code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
a_ : Dict = 8.3_14_45_98
def a_ ( __snake_case : float , __snake_case : float ) -> float:
"""simple docstring"""
if temperature < 0:
raise Exception('''Temperature cannot be l... | 75 |
'''simple docstring'''
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 75 | 1 |
"""simple docstring"""
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test... | 368 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, ... | 144 | 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 AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def Upper... | 344 |
'''simple docstring'''
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,... | 344 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
A : str = logging.get_logger(__name__)
A : str ... | 353 |
from string import ascii_uppercase
A : List[str] = {str(ord(c) - 5_5): c for c in ascii_uppercase}
def __lowerCamelCase ( __a :int , __a :int ) -> str:
"""simple docstring"""
if isinstance(__a , __a ):
raise TypeE... | 276 | 0 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..... | 209 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class _UpperCAmelCase ( UpperCAmelCase__ , UpperCAmelCase__ ):
'''simple docstring... | 286 | 0 |
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 : Any = logging.get_logger(__name... | 206 | import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class lowercase ( a ):
lowercase__ : Dict ... | 206 | 1 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
lowerCAmelCase = logging.get_logger(__name__)
class _a ( UpperCamelCase__ ):
def __init__( self: Tuple , *UpperCamelCase_: Tuple , **Upper... | 110 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
lowerCAmelCase = {'configuration_dpt': ['DPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DPTConfig']}
try:
i... | 110 | 1 |
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
lowerCAmelC... | 119 | import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def __lowerCamelCase ( ):
lowerCAmel... | 119 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( UpperCamelCase_ ):
_a = ['''image_processor''', '''tokenizer''']
_a = '''CLIPImageProcessor'''
_a = ('''XLMRober... | 103 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', leve... | 144 | 0 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from t... | 57 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import ASTFeatureExtractor
from transformers.testing_utils import require_torch, require_torchaudio
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_... | 57 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase : str = {
'''configuration_bridgetower''': [
'''BRIDGETOWER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BridgeTowerConfig''',
'''... | 18 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: List[str] = logging.get_logger(__name__)
A__: Union[str, Any] ... | 276 | 0 |
import enum
import shutil
import sys
_a , _a = shutil.get_terminal_size()
_a = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class A_ (enum.Enum ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Dict = 0
SCREAMING_SNAKE_CASE__ : Union[str, Any] ... | 368 |
"""simple docstring"""
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_a = object()
# For specifying empty leaf dict `{}`
_a = object()
def __a ( __lower... | 23 | 0 |
'''simple docstring'''
import math
def a ( lowerCamelCase__ , lowerCamelCase__ ):
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(lowerCamelCase__ )
else:
if x == 0: # 0 raised t... | 206 |
'''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-2.0
#... | 206 | 1 |
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ) -> bool:
'''simple docstring'''
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is not already in path
return not any(vertex ==... | 368 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A : Optional[Any] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''UniSpeechCo... | 323 | 0 |
# Function to print upper half of diamond (pyramid)
def UpperCamelCase ( snake_case__ : int ) -> List[Any]:
for i in range(0 , snake_case__ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 , i... | 119 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ) -> Optional[int]:
UpperCamelCase : List[Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'--src_path' , type=snake_case__ , default='biencoder-nq-dev.json' ... | 119 | 1 |
"""simple docstring"""
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def _snake_case ( lowercase__ ):
return 1 / (1 + np.exp(-z ))
def _snake_case ( lowercase__ , lowercase__ ):
return ... | 368 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
lowercase__ = logging.get_logger(__name__)
class lo... | 12 | 0 |
"""simple docstring"""
# This is the module that test_patching.py uses to test patch_submodule()
import os # noqa: this is just for tests
import os as renamed_os # noqa: this is just for tests
from os import path # noqa: this is just for tests
from os import path as renamed_path # noqa: this is just for tests... | 57 |
"""simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A : str = logging.get_logger(__name__)
class _UpperCamelCase ( lowerCAmelCase__ ):
'''simple docstring''... | 57 | 1 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class _snake_case ( nn.Module):
UpperCamelCase__ : int
UpperCamelCase__ : int
UpperCamelCase__ : float ... | 359 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureEx... | 224 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMSchedul... | 219 |
'''simple docstring'''
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_... | 23 | 0 |
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
UpperCamelCase = [
# (stable-diffusion, HF Diffusers)
("""time_embed.0.weight""", """time_embedding.linear_1.weight"""),... | 65 |
from manim import *
class _lowerCamelCase ( UpperCamelCase ):
"""simple docstring"""
def _snake_case ( self )->Tuple:
'''simple docstring'''
A_ : Optional[int] = Rectangle(height=0.5 , width=0.5 )
A_ : Union[str, Any] ... | 65 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTo... | 40 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCa... | 323 | 0 |
"""simple docstring"""
def lowerCAmelCase (__UpperCamelCase : int ):
"""simple docstring"""
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
raise ValueError('''Input must ... | 85 | """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/LICENSE... | 85 | 1 |
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class ... | 88 |
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_list_of_images, to_numpy_array, vali... | 12 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
A : List[Any] = logging.get_logger(__name__)
def _lowerCamelCase ( _UpperCamelCase ):
'''simple docstring'''
if isinstance(_UpperCame... | 357 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
A : Tuple = logging.get_logger(__name__)
A : ... | 259 | 0 |
from __future__ import annotations
from collections.abc import MutableSequence
class __magic_name__ :
"""simple docstring"""
def __init__( self :Optional[int] , snake_case :int , snake_case :MutableSequence[float] ):
'''simple docstring'''
... | 300 |
"""simple docstring"""
import re
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> list:
"""simple docstring"""
return [char.split() for char in re.split(R'[^ a-z A-Z 0-9 \s]' , str_ )]
def UpperCamelCase_ ( lowerCAmelCase__ ... | 224 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__snake_case : List[str] =re.compile(R'\b(a|an|the)\b', re.UNICODE)
__snake_case : Optional[Any] =None
def lowerCAmelCase__ ( ):
'''simple docstring'''
lowerCAmelC... | 94 |
def lowerCAmelCase__ ( lowerCamelCase_ : int = 1000):
'''simple docstring'''
lowerCAmelCase__ , lowerCAmelCase__ : int = 1, 1
lowerCAmelCase__ : Any = 2
while True:
lowerCAmelCase__ : Optional[Any] = 0
... | 94 | 1 |
UpperCamelCase__ = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
def lowerCAmelCase_ ( ) -> None:
'''simple docstring'''
UpperCAmelCase__ = input("Enter message: " )
UpperCAmelCase__ = input("Enter key [alphanumeric]: " )
Uppe... | 65 | import math
import random
def lowerCAmelCase_ ( __A, __A = False ) -> float:
'''simple docstring'''
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
UpperCamelCase__ = 0.0_... | 65 | 1 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class a_ :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> str:
"""simple docstring"""
UpperCamelCase = str(id_ )
... | 361 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig',
]
... | 183 | 0 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
from ..... | 244 |
"""simple docstring"""
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
__UpperCAm... | 84 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats... | 186 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatu... | 186 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Sequence[float] ,_lowerCamelCase : float ) -> float:
return sum(c * (x**i) for i, c in enumerate(_lowerCamelCase ) )
def SCREAMING_SNAKE_CASE ... | 44 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)... | 259 | 0 |
"""simple docstring"""
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def a__ ( __UpperCamelCase ):
return x + 2
class lowerCamelCase (unittest.TestCase ):
"""simple docstring"""
def ... | 362 | import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def a__ ( __UpperCamelCase ):
return x + 2
class lowerCamelCase (unittest.TestCase ):
"""simple docstring"""
def __A ( self : ... | 305 | 0 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# full vocab, merges file, and t... | 94 |
def __lowerCamelCase ( UpperCAmelCase_ : list , UpperCAmelCase_ : list , UpperCAmelCase_ : int ):
"""simple docstring"""
if len(UpperCAmelCase_ ) != len(UpperCAmelCase_ ):
raise ValueError('''The length of profit and weight must be same.'''... | 94 | 1 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( lowerCAmelCase):
_a = (DDIMParallelScheduler,)
_a = (('''eta''', 0.0), ('''num_inference_steps''', 50))
def SCREAMING_SNAKE_CAS... | 360 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils import Con... | 158 | 0 |
from __future__ import annotations
import requests
def UpperCamelCase (lowercase_: str ) -> dict:
A__ : List[str] = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(_lowerCamelCase ).json()
def UpperCamelCase ... | 192 |
"""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.apach... | 183 | 0 |
lowercase_ = """Tobias Carryer"""
from time import time
class _snake_case :
def __init__( self : Optional[int], __lowercase : Dict, __lowercase : Optional[Any], __lowercase : Tuple, __lowercase : Optional[Any]=int(time() ) ): # noqa: B008
lowercase__ ... | 224 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"""facebook/dpr-ctx_encoder-single-nq-base""": (
"""https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json""... | 224 | 1 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
A_ : List[Any] = [0 for i in range(r + 1 )]
# nc0 = 1
A_ : str = 1
for i in range(1 , n + 1 ):
# to compute current row from previous row.
A_ : Union[str, Any... | 186 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase = {
"""configuration_mobilevit""": ["""MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MobileViTConfig""", "... | 186 | 1 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDi... | 107 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
__lowerCAmelCase = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
__lowerCAmelCase = BASE_... | 107 | 1 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class __lowercase (UpperCAmelCase__ ):
_UpperCamelCase = ["""... | 275 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 305 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowerCamelCase_ ( a__ ):
'''simple docstring'''
def __init__( self... | 370 | import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( UpperCAmelCase_ , unittest.TestCase ):
'''simple docstring'''
... | 105 | 0 |
"""simple docstring"""
def a_ ( lowerCamelCase , lowerCamelCase ):
UpperCAmelCase__ = len(SCREAMING_SNAKE_CASE_ )
UpperCAmelCase__ = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr value, a sum of zero(0... | 98 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def __a(SCREAMING_SNAKE_CASE_ : float ):
'''simple docstring'''
if num <= 0:
raise ValueError("math domain error" )
return quad(SCREAMING_SNAKE_CASE_ , 0 , SCREA... | 158 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_en... | 359 | """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, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils imp... | 312 | 0 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> str:
"""simple docstring"""
lowerCAmelCase_ : int = int(lowerCAmelCase__ )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowerCAmelCas... | 224 |
"""simple docstring"""
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowercase__ : List[str] = loggi... | 224 | 1 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import deprecate
deprecate(... | 369 | # DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor... | 81 | 0 |
def __magic_name__ ( A : str, A : list[str] ):
'''simple docstring'''
a = ""
for word_or_phrase in separated:
if not isinstance(A, A ):
raise Exception("join() accepts only strings to be joined" )
joined += word_or_phrase + separator
return... | 107 |
def __magic_name__ ( A : str ):
'''simple docstring'''
a = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __magic_name__ ( A : str ):
'''simple docstring'''
... | 107 | 1 |
from ...processing_utils import ProcessorMixin
class __lowerCAmelCase ( A ):
UpperCamelCase = '''SpeechT5FeatureExtractor'''
UpperCamelCase = '''SpeechT5Tokenizer'''
def __init__( self : Optional[int] , A : Any , A : List[Any... | 290 |
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def A ( ) -> tuple[list[int], int]:
'''simple docstring'''
_UpperCAmelCase = [randint(-1_000 , 1_000 ) for i in range(10 )]
_Up... | 290 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
_a = version.parse(version.parse(torch.__version__).base_version) < version.parse('1.11')
def __a ( __lowerCam... | 61 |
"""simple docstring"""
from __future__ import annotations
def _SCREAMING_SNAKE_CASE ( _lowercase : list[int] , _lowercase : int ) ->int:
'''simple docstring'''
if len(_lowercase ) < k or k < 0:
raise ValueError("Inv... | 105 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lo... | 219 |
'''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
fro... | 219 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
norm... | 23 |
from __future__ import annotations
def __snake_case ( __UpperCamelCase : list[list[int]] ):
"""simple docstring"""
for i in range(1 ,len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first column
for i in range(1 ... | 312 | 0 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rouge, chunks, ... | 343 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase (... | 343 | 1 |
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
)
__snake_case = logging.getLogger(__name__)
if __name__ == "__main__":
__snake_case... | 348 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase_ : Optional[Any] = {}
try:
... | 81 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
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 PIL import Image
from ..image_uti... | 367 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import ... | 43 | 0 |
"""simple docstring"""
class __snake_case ( __lowerCAmelCase ):
pass
class __snake_case ( __lowerCAmelCase ):
pass
class __snake_case :
def __init__( self) -> Optional[Any]:
'''simple docstring'''
a__: Tuple... | 290 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'andreasmadsen/efficient_mlm_m0.4... | 290 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int = 1_0_0_0_0_0_0 ) ->int:
A__ : int = set(range(3, UpperCAmelCase__, 2 ) )
primes.add(2 )
for p in range(3, UpperCAmelCase__, 2 ):
if p not in primes:
... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
def __SCREAMING_SNAKE_CASE ( __UpperCamelCase : list[list[int]] , __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : list[int] ) -> bool:
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 219 | from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import Fr... | 219 | 1 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : Tuple , SCREAMING_SNAKE_CASE__ : List[str] , SCREAM... | 61 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
'microsoft/cvt-13': 'https://huggingface.co/microsoft/cvt-13/resolve/main/config.json',
# See all Cvt models at https... | 61 | 1 |
def _snake_case( SCREAMING_SNAKE_CASE__ ) -> int:
lowercase : Any = hex_num.strip()
if not hex_num:
raise ValueError("""No value was passed to the function""" )
lowercase : int = hex_num[0] == """-"""
if is_negative:... | 20 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
UpperCamelCase = '''
import os
'''
UpperCamelCase = '''
def foo():
import os
return False
'''
UpperCamelCase = '''
def foo():
def bar():
... | 319 | 0 |
def UpperCamelCase ( _a = 1_0_0_0 ) -> int:
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 352 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Tuple = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE : Dict = {
"bigcode/gpt_bigcode-santacoder": "https://huggingface.co/bigcode/gpt_bigcode-santa... | 252 | 0 |
'''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 import (
AutoConfig,
Au... | 83 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config... | 43 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_ : Tuple = {
'configuration_nllb_moe': [
'NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP',
'NllbMoeConfig',
... | 69 |
"""simple docstring"""
from typing import Any
class a :
"""simple docstring"""
def __init__( self: List[Any] , UpperCamelCase: Any ):
"""simple docstring"""
A__ = data
A__ = None
... | 69 | 1 |
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_available... | 296 |
from pathlib import Path
import fire
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = Path(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if i... | 358 |
def _UpperCamelCase (a__ :dict ):
"""simple docstring"""
UpperCamelCase__ = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
UpperCamelCase__ = set()
return any(
node not in v... | 87 | 0 |
"""simple docstring"""
import os
import sys
_a = os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceClassif... | 61 |
"""simple docstring"""
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transfo... | 61 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTest... | 365 |
"""simple docstring"""
from itertools import permutations
def _A (__a ) -> bool:
"""simple docstring"""
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
SCREAMING_SNAK... | 318 | 0 |
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
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 (
... | 26 |
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If user passes --user <user> --host <host> --key_path <... | 252 | 0 |
"""simple docstring"""
from __future__ import annotations
a__ : Optional[int] = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_... | 352 |
"""simple docstring"""
from __future__ import annotations
import requests
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = f"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return request... | 195 | 0 |
"""simple docstring"""
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_trans... | 69 | """simple docstring"""
import inspect
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_config_docstrings.py
__UpperCamelCase = '''src/transformers'''
# This ... | 69 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A : Dict = {
'''configuration_transfo_xl''': ['''TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TransfoXLConfig'''],
'''tokenization_transfo_xl''':... | 276 |
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... | 276 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
A__: List[str] = {'''configuration_dpt''': ['''DPT_PRETRAINED... | 276 | UpperCamelCase = [0, 2, 4, 6, 8]
UpperCamelCase = [1, 3, 5, 7, 9]
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int , _lowerCamelCase : list[int] , _lowerCamelCase : int):
if remaining_length == 0:
if dig... | 87 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def UpperCAmelCase_ ( __lowerCamelCase : List[Any] ):
# vision encoder
if "img_encoder.pos_embed" in name:
... | 364 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Optional[int] ={'''configuration_wavlm''': ['''WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''WavLMConfig''']}
try:
if not is... | 147 | 0 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
snake_case_ = "EncodecFeatureExtractor"
snake_case_ = ("T5To... | 15 |
'''simple docstring'''
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all feature extractors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_r... | 318 | 0 |
"""simple docstring"""
def __lowercase ( snake_case_ : int ) ->bool:
'''simple docstring'''
if number < 0:
raise ValueError('''number must not be negative''' )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
... | 354 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@r... | 291 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Tuple = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwritten/res... | 20 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 195 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_snake_... | 360 |
import logging
from transformers.configuration_utils import PretrainedConfig
_snake_case : Optional[Any] = logging.getLogger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
__UpperCAmelCase : Tuple = "masked_bert"
def __init__( se... | 134 | 0 |
'''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 requ... | 276 |
'''simple docstring'''
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 ,isqrt(_UpperCAmelCase ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 10**6 ) -... | 276 | 1 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
fro... | 228 |
'''simple docstring'''
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCAmelCase = logging.get_logge... | 228 | 1 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
_snake_case = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def _A ( ) -> Optional[int]:
_lowercase : Any = os.path.dirname(os.path.realpath(lowerCAmelCase__ ) )
_lowercase ... | 250 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" , [
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""": 1_0, """max_num_job... | 147 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from tran... | 352 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vi... | 13 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConformerConfig,
WavaVecaConformerForCTC,
WavaVecaConformerForPreTraining,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)... | 19 |
"""simple docstring"""
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
... | 291 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
__UpperCAmelCase ={"configuration_speech_encoder_decoder": ["SpeechEncoderDecoderConfig"]}
try:
if not is_torch_available():
raise Opti... | 356 | '''simple docstring'''
__UpperCAmelCase ="ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def __lowerCAmelCase ( ) -> None:
__lowerCamelCase = input('''Enter message: ''' )
__lowerCamelCase = input('''Enter key [alphanumeric]: ''' )
__lowerCamelCase = input... | 237 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase = {
'configuration_electra': ['ELECTRA_PRETRAINED_CONFIG_ARCH... | 59 |
'''simple docstring'''
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__snake_case : Any = pytest.mark.integration
@pytest.mark.parametrize("""p... | 134 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class ... | 370 |
# 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 require... | 315 | 0 |
from __future__ import annotations
def __A ( __lowerCamelCase , __lowerCamelCase ) -> float:
a = sorted(numsa + numsa )
a , a = divmod(len(__lowerCamelCase ) , 2 )
if mod == 1:
return all_numbers[div]
else:
ret... | 228 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__UpperCamelCase : List[str... | 228 | 1 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def snake_case ( snake_case__ :Tuple) -> Union[str, Any]:
_A = {}
_A = job["""started_at"""]
_A = job["""completed_at"""... | 81 | import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
_SCREAMING_SNAKE_CASE = {
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36'
' (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.195... | 81 | 1 |
"""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/LIC... | 91 |
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 jnp
from jax import jit
fro... | 13 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
fro... | 38 |
"""simple docstring"""
from math import sqrt
def lowercase (SCREAMING_SNAKE_CASE_ : int ) -> int:
SCREAMING_SNAKE_CASE = 0
for i in range(1 , int(sqrt(SCREAMING_SNAKE_CASE_ ) + 1 ) ):
if n % i == 0 and i != sqrt(SCREAMING_SNAKE... | 38 | 1 |
"""simple docstring"""
import enum
import shutil
import sys
_a , _a : int = shutil.get_terminal_size()
_a : Optional[Any] = {'UP': 'A', 'DOWN': 'B', 'RIGHT': 'C', 'LEFT': 'D'}
class __A ( enum.Enum ):
_UpperCamelCase : int = 0
_UpperC... | 44 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from numpy import array
def UpperCamelCase ( _lowerCamelCase : list[list[float]] ):
A__ = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implem... | 237 | 0 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
a__ : Tuple = logging.get_logger(__name__) # pylint: disable=invalid-name
class a_ ( a__ ):
... | 19 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a__ : Optional[Any] = {'''configuration_deit''': ['''DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DeiTConfig''', '''... | 19 | 1 |
import argparse
import datetime
def lowerCamelCase__ ( A__ : str ):
'''simple docstring'''
__lowerCamelCase = {
"""0""": """Sunday""",
"""1""": """Monday""",
"""2""": """Tuesday""",
"""3""": """Wednesday""",
... | 12 |
"""simple docstring"""
def _snake_case ( _snake_case : int = 10_00 ) -> int:
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 315 | 0 |
from functools import lru_cache
@lru_cache
def A_ ( snake_case_ : Optional[Any] ):
'''simple docstring'''
if num < 0:
raise ValueError("""Number should not be negative.""" )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __name__ == "__... | 359 |
"""simple docstring"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 27 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCamelCase_ : str = logging.get_logger(__name__)
lowerCamelCase_ : Any = {
"""CarlCochet/trajectory-transformer-halfcheetah-medium-v2""": (
... | 81 |
"""simple docstring"""
from __future__ import annotations
import math
def _A ( lowercase ):
"""simple docstring"""
if num <= 0:
a =f'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(lowercase )
a =[Tr... | 81 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case = {
"""configuration_roberta""": ["""ROBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP... | 319 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE ( lowerCAmelCase ):
'''simple docstring'''
UpperCamelCase_ : Dict = '''ClapFeatureExtractor'''
UpperCamelCase_ : Any = ... | 319 | 1 |
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 38 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _SCREAMING_SNAKE_CASE ( _a , unittest.TestCase ):
snake_case__ : Optional[Any] ... | 38 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import tor... | 351 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
a : Union[str, Any] = Fals... | 150 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https://huggingface.co/RWKV/rwkv-4-430m-pi... | 19 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_utils ... | 19 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCAmelCase__ :
def __init__( self : Union[str, Any] , lowerCamelCase__ : Tuple , lowerCamelCase__ : Tuple ) ->None:
'''simple d... | 366 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
lowerCamelCase__ = list[list[float | int]]
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
_UpperCAmelCase : int = len(__lowerCAmelCase )
_Up... | 322 | 0 |
'''simple docstring'''
import math
import sys
def a ( __a ) -> int:
'''simple docstring'''
if number != int(__a ):
raise ValueError('''the value of input must be a natural number''' )
if number < 0:
raise ValueError('''the value of input must not be a ne... | 97 |
'''simple docstring'''
import torch
from transformers import AutoModel
class __UpperCamelCase ( torch.nn.Module ):
def __init__( self , __a="sayef/fsner-bert-base-uncased" ):
'''simple docstring'''
super(__a , self ).__init__()
__a ... | 27 | 0 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
__UpperCAmelCase = False
class UpperCamelCase__ ( unittest.TestCase ):
... | 257 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
UpperCAmelCase_ =["transformers", "torch", "note_seq"]
def __init__( self , *_A , **_A ) ... | 257 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase = {
'''configuration_roberta''... | 319 |
'''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __lowercase ) -> bool:
if len(__lowercase ) < 2:
raise ValueError('''Monogons and Digons are not polygons in the Euclidean space''' )
if any(i <= 0 for i in nums ):
... | 319 | 1 |
"""simple docstring"""
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __SCREAMING_SNAKE_CASE ( unittest.TestCase ):
def _UpperCamelCase ( self : int ):
'''... | 360 |
"""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_ = logging.get_logge... | 296 | 0 |
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