Dict[str, torch.Tensor] ):
"""simple docstring"""
_lowerCAmelCase = []
_lowerCAmelCase ... | 585 | 0 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.test... | 611 |
class a :
def __init__( self : Union[str, Any] , snake_case__ : str ):
"""simple docstring"""
__lowerCAmelCase = arr.split("," )
def UpperCAmelCase__ ( self : str ):
"""simple docstring"""
__lowerCAmelCase ... | 611 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCAmelCase : Union[str, Any] = {
"configuration_chinese_clip": [
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"ChineseCLIPConfig... | 155 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 155 | 1 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class lowerCam... | 390 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
a__ = """\
"""
a__ = """
Perplexity (PPL) is one of the most common metrics for evaluating language mo... | 477 | 0 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
fr... | 636 | import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNetYaagf, RegNetYaagf, RegNetYaaagf
... | 636 | 1 |
import qiskit
def lowerCamelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : int ) -> qiskit.result.counts.Counts:
"""simple docstring"""
__lowerCamelCase = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum ... | 469 |
def lowerCamelCase_ ( UpperCamelCase__ : str , UpperCamelCase__ : int ) -> list:
"""simple docstring"""
__lowerCamelCase = word.split()
def justify(UpperCamelCase__ : list , UpperCamelCase__ : int , UpperCamelCase__... | 469 | 1 |
'''simple docstring'''
import argparse
import os
import re
lowercase : str = "src/diffusers"
# Pattern that looks at the indentation in a line.
lowercase : str = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase : str = ... | 542 |
'''simple docstring'''
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,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler... | 542 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transf... | 65 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__snake_case : List[Any] = logging.get_logger(__name__)
class UpperCamelCase ( a ):
"""simple docstring... | 571 | 0 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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 requi... | 716 |
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig,
C... | 198 | 0 |
'''simple docstring'''
import argparse
import json
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
... | 42 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ , lowerCamelCase_ ) -> Optional[int]:
# Initialise ... | 89 | 0 |
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
__snake_case : List[Any] = [1]
for i in range(2 , SCREAMING_SNAKE_CASE_ ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1] * n, "k out of bounds"
... | 702 |
def lowerCAmelCase_ ( __lowerCamelCase , __lowerCamelCase ):
return int((input_a, input_a).count(0 ) == 0 )
def lowerCAmelCase_ ( ):
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_gate(1 , 0 ... | 203 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : str = {
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ct... | 50 |
'''simple docstring'''
def A__ ( ):
return [list(range(1000 - i , -1000 - i , -1 ) ) for i in range(1000 )]
UpperCamelCase : Dict = generate_large_matrix()
UpperCamelCase : Any = (
[[4, 3, 2, -1], [3, 2, 1, -1], [1, 1, -1, -2], [-1, -1, -... | 50 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_a : Optional[int] = list[list[float | int]]
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Matrix ,_lowerCamelCase : Matrix ) -> Matrix:
_lowerCAmelCase : int = len(_lowerCam... | 711 | """simple docstring"""
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Union[str, Any] ,_lowerCamelCase : Tuple ) -> Dict:
_lowerCAmelCase : List[str] = int(_lowerCamelCase )
assert noofclusters < len(... | 663 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase )-> float:
__UpperCAmelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
def _lowerCAmelCase ( ... | 126 |
'''simple docstring'''
from pathlib import Path
import fire
from tqdm import tqdm
def _lowerCAmelCase ( _lowerCAmelCase="ro" , _lowerCAmelCase="en" , _lowerCAmelCase="wmt16" , _lowerCAmelCase=None )-> None:
try:
import datasets
except (ModuleNotFoundError, Imp... | 126 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__SCREAMING_SNAKE_CASE :Union[str, Any] = logging.get_logger(__name__)
class A_ ( lowerCAmelCase_ ):
def __init__( self : in... | 119 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
__SCREAMING_SNAKE_CASE :int = True
except (ImportError, ModuleNotFoundError):
__SCREAMING_SNAKE_CASE :Optional[int] = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.d... | 119 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_to... | 34 | '''simple docstring'''
def __lowerCAmelCase ( a_ = 1 , a_ = 1000 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE : Tuple = 1
SCREAMING_SNAKE_CASE : Optional[int] = 0
for div... | 251 | 0 |
'''simple docstring'''
from __future__ import annotations
def _lowercase ( lowerCamelCase__ : float, lowerCamelCase__ : float, lowerCamelCase__ : float, ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more or less than 2 val... | 691 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case : int = {
"configuration_bloom": ["BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP", "BloomConfig", "BloomOnnxConfig"],... | 691 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 216 | import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging
log... | 216 | 1 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_UpperCAmelCase : Optional[int] = datasets.logging.get_logger(__name__)
_UpperCAmelCase : List[Any] =... | 721 |
'''simple docstring'''
from __future__ import annotations
_UpperCAmelCase : str = 10
def UpperCamelCase ( lowercase_ : list[int] ) -> list[int]:
'''simple docstring'''
lowercase =1
lowercase =max(lowercase_ )
while placement <= max_digit:
# declare... | 145 | 0 |
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
__magic_name__ = logging.getLogger(__name__)
if is_torch_tpu_available(check_device=False):
... | 276 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
Auto... | 276 | 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 import ... | 366 | """simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_ava... | 366 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 183 |
def a ( lowerCamelCase_ , lowerCamelCase_ ):
'''simple docstring'''
lowercase__ = len(lowerCamelCase_ )
lowercase__ = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0) can be formed by not... | 183 | 1 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class __A (snake_case__):
'''simple docstring'''
pass
class __A :
'''simple docstring'''
def __init__( self : str , UpperCAmelCase_ : A... | 2 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class __A :
'''simple docstring'''
def __init__( self : List[Any] , UpperCAmelCase_ : list[str] ) ->List[Any]:
"""simple docstring"""
... | 2 | 1 |
"""simple docstring"""
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
_UpperCamelCase = {
'fa... | 179 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, 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,
... | 179 | 1 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
A... | 702 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class a_ ( _snake_case ):
UpperCamelCase__ : str =""
UpperCamelCase__ : str =(
None # protocol pas... | 561 | 0 |
import math
import sys
def lowerCAmelCase__(__snake_case ) -> str:
'''simple docstring'''
lowerCamelCase__ = ''''''
try:
with open(__snake_case ,'''rb''' ) as binary_file:
lowerCamelCase__ = binary_file.read()
for dat in data:
lower... | 481 |
_a = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
_a ... | 481 | 1 |
import argparse
from collections import OrderedDict
from pathlib import Path
import torch
from transformers import (
VisualBertConfig,
VisualBertForMultipleChoice,
VisualBertForPreTraining,
VisualBertForQuestionAnswering,
VisualBertForVisualReasoning,
)
from transformers.utils import logging
... | 702 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class _A( snake_case__ ):
"""simple docstring"""
def __init__( self , *_A , **_A ):
... | 77 | 0 |
'''simple docstring'''
from typing import List
import numpy as np
def __snake_case ( lowercase : Any ):
snake_case_ = {key: len(__UpperCamelCase ) for key, value in gen_kwargs.items() if isinstance(__UpperCamelCase , __UpperCamelCase )}
if len(set(lists_lengths.values(... | 508 |
"""simple docstring"""
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 import BertTokenizer
a_ = lo... | 76 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
SCREAMING_SNAKE_CASE = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot ap... | 186 |
import os
from collections.abc import Iterator
def _lowerCamelCase ( __A : str = "." ) -> Iterator[str]:
for dir_path, dir_names, filenames in os.walk(__A ):
_UpperCAmelCase : List[Any] = [d for d in dir_names if d != '''scripts''' and d[0] not ... | 186 | 1 |
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def a_ ( _A ) -> Optional[Any]:
"""simpl... | 328 |
# 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
#
# U... | 328 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE = {
'configuration_upernet': ['UperNetConfig'],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDepend... | 153 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
class lowerCAmelCase_ ( __A ):
'''simple docstring'''
def __init__( self , *__UpperCAmelCase , **_... | 153 | 1 |
"""simple docstring"""
class lowercase__ : # Public class to implement a graph
def __init__( self , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE) -> None:
_lowerCamelCase : str = row
_lowerCamelCase : Dict = col
... | 88 |
"""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_avai... | 34 | 0 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('.')
def _a ( _SCREAMING_SNAKE_CASE ) -> Any:
snake_case_ = test_file.split(... | 707 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_visio... | 2 | 0 |
def UpperCAmelCase_ ( UpperCAmelCase__ = 4_0_0_0_0_0_0 ):
lowercase_ = [0, 1]
lowercase_ = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
lowercase_ = 0
for j in range(l... | 412 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggin... | 412 | 1 |
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE_:str = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:int = {
"""vocab_file""": """vocab.json""",
"""tokenizer_config_... | 520 |
from __future__ import annotations
def __UpperCamelCase ( _lowerCAmelCase , _lowerCAmelCase = None , _lowerCAmelCase = None , _lowerCAmelCase = False , ) -> tuple[int, float, str]:
"""simple docstring"""
A : str = cipher_alphabet or [chr(_lowerCAmelCase ) fo... | 520 | 1 |
'''simple docstring'''
print((lambda quine: quine % quine)("print((lambda quine: quine %% quine)(%r))"))
| 316 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase : Dict ={"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
t... | 316 | 1 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase=None , **__lowerCamelCase ):
__a = [x.strip() for x in open(__lowerCamelCase ).readlines()]
_... | 705 | import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import AutoImageProcess... | 246 | 0 |
lowerCamelCase_ = tuple[float, float, float]
lowerCamelCase_ = tuple[float, float, float]
def lowerCamelCase ( a_ , a_ ) -> Union[str, Any]:
lowerCAmelCase_ = end_pointa[0] - end_pointa[0]
lowerCAmelCase_ = end_pointa[1] - end_pointa[1]
... | 318 |
"""simple docstring"""
import math
import flax.linen as nn
import jax.numpy as jnp
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase = 1 , __UpperCamelCase = 1 , __UpperCamelCase = 1.0e4 , __UpperCamelCase = False , __UpperCame... | 76 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils impor... | 612 |
"""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_mo... | 612 | 1 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
snake_case = HfArgumentParser(InitializationArguments)
snake_case = parser.parse_args()
# Load codeparrot tokenizer ... | 67 |
"""simple docstring"""
def lowercase__ ( snake_case_ :dict ):
__UpperCAmelCase = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
__UpperCAmelCase = set()
return any(
node not in visited and depth_first_search(snake_cas... | 49 | 0 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
UpperCamelCase : Optional[int] = logging.get_logger(__name__)
def SCREAMING_SNAKE_CASE__ ( snake... | 716 | '''simple docstring'''
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
... | 610 | 0 |
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