code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, s... | 433 |
'''simple docstring'''
import requests
_SCREAMING_SNAKE_CASE = '''YOUR API KEY'''
def _lowerCAmelCase ( lowerCamelCase_ : str , lowerCamelCase_ : str = giphy_api_key ):
__lowercase = '''+'''.join(query.split() )
__lowercase ... | 502 | 0 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTokenizerFast,
C... | 531 |
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def __lowerCAmelCase (SCREAMING_SNAKE_CASE=... | 531 | 1 |
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def lowercase_ (A : List[str] , A : List[Any] , A : Tuple ):
# Initialise PyT... | 478 |
from __future__ import annotations
def lowercase_ (A : list , A : int | None = None , A : int | None = None ):
if start is None:
snake_case__ : Any = 0
if end is None:
snake_case__ : List[str] =... | 478 | 1 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowercase)
class __SCREAMING_SNAKE_CASE ( lowercase):
__SCREAMING_SNAKE_CASE : str = field(... | 719 |
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 ...utils import add_start_docstrings, add_start... | 129 | 0 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging import get_logger... | 36 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase ={
"""configuration_rembert""": ["""REMBER... | 337 | 0 |
def snake_case__ ( lowerCAmelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE =set()
# To detect a back edge, keep track of vertices currently in the recursion stack
SCREAMING_SNAKE_CASE =set()
return any(
node not in visited and depth_first... | 711 |
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.utils.data import DataLoa... | 252 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
__SCREAMING_SNAKE_CASE = {
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-e... | 553 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester... | 208 | 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
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ ... | 549 |
"""simple docstring"""
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_sin... | 549 | 1 |
"""simple docstring"""
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__SCREAMING_SNAKE_CASE = (
'4S 3H 2C 7S 5H',
'9D 8H 2C 6S 7H',
'2D 6D 9D TH 7D',
'TC 8C 2S JH 6C',
'JH 8S TH AH QH',
'TS KS 5S 9S AC',
... | 553 |
"""simple docstring"""
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def UpperCAmelCase ( a__ , a__ , a__ ):
'... | 553 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCAmelCase ):
'''simple docstring'''
for i in range(len(lowerCAmelCase ) - 1 , 0 , -1 ):
UpperCAmelCase = False
for j in range(lowerCAmelCase , 0 , -1 ):
... | 378 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Any = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'''google/canine-s''': '''https://huggingface.co/google/canine-s/resolve/main/... | 378 | 1 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
lowerCamelCase__ : Any = get_logger(__name__)
class _snake_case ( enum.Enum ):
__lowerCAmelCase : Optional[Any] = 'all_checks'
__low... | 12 | import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowerCamelCase ( UpperCamelCase : List[str] ) -> ... | 544 | 0 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
__A : List[Any] = get_tests_dir("""fixtu... | 709 |
'''simple docstring'''
from __future__ import annotations
class lowercase :
'''simple docstring'''
def __init__( self : Optional[int] , __lowerCamelCase : int ) -> None:
'''simple docstring'''
lowerCamelCase__ = order
... | 187 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common imp... | 56 | """simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__A = logging.get_logger(__name__)
__A = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config.j... | 646 | 0 |
import itertools
import string
from collections.abc import Generator, Iterable
def snake_case ( lowerCamelCase , lowerCamelCase ):
'''simple docstring'''
__lowercase = iter(lowerCamelCase )
while True:
__lowercase = ... | 705 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_commo... | 53 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE : str = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
... | 156 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __lowerCamelCase ( __lowercase , unittest.TestCase ):
__UpperCamelCase ... | 156 | 1 |
from typing import Any
def A__ ( lowercase: list ) -> list[Any]:
if not input_list:
return []
A : Optional[int] =[input_list.count(lowercase ) for value in input_list]
A : Tuple =max(lowercase ) # Gets the maximum co... | 707 | 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.utils import cached_property
from ...test... | 661 | 0 |
"""simple docstring"""
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __a ( A ) -> ... | 337 |
"""simple docstring"""
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(UpperCAmelCase... | 337 | 1 |
"""simple docstring"""
import torch
from transformers import CamembertForMaskedLM, CamembertTokenizer
def _A ( _a : List[Any] , _a : List[Any] , _a : str , _a : Tuple=5 ):
"""simple docstring"""
assert masked_input.count("""<m... | 255 |
"""simple docstring"""
from itertools import count
def _A ( _a : int = 5_0 ):
"""simple docstring"""
A = [1] * min_block_length
for n in count(_a ):
fill_count_functions.append(1 )
for block_leng... | 255 | 1 |
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord import VideoReader
... | 302 |
'''simple docstring'''
import argparse
import os
import re
__lowerCAmelCase = "src/diffusers"
# Pattern that looks at the indentation in a line.
__lowerCAmelCase = re.compile(R"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
__lowerCAmelCase = ... | 536 | 0 |
def UpperCAmelCase ( _lowerCamelCase : int = 1_000 ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Dict = -1
SCREAMING_SNAKE_CASE__ : str = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**... | 710 |
from __future__ import annotations
def UpperCAmelCase ( _lowerCamelCase : list[int] , _lowerCamelCase : int ):
'''simple docstring'''
if len(_lowerCamelCase ) < k or k < 0:
raise ValueError("Invalid Input" )
SCREAMING_SNAKE_CA... | 26 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a__ : Dict = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'MobileNetV... | 51 | """simple docstring"""
import unittest
from typing import Dict, List, Optional, Union
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 ImageProcessingSavingTe... | 646 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( _UpperCamelCase ):
"""simple docstring"""
_lowercase: int = [0] * len(_UpperCamelCase )
_lowercase: int = []
_lowercase: Union[str, Any] = []
_lowercase: Union[str, Any] = 0
for values in... | 272 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingIndex
from .utils import req... | 272 | 1 |
from sklearn.metrics import recall_score
import datasets
lowercase_ : int = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and FN is the false negatives... | 64 | '''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
... | 523 | 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 by a... | 657 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
snake_case : Optional[Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if ... | 657 | 1 |
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTeacher,... | 387 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,... | 387 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
"transfo-xl-wt103": "https://huggingface.co/transfo-xl-wt103/resolve/main/config.json",
}
class __snake_case... | 707 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
A = {
'<': operator.lt,
'<=': operator.le,
'==': operator.eq,
'!=': operator.ne,
'>=': operator.ge,
'>': o... | 449 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_pro... | 7 |
import qiskit
def UpperCamelCase ( __lowerCamelCase : int , __lowerCamelCase : int ):
snake_case : int = qiskit.Aer.get_backend("aer_simulator" )
# Create a Quantum Circuit acting on the q register
snake_case : Dict = ... | 204 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_: Dict = {
'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}
try:
if not is_torch_available():
ra... | 710 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_: int = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryTransformerConfig',
... | 127 | 0 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__( self , lowerCamelCase ):
_snake_case = data
_snake_case = ... | 672 |
'''simple docstring'''
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import datasets
import datasets.config
from .utils import require_beam
class __SCREAMING_SNAKE_CASE ( datasets.BeamBasedBuilder ):
'''simple d... | 672 | 1 |
from math import pi
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 701 |
"""simple docstring"""
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if "model" in orig_key:
UpperCAmelCase__ : List[str] = orig_key.replace("""model."... | 194 | 0 |
from collections.abc import Callable
import numpy as np
def SCREAMING_SNAKE_CASE ( snake_case_ : Callable , snake_case_ : float , snake_case_ : float , snake_case_ : float , snake_case_ : float ):
snake_case__ : List[Any] = int(np.ceil((x_end - xa... | 297 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_albert import... | 297 | 1 |
"""simple docstring"""
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_sub... | 715 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCAmelCase__ : int, UpperCAmelCase__ : int ) ->str:
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
A__ : str = str(bin(UpperCAmelCase__ ... | 498 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
def __UpperCamelCase ( ):
'''simple docstring'''
__lowercase ={}
__lowercase =2
while True:
__lowercase =factor_map.pop(lowercase__, lower... | 119 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 1 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
A = 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_copies # noqa: E402
# This is the re... | 709 |
"""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 ... | 109 | 0 |
from string import ascii_lowercase, ascii_uppercase
def __a ( A__ : str ):
if not sentence:
return ""
SCREAMING_SNAKE_CASE = dict(zip(A__ , A__ ) )
return lower_to_upper.get(sentence[0] , sentence[0] ) + sentence[1:]
if __... | 16 | import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_bird import B... | 167 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : List[str] = logging.get_logger(__name__)
snake_case__ : Dict = {
'EleutherAI/gpt-neox-20b': 'https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json',
# See all GPTNeoX m... | 592 |
def lowerCamelCase__ ( _lowerCamelCase = 50 ) ->int:
_UpperCAmelCase =[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_length - block_length ):
ways_number[row_length] += ways_numb... | 592 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class a__ ( __snake_case ):
def __init__( self , UpperCAmelCase , UpperCAmelCase... | 559 | def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase = 0 ):
__a = length or len(__lowerCamelCase )
__a = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
__a , __a = list_data[i + 1], list_data[i]
... | 559 | 1 |
"""simple docstring"""
import numpy as np
def lowerCamelCase__ ( _lowerCamelCase : np.array ) -> List[Any]:
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 721 |
"""simple docstring"""
# Note: if you intend to run this script make sure you look under scripts/fsmt/
# to locate the appropriate script to do the work correctly. There is a set of scripts to:
# - download and prepare data and run the conversion script
# - perform eval to get the best hpara... | 137 | 0 |
import numpy as np
from PIL import Image
def _UpperCamelCase ( lowercase__ , lowercase__ , lowercase__ ):
__SCREAMING_SNAKE_CASE : List[Any] = np.array(SCREAMING_SNAKE_CASE_ )
if arr.shape[0] != arr.shape[1]:
raise ValueError('''The input array is not a... | 696 |
"""simple docstring"""
from collections.abc import Callable
def lowercase (SCREAMING_SNAKE_CASE_ : Callable[[float], float] , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float ) -> float:
SCREAMING_SNAKE_CASE = ... | 247 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffu... | 720 | '''simple docstring'''
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import ... | 438 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {"""configuration_speech_encoder_decoder""": ["""SpeechEncoderDecoderConfig"""]}
try:
if not is_torch_available():
raise Optiona... | 507 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def __lowercase (_SCREAMING_SNAKE_CASE :int , _SCREAMING_SNAKE_CASE :int , _SCREAMING_SNAKE_CASE :float = 1 / sqrt(2 ) ):
SCREAMING_SNAKE_CASE : List[str] ... | 507 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, ... | 705 | """simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _lowerCamelCase (__lowerCamelCase ):
_snake_case = ""
_snake_case = (
None # protocol passed in p... | 283 | 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_torc... | 379 |
'''simple docstring'''
import random
def __A ( lowerCamelCase_ ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : str = num - 1
SCREAMING_SNAKE_CASE : Union[str, Any] = 0
while s % 2 == 0:
SCREAMING_SNAKE_CASE : List[str] = s // 2
t += 1
for _ in range(5 ):
... | 379 | 1 |
'''simple docstring'''
def UpperCAmelCase__ ( UpperCAmelCase__, UpperCAmelCase__ ) -> str:
A_ = [[] for _ in range(UpperCAmelCase__ )]
A_ = key - 1
if key <= 0:
raise ValueError("""Height of grid can't be 0 or negative""" ... | 667 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_ava... | 667 | 1 |
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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLI... | 253 |
'''simple docstring'''
# Copyright 2022 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
#
# U... | 591 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {"configuration_deit": ["DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DeiTConfig", "DeiTOnnxConfig"]}
try:
if not i... | 720 |
from __future__ import annotations
from math import ceil, floor, sqrt
def _UpperCAmelCase ( UpperCamelCase: int = 2_0_0_0_0_0_0 ):
"""simple docstring"""
__lowerCAmelCase = [0]
__lowerCAmelCase = 42
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 376 | 0 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def lowerCAmelCase_ ( __a ) -> Any:
"""simple docstring"""
for param in module.parameters():
lowerCamelCase__: Tuple =False
def lowerCAmelCase_ ( ) -> Optional[int]:
... | 59 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
'''configuration_tapas''': ['''TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TapasConfig'''],
'''tokenization_tapas''': ['''TapasTokenizer'''],
... | 340 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Optional[int] = logging.get_logger(__name__)
UpperCamelCase__ : str = {
'''huggingface/informer-tourism-monthly''': (
'''https://hug... | 721 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fr... | 685 | 0 |
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
a_ : ... | 194 |
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Optional[Any] = {
'kakaobrain/align-ba... | 194 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_com... | 721 |
'''simple docstring'''
lowercase__ = 256
# Modulus to hash a string
lowercase__ = 1_000_003
def __UpperCamelCase ( __lowerCamelCase : str , __lowerCamelCase : str ) -> bool:
'''simple docstring'''
_a = len(__lowerCamelCase )
_a ... | 276 | 0 |
import random
from typing import Any
def __lowercase ( snake_case ):
"""simple docstring"""
for _ in range(len(snake_case ) ):
__magic_name__ :Optional[int] = random.randint(0, len(snake_case ) - 1 )
__magic_name__ :Union[str, Any] = random.rand... | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def __lowercase ( snake_case ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negati... | 0 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCamelCase__ : List[Any] ) -> str:
_SCREAMING_SNAKE_CASE : Union[str, Any] = len(lowerCamelCase__ )
while cur > 1:
# Find the maximum number in arr
_SCREAMING_SNAKE_CASE : Union[str, Any] = ... | 295 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowercase_ : Union[str, Any] = logging.get_logger(__name__)
class UpperCamelCase ( __SCREAMING_SNAKE_CASE ):
def __init__( self ... | 295 | 1 |
"""simple docstring"""
def _A( lowerCAmelCase , lowerCAmelCase ):
A__ : Optional[Any] = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def _A( lowerCAmelCase , lowerCAmelCase , lo... | 363 | """simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils imp... | 363 | 1 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCamelCase ... | 387 | import os
import string
import sys
UpperCamelCase = 1 << 8
UpperCamelCase = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,
'left': 68 + ARROW_KEY_FLAG,
'mod_int... | 387 | 1 |
"""simple docstring"""
from maths.prime_factors import prime_factors
def lowerCamelCase_ ( _lowerCamelCase : int ):
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
lowerCamelCase_ = F"""Input value of [number={number}] must be an integer"""
... | 142 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__lowercase : Tuple = logging.get_logger(__name__)
__lowercase : List[str] = {
"""speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-l... | 142 | 1 |
from __future__ import annotations
def _A( UpperCamelCase__ : Any ) -> Optional[int]:
'''simple docstring'''
if not nums:
raise ValueError('''List is empty''' )
return sum(UpperCamelCase__ ) / len(UpperCamelCase__ )
if __name__ == "__main... | 714 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class a ( __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
... | 362 | 0 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
a = ""
a = ""
a = ""
a = ""
def __magic_name__ ( __UpperCAmelCase ) -> None:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = tweepy.OAuthHandler(__UpperCAmelCase ... | 109 |
"""simple docstring"""
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def lowercase (*SCREAMING_SNAKE_CASE_ : Optional[Any] , SCREAMING_SNAKE_CASE_ : Optional[Union[Dict, Any]] = None , ... | 247 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _lowerCamelCase ( lowerCamelCase_ : Tuple ):
"""simple docstring"""
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code ... | 713 | '''simple docstring'''
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disab... | 389 | 0 |
import warnings
from ..trainer import Trainer
from ..utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE( __lowerCamelCase ):
def __init__( self: List[str] , UpperCamelCase: int... | 328 |
import os
def a ( a = "matrix.txt" ) ->int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(a ) , a ) ) as in_file:
SCREAMING_SNAKE_CASE = in_file.read()
SCREAMING_SNAKE_CASE = [[int(a ) for cell in row.split(''',''' )] for row in data.strip()... | 201 | 0 |
from typing import Dict, Optional
import numpy as np
import datasets
__magic_name__ = '''
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. For binary (two classes) or multi-class... | 704 | import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name_... | 679 | 0 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
UpperCamelCase__ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_pytorch': 'https://hugg... | 486 | 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 rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
ImageInput,
PILImageR... | 486 | 1 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : float ):
return 10 - x * x
def A__ ( __lowerCAmelCase : float , __lowerCAmelCase : float ):
# Bolzano theory in order to find if there is a root between a and b
if equation(__lowerCAmelCase ... | 9 |
'''simple docstring'''
def A__ ( ):
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(__lowerCAmelCase , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name__ == "__main__":
print(F... | 9 | 1 |
'''simple docstring'''
def __A ( _SCREAMING_SNAKE_CASE : Tuple = 1_0 , _SCREAMING_SNAKE_CASE : int = 1_0_0_0 , _SCREAMING_SNAKE_CASE : str = True ):
"""simple docstring"""
assert (
isinstance(a_ , a_ )
and... | 211 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE :Any = {
'configuration_pegasus_x': ['PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP', 'PegasusXConfig'],
}
try:
if not is_torch_available():
raise... | 55 | 0 |
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : int , _lowerCamelCase : int) -> str:
'''simple docstring'''
if not isinstance(_lowerCamelCase , _lowerCamelCase):
raise ValueError("iterations must be defined as integers")
... | 94 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Optional[Any] = {
'configuration_blip_2': [
'BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Blip2Config',
'Blip2QFormerConfig',
... | 94 | 1 |
'''simple docstring'''
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTes... | 585 | '''simple docstring'''
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
_A : Optional[Any] = object()
# For specifying empty leaf dict `{}`
_A : Dict = ob... | 427 | 0 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin... | 718 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_... | 551 | 0 |
import math
def UpperCamelCase_( __magic_name__ : str ):
"""simple docstring"""
_lowerCAmelCase :int = 0
_lowerCAmelCase :Union[str, Any] = 0
while num > 0:
_lowerCAmelCase :int = num % 8
... | 687 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class _a ( A__ ):
"""simple docstring"""
def __init__( self , _snake_case , _snake_case ):
_UpperCAmelCase =params
_UpperCAmelCase ... | 408 | 0 |
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,
MaxNewTokensCriter... | 714 |
import warnings
from ...utils import logging
from .image_processing_perceiver import PerceiverImageProcessor
snake_case_ : str = logging.get_logger(__name__)
class snake_case_ ( __A ):
'''simple docstring'''
def __init__( self : Union[str, Any] , *_... | 253 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 118 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.d... | 118 | 1 |
'''simple docstring'''
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
Ber... | 714 |
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_imag... | 332 | 0 |
# flake8: noqa
# Lint as: python3
lowerCAmelCase__ : Optional[Any] =[
'VerificationMode',
'Version',
'disable_progress_bar',
'enable_progress_bar',
'is_progress_bar_enabled',
'experimental',
]
from .info_utils import VerificationMode
from .logging import disable_... | 101 |
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, Callable, Dict, Iterable, List, Literal, NewType, Opti... | 9 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
fr... | 155 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggi... | 155 | 1 |
"""simple docstring"""
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common i... | 473 | """simple docstring"""
def lowerCAmelCase_ (_SCREAMING_SNAKE_CASE :int = 1 , _SCREAMING_SNAKE_CASE :int = 1000 ) -> int:
a_ : Tuple = 1
a_ : Optional[int] = 0
for divide_by_number in range(_SCREAMING_SNAKE_CASE , digit + 1 ):
... | 473 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def A_ ( __lowercase , __lowercase ):
UpperCamelCase_ : str =list(__lowercase )
UpperCamelCase_ : Optional[Any] =list(__lowercase )
UpperCam... | 395 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verb... | 395 | 1 |
from collections import defaultdict
def a ( A__ , A__ ) -> Optional[int]:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : str = first_str.lower().strip()
SCREAMING_SNAKE_CASE__ : Dict = second_str.lower().strip()
# Remove ... | 35 |
def A__( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(__lowerCAmelCase ) )
def A__( __lowerCAmelCase , __lowerCAmelCase , ... | 304 | 0 |
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.w... | 458 |
def _UpperCAmelCase ( UpperCAmelCase : str ):
"""simple docstring"""
__lowerCamelCase : List[Any] = hex_num.strip()
if not hex_num:
raise ValueError("""No value was passed to the function""" )
__lowerCamelCas... | 458 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
UpperCamelCase = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
UpperCamelCase = [file for file i... | 269 |
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
UpperCamelCase = ... | 269 | 1 |
'''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__ = {
... | 714 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, req... | 411 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_xlm": ["XLM_PRETRAINED_CONFIG_ARCHIVE_MAP", "XLMConfig", "XLMOnnxConfig"],
"tokenization_xlm": ["... | 608 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__lowerCamelCase = {
"configuration_groupvit": [
"GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"GroupViTConfig",
"Gro... | 608 | 1 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : float = 0.0 , __UpperCamelCase : float = 1.0 ):
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 )... | 21 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
__lowerCAmelCase : Optional[int] = logging.get_logger(__name__)
def __lowerCAmelCase ( __UpperCamelCas... | 21 | 1 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( _lowercase , unittest.TestCas... | 17 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
... | 69 | 0 |
'''simple docstring'''
from __future__ import annotations
_UpperCamelCase : List[str] = "Muhammad Umer Farooq"
_UpperCamelCase : List[Any] = "MIT"
_UpperCamelCase : Any = "1.0.0"
_UpperCamelCase : List[Any] = "Muhammad Umer Farooq"
_UpperCamelCase : ... | 700 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=a_ ):
SCREAMING_SNAKE_CASE : List[str] = ['''torch''', '''torchsde''']
def __init__( self , *_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_CASE ):
'''si... | 514 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowercase : List[str] = {"""configuration_van""": ["""VAN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """VanConfig"""]}
try:
if not i... | 142 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
__lowercase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase ( a ):
"""simple docstring"""
def __init__( self , ... | 142 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase = {
'''configuration_funnel''': ['''FUNNEL_PRETRAINED_C... | 41 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
lowercase = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
... | 41 | 1 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingS... | 323 |
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils impo... | 323 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__a = logging.get_logger(__name__)
class A__ ( UpperCamelCase ):
"""simple docstring"""
def __init__( self : int , *lowerCAmelCase__... | 257 | '''simple docstring'''
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
__a = ... | 257 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
... | 19 |
'''simple docstring'''
import json
import os
from typing import Optional
import numpy as np
from ...feature_extraction_utils import BatchFeature
from ...processing_utils import ProcessorMixin
from ...utils import logging
from ...utils.hub import get_file_from_repo
from ..auto import AutoTokenizer
lowerCamel... | 667 | 0 |
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_dat... | 704 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : Union[str, Any] = {
"configuration_git": ["GIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "GitConfig", "GitVisionConfig"],
"processing_git": ["GitProcessor"],
}
try:... | 3 | 0 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def UpperCamelCase_ ( __a , __a , __a ) -> Any:
a__ : Optional[Any] = {
"en": "Machine learning is great, isn't it?",
"ru": "Машинное обучение - это здорово, не так ли?",
"... | 37 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available... | 142 | 0 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils impor... | 703 |
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 Decoder, DecoderOutput, Enc... | 607 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE ( lowerCamelCase__ ):
'''simple docstring'''
def _... | 517 |
'''simple docstring'''
import collections
import importlib.util
import os
import re
from pathlib import Path
SCREAMING_SNAKE_CASE_ = "src/transformers"
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE_ = re.compile(r"is\_([a-z_]*)_available()")
# Catches a one-lin... | 597 | 0 |
from collections.abc import Callable
import numpy as np
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ):
"""simple docstring"""
__A = int(np.ceil((x_end - xa) / step_size ) )
__A = np... | 715 |
"""simple docstring"""
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class snake_case ( _lowerCAmelCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( self : Tuple, _lower... | 215 | 0 |
import random
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : Dict ) -> tuple:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = [], [], []
for element in data:
if element < pivot:
... | 31 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class _UpperCAmelCase ( unittest.TestCase ):
"""simple docstring"""
def lowercase ( self : Union[str, Any] ) -> List[str]:
__lowerCAmelCase = ... | 53 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMod... | 334 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils impo... | 334 | 1 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code... | 381 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__UpperCAmelCase = {
'configuration_mobilebert': [
'MOBILEBERT_PRETRAINED_CONFIG_AR... | 406 | 0 |
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_t... | 711 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _SCREAMING_SNAKE_CASE ( ) -> Tuple:
"""simple docstring"""
__A = HfArgumentParser(__lowercase )
__A = parser.parse_args_into_dataclasses()[0]
__A ... | 199 | 0 |
def __lowerCamelCase ( ) -> int:
return 1
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
return 0 if x < 0 else two_pence(x - 2 ) + one_pence()
def __lowerCamelCase ( _lowerCAmelCase ) -> int:
return 0 if x < 0 else five_pence(x - 5 ) + two_pence(_lowerCAmelCase )
def _... | 684 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __lowerCamelCase ( _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase ) -> Optional[Any]:
# In... | 684 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCamelCase_ ):
__SCREAMING_SNAKE_CASE = int(UpperCamelCase_ )
if decimal in (0, 1): # Exit cases for the recursion
return str(UpperCamelCase_ )
__SCREAMING_SNAKE_CASE ,__SCREAMING_SNAKE_CASE = divmod(UpperCamelCa... | 248 |
"""simple docstring"""
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxrunt... | 248 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( ):
__SCREAMING_SNAKE_CASE : Optional[Any] = []
__SCREAMING_SNAKE_CASE : List[str] = 1
while len(_lowerCamelCase ) < 1E6:
constant.append(str(_lowerCamelCase ) )
i += 1
__SCREAMING_SNAKE_CA... | 578 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCamelCase__ : int = {
'''configuration_poolformer''': [
'''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 578 | 1 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_... | 702 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmbedding, ... | 188 | 0 |
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