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'''
from typing import Any
import numpy as np
def __lowerCamelCase ( __snake_case : np.ndarray ) -> List[Any]:
"""simple docstring"""
return np.array_equal(snake_case__, matrix.conjugate().T )
def __lowerCamelCase ( ... | 134 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if ... | 64 | 0 |
"""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
__UpperCamelCase : List[str] = logging.get_logger(__name__)
__Upp... | 74 |
"""simple docstring"""
__UpperCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789+/'''
def __SCREAMING_SNAKE_CASE ( A_ ):
# Make sure the supplied data is a bytes-like object
if not isinstance(A_ , A_ ):
lowerCAmelCase__ : ... | 74 | 1 |
'''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 Mode... | 27 |
from __future__ import annotations
import os
from collections.abc import Mapping
a_ = tuple[int, int]
class lowercase__ :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase )-> None:
'''simple docstring'''
lowerCAmelCase__ = ... | 340 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
def... | 225 |
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import floats_tensor, ids_tensor,... | 225 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import FlaxMod... | 87 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils i... | 57 | 0 |
'''simple docstring'''
from functools import lru_cache
def UpperCAmelCase__ ( UpperCAmelCase__ ) -> set:
A_ = 2
A_ = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
fac... | 101 |
'''simple docstring'''
import sys
__lowerCamelCase = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'... | 101 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class a__ :
def __init__( self : List[Any] , a : Any ):
"""simple docstring"""
__lowerCamelCase = data
__lowerCamelCase = N... | 67 |
'''simple docstring'''
def _UpperCAmelCase ( _lowerCamelCase : list[int] , _lowerCamelCase : str ) -> list[int]:
_lowerCAmelCase : List[Any] = int(_lowerCamelCase )
# Initialize Result
_lowerCAmelCase : Any = []
# Traverse through all denomi... | 309 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import _LazyModule
__lowerCAmelCase : Union[str, Any] ={"tokenization_tapex": ["TapexTokenizer"]}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
__lowerCAmelCase : Dic... | 123 |
'''simple docstring'''
def UpperCamelCase ( _lowerCamelCase : int ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
A__ = F"Input value of [number={number}] must be an integer"
raise TypeError(_lowerCamelCase )
if number < 1:
A__ = F"I... | 123 | 1 |
from __future__ import annotations
import pandas as pd
def A_ ( A__ , A__ , A__ ) -> list[int]:
a__ : Optional[Any] = [0] * no_of_processes
a__ : Tuple = [0] * no_of_processes
# Copy the burst time into remaining_time[]
for i in range(A__ ):
... | 99 |
'''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
UpperCamelCase_ = logging.get_logger(__name__)
class a_ :
def __init__( self ... | 309 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase_ = {
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Per... | 365 |
class _A : # Public class to implement a graph
def __init__( self : List[Any] , _A : int , _A : int , _A : list[list[bool]] ) -> None:
"""simple docstring"""
lowercase : Tuple = row... | 116 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.impo... | 187 |
def lowerCamelCase__ ( ):
'''simple docstring'''
snake_case_ = []
snake_case_ = 1
while len(_A ) < 1E6:
constant.append(str(_A ) )
i += 1
snake_case_ = "".join(_A )
return (
int(constant[0] ... | 187 | 1 |
"""simple docstring"""
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__ : Dict = logging.get_logger(__name__)
__magic_name__ : int = {
"snap-research/efficientformer-l1-300": (
"https://huggingface.co/snap-resea... | 351 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTes... | 255 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : Dict = logging.get_logger(__name__)
A : int = {
"google/realm-cc-news-pretrained-embedder": (
"https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/config.json"
)... | 118 | import math
from datetime import datetime, timedelta
def a__ ( __UpperCamelCase ):
SCREAMING_SNAKE_CASE_ = year % 1_9
SCREAMING_SNAKE_CASE_ = year % 4
SCREAMING_SNAKE_CASE_ = year % 7
SCREAMING_SNAKE_CASE_ = math.floor(year / 1_0_0 )
SCRE... | 118 | 1 |
"""simple docstring"""
from torch import nn
class __UpperCAmelCase( nn.Module ):
"""simple docstring"""
def __init__( self , snake_case__ , snake_case__ ):
'''simple docstring'''
super().__init__()
... | 150 |
"""simple docstring"""
from __future__ import annotations
def lowercase__(A ) ->int:
"""simple docstring"""
for i in range(1 , len(matrix[0] ) ):
matrix[0][i] += matrix[0][i - 1]
# preprocessing the first ... | 150 | 1 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import torch
... | 343 | 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
_SCREAMING... | 343 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import ... | 174 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase_ = {'''configuration_... | 174 | 1 |
'''simple docstring'''
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require... | 2 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase : List[Any] = logging.get_logger(__name__)
lowerCamelCase : str = {
"huggingface/time-series-transformer-tourism-monthly":... | 47 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''facebook/s2t-wav2vec2-large-en-de''': (
'''https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json'''
),
... | 64 | """simple docstring"""
import requests
__A = '''YOUR API KEY'''
def lowercase_ ( _lowerCamelCase: str , _lowerCamelCase: str = giphy_api_key ) -> list:
'''simple docstring'''
__lowerCamelCase : Dict = "+".join(query.split() )
__lowerCamelCase ... | 64 | 1 |
'''simple docstring'''
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class UpperCAmelCase_ ( __lowercase ):
def __lt__( self : Optional[int] , UpperCAmelCa... | 4 |
'''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/f... | 4 | 1 |
"""simple docstring"""
from typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class __lowerCamelCase ( a__ ):
'''simple docstring'''
... | 365 |
"""simple docstring"""
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
... | 153 | 0 |
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowerCAmelCase : Optional[Any] = """src/diffusers"""
# Matches is_xxx_available()
lowerCAmelCase : str = re.com... | 13 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iter... | 45 | 0 |
"""simple docstring"""
def __lowerCamelCase ( __UpperCamelCase ) -> int:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function" )
lowerCAmelCase_ : Tuple =... | 357 |
"""simple docstring"""
class __lowerCamelCase ( A__ ):
'''simple docstring'''
pass
class __lowerCamelCase ( A__ ):
'''simple docstring'''
pass
class __lowerCamelCase :
'''simple docstring'''
def __init__( self : ... | 161 | 0 |
"""simple docstring"""
def __lowerCAmelCase ( lowercase : int = 100 ) -> Optional[Any]:
"""simple docstring"""
snake_case : Tuple = (n * (n + 1) // 2) ** 2
snake_case : Tuple = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum... | 203 |
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_common import TokenizerTesterMixin
UpperCamelCase... | 92 | 0 |
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class UpperCamelCase_ :
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( self : Tuple , UpperCAmelCase__ : Optional[Any]) ->List[... | 352 |
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def SCREAMING_SNAKE_CASE ( lowercase_ = "" ) -> dict[str, float]:
"""simple docstring"""
A__ = url or '''https://www.imdb.com/chart/top/?ref_=nv_mv_250'''
A__ = ... | 231 | 0 |
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import Confi... | 51 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constan... | 311 | 0 |
"""simple docstring"""
A : Union[str, Any] = 8.3_144_598
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Exceptio... | 259 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
__lowerCAmelCase = [False] * len(_UpperCamelCase )
__lowerCAmelCase = []
queue.append(_UpperCamelCase )
__... | 259 | 1 |
'''simple docstring'''
lowerCamelCase : Any = "\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
low... | 47 |
'''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
#
# Unl... | 47 | 1 |
import argparse
from collections import defaultdict
import yaml
_UpperCAmelCase = """docs/source/en/_toctree.yml"""
def UpperCamelCase ( __lowercase : List[str] ):
'''simple docstring'''
A_ : Optional[Any] = defaultdict(__lowercase )... | 362 | from __future__ import annotations
import requests
_UpperCAmelCase = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories created_utc ... | 192 | 0 |
"""simple docstring"""
lowercase__ = [
'DownloadConfig',
'DownloadManager',
'DownloadMode',
'StreamingDownloadManager',
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingDownloadManager
... | 290 | """simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
lowercase__ = logging.getLogger(__name__)
class __snake_case :
def __init__( self) -> ... | 290 | 1 |
def lowerCAmelCase_ ( __a ) -> Optional[int]:
"""simple docstring"""
if collection == []:
return []
# get some information about the collection
lowerCamelCase__: int =len(__a )
lowerCamelCase__: str =max(__a )
lowerCamelCase__: Optional[Any] ... | 357 |
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
__A = "src/transformers"
# This is to make sure the transformers module... | 273 | 0 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeli... | 192 |
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
a_ : str = logging.get_logger(__name__)
def low... | 137 | 0 |
"""simple docstring"""
import warnings
from typing import List
from unittest.mock import Mock
import torch
from torch.utils.data import DataLoader, IterableDataset, TensorDataset
from accelerate.accelerator import Accelerator
from accelerate.utils.dataclasses import DistributedType
cla... | 368 | """simple docstring"""
def UpperCAmelCase__ ( lowerCAmelCase__ :str ) -> bool:
'''simple docstring'''
return credit_card_number.startswith(("""34""", """35""", """37""", """4""", """5""", """6""") )
def UpperCAmelCase__ ( lowerCAmelCase__ :str ) -> ... | 32 | 0 |
"""simple docstring"""
def A ( snake_case :list[int] ) -> int:
if not numbers:
return 0
if not isinstance(snake_case , (list, tuple) ) or not all(
isinstance(snake_case , snake_case ) for number in numbers ):
raise ValueError('numbers must be an iterable of integ... | 316 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, ... | 316 | 1 |
def lowercase_ ( _lowerCamelCase : Union[str, Any]):
lowercase__ : List[Any] = []
lowercase__ : Any = set({"(", "[", "{"})
lowercase__ : Any = set({")", "]", "}"})
lowercase__ : Any = {"{": "}", "[": "]", "(": ")"}
fo... | 333 | def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
while a != 0:
lowercase__ , lowercase__ : Dict = b % a, a
return b
def lowercase_ ( _lowerCamelCase : int , _lowerCamelCase : int):
if gcd(_lowerC... | 333 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase_ = loggi... | 243 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
UpperCam... | 243 | 1 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_tests_d... | 281 |
def __lowerCamelCase ( UpperCAmelCase_ : str ):
"""simple docstring"""
if n_term == "":
return []
a :list = []
for temp in range(int(UpperCAmelCase_ ) ):
series.append(F'''1/{temp + 1}''' if series else '''1''' ... | 281 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : Optional[Any] =logging.get_logger(__name__)
_UpperCAmelCase : int ={
'microsoft/unispeech-sat-base-100h-libri-ft': (
'https://huggingface.co/microsoft/unispe... | 262 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForC... | 167 | 0 |
'''simple docstring'''
lowerCAmelCase : int = 2_56
# Modulus to hash a string
lowerCAmelCase : Tuple = 1_00_00_03
def lowercase (_A , _A ):
"""simple docstring"""
_lowerCAmelCase : int... | 371 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCAmelCase : List[str] = [
"""kernels/rwkv/wkv_cuda.cu""",
"""kernels/rwkv/wkv_op.cpp""",
"""kernels/deformable_detr/ms_deform_att... | 25 | 0 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransformer, ... | 18 |
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():
import tor... | 38 | 0 |
'''simple docstring'''
def lowercase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
"""simple docstring"""
if not isinstance(lowercase__ , lowercase__ ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstanc... | 355 |
'''simple docstring'''
class _A :
def __init__( self , __UpperCAmelCase , __UpperCAmelCase=None , __UpperCAmelCase=None ) -> Optional[int]:
'''simple docstring'''
__UpperCAmelCase : int = data
__UpperCAmelCase : int = prev... | 16 | 0 |
'''simple docstring'''
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteSche... | 53 |
'''simple docstring'''
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import pa... | 53 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 362 |
import sys
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] ):
'''simple docstring'''
lowercase_ = len(__lowerCamelCase )
lowercase_ = [[0 for x in range(__lowerCamelCase )] for x in range(__lowerCamelCase )]
lowercase_ = [[0 ... | 297 | 0 |
from ...configuration_utils import PretrainedConfig
class __lowerCamelCase ( snake_case__):
"""simple docstring"""
UpperCamelCase__ = "bert-generation"
def __init__( self , UpperCAmelCase=5_0358 , UpperCAmelCase=1024 ,... | 39 |
import heapq as hq
import math
from collections.abc import Iterator
class lowerCamelCase__ :
def __init__(self , UpperCAmelCase ) -> Any:
_lowercase =str(id_ )
_lowercase =None
_lowercase =None
_lowercase ... | 5 | 0 |
"""simple docstring"""
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def UpperCamelCase ( __lowercase : str ):
'''simple docstring'''
return "".join(sorted(__lowercase ) )
def UpperCamelCase ... | 359 | from math import isqrt
def UpperCamelCase ( __lowercase : int ):
'''simple docstring'''
return all(number % divisor != 0 for divisor in range(2 ,isqrt(__lowercase ) + 1 ) )
def UpperCamelCase ( __lowercase : int = 10**6 ):
'''si... | 192 | 0 |
import os
from math import logaa
def SCREAMING_SNAKE_CASE ( lowercase_ = "base_exp.txt" ) -> Any:
"""simple docstring"""
A__ = 0
A__ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(lowercase_ ) , lowercase_ )... | 14 |
'''simple docstring'''
from collections import UserDict
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_availab... | 37 | 0 |
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_common import ConfigTester
from ...te... | 355 |
from __future__ import annotations
def _A ( __magic_name__ , __magic_name__ ):
lowercase__ = []
create_all_state(1 , __magic_name__ , __magic_name__ , [] , __magic_name__ )
return result
def _A ( __magic_name__ , __magic_name__ , __magic_name__ , __magic_name__ , __... | 201 | 0 |
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDataS... | 29 |
import os
# Precomputes a list of the 100 first triangular numbers
__UpperCAmelCase = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def lowercase__ ( ):
'''simple docstring'''
UpperCAmelCase_ : Any = os.path.dirname(os.pa... | 29 | 1 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
snake_case__ : int = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translatio... | 371 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case__ : List[str] = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Trajecto... | 250 | 0 |
from string import ascii_lowercase, ascii_uppercase
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> str:
'''simple docstring'''
if not sentence:
return ""
A__ = dict(zip(__lowerCAmelCase , __lowerCAmelCase ) )
return lower_to_upper.g... | 68 |
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ : Optional[int] = logging.getLogger(__na... | 270 | 0 |
import os
import tempfile
import unittest
from transformers.models.marian.convert_marian_tatoeba_to_pytorch import DEFAULT_REPO, TatoebaConverter
from transformers.testing_utils import slow
from transformers.utils import cached_property
@unittest.skipUnless(os.path.exists(lowerCamelCase_... | 358 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
UpperCAmelCase_ = {
'configuration_audio_spectrogram_transformer': [
'AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
... | 247 | 0 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_av... | 102 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case : Optional[Any] = {'con... | 134 | 0 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def UpperCAmelCase ( a_ , a_ , a_ ) -> Dict:
"""simple docstring"""
A_ : List[str] = 0
if start < end:
... | 164 |
'''simple docstring'''
def UpperCAmelCase ( a_ , a_ ) -> int:
"""simple docstring"""
A_ : int = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
A_ : Tuple = n - k
# Calculate... | 164 | 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,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_cha... | 60 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .to... | 60 | 1 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
imp... | 247 |
def lowerCAmelCase_ ( __UpperCAmelCase: int ) -> list[int]:
if length <= 0 or not isinstance(__UpperCAmelCase , __UpperCAmelCase ):
raise ValueError('''Length must be a positive integer.''' )
return [n * (2 * n - 1) for n in range(__UpperCAmelCase )]
... | 247 | 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 AutoTokenizer,... | 219 |
import requests
from bsa import BeautifulSoup
def A ( _UpperCAmelCase : str , _UpperCAmelCase : dict ) -> str:
'''simple docstring'''
_UpperCAmelCase = BeautifulSoup(requests.get(_UpperCAmelCase , params=_UpperCAmelCase ).content , 'h... | 339 | 0 |
def __lowercase ( __lowerCAmelCase : int ):
if num <= 0:
raise ValueError('Input must be a positive integer' )
a__ = [True] * (num + 1)
a__ = 2
while p * p <= num:
if primes[p]:
for i i... | 109 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from unilm.wavlm.WavLM i... | 109 | 1 |
'''simple docstring'''
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
A =Tru... | 34 |
'''simple docstring'''
def __lowerCAmelCase ( snake_case__ ):
return "".join([hex(snake_case__ )[2:].zfill(2 ).upper() for byte in list(snake_case__ )] )
def __lowerCAmelCase ( snake_case__ ):
# Check data validity, following RFC3548
... | 298 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def UpperCAmelCase ( UpperCAmelCase = None ) -> int:
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
snake_case_ = nums[0]
for i in range(1 , len(UpperCAmelCase ) ):
... | 312 | """simple docstring"""
from math import pi
def UpperCAmelCase ( UpperCAmelCase , UpperCAmelCase ) -> float:
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 312 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
StableDiffusionX... | 215 |
'''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.ut... | 215 | 1 |
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowercase__ ='''▁'''
lowercase__ ... | 369 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 0 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowerCamelCase_ ( UpperCamelCase__ : Union[str, Any] ... | 90 |
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.rob... | 36 | 0 |
'''simple docstring'''
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..st... | 368 |
'''simple docstring'''
# Imports
import numpy as np
class a__ :
"""simple docstring"""
def __init__(self , __lowercase=None , __lowercase=None , __lowercase=None , __lowercase=None , __lowercase=None ):
self.set_matricies... | 9 | 0 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
SCREAMING_SNAKE_CASE_: Any =Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_repo_path))
import dataclasses # n... | 1 |
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__) # pylint: disable=invalid-name
class _lowerCamelCase ( a ):
... | 326 | 0 |
from __future__ import annotations
def _a ( _lowercase : list , _lowercase : int ):
'''simple docstring'''
if len(_lowercase ) <= 1 or n <= 1:
return
insert_next(_lowercase , n - 1 )
rec_insertion_sort(_lowercas... | 368 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common i... | 240 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availab... | 256 | """simple docstring"""
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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {"""vocab_fil... | 256 | 1 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowerCAmelCase: List[str] = (7_2_0, 1_2_8_0) # Height, Width
lowerCAmelCase: str = (0.4, 0.6) # if height or width lower than this scale, drop... | 360 |
'''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__( lowerCamelCase__ , unittest.TestCase ):
lowercase__ = CTRLTokeni... | 96 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require... | 85 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_SCREAMING_SNAKE_CASE : Any = F... | 85 | 1 |
"""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
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelC... | 357 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...util... | 302 | 0 |
print((lambda quine: quine % quine)("""print((lambda quine: quine %% quine)(%r))"""))
| 176 |
from collections.abc import Generator
from math import sin
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : bytes ) -> bytes:
"""simple docstring"""
if len(__magic_name__ ) != 32:
raise ValueError("""Input must be of length 32""" )
UpperCamelCase :int =... | 38 | 0 |
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogram_diffusion import S... | 367 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available()... | 65 | 0 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callabl... | 168 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
a_ = logging.getLogger(__name__)
class __snake_case ( SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
_lowerCamelCase = """masked_bert"""
def __init__( self , ... | 179 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_auto import TF_... | 370 |
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def __lowerCamelCase ( lowerCamelCase__ , lowerCamelCase__=1 ):
"""simple docstring"""
if n_shave_prefix_segments >= 0:
return ".".join(path.split("." )[n_sha... | 121 | 0 |
"""simple docstring"""
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common i... | 191 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {
"facebo... | 191 | 1 |
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 <... | 63 | import os
def lowerCAmelCase__ ( ) ->Any:
'''simple docstring'''
with open(os.path.dirname(a__ ) + "/grid.txt" ) as f:
_UpperCamelCase = [] # noqa: E741
for _ in range(20 ):
l.append([int(a__ ) for x in f.readline().split()] )
_UpperCamelCase ... | 63 | 1 |
def lowerCAmelCase_ ( __lowerCamelCase ):
__snake_case : Dict = [1]
__snake_case : str = 0, 0, 0
__snake_case : List[str] = ugly_nums[ia] * 2
__snake_case : Optional[int] = ugly_nums[ia] * 3
__snake_case : Optional[int... | 123 |
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configurat... | 232 | 0 |
def UpperCAmelCase ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
A , A : Optional[Any] = len(_lowerCamelCase ), len(grid[0] )
if (
min(_lowerCamelCase , _lowerCamelCase ) < 0
or row == row_lengt... | 256 |
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 import s... | 256 | 1 |
def a ( snake_case__: int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('''Limit for the Catalan sequence must be ≥ 0''' )
lowercase_ = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
lowercase_ = 1
if ... | 30 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def __UpperCamelCase ( _A , _A ):
lowerCAmelCase_ = args.log_outputs
lowerCAmelCase_ = ... | 278 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
'junnyu/roformer_chinese_small': 'https://h... | 205 |
"""simple docstring"""
import numpy as np
def UpperCAmelCase ( a_, a_, a_ = 1E-12, a_ = 100, ):
'''simple docstring'''
assert np.shape(a_ )[0] == np.shape(a_ )[1]
# Ensure proper dimensionality.
assert np.shape(a_ )[0] == np.shape(a_ )[0]
# E... | 205 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax.numpy as jnp
from jax import random
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .scheduling_utils_flax import FlaxSchedulerMixin
@flax.struct.dataclass
class ... | 68 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
__snake_case = '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def _A ( _lowercase = "mumbai" ) -> Generator[tuple[str, s... | 310 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : Union[str, Any] = abs(UpperCamelCase__ )
_a : Tuple = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def lowerCAmelCase__... | 324 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'configuration_vision_encoder_decoder': ['Vision... | 324 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
A : Dict = {
'configuration_trocr': ['TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TrOCRConfig'],
'processing_trocr... | 6 |
'''simple docstring'''
def snake_case ( UpperCAmelCase )-> list[int]:
"""simple docstring"""
if length <= 0 or not isinstance(UpperCAmelCase , UpperCAmelCase ):
raise ValueError('Length must be a positive integer.' )
return [n * (2... | 161 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
... | 341 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def _lowerCamelCase(__UpperCamelCase , __UpperCamelCase=1 ) -> Tuple:
if n_shave_prefix_segments >= 0:
return ".".join(path.split(""".""" )[n_shave... | 341 | 1 |
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowerCamelCase =logging.get_logger(__name__)
class A__ ( __SCREAMING_SNAKE_CASE):
def __init__( self , *__magic_name__ , **__magic_name__ ):
warnings.warn(
... | 287 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase =logging.get_logger(__name__)
_lowerCamelCase ={
"""BridgeTower/bridgetower-base""": """https://huggingface.co/BridgeTower/bridgetower-base/blob/main/con... | 287 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class __UpperCAmelCase ( A__ ):
... | 360 |
'''simple docstring'''
from __future__ import annotations
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import is_tf_available, is_vision_available
from ...test_modeling_tf_common import f... | 337 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required ... | 178 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowercase = "src/transformers"
# Matches is_xxx_available()
lowercase = re.compile(r"is\_([a-z_]*)_available()")
# Catches a one-line _import_struct = {xxx}
lowercase = re.compile(r"^_imp... | 178 | 1 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
a_ : str = logging.get_logger(_... | 352 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def a_ ( ) -> Tuple:
"""simple docstring"""
lowerCamelCase_ ={
'''repo_name''': ['''t... | 6 | 0 |
"""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
_A : List[str] = logging.get_l... | 202 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMSchedu... | 202 | 1 |
def lowerCAmelCase_ ( snake_case_ ):
if not isinstance(snake_case_,snake_case_ ):
_A : List[str] = f'''Input value of [number={number}] must be an integer'''
raise TypeError(snake_case_ )
if number < 1:
_A : Dic... | 343 |
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class lowercase ( unittest.TestCase ):
def a__ ( self ) -> List[str]:
debug_launcher(test_script.main )
... | 343 | 1 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TFCamembertModel
... | 26 |
'''simple docstring'''
def _A ( snake_case , snake_case ) -> float:
return price * (1 + tax_rate)
if __name__ == "__main__":
print(F'''{price_plus_tax(100, 0.2_5) = }''')
print(F'''{price_plus_tax(1_2_5.5_0, 0.0_5) = }''')
| 250 | 0 |
"""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_... | 354 |
"""simple docstring"""
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_a ... | 100 | 0 |
'''simple docstring'''
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionImg2ImgPipeline` instead.'''
)
| 53 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 20 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.util... | 368 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'''junnyu/roformer_chinese_small''': '''https://... | 59 | 0 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
_lowerCAmelCase : int = logging.getLogger()
@unittest.skip('Temporarily d... | 218 |
"""simple docstring"""
def _snake_case ( lowercase__ ):
if not isinstance(lowercase__ , lowercase__ ):
raise ValueError('Input series is not valid, valid series - [2, 4, 6]' )
if len(lowercase__ ) == 0:
raise ValueError('Input list must be a non ... | 96 | 0 |
"""simple docstring"""
from math import factorial, radians
def a__ ( lowerCAmelCase , lowerCAmelCase = 18 , lowerCAmelCase = 10 ) -> float:
UpperCAmelCase__ : List[Any] = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# Converting from degrees to radians
... | 166 |
"""simple docstring"""
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_torch_available... | 166 | 1 |
"""simple docstring"""
from collections.abc import Sequence
def _lowerCAmelCase ( lowercase_ , lowercase_ = False ):
if not arr:
return 0
UpperCAmelCase = 0 if allow_empty_subarrays else float('-inf' )
UpperCAmelCase = 0.0
... | 78 |
import pytest
__UpperCAmelCase : Optional[Any] = "__dummy_dataset1__"
__UpperCAmelCase : List[str] = "\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"\nURLS = {\"train\":... | 111 | 0 |
'''simple docstring'''
class _lowerCAmelCase :
'''simple docstring'''
def __init__(self , UpperCAmelCase = "" , UpperCAmelCase = False ) -> None:
_snake_case = {}
# A node will be a leaf if the tree contains its word
_snake_... | 367 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__lowerCAmelCase = {
'configuration_resnet': ['RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ResNetConfig... | 270 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A__ ( metaclass=UpperCamelCase ):
"""simple docstring"""
UpperCamelCase_ : List[Any] = ['''flax''', '''transformers''']
def __init__( self : Dict , *low... | 145 |
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
# TODO Update this
UpperCAmelCase__ = {
'''facebook/esm-1b''': '''https://huggingface.co/fac... | 5 | 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 _SCREAMING_SNAKE_CASE ( SC... | 364 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@slow
class _lowerCa... | 65 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A : Union[str, Any] = logging.get_logger(__name__)
_A : List[str] = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/... | 202 | """simple docstring"""
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization import fr... | 290 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def UpperCAmelCase ( lowerCamelCase_ :Callable[[int | float], int | float] , lowerCamelCase_ :int | float , lowerCamelCase_ :int | float , lowerCamelCase_ :int = 1_00 , ):
... | 370 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
i... | 8 | 0 |
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