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 |
|---|---|---|---|---|
from __future__ import annotations
def __lowerCamelCase (UpperCAmelCase__ : str , UpperCAmelCase__ : list[str] | None = None , UpperCAmelCase__ : dict[str, float] | None = None , UpperCAmelCase__ : bool = False , ):
SCREAMING_SNAKE_CASE = cipher_... | 403 | import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
_lowerCamelCase : Optional[Any] = logging.get_logg... | 403 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__magic_name__ = {
"configuration_mvp": ["MVP_PRETRAINED_CONFIG_ARCHIVE_MAP", "MvpConfig", "MvpOnnxConfig"],
"tokenization_mvp": ["Mvp... | 248 |
"""simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def _lowerCAmelCase ( UpperCamelCase_ ):
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... | 248 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers impor... | 688 |
'''simple docstring'''
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
__SCREAMING_SNAKE_CASE = False
__SCREAMING_SNAKE_CASE = True
__SCREAMING_SNAKE_CASE = False
if __name__ ... | 688 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from transformers import BeitConfig
from transformers.testing_utils import require_flax, require_vision, slow
from transformers.utils import cached_property, is_flax_available, is_vision_available
from ...test_configuration_co... | 720 |
'''simple docstring'''
import math
def __snake_case ( UpperCAmelCase_ : float , UpperCAmelCase_ : float ):
return math.pow(UpperCAmelCase_ , 2 ) - a
def __snake_case ( UpperCAmelCase_ : float ):
return 2 * x
def __snake_case ( ... | 445 | 0 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def _lowerCAmelCase ( __magic_name__ : Any ) -> Optional[int]:
# getting number of pixels in the image
lowercase , lowercase : List[Any] =img.shape[0], img.shape[1]
# c... | 92 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
UpperCamelCase_ = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of ... | 92 | 1 |
"""simple docstring"""
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelC... | 553 |
"""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_torc... | 553 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common imp... | 189 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A_ : Optional[Any] = logging.get_logger(__name__)
A_ : Optional[Any] = ... | 57 | 0 |
def lowercase_ ( _UpperCAmelCase ):
"""simple docstring"""
if not isinstance(_UpperCAmelCase , _UpperCAmelCase ):
raise TypeError('''only integers accepted as input''' )
else:
A_ : int = str(abs(_UpperCAmelCase ) )
A_ : List[Any] = [list(_UpperC... | 719 |
"""simple docstring"""
from collections.abc import Generator
from math import sin
def lowercase_ ( _UpperCAmelCase ):
"""simple docstring"""
if len(_UpperCAmelCase ) != 32:
raise ValueError('''Input must be of length 32''' )
A_ : int = b''''''
for i in [... | 361 | 0 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE : int = TypeVar("T")
class UpperCamelCase ( Generic[T] ):
'''simple docstring'''
lowercase : deq... | 257 |
import math
def UpperCamelCase ( _a ) -> bool:
'''simple docstring'''
lowercase_ :int = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(_a )
def UpperCamelCase ( _a = 1 / 1_2_3... | 257 | 1 |
'''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, DPTImageProcessor
from transformers.utils ... | 434 |
'''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 snake_case ( unittest.T... | 434 | 1 |
"""simple docstring"""
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow,... | 575 |
"""simple docstring"""
from __future__ import annotations
def snake_case__ ( _lowerCamelCase, _lowerCamelCase, _lowerCamelCase, ) ->tuple:
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("You cannot supply more o... | 575 | 1 |
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
class _a ( lowerCamelCase_ ):
"""simple docstring"""
__SCREAM... | 594 | import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
lowerCAmelCase__ = models.Sequential()
# Step 1 - Con... | 594 | 1 |
def _SCREAMING_SNAKE_CASE ( __snake_case ) -> int:
if not isinstance(__snake_case , __snake_case ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive""" )
return sum(
... | 108 |
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
__a: Dict = logging.get_logger(__name__)
__a: Optional[int] = {
... | 108 | 1 |
"""simple docstring"""
def lowerCAmelCase ( UpperCamelCase_: str ) -> list[int]:
'''simple docstring'''
_a = [0 for i in range(len(UpperCamelCase_ ) )]
# initialize interval's left pointer and right pointer
_a , _a = 0, 0
for i... | 612 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_commo... | 612 | 1 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from typing import List, Optional, Union
import tqdm
from filelock import FileLock
from transformers import (
BartTokenizer,
BartTokenizerFast,
DataProcessor,
PreTrainedTokenizer,
RobertaTok... | 69 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE__ ( _UpperCamelCase ):
__SCREAMING_SNAKE_CASE = """SpeechT5FeatureExtractor"""
__SCREAMING_SNAKE_CASE = """SpeechT5Tokenizer"""
def __init__( self : List... | 69 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 222 |
"""simple docstring"""
A_ : List[Any] =9.8_0665
def SCREAMING_SNAKE_CASE_ ( snake_case : float , snake_case : float , snake_case : float = g )-> float:
if fluid_density <= 0:
raise ValueError('Impossible fluid density' )
if... | 222 | 1 |
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTest... | 30 |
"""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,
... | 139 | 0 |
import os
import sys
import unittest
SCREAMING_SNAKE_CASE_:str = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_ba... | 520 |
import hashlib
import unittest
from typing import Dict
import numpy as np
from transformers import (
MODEL_FOR_MASK_GENERATION_MAPPING,
TF_MODEL_FOR_MASK_GENERATION_MAPPING,
is_vision_available,
pipeline,
)
from transformers.pipelines import MaskGenerationPipeline
from transformers.testing_utils i... | 520 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( __snake_case ) -> int:
"""simple docstring"""
_UpperCamelCase = 1
for i in range(1, num + 1 ):
fact *= i
return fact
def lowerCamelCase__ ( __snake_case ... | 19 |
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tens... | 322 | 0 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__lowercase = TypeVar('''T''')
def SCREAMING_SNAKE_CASE__ ( _SCREAMING_SNAKE_CASE ):
return (position - 1) // 2
def SCREAMING_SNAKE_CASE__ ( _SCR... | 305 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
__lowercase = logging.getLogger(__name__)
class _snake_case ( lowerCAmelCase_ ):
"""simple docstring""... | 305 | 1 |
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/data2vec-audio-base-960h/resolve/main/confi... | 458 |
def __magic_name__ ( lowercase ) -> list:
"""simple docstring"""
if n_term == "":
return []
lowercase_ : list = []
for temp in range(int(lowercase ) ):
series.append(f"""1/{temp + 1}""" if series else """1""" ... | 458 | 1 |
def __lowerCAmelCase ( _UpperCamelCase ) -> list:
'''simple docstring'''
lowerCamelCase__: Optional[int] = len(_UpperCamelCase )
for _ in range(_UpperCamelCase ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
... | 242 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
_lowercase = logging.get_logger(__name__)
_lowercase ... | 242 | 1 |
"""simple docstring"""
import sys
def UpperCAmelCase ( snake_case : Union[str, Any] ):
_lowerCAmelCase:Dict = len(snake_case )
_lowerCAmelCase:List[str] = [[0 for x in range(snake_case )] for x in range(snake_case )]
_lowerCAmelCase:str = [[... | 227 |
"""simple docstring"""
from datetime import datetime
import requests
def UpperCAmelCase ( snake_case : str ):
_lowerCAmelCase:Optional[Any] = '''https://downloadgram.net/wp-json/wppress/video-downloader/video?url='''
_lowerCAmelCase:Any = requests.get(base_url +... | 227 | 1 |
'''simple docstring'''
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase =logging.get_logger(__name__)
lowercase ={'vocab_file': 'vocab.json', 'merges_... | 716 |
'''simple docstring'''
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/confi... | 331 | 0 |
from __future__ import annotations
__a = '#'
class lowercase__:
"""simple docstring"""
def __init__( self : Dict ) -> None:
lowercase_ = {}
def _lowercase ( self : str , SCREAMING_SNAKE_CASE_ : str ) -> None:
lowercase... | 97 |
def _A ( SCREAMING_SNAKE_CASE : list[int] , SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
a__ : List[str] =len(SCREAMING_SNAKE_CASE )
a__ : Optional[int] =[[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for each arr ... | 563 | 0 |
def lowercase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ) -> int:
if exponent == 1:
return base
if exponent % 2 == 0:
_snake_case : int = _modexpt(SCREAMING_SNAKE_CASE__ , ... | 198 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
Au... | 198 | 1 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {'''vocab_file''': '''vocab.txt'''}
__magic_name__ ... | 276 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from trans... | 276 | 1 |
"""simple docstring"""
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
... | 310 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"huggingface/time-series-transformer-tourism-monthly": (
"https://huggingface.co... | 310 | 1 |
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 import ... | 623 |
from __future__ import annotations
from math import pow, sqrt
def __lowercase( UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ):
"""simple docstring"""
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError("One and only one argume... | 623 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import... | 565 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase = {
'''configuration_xlm_roberta_xl''': [
'''XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''XLMRobertaXLConfig''',
'''XLMRobertaXLOnnxConfig''... | 565 | 1 |
'''simple docstring'''
import inspect
from typing import Optional, Union
import numpy as np
import PIL
import torch
from torch.nn import functional as F
from torchvision import transforms
from transformers import CLIPFeatureExtractor, CLIPModel, CLIPTextModel, CLIPTokenizer
from dif... | 26 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case : int = logging.get_logger(__name__)
_snake_case : str = {
"Visual-Attention-Network/van-base": (
"https://huggingface.co/Visual-Attention-Network/van-base/blob/main/con... | 81 | 0 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class a_ :
UpperCamelCase_ : str = field(
metadata={"help": "... | 674 | """simple docstring"""
import os
def _UpperCAmelCase ( ):
"""simple docstring"""
lowerCAmelCase__ = os.path.dirname(os.path.realpath(lowerCamelCase__ ) )
lowerCAmelCase__ = os.path.join(lowerCamelCase__ , """triangle.txt""" )
with open(lowerCam... | 674 | 1 |
from __future__ import annotations
import pandas as pd
def __SCREAMING_SNAKE_CASE ( a__ : list[int] ,a__ : list[int] ,a__ : int ) -> list[int]:
__A : List[str] = [0] * no_of_processes
__A : Dict = [0] * no_of_processes
# Copy the burst time into remai... | 17 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase : str = logging.get_logger(__name__)
__lowerCamelCase : Tuple = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/... | 653 | 0 |
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable... | 709 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository ... | 64 | 0 |
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : Dict , lowerCamelCase : Optional[int] , lowerCamelCase : Dict ) -> List[str]:
"""simple docstring"""
_UpperCAmelCase = name
_UpperCAmelCase ... | 108 |
"""simple docstring"""
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
A__ : Optional[int] = [
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernels/deformable_detr/cuda/ms_deform... | 353 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmel... | 711 |
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
lowercase = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
lowercase = set()
return any(
node not in visited and depth_first_search(__SCREAMING_SNAKE_CASE , __SCREAMING_SNA... | 565 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class _UpperCAmelCase ( _lowerCAmelCase ):
a__ : Optional[Any] = "bert-generation"
def __init__( self : Any , _lowercase : List[Any]=5_03_58 , _lowercase : ... | 49 |
import argparse
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator, Di... | 487 | 0 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
SCREAMING_SNAKE_CASE_: List[Any] ='<<<<<<< This should probably be modified because it mentions: '
SCR... | 415 | '''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common... | 415 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a : str = {
"configuration_trajectory_transformer": [
"TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"TrajectoryTransformerConfi... | 679 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
a : Optional[int] = logging.get_logger(__name__)
def lowercase ( __magic_name__ ):
'''simple docstring'... | 679 | 1 |
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __magic_name__ ( unittest.TestCase):
def UpperCAmelCase__ ( self : Dict ) -> str:
'''simple docstring'''... | 720 |
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
__UpperCamelCase : Tuple = logging.get_logger(__name__)
__UpperCamelCase... | 106 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_A = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 182 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class lowerCamelCase ( unittest.TestCase ):
'''simple docstring'''
def _a (self ):
"""simple docstrin... | 182 | 1 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOut... | 716 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ : Union[str, Any] = {'''configuration_sew''': ['''SEW_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SEWConfig''']}
try:
if not ... | 165 | 0 |
'''simple docstring'''
def A_ ( SCREAMING_SNAKE_CASE_ ) ->bool:
if num < 0:
return False
lowercase_ = num
lowercase_ = 0
while num > 0:
lowercase_ = rev_num * 10 + (num % 10)
num //= 10
return num_copy == rev_num
if __name__ == "__main__":
... | 451 | '''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 accelerate ... | 451 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : str = logging.get_logger(__name__)
lowerCamelCase : int = {
'''studio-ousia/luke-base''': '''https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json''',
'''studi... | 719 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : int = logging.get_logger(__name__)
lowerCamelCase : Tuple = {
'''caidas/swin2sr-classicalsr-x2-64''': (
'''https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/m... | 290 | 0 |
def _lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
A_ = str(SCREAMING_SNAKE_CASE )
A... | 203 |
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 | 1 |
'''simple docstring'''
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
a_ = "sshleifer/bart-tiny-random"
... | 703 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torch.uti... | 92 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
lo... | 453 |
from math import sqrt
def __snake_case ( _lowerCAmelCase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
retur... | 454 | 0 |
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCamelCase__ :
'''simple docstring'''
def __init__( self, snake_case__, snake_case__, snake_case__, snake_case__, snake_case__, snake_case__=0.2, ... | 436 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDecoderConfig"""... | 436 | 1 |
"""simple docstring"""
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(">=", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
fr... | 510 |
"""simple docstring"""
def snake_case ( _a: int , _a: int )-> int:
'''simple docstring'''
lowerCamelCase__ = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
lowerCamelCase__ = n - k
# Calc... | 510 | 1 |
'''simple docstring'''
from math import pi, sqrt
def lowerCAmelCase__ ( lowerCamelCase_ : float):
'''simple docstring'''
if num <= 0:
raise ValueError('''math domain error''')
if num > 171.5:
raise OverflowError('''math range error''')
elif num - int(_A) not i... | 705 |
from bisect import bisect
from itertools import accumulate
def lowerCAmelCase__ ( lowerCamelCase_ : List[str] ,lowerCamelCase_ : Optional[Any] ,lowerCamelCase_ : List[str] ,lowerCamelCase_ : Optional[int]):
'''simple docstring'''
lowerCAmelCase__ : Any = sorted(zip(lowerCamelCa... | 90 | 0 |
'''simple docstring'''
import os
def lowerCAmelCase_ ( __A : str = "matrix.txt" ):
'''simple docstring'''
with open(os.path.join(os.path.dirname(__A ) , __A ) ) as in_file:
snake_case: Any = in_file.read()
snake_case: Dict =... | 329 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
def lowerCAmelCase_ ( __A : Union[str, Any] )... | 329 | 1 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
)
UpperCamelCase :... | 610 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCamelCase : Optional[int] = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """Lo... | 610 | 1 |
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
resize,
to_channel_dim... | 658 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmR... | 658 | 1 |
import os
import string
import sys
__a : Dict = 1 << 8
__a : List[str] = {
'''tab''': ord("""\t"""),
'''newline''': ord("""\r"""),
'''esc''': 2_7,
'''up''': 6_5 + ARROW_KEY_FLAG,
'''down''': 6_6 + ARROW_KEY_FLAG,
'''right''': 6_7 + ARROW_KEY_FLAG,
... | 709 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
__a : Optional[int] = lo... | 414 | 0 |
'''simple docstring'''
import numpy as np
import torch
from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class SCREAMING_SNAKE_CASE ( __a ):
... | 329 |
"""simple docstring"""
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase = logging.get_logger(__name__)
def lowerCAmelC... | 118 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
cente... | 116 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql impo... | 116 | 1 |
'''simple docstring'''
from __future__ import annotations
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : str , lowerCAmelCase__ : int = 0 ) -> Dict:
'''simple docstring'''
_UpperCamelCase = ... | 98 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, l... | 503 | 0 |
def A ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
UpperCAmelCase__ :int = len(A_ )
UpperCAmelCase__ :Optional[Any] = len(A_ )
UpperCAmelCase__ :Optional[Any] = [[False for _ in range(m + 1 )] for _ in range(n +... | 710 |
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
__snake_case : Dict = {
'gwf-440... | 433 | 0 |
import sys
import turtle
def UpperCAmelCase ( UpperCAmelCase ,UpperCAmelCase )-> Dict:
'''simple docstring'''
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def UpperCAmelCase ( UpperCAmelCase ,UpperCAmelCase ,UpperCAmelCase ,UpperCAmelCase ... | 393 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __A ( A , unittest.TestCase ):
'''simple docstring'''
__lowerCame... | 11 | 0 |
from ....utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class __A ( __UpperCAmelCase ):
"""simple docstring"""
def __init__( self , a__ , a__=None , a__=2048):
"""simple docstring"""... | 716 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , ... | 613 | 0 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class _SCREAMING_SNAKE_CASE ( __UpperCamelCase ):
def __init__( self , lowerCamelCase="" , lowerCamelCase="train" ):
assert os.path.isdir(lowerCamelCase )
snake_case... | 276 |
def SCREAMING_SNAKE_CASE__ ( __lowerCAmelCase ):
if any(not isinstance(__lowerCAmelCase , __lowerCAmelCase ) or x < 0 for x in sequence ):
raise TypeError("Sequence must be list of non-negative integers" )
for _ in range(len(__lowerCAmelCase ) ):
for i, (rod_u... | 276 | 1 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( ):
__snake_case = 0
for i in range(1, 10_01):
total += i**i
return str(UpperCAmelCase__)[-10:]
if __name__ == "__main__":
print(solution())
| 708 | """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 ... | 93 | 0 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from ... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_UpperCAmelCase = logging.getLogger(__n... | 721 |
from datetime import datetime
import requests
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :str ) -> bytes:
__lowerCAmelCase : Optional[Any] = """https://downloadgram.net/wp-json/wppress/video-downloader/video?url="""
__lowerCAmelCase : Any = requests.get(base... | 240 | 0 |
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __UpperCAmelCase ( lowerCamelCase_ : str , lowerCamelCase_ : complex , lowerCamelCase_ : str = "x" , lowerCamelCase_ : float = 10**-10 , lowerCamelCase_ : ... | 105 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fe... | 38 | 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 (... | 557 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanlp/visualbert-... | 557 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {'vocab_file': 'spiec... | 354 |
import math
import flax.linen as nn
import jax.numpy as jnp
def UpperCamelCase__ ( _A: jnp.ndarray , _A: int , _A: float = 1 , _A: float = 1 , _A: float = 1.0e4 , _A: bool = False , _A: float = 1.0 , ):
'''sim... | 479 | 0 |
"""simple docstring"""
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
_SCREAMING_SNAKE_CASE = logging.getLogger(__na... | 239 |
"""simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PI... | 239 | 1 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
__snake_case = HfArgumentParser(InitializationArguments)
__snake_case = parser.parse_args()
# Load codeparrot tokenizer tr... | 451 |
import os
lowerCAmelCase__ : str ={'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def __lowercase ( a__ ) -> int:
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = 0
while index < len(a_... | 148 | 0 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def __a ( A__ : Optional[int] , A__ : List[Any] , A__ : Any ):
SCREAMING_SNAKE_CASE = ... | 703 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A : Union[str, Any] = {'configuration_fnet': ['FNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FNetConfig']}
... | 698 | 0 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class __magic_name__ ( UpperCAmelCase__ ):
'''simple docstring'''
def __init_... | 543 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase : Union[str, Any] = {
"""speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrai... | 543 | 1 |
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCamelCase : Optional[Any] = get_tests_dir("""... | 151 |
def UpperCamelCase_ ( __a ) -> bool:
a__ : Tuple = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def UpperCamelCase_ ( __a = 5_000 ) -> int:
a__ : List[Any] = [(i * (3 * i - 1)) // 2 for i in range(1 , __a )]
... | 151 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
lowerCamelCase_ : List[str] = {
# 1536-bit
5: {
"""prime""": int(
... | 548 |
'''simple docstring'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __UpperCAmelCase ( lowerCAmelCase ,unittest.TestCase ):
'''simple docstring... | 366 | 0 |
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase : Union[str, Any] = 0b1011_0011_1110_1100_1001_0000_01... | 703 |
'''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 timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers im... | 432 | 0 |
"""simple docstring"""
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_... | 695 |
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, ... | 354 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = int(_lowerCamelCase )
# Initialize Result
__SCREAMING_SNAKE_CASE = []
# Traverse through all denominatio... | 704 |
"""simple docstring"""
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-sm... | 553 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
... | 102 | '''simple docstring'''
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_uti... | 396 | 0 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class A_ ( _UpperCAmelCase ):
UpperCAmelCase__ = (IPNDMScheduler,)
UpperCAmelCase__ = (('''num_inference_... | 708 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
... | 468 | 0 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_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_... | 102 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 102 | 1 |
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
lowercase_ : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
lowercase_ : list[int] = [ord(letter) for letter in string.ascii_lowercase]
... | 107 | # tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching between checkouts ... | 107 | 1 |
from __future__ import annotations
def __a ( __UpperCAmelCase : list[int] ) -> List[Any]: # This function is recursive
"""simple docstring"""
lowerCamelCase_ : Dict = len(lowerCamelCase__ )
# If the array contains only one element, we... | 488 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
UpperCAmelCase : Any = logging.getLogger(__name__)
def __lowerCamelCase ( ):
'''simple docstring'''
lowerCamelCase = argparse.ArgumentParser(
... | 457 | 0 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
_lowerCamelCase : int = logging.get_logger(__name__)
class low... | 721 |
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : List[str] = logging.get_logger(__name__)
_lowerCamelCase : List[str] = {
'''facebook/encodec_24khz''': '''https://huggi... | 516 | 0 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( __lowercase ):
"""simple docstring"""
UpperCAmelCase__ : int = (UnCLIPScheduler,)
def __lowercas... | 14 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ = {
"configuration_deberta": ["DEBERTA_PRETRAINE... | 574 | 0 |
"""simple docstring"""
def UpperCamelCase_ ( SCREAMING_SNAKE_CASE_ = 5_0 ):
SCREAMING_SNAKE_CASE = [1] * (length + 1)
for row_length in range(3, length + 1 ):
for block_length in range(3, row_length + 1 ):
for block_start in range(row_len... | 406 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transforme... | 406 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Any = {
'''facebook/timesformer''': '''https://huggingface.co/facebook/timesformer/resolve/mai... | 275 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ : Any = {'''configuration_vit_msn''': ['''VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMSNConfig''']}
try:
if not is_torch... | 572 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import random
class SCREAMING_SNAKE_CASE :
def __init__( self : Tuple , A__ : int | None = None ):
"""simple docstring"""
__lowerCamelCase : int = v... | 703 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
class SCREAMING_SNAKE_CASE ( lowerCAmelCase_ ):
snake_case__ : List[Any] = 'SpeechT5FeatureExtractor'
snake_case__ : Union[str, Any] = 'SpeechT5Tokenizer'
def __init__( self... | 483 | 0 |
'''simple docstring'''
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XLMRobertaTokenizer, XLMRobertaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.ut... | 90 |
'''simple docstring'''
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
UpperCAmelCase_ = Lock()
def SCREAMING_SNAKE_CASE ( a_ : str , a_ : Tuple , a_ : Dic... | 539 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__snake_case ={
"""configuration_mask2former""": [
"""MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Mas... | 513 |
'''simple docstring'''
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__snake_case =logging.get_logger(__nam... | 513 | 1 |
"""simple docstring"""
from __future__ import annotations
class UpperCamelCase :
def __init__( self , snake_case__=None ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE : int = data
_SCREAMING_SNAKE_CASE : Optional[int] = None
... | 572 |
from __future__ import annotations
class lowerCAmelCase :
def __init__( self :Union[str, Any] , _lowercase :List[Any]=None ):
'''simple docstring'''
lowercase__ = data
lowercase__ = None
def __repr__( self :Dict ... | 655 | 0 |
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
lowerCAmelCase__ = 6_378_137.0
lowerCAmelCase__ = 6_356_752.314_245
lowerCAmelCase__ = 6_3_7_8_1_3_7
def __lowerCamelCase ( lowerCamelCase__ , lowerCamelCase__ ... | 81 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''huggingface/informer-tourism-monthly''': (
'''https://huggingface.co/huggingface/i... | 81 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
a : Dict = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"
... | 679 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__ ( lowercase__ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE__ : Dict = (EulerDiscr... | 679 | 1 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_... | 709 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('''repo_id''' , ['''canonical_dataset_name''', '''org-name/dataset-name'''] )
@pytest.mark.parametrize('''path''' , ['''filename.csv''', '''filename with blanks.csv'''] )
@p... | 241 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A = {
"""configuration_deberta""": ["""DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """De... | 77 |
"""simple docstring"""
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, to... | 560 | 0 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class __lowerCAmelCase( lowerCAmelCase__ ):
def __init__( self : List[Any] , SCREA... | 233 |
'''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 torch
if is_torc... | 233 | 1 |
'''simple docstring'''
import os
from typing import Dict, List, Union
import tensorflow as tf
from keras_nlp.tokenizers import BytePairTokenizer
from tensorflow_text import pad_model_inputs
from .tokenization_gpta import GPTaTokenizer
class __snake_case( tf.keras.layers.Layer ):
'''s... | 433 |
UpperCAmelCase_ : dict[tuple[int, int, int], int] = {}
def __SCREAMING_SNAKE_CASE ( a__ : int ,a__ : int ,a__ : int ) -> int:
# if we are absent twice, or late 3 consecutive days,
# no further prize strings are possible
if late == 3 or absent == 2:
retu... | 17 | 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 FlaxModelTesterMi... | 179 | '''simple docstring'''
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common im... | 179 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase_ : List[Any] = {
"configuration_jukebox": [
"JUKEBOX_PRETRAINED_CONFIG_ARCHIVE_MAP",
"JukeboxConfig",
"Jukebox... | 120 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
UpperCAmelCase_ : Optional[Any] = {"vocab_file": "vocab.txt", "tokeniz... | 120 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glu... | 708 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_comm... | 637 | 0 |
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class lowerCamelCase_ :
pass
| 17 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase_ : Optional[Any] = {
'''configuration_wav2vec2''': ['''WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP''', ''... | 17 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
__snake_case = logging.get_logger(__name__)
__s... | 603 | '''simple docstring'''
def A_ ( SCREAMING_SNAKE_CASE_ ) ->int:
lowercase_ = [[0 for _ in range(SCREAMING_SNAKE_CASE_ )] for _ in range(m + 1 )]
for i in range(m + 1 ):
lowercase_ = 1
for n in range(m + 1 ):
for k in range(1 , SCREAMING_SNAKE_CASE_ ):
memo[n][k] += memo... | 603 | 1 |
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