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 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class A :
def __init__( self : str , __magic_name__ : Any ):
"""simple docstring"""
lowerCAmelCase__ = data
lowerCAmelCase... | 48 |
from collections.abc import Sequence
def SCREAMING_SNAKE_CASE_ ( UpperCAmelCase_ : Sequence[int] | None = None ) -> int:
if nums is None or not nums:
raise ValueError('''Input sequence should not be empty''' )
SCREAMING_SNAKE_CASE_ : Tuple =nums[... | 443 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
... | 79 |
'''simple docstring'''
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default... | 79 | 1 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
)
... | 6 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcesso... | 571 | 0 |
from __future__ import annotations
def _UpperCAmelCase ( _SCREAMING_SNAKE_CASE : list[int] , _SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if len(_SCREAMING_SNAKE_CASE ) == 0:
return False
SCREAMING_SNAKE_CASE_ = len(_SCREAMING_SNAK... | 620 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
UpperCamelCase__ : Tuple = {
"configuration_trocr": ["TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP", "TrOCRConfig"],
... | 620 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_... | 103 |
"""simple docstring"""
from copy import deepcopy
class UpperCAmelCase :
def __init__( self : Optional[Any] , __lowerCamelCase : list[int] | None = None , __lowerCamelCase : int | None = None ):
"""simple docstring"""
... | 103 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin... | 119 |
'''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 A_ ( unittes... | 119 | 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 req... | 392 |
import tensorflow as tf
from ...tf_utils import shape_list
class snake_case ( tf.keras.layers.Layer ):
'''simple docstring'''
def __init__( self : List[Any] , lowerCamelCase_ : Optional[Any] , lowerCamelCase_ : Union[st... | 392 | 1 |
"""simple docstring"""
def _UpperCamelCase ( _A ) -> int:
"""simple docstring"""
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_UpperCAmelCase = 1
_UpperCAmelCase = 1
while repunit:
_UpperCAmelCase = (1_0 * repunit + 1) % ... | 715 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting import TensorForma... | 19 | 0 |
import math
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Tuple = []
lowerCamelCase : Dict = 2
lowerCamelCase : List[str] = int(math.sqrt(_a ) ) # Size of every segment
... | 340 |
"""simple docstring"""
from __future__ import annotations
def _A ( _a : list[float] , _a : list[float] ):
"""simple docstring"""
A = sorted(numsa + numsa )
A , A = divmod(len(_a ) , 2 )
if mod == 1:
... | 617 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase__ =logging.get_logger(__name__)
lowerCAmelCas... | 690 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torc... | 690 | 1 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 133 |
'''simple docstring'''
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,
)
fr... | 133 | 1 |
import os
def A ( a_ = "matrix.txt" ) -> int:
with open(os.path.join(os.path.dirname(a_ ) ,a_ ) ) as in_file:
__UpperCamelCase : str =in_file.read()
__UpperCamelCase : List[Any] =[[int(a_ ) for cell in row.split(',' ... | 709 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=a )
class __A ( a ):
"""simple docstring"""
UpperCam... | 154 | 0 |
'''simple docstring'''
def UpperCAmelCase__( _SCREAMING_SNAKE_CASE : int,_SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def UpperCAmelCase__( ):
"""simple docstring"""
assert or_gate(0,0 ) == 0
... | 186 |
'''simple docstring'''
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def UpperCAmelCase__( _SCREAMING_SNAKE_CASE : str = "" ):
"""simple docstring"""
__A= url or 'https://www.imdb.com/chart/top/?ref_=nv_mv_250'
__A= BeautifulS... | 186 | 1 |
'''simple docstring'''
def __lowerCamelCase ( __snake_case : int | float | str ) -> tuple[int, int]:
"""simple docstring"""
try:
A__ : Union[str, Any] =float(__snake_case )
except ValueError:
raise ValueError("""Please enter a valid number""" )
... | 714 |
'''simple docstring'''
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 impo... | 687 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a_ : List[Any] = {
"configuration_wav2vec2": ["WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP", "Wav2Vec2Config"],
"fe... | 439 |
def a (lowerCAmelCase__ = 1_000_000 ):
__a = 1
__a = 1
__a = {1: 1}
for inputa in range(2 , lowerCAmelCase__ ):
__a = 0
__a = inputa
while True:
if number in counters:
counter += counters[number]
break... | 99 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils import TO... | 129 |
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
__lowerCAmelCase = 5_0_0_0_0_0
__lowerCAmelCase , __lowerCAmelCase = os.path.split(__file__)
__lowerCAmelCase = os.path.join(RESU... | 129 | 1 |
import unittest
from dataclasses import dataclass
import pytest
from accelerate.commands.config.config_args import SageMakerConfig
from accelerate.utils import ComputeEnvironment
from accelerate.utils.launch import _convert_nargs_to_dict
@dataclass
class __a( _a ):
"""simple docstring"""
... | 30 |
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 = logging.get_logger(__name__)
__a ... | 30 | 1 |
'''simple docstring'''
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import trans... | 710 |
'''simple docstring'''
# Copyright 2021 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/LICEN... | 220 | 0 |
class snake_case_ :
def __init__( self :Any ,__snake_case :Dict ) -> Tuple:
a__ = val
a__ = None
a__ = None
def lowerCamelCase__( self :List[str] ,__snake_case :Dict ) -> Optional[int]:
if self.val:
... | 335 | import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a__ ( A__ ):
A = ['image_processor', 'tokenizer']
A = 'ViTImageProcessor'
A = ('CLIPTokenizer', 'CLIPTokenizerFast')
def __ini... | 216 | 0 |
"""simple docstring"""
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available... | 348 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
_lowerCAmelCase = 'examples/'
_lowerCAmelCase = {
'examples': (re.compile(r'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(r'^__versio... | 348 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTes... | 90 | import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
A = {
'gwf-440k': {
'url... | 544 | 0 |
"""simple docstring"""
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as j... | 361 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_dif... | 361 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( _A ):
'''simple docstring'''
a__ = """ClapFeatureExtractor"""
a__ = ("""RobertaTokenizer""", """RobertaTokenizerFast""... | 529 |
import argparse
import collections
import os
import re
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_table.py
__lowerCAmelCase : Dict = 'src/transformer... | 529 | 1 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_to... | 703 | """simple docstring"""
import re
def SCREAMING_SNAKE_CASE ( snake_case):
__snake_case = re.compile(R'''^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$''')
if match := re.search(snake_case, snake_case):
return match.string == phone
return False
if __name... | 93 | 0 |
'''simple docstring'''
def lowercase__ ( ) -> List[str]:
"""simple docstring"""
for n in range(1 , 1000000 ):
yield n * (n + 1) // 2
def lowercase__ ( __lowercase : Any ) -> Union[str, Any]:
"""simple docstring"""
_... | 399 |
'''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_availa... | 399 | 1 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_... | 443 |
UpperCAmelCase_ : Optional[int] = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
UpperCA... | 443 | 1 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def _UpperCAmelCase ... | 540 |
from __future__ import annotations
def _UpperCAmelCase ( a__):
'''simple docstring'''
if len(a__) == 0:
return []
a_ , a_ : List[Any] = min(a__), max(a__)
a_ : Tuple = int(max_value - min_value) + 1
a_ : list[list] = ... | 540 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'''abeja/gpt-neox-japanese-2.7b''': '''https://huggingface.co/abeja/gpt-neox-japanese-2.7b/r... | 399 |
'''simple docstring'''
def __lowerCAmelCase ( snake_case__ ):
if not grid or not grid[0]:
raise TypeError("The grid does not contain the appropriate information" )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
... | 399 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a__ : List[str] = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
... | 601 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTeste... | 601 | 1 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_ca... | 702 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
class snake_case_( a__ ):
pass
class snake_case_:
def __init__( self : Any , UpperCamelCase_ : Any ):
lowerCAmelCase : Any = data
lowerCAmelCa... | 637 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase_ = {'''configuration_vit''': ['''VIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTCo... | 60 | import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import AutoConfi... | 524 | 0 |
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
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_ut... | 586 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_ver... | 586 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_s... | 46 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
_A = ... | 182 | 0 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> list[int]:
__lowerCAmelCase : List[str] = int(__snake_case )
# Initialize Result
__lowerCAmelCase : List[Any] = []
# Traverse through all denomination
for... | 703 |
"""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,
AutoMod... | 615 | 0 |
"""simple docstring"""
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
... | 103 |
"""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 logg... | 103 | 1 |
'''simple docstring'''
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def A ( A_ : str , A_ : complex , A_ : str = "x" , A_ : float = 10**-10 , A_ : int = 1 , ):
... | 555 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
imp... | 555 | 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 ...test_co... | 74 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import numpy as np
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
import transformers
from transfor... | 74 | 1 |
def snake_case_ (__A : Tuple = 1_0 ) -> int:
if not isinstance(__A , __A ) or n < 0:
raise ValueError("""Invalid input""" )
__lowerCAmelCase : List[Any] = 1_0**n
__lowerCAmelCase : Optional[Any] = 2_8_4_3_3 * (pow(2 ... | 709 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"""caidas/swin2sr-classicalsr-x2-64""": (
"""https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json""... | 218 | 0 |
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
UpperCamelCase__ = logging.getLogger(__name__)
U... | 619 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {
"configuration_roberta_prelayernorm": [
"ROBERTA_PRELAYERNORM_... | 532 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_uti... | 705 |
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
lowercase = logging.get_logger(__name__)
lowercase ... | 103 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
a_ = 637_8137.0
a_ = 635_6752.31_4245
a_ = 637_8137
def lowerCamelCase__ ( _a , _a , _a , _a):
SCREAMING_SNAKE_CASE : List[str] = (AXIS_A - AXIS_B) / AXIS_A
SCREAMING_SNAKE_CASE : ... | 25 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import ... | 688 | 0 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
__A = importlib.util.find_spec('''s3fs''') is not None
if _has_safs:
from .safilesystem impor... | 366 | """simple docstring"""
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _snake_case :
snake_case__ = None
snake_case__ = False
snake_case__ = False
snake_case__ = False
snake_c... | 366 | 1 |
def _lowercase( __a : int ):
a__ =len(__a )
a__ =sum(__a )
a__ =[[False for x in range(s + 1 )] for y in range(n + 1 )]
for i in range(1 , n + 1 ):
a__ =True
for i in range(1 , s + 1 ):
... | 20 |
'''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... | 275 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
lowercase_ : Any = 0
lowercase_ : List[Any] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's ... | 707 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
lowercase_ : Union[str, Any] = '''src/transformers'''
# Matches is_xxx_available()
lowercase_ : str = re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import... | 295 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
a : List[str] = logging.get_logger(__name__)
class a ( _lowerCamelCase ):
def __init__( self : int , *lowercase_ : str... | 640 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attentio... | 640 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransformerConfig',
'T... | 701 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppToken... | 613 | 0 |
"""simple docstring"""
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_u... | 29 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, s... | 529 | 0 |
from __future__ import annotations
def __magic_name__ ( __a : int ):
'''simple docstring'''
UpperCamelCase__ = [True] * limit
UpperCamelCase__ = False
UpperCamelCase__ = False
UpperCamelCase__ = True
for i in range(3 , int(limit**0.5 ... | 705 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
lowerCamelCase_ = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32accea... | 86 | 0 |
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_com... | 105 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase_ ( A__ : list , A__ : int , A__ : int , A__ : int ):
'''simple docstring'''
lowerCAmelCase_ : int = []
lowerCAmelCase_, ... | 275 | 0 |
from math import asin, atan, cos, radians, sin, sqrt, tan
__A : Union[str, Any] = 6_37_81_37.0
__A : Tuple = 6_35_67_52.31_42_45
__A : Union[str, Any] = 6_378_137
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> ... | 334 |
def UpperCAmelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> bool:
'''simple docstring'''
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(UpperCamelCase__ ) )
def UpperCAmelCase ... | 334 | 1 |
'''simple docstring'''
class _lowerCamelCase :
'''simple docstring'''
def __init__( self , __lowercase ):
"""simple docstring"""
__A : Optional[int] = arr.split(',' )
def snake_case__ ( self ):
"""simple docstring"""
__A : List[str] = ... | 365 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenizatio... | 365 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
__UpperCAmelCase :Optional[int] = logging.get_logger(__name__) # pylint: disable=invalid-name
class a ... | 718 |
'''simple docstring'''
from scipy.stats import pearsonr
import datasets
__UpperCAmelCase :Tuple = "\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation ... | 266 | 0 |
"""simple docstring"""
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _UpperCame... | 391 | """simple docstring"""
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__A : Optional[int] = l... | 656 | 0 |
from __future__ import annotations
from statistics import mean
def UpperCAmelCase__ ( _A , _A , _A ):
"""simple docstring"""
a_ = [0] * no_of_processes
a_ = [0] * no_of_processes
# Initialize remaining_time to waiting... | 143 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
... | 143 | 1 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
_SCREAMING_SNAKE_CASE : List[Any] = """ClapFeatureExtractor"""
_SCR... | 427 | '''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def UpperCamelCase_ ( snake_case_ : str , snake_case_ : List[str]=10_00 ) -> Dict:
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means... | 427 | 1 |
from __future__ import annotations
from typing import Any
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self : Optional[int] , UpperCamelCase__ : int = 6 ) -> None:
"""simple docstring"""
__magi... | 715 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class UpperCAmelCase_ :
'''simple docstring'''
a__ = None
def _lowercase ( self : Optional[int] ) -> str:
... | 76 | 0 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.s... | 397 |
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 397 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
snake_case_ : Tuple = logging.get_logger(__name__)
snake_case_ : Opt... | 253 |
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeniz... | 253 | 1 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
... | 99 |
import math
def a (lowerCAmelCase__ ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes number are in... | 99 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int ):
'''simple docstring'''
if length <= 0 or not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for... | 43 | '''simple docstring'''
import comet # From: unbabel-comet
import torch
import datasets
lowercase__ : str = datasets.logging.get_logger(__name__)
lowercase__ : Dict = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and ... | 43 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCamelCase : Union[str, Any] = logging.get_logger(__name__)
_low... | 663 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
de... | 647 | 0 |
'''simple docstring'''
_A : Tuple ="0.18.2"
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_... | 712 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A : Dict ={
'''configuration_git''': ['''GIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GitConfig''', '''GitVisionConfig'''],
... | 631 | 0 |
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers.utils.testing_utils import en... | 669 |
import math
from datetime import datetime, timedelta
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
__lowerCamelCase : Tuple = year % 19
__lowerCamelCase : int = year % 4
__lowerCamelCase : Any = year % 7
__lowerCamelCase : Dict = math.fl... | 669 | 1 |
'''simple docstring'''
def snake_case_ ( __snake_case : int = 1 , __snake_case : int = 1000) -> int:
lowerCAmelCase_ = 1
lowerCAmelCase_ = 0
for divide_by_number in range(__snake_case , digit + 1):
lowerCAmelCase_ = []
lowerCAmelCase_... | 606 | '''simple docstring'''
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_avail... | 606 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Union[str, Any] =logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] ={
"microsoft/trocr-base-handwritten": (
"https://huggingface.co/mic... | 316 |
'''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/LICEN... | 316 | 1 |
'''simple docstring'''
class a_ :
def __init__( self , UpperCAmelCase ):
# we need a list not a string, so do something to change the type
a_ = arr.split(""",""" )
def lowerCAmelCase__ ( self ):
a_ = [int(self.array[0] )] * len(self.array ... | 511 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
'microsoft/focalnet-tiny'... | 511 | 1 |
"""simple docstring"""
def UpperCamelCase ( _lowerCAmelCase : str, _lowerCAmelCase : int ) -> list:
_UpperCAmelCase : Any = word.split()
def justify(_lowerCAmelCase : list, _lowerCAmelCase : int, _lowerCAmelCase : int ) -> str:
... | 238 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers impor... | 238 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
i... | 216 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case__ ( UpperCamelCase ... | 216 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...t... | 694 |
'''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 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accele... | 305 |
'''simple docstring'''
import operator as op
def SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE ):
lowerCAmelCase_ : Union[str, Any] =[]
lowerCAmelCase_ : Tuple =lambda _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE : int(x / y ) ... | 305 | 1 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require... | 60 |
from sklearn.metrics import mean_squared_error
import datasets
lowerCAmelCase_ = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blondel, M. and Pre... | 60 | 1 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = """Speech2TextFeatureExtractor"""
_SCREAMING_SNAKE_CASE = """Speech2TextTo... | 243 |
from math import sqrt
def lowercase_ (A : int ):
snake_case__ : Optional[int] = 0
for i in range(1 , int(sqrt(A ) + 1 ) ):
if n % i == 0 and i != sqrt(A ):
total += i + n // i
elif i == sqrt(A ):
... | 243 | 1 |
'''simple docstring'''
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__SCREAMING_SNAKE_CASE : Tuple =logging.get_logger(__name__) # pylint: disable=inval... | 135 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
__SCREAMING_SNAKE_CASE : List[str] =[
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernel... | 135 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acceler... | 248 |
"""simple docstring"""
import baseaa
def _lowerCAmelCase ( UpperCamelCase_ ):
return baseaa.baaencode(string.encode("""utf-8""" ) )
def _lowerCAmelCase ( UpperCamelCase_ ):
return baseaa.baadecode(UpperCamelCase_ ).decode("""utf-8""" )
if... | 248 | 1 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_tf, sl... | 219 |
'''simple docstring'''
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase : Union[str, Any] = logging... | 405 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
UpperCamelCase_ = {
'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapaneseConfig... | 210 |
"""simple docstring"""
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = '▁'
Up... | 210 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Tuple = logging.get_logger(__name__)
_lowerCamelCase : Optional[int] = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# ... | 87 |
import argparse
import json
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
VideoMAEConfig,
VideoMAEForPreTraining,
VideoMAEForVideoClassification,
VideoMAEImageProcessor,
)
def SCREAMING_SNAKE_CASE ( __UpperCamelCase) ... | 515 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
... | 145 |
'''simple docstring'''
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_UpperCAmelCase : Tuple = False
class __magic_name__ ( unittest.TestCase ):
... | 145 | 1 |
from __future__ import annotations
import time
__A : int = list[tuple[int, int]]
__A : str = [
[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],
[1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, ... | 343 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase ) -> Optional[Any]:
'''simple docstring'''
def wrapper(*_UpperCAmelCase, **_UpperCAmelCa... | 343 | 1 |
'''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,
EulerAncestralDis... | 432 |
'''simple docstring'''
lowerCAmelCase : Optional[Any] = '\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 ... | 432 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __A ( metaclass=snake_case__ ):
_UpperCamelCase : Optional[Any] = ["onnx"]
def __init__( self , *a__ , **a__ ):
requires_backends(self , ["""onnx"""] ... | 213 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert import... | 593 | 0 |
'''simple docstring'''
import unittest
from transformers.testing_utils import require_bsa
from transformers.utils import is_bsa_available
from ...test_feature_extraction_common import FeatureExtractionSavingTestMixin
if is_bsa_available():
from transformers import MarkupLMFeatureExtractor
class _Upp... | 716 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(__A ) , 'Tatoeba directory doe... | 193 | 0 |
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 __UpperCamelCase ( unittest.TestCase ):
"""simp... | 74 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCamelCase_ = {
"configuration_altclip": [
"ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AltCLIPConfig",
"AltCLIPTextConfig",
... | 611 | 0 |
def _A ( __magic_name__ , __magic_name__ ):
while a != 0:
lowercase__ , lowercase__ = b % a, a
return b
def _A ( __magic_name__ , __magic_name__ ):
if gcd(__lowerCAmelCase , __lowerCAmelCase ) != 1:
lowercase__ ... | 712 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...ima... | 611 | 0 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
snake_case_ : Any = [0 for i in range(len(__UpperCamelCase ) )]
# initialize interval's left pointer and right pointer
... | 58 |
from __future__ import annotations
from math import pow, sqrt
def _A ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float ):
"""simple docstring"""
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueErr... | 563 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor imp... | 556 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
... | 556 | 1 |
'''simple docstring'''
from manim import *
class _lowerCAmelCase ( A__ ):
"""simple docstring"""
def lowerCAmelCase ( self : Optional[Any] )-> Union[str, Any]:
snake_case = Rectangle(height=0.5 , width=0.5 ... | 369 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _low... | 369 | 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 ...test_configuration... | 422 |
"""simple docstring"""
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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 ImageProc... | 422 | 1 |
'''simple docstring'''
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... | 28 |
'''simple docstring'''
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedule... | 28 | 1 |
"""simple docstring"""
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase : List[str] = HfApi()
lowerCAmelCase : Tuple = {}
# fmt: off
lowerCAmelCase : List[str] = torch.tensor([... | 533 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class __magic_name__ ... | 533 | 1 |
'''simple docstring'''
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_lis... | 675 |
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
__lowercase = logging.get_logger(__name__)
__lowercas... | 203 | 0 |
import copy
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
from ..auto import CONFIG_MAPPING
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCas... | 718 | """simple docstring"""
import argparse
from collections import defaultdict
def lowerCamelCase_(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE )-> int:
_SCREAMING_SNAKE_CASE : str = F"""{file}... | 635 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='%(message)s')
def A ( _SCREAMING_SNAKE_CASE ) -> Tuple:
return input_array.reshape((input_array.size, 1) )
def A ( _SCREAMING_SNAKE_CASE ... | 311 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
... | 211 | 0 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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
UpperCa... | 711 |
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 RealmTokenizer
UpperCamelCa... | 144 | 0 |
"""simple docstring"""
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def SCREAMING_SNAKE_CASE__ ( snake_case : Optional[Any] )-> List[str]:
'''simple docstring'''
if not is_accelerate_a... | 438 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformers impo... | 438 | 1 |
'''simple docstring'''
from manim import *
class SCREAMING_SNAKE_CASE ( _A):
"""simple docstring"""
def UpperCamelCase__ ( self ) -> Union[str, Any]:
_lowerCAmelCase =Rectangle(height=0.5 , width=0.5 )
_lowerCAmelCase =Rectangle(heig... | 709 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']... | 58 | 0 |
def __snake_case ( lowerCAmelCase_ = 1_0_0 ) -> int:
SCREAMING_SNAKE_CASE__ = 0
SCREAMING_SNAKE_CASE__ = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
return sum_of_ints**2 - sum_of_squares
if __name__ ... | 100 |
"""simple docstring"""
def lowerCamelCase__ ( UpperCAmelCase_ = 60_08_51_47_51_43 )-> int:
"""simple docstring"""
try:
UpperCamelCase = int(UpperCAmelCase_ )
except (TypeError, ValueError):
raise TypeError("P... | 554 | 0 |
"""simple docstring"""
from math import factorial, radians
def __UpperCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = 18 , SCREAMING_SNAKE_CASE = 10 ) -> float:
"""simple docstring"""
__snake_case = angle_in_degrees - ((angle_in_degree... | 614 |
"""simple docstring"""
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def __UpperCamelCase ( ) -> tuple[list[int], int]:
"""simple docstring"""
__snake_case = [randint(-10_00 , ... | 614 | 1 |
from math import pi, sqrt, tan
def _A ( SCREAMING_SNAKE_CASE : float ):
"""simple docstring"""
if side_length < 0:
raise ValueError("surface_area_cube() only accepts non-negative values" )
return 6 * side_length**2
def _A ( SCREAMING_SNAKE_CASE : float ,... | 563 |
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import Batch... | 563 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .at... | 339 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
snake_case : Optional[int] = 500_000
snake_case , snake_case : Optional[int] = os.path.split(__file__)
snake_case ... | 339 | 1 |
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