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'''
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class _lowerCAmelCase ( __... | 344 |
'''simple docstring'''
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _lowerCAmelCase ( __A ):
"""simple docstring"""
def __init__( self , _lowerCamelC... | 344 | 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
... | 197 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase_ : Optional[int] = {"""configuration_xlnet""": ["""XLNET_PRETRA... | 197 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"s-JoL/Open-Llama-V1": "https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json",
}
class lowerCamelCase ( lowerCAmelCase_ ):
... | 66 | """simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_av... | 289 | 0 |
"""simple docstring"""
from __future__ import annotations
def a_ ( _lowercase ):
_UpperCamelCase : List[str] = str(_lowercase )
return len(_lowercase ) == 9 and set(_lowercase ) == set('''123456789''' )
def ... | 354 |
"""simple docstring"""
def a_ ( _lowercase = 100 ):
_UpperCamelCase : List[Any] = 0
_UpperCamelCase : Optional[Any] = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
... | 128 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {"vocab_file": "spiece.mo... | 7 |
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_common import Confi... | 7 | 1 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 355 |
import argparse
import struct
import unittest
class UpperCamelCase :
def __init__( self , UpperCAmelCase__ ):
A__ = data
# Initialize hash values
A__ = [
0x6A_09E_667,
0xBB_67A_E85,
0x3C_6EF_372,
0xA... | 198 | 0 |
import argparse
import hashlib
import os
import urllib
import warnings
import torch
from torch import nn
from tqdm import tqdm
from transformers import WhisperConfig, WhisperForConditionalGeneration
_snake_case = {
"tiny.en": "https://openaipublic.azureedge.net/main/whisper/models/d3dd57d32a... | 26 |
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __lowercase ( a_ ):
"""simple docstring"""
... | 252 | 0 |
'''simple docstring'''
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class _lowercase ( _lower... | 129 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.util... | 129 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...... | 101 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedKVPro... | 101 | 1 |
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test... | 306 |
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.iterators import ThreadedIterator
from tqdm ... | 306 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ..utils import _LazyModule
_a = {
'config': [
'EXTERNAL_DATA_FORMAT_SIZE_LIMIT',
'OnnxConfig',
'OnnxConfigWithPast',
'OnnxSeq2SeqConfigWithPast',
'PatchingSpec',
],
'convert': ['export'... | 17 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase__ = {
'''configuration_autoformer''': [
'''AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 72 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase = {}
try:
if not is_sentencepiece_available():
raise Opt... | 270 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = {
'shi-labs/nat-min... | 270 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__: Any = logging.get_logger(__name__)
UpperCamelCase__: Optional[Any] = {
"microsoft/trocr-base-handwritten": (
"https://huggingface.co... | 23 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
UpperCamelCase__: Union[str, Any] = "examples/"
UpperCamelCase__: Optional[Any] = {
"examples": (re.compile(r"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_ve... | 23 | 1 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_im... | 119 | 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__ = {
'facebook/xlm-roberta-xl': 'https://huggingf... | 119 | 1 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def __UpperCamelCase ( _lowerCAmelCase = "isbn/0140328726" ) -> Dict:
"""simple docstring"""
A : Union[str, Any] = olid.strip().strip("""/""" ) # Remove leading/t... | 116 |
def lowerCamelCase_ ( _a ):
"""simple docstring"""
lowerCAmelCase__ : Optional[Any] = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def lowerCamelC... | 131 | 0 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
_A = logging.get_logger(__name__)
_A = {"v... | 137 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_A = logging.get_logger(__name__)
_A = {"vocab_file": "vocab.txt", "... | 137 | 1 |
# 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
#
# Unless required by applicabl... | 343 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/config.js... | 343 | 1 |
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
__UpperCA... | 367 |
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
default_data_collator... | 257 | 0 |
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class __lowercase (lowerCAmelCase_ ):
def __init__( self , ... | 275 |
'''simple docstring'''
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..... | 22 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils... | 355 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
__snake_case = logging.getLogger(__name__)
class lowercase ( A__ ):
"""simple docstring"""
_a = 'masked_bert'
def __init__( self , UpperCamelCase_=30522 ... | 219 | 0 |
'''simple docstring'''
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 tensorflow as tf
from transformers import AutoTokenize... | 331 |
"""simple docstring"""
def UpperCamelCase ( _lowerCAmelCase : int ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_UpperCAmelCase : Optional[Any] = 1
_UpperCAmelCase : List[str] = 1
while repunit:
_UpperCAmelCase : Tuple = ... | 246 | 0 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common im... | 333 | def lowercase_ ( _lowerCamelCase : int = 1 , _lowerCamelCase : int = 1000):
lowercase__ : Union[str, Any] = 1
lowercase__ : int = 0
for divide_by_number in range(_lowerCamelCase , digit + 1):
lowercase__ : list[int] = ... | 333 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {"""vocab_file""": """sentencepiece.m... | 92 |
from functools import reduce
UpperCAmelCase__ = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"668966489504452445231617... | 339 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Dict= logging.get_logger(__name__)
_a : Optional[Any]= {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
... | 95 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_funnel import FunnelTokenizer
_a : Any= logging.get_logger(... | 95 | 1 |
def UpperCamelCase ( __lowercase : int ,__lowercase : int ):
'''simple docstring'''
if not isinstance(__lowerCAmelCase ,__lowerCAmelCase ):
raise ValueError('iterations must be defined as integers' )
if not isinstance(__lowerCAmelCase ,__lowerCAmelCase ) or ... | 140 |
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interl... | 231 | 0 |
'''simple docstring'''
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
a_ = datasets.load_iris()
a_ = np.array(data['data'])
a_ = np.array(data['target'])
a_ = data['target_names']
a_ , a_ ,... | 351 |
'''simple docstring'''
from __future__ import annotations
import os
from collections.abc import Mapping
a_ = tuple[int, int]
class __SCREAMING_SNAKE_CASE :
def __init__( self : Any , __lowercase : set[int] , __lowercase : Mapping[EdgeT, in... | 222 | 0 |
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
_lowerCAmelCase : Tuple = models.Sequential()
# Step 1 -... | 169 |
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if is_vision_ava... | 169 | 1 |
'''simple docstring'''
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def __lowercase ( __lowercase ) -> Union[str, Any]:
'''simple docstring'''
... | 174 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def __lowercase ( __lowercase , __lowercase , __lowercase=None , **__lowercase ) -> Optional[int]:
'''simple docstring'''
_A = [x.strip() for x in open(__lowerca... | 174 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
lowerCAmelCase__ :Any = logging.get_logger(__name__)
l... | 329 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 21 | 0 |
"""simple docstring"""
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.uti... | 76 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( UpperCamelCase : str ):
def decorator(UpperCamelCase : Optional[int] ):
UpperCAmelCase : List[Any] = getattr(UpperCamelCase , """handle_key""" ,... | 76 | 1 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
__SCREAMING_SNAKE_CASE :Optional[int] = True
except (ImportError, ModuleNotFoundError):
__SCREAMING_SNAKE_CASE :str = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.dow... | 22 |
from math import factorial
def UpperCamelCase ( _A, _A, _A ):
"""simple docstring"""
if successes > trials:
raise ValueError("""successes must be lower or equal to trials""" )
if trials < 0 or successes < 0:
raise ValueError("""the func... | 342 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_snak... | 201 |
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
PixaStructTextConfig,
... | 201 | 1 |
import functools
import gc
import inspect
import torch
from .imports import is_npu_available, is_xpu_available
def __magic_name__ ( *__lowerCAmelCase : int ) -> str:
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
__lowerCamelCase = list(__lowerCAmelCase ... | 270 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(">=", "4.25.0")):
raise OptionalDependencyNotAvailable()
except... | 270 | 1 |
'''simple docstring'''
def a__ ( lowercase : int ) -> bool:
"""simple docstring"""
if p < 2:
raise ValueError('''p should not be less than 2!''' )
elif p == 2:
return True
_UpperCamelCase = 4
_UpperCamelCase = (1 << p) - 1
fo... | 287 |
'''simple docstring'''
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers import HfArgume... | 287 | 1 |
'''simple docstring'''
from math import sqrt
def lowerCamelCase ( __lowerCamelCase : int = 100_0000 ) ->int:
_SCREAMING_SNAKE_CASE = 0
_SCREAMING_SNAKE_CASE = 0
_SCREAMING_SNAKE_CASE = 42
while num_cuboids <= limit:
max_cuboid_size +... | 58 |
'''simple docstring'''
lowercase__ : Dict = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
... | 190 | 0 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
__a :Optional[Any] = yaml.safe_load(
'\\nname: ""\nallow_empty: false\nallow_empty_text: true\nsubsections:\n - name: "Dat... | 360 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map... | 329 | 0 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFlowBenchmarkArguments
@require_tf
... | 244 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
lowerCamelCase_ = ['''small''', '''medium''', '''large''']
lowerCamelCase_ = '''lm_head.decoder.weight'''
lowerCamelCase_ = '''lm_head.weight'''
def __magic_name__ ( __a : str ... | 244 | 1 |
import numpy
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Tuple , _lowerCAmelCase : numpy.ndarray , _lowerCAmelCase : numpy.ndarray ):
SCREAMING_SNAKE_CASE_ = input_array
# Random initial weights are as... | 370 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def UpperCAmelCase_ ( __UpperCAmelCase : List[str] ) -> List[Any]:
# vision encoder
if "img_encoder.pos_embed" in name:
SCRE... | 210 | 0 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class UpperCamelCase_ ( __snake_case , unittest.TestCase ):
lowercase = DownBlocka... | 265 |
import functools
def A_ ( _lowerCAmelCase , _lowerCAmelCase ) -> int:
UpperCamelCase : Optional[int] = len(_lowerCAmelCase )
UpperCamelCase : List[str] = len(_lowerCAmelCase )
@functools.cache
def min_distance(_lowerCAmelCase , _lowerCAme... | 52 | 0 |
def __lowerCamelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ = 0 , lowerCAmelCase__ = 0 ):
lowerCAmelCase__ = right or len(lowerCAmelCase__ ) - 1
if left > right:
return -1
elif list_data[left] == key:
return lef... | 119 | import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...uti... | 119 | 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_tok... | 64 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with... | 64 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
A__ : List[str] = datasets.utils.logging.get_logger(__name__)
@dataclass
class ... | 363 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
A__ : Optional[int] = {
'configuration_speech_to_text': ['SPE... | 209 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class _SCREAMING_SNAKE_CASE ( unittest.TestCase):
def _snake_case ( self )-> Tuple:
lowerCamelCase_ =inspect... | 154 |
# 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
#
# Unless required by applica... | 154 | 1 |
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,
EulerAncestralDiscreteScheduler,
EulerDiscreteSched... | 365 |
import argparse
import os
import re
import tensorflow as tf
import torch
from transformers import BertConfig, BertModel
from transformers.utils import logging
logging.set_verbosity_info()
__a = logging.get_logger(__name__)
def __lowercase ( _UpperCamelCase, _UpperCamelCase, _UpperCamel... | 173 | 0 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _UpperCamelCase ( ):
'''simple docstring'''
UpperCAmelCase__ = ArgumentParser(
description=(
... | 346 |
'''simple docstring'''
import string
from math import logaa
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : str ):
'''simple docstring'''
UpperCAmelCase__ = document.translate(
str.maketrans("""""" , """""" , string.punctuatio... | 346 | 1 |
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as np
from .import_utils... | 354 |
import copy
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase : List[Any] = logging.ge... | 36 | 0 |
lowercase__ =tuple[float, float, float]
lowercase__ =tuple[float, float, float]
def __UpperCamelCase ( lowerCAmelCase__ : Pointad , lowerCAmelCase__ : Pointad ):
__a : Optional[int] = end_pointa[0] - end_pointa[0]
__a : Optional[int] = end_pointa[1] - end... | 216 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses... | 335 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : int = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE : List[Any] = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main... | 218 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorType, ... | 218 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase_ = {'''configuration_glpn''': ['''GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GLPNConfig''']}
try:
if not is_vision_availa... | 268 |
"""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_availa... | 268 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
... | 363 |
"""simple docstring"""
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_inf... | 239 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_snake_case : int = logging.get_logger(__name__)
_snake_... | 284 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 284 | 1 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : int = 1_0_0_0 ):
'''simple docstring'''
lowerCAmelCase : List[str] = 2**power
lowerCAmelCase : Any = 0
while n:
lowerCAmelCase , lowerCAmelCase : int = ... | 133 |
"""simple docstring"""
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def a__ ( SCREAMING_SNAKE_CASE : str ): # picklable fo... | 133 | 1 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class a__ ( snake_case__ ):
_a : int = (DEISMul... | 92 |
"""simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
... | 126 | 0 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
__A = logging.getLogger(__name__)
class _SCREAMING_SNAKE_CASE ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "masked_bert"
def __init__(self :... | 370 |
from __future__ import annotations
from typing import Any
class _SCREAMING_SNAKE_CASE :
'''simple docstring'''
def __init__(self : Any , UpperCAmelCase_ : int) ->None:
'''simple docstring'''
lowerCamelCase__: int =num_of_nodes
lowerCamelCase__... | 273 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ : int ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 45 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMSch... | 29 | 0 |
'''simple docstring'''
from manim import *
class lowerCAmelCase_ ( lowerCAmelCase_ ):
'''simple docstring'''
def _snake_case ( self : Tuple ) -> Dict:
'''simple docstring'''
A = ... | 352 |
'''simple docstring'''
import os
from distutils.util import strtobool
def SCREAMING_SNAKE_CASE( __lowercase , __lowercase ) -> List[Any]:
for e in env_keys:
A: Dict = int(os.environ.get(__lowercase , -1 ) )
if val ... | 334 | 0 |
import random
def lowerCamelCase_ ( _a : list , _a : Any ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ , UpperCAmelCase_ : Dict = [], [], []
for element in data:
if element < pivot:
less.append(SCREAMI... | 345 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def lowercase (SCREAMING_SNAKE_CASE_ : Callable[[int | float], int | float] , SCREAMING_SNAKE_CASE_ : int | float , SCREAMING_SNAKE_CASE_ : int | float , SCREAMING_SNAKE_CASE_ :... | 113 | 0 |
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
__SCREAMING_SNAKE_CASE : Union[str, Any] = [
# tf -> hf
('''/''', '''.'''),
('''layer_''', '''laye... | 364 |
"""simple docstring"""
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is... | 73 | 0 |
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase_ : Any ... | 32 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
UpperCamelCase__ : Optional[Any] = logging.g... | 344 | 0 |
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import... | 306 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase : Optional[Any] = {
'''configuration_poolformer''': [
'''POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''PoolFormerConfig''',
... | 306 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils... | 213 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __lowerCAmelCase ( _a ):
lowerCamelCase_ : int = ''''''
lowerCamelCase_ : str = (
... | 279 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def _lowerCamelCase(__UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> int:
if depth < 0:
raise ValueError("""Depth cannot be less than 0""" )
if len(_... | 341 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = '▁'
... | 341 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __UpperCamelCase ( metaclass=lowerCAmelCase_ ):
A_ = ["torch", "transformers", "onnx"]
def __init__( self , *__a , **__a ):
'''simple docstring'''
requires_back... | 27 |
from collections.abc import Callable
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self , _a = None ) -> None:
# Stores actual heap items.
_a : list = []
# Stores indexes of each item fo... | 235 | 0 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def a__ ( lowerCAmelCase__ ) -> List[Any]:
# vision encoder
if "img_encoder.pos_embed" in name:
UpperCA... | 299 |
'''simple docstring'''
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def a__ ( lowerCAmelCase__ ) -> None:
UpperCAmelCase__ , UpperCAmelCase__ : Optional[Any] = analyze_text(lowerCA... | 299 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
def lowerCAmelCase__ ( _UpperCamelCase : Union[tf.Tensor, np.ndarray] ) -> List[i... | 150 | """simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def lowerCAmelCase__ ( _UpperCamelCase : Any="ro" , _UpperCamelCase : Optional[Any]="en" , _UpperCamelCase : Any="wmt16" , _UpperCamelCase : Tuple=None ) -> None:
... | 150 | 1 |
from copy import deepcopy
class lowercase :
'''simple docstring'''
def __init__( self , _snake_case = None , _snake_case = None ) -> None:
"""simple docstring"""
if arr is None and size is not None:
UpperCAm... | 364 |
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.transfo... | 152 | 0 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
SCREAMING_SNAKE_CASE__ : List[str] = logging.get_logger(__name__)
class UpperCamelCase__ (lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self ... | 48 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 51 | 0 |
import warnings
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 = ... | 10 |
import fire
from utils import calculate_rouge, save_json
def UpperCamelCase ( __lowerCamelCase : Dict , __lowerCamelCase : Dict , __lowerCamelCase : Tuple=None , **__lowerCamelCase : Tuple ):
snake_case : Optional[Any] = [x.strip() for x in ... | 10 | 1 |
class UpperCAmelCase :
def __init__(self : Dict , snake_case__ : Optional[Any] ) -> List[Any]:
'''simple docstring'''
snake_case : Optional[int] = val
snake_case : Any = None
snake_case : ... | 59 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : list ):
"""simple docstring"""
if len(snake_case__ ) <= 1:
return [tuple(snake_case__ )]
_snake_case : List[Any] = []
def generate(snake_case__ : int , snake_case__... | 64 | 0 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling_auto import... | 358 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 141 | 0 |
'''simple docstring'''
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
a__ : Optional[Any] = 2_9_9_7_9_2_4_5_8
# Symbols
a__ , a__ , a__ , a__ : Optional[Any] = symbols("ct x y... | 161 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelF... | 161 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set... | 361 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ... | 12 | 0 |
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase_ ( UpperCamelCase_ , unittest.TestCas... | 338 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
__A = 10
def lowerCamelCase_ ( UpperCamelCase__ : int , UpperCamelCase__ : ... | 90 | 0 |
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS_TRUE_VALUES,
... | 369 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_availab... | 60 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
_UpperCAmelCase : int = logging.get_logger(__name__)
_UpperCAmelCase : str = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/d... | 50 | """simple docstring"""
from collections import Counter
from timeit import timeit
def _lowerCamelCase( a = "" , ):
return sum(c % 2 for c in Counter(input_str.replace(" " , "" ).lower() ).values() ) < 2
def _lowerCamelCase( a = "" ):
if len(a ... | 261 | 0 |
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
__lowerCamelCase = pd.read_csv('''sample_data.csv''', heade... | 101 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class A__ :
def __init__( self , UpperCamelCase__ ) -> Dict:
'''simple docstring'''
A_ = str(id_ )
A_ = None
A_ = None
A... | 101 | 1 |
"""simple docstring"""
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require... | 332 |
'''simple docstring'''
from __future__ import annotations
def __UpperCAmelCase ( A : str ) -> list[int]:
return [ord(A ) - 9_6 for elem in plain]
def __UpperCAmelCase ( A : list[int] ) -> str:
return "".join(chr(elem + 9_6 ) for elem in encoded )
... | 304 | 0 |
"""simple docstring"""
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_lowercase : Op... | 86 |
"""simple docstring"""
def lowercase__ ( snake_case_ :int , snake_case_ :int , snake_case_ :int ):
__UpperCAmelCase = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of series
return total
def lowercase__ ( ... | 86 | 1 |
import torch
from diffusers import DiffusionPipeline
class UpperCamelCase__ (lowerCAmelCase__ ):
'''simple docstring'''
def __init__( self , UpperCamelCase__ , UpperCamelCase__ ) -> Optional[Any]:
super().__init__()
self.r... | 48 |
from math import sqrt
def A ( _SCREAMING_SNAKE_CASE = 100_0000 ) -> int:
lowerCamelCase : int = 0
lowerCamelCase : int = 0
lowerCamelCase : int
while num_cuboids <= limit:
max_cuboid_size += 1
... | 48 | 1 |
'''simple docstring'''
import pprint
import requests
A__ : Tuple ='''https://zenquotes.io/api'''
def UpperCamelCase__ ( ):
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def UpperCa... | 220 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
A__ : List[str] =datasets.logging.get_logger(__name__)
A__ : ... | 220 | 1 |
def A ( a_ ) -> List[str]:
__UpperCamelCase : List[Any] =len(a_ )
__UpperCamelCase : Optional[int] =sum(a_ )
__UpperCamelCase : Optional[int] =[[False for x in range(s + 1 )] for y in range(n +... | 71 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
a__ : Tuple = {'UserAgent': UserAgent().random}
def _UpperCamelCase ( __A ) -> dict:
'''simple docstr... | 80 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, ... | 358 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCAmelCase_ : List[str] = TypeVar('T')
lowerCAmelCase_ : Dict = TypeVar('U')
class __SCREAMING_SNAKE_CASE (Generic[T, U] ):
... | 346 | 0 |
"""simple docstring"""
from __future__ import annotations
from functools import lru_cache
from math import ceil
lowerCAmelCase__ = 100
lowerCAmelCase__ = set(range(3, NUM_PRIMES, 2))
primes.add(2)
lowerCAmelCase__ = 42
for prime in range(3, ceil(NUM_PRIMES**0.5), 2):
... | 108 | """simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
__A = logging.get_logger(__name__)
__A ... | 177 | 0 |
from datetime import datetime as dt
import os
from github import Github
__a = [
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def lowerCamelCase__ ( ):
'''simple docstring'''
UpperCAmelC... | 368 |
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
__a = logging.getLogger(__name__)
if __name__ == "__main__":
__a = arg... | 235 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaInpaintPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, lo... | 73 |
import csv
import tweepy
# Twitter API credentials
a =""""""
a =""""""
a =""""""
a =""""""
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ ) -> None:
# authorize twitter, initialize tweepy
__lowerCamelCase : Tuple = tweepy.OAuthHandler(lowerCamelCase__ ... | 73 | 1 |
import os
from pathlib import Path
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase ):
"""simple docstring"""
_lowerCAmelCase = {
"""en""": """Machine learning is great, isn't it?""",
... | 369 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
A__ : int ={'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
... | 220 | 0 |
"""simple docstring"""
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class __A (snake_case__):
'''simple docstring'''
__lowercase: List[str] = """"""
__lowerc... | 347 |
"""simple docstring"""
def _a ( _SCREAMING_SNAKE_CASE ) -> bool:
if num < 0:
return False
snake_case_ = num
snake_case_ = 0
while num > 0:
snake_case_ = rev_num * 10 + (num % 10)
num //= 10
return ... | 347 | 1 |
'''simple docstring'''
def _a ( _lowerCamelCase ) -> Dict:
"""simple docstring"""
__snake_case : Union[str, Any] = len(_lowerCamelCase )
for i in range(length - 1 ):
__snake_case : Union[str, Any] = i
... | 13 |
'''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,
)
if is_sentencepi... | 13 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,
UnCLIPImag... | 146 |
import json
import os
import re
import sys
import urllib.request
import requests
from bsa import BeautifulSoup
__UpperCamelCase : Dict = {
"User-Agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36"
" (KHTML, like Gecko) Chrome/70.0.3538.102 Safari/537.36 Edge/18.19582"
}
def ... | 146 | 1 |
"""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 .... | 317 |
"""simple docstring"""
from __future__ import annotations
class __lowerCamelCase :
def __init__(self , lowerCamelCase , lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase , _lowerCAmelCase = text, pattern
_lowerCAmelCase , _low... | 317 | 1 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@requ... | 279 |
'''simple docstring'''
import unittest
import torch
from diffusers import VQModel
from diffusers.utils import floats_tensor, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
enable_full_determinism()
class ... | 185 | 0 |
'''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
__UpperCAmelCase :int = [
# (stable-diffusion, HF Diffusers)
("time_... | 361 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransfo... | 240 | 0 |
"""simple docstring"""
from timeit import timeit
def _A ( UpperCamelCase_ : Union[str, Any]) -> Any:
'''simple docstring'''
if number < 0:
raise ValueError("the value of input must not be negative")
__lowercase = 0
while number:
number &= number - 1
... | 17 |
import argparse
import json
import os
import torch
from torch import nn
from transformers import NllbMoeConfig, NllbMoeModel
from transformers.modeling_utils import dtype_byte_size
from transformers.utils import WEIGHTS_INDEX_NAME, WEIGHTS_NAME
def lowerCamelCase__ (_UpperCAmelCase):
SCREAMING_SNAKE_... | 137 | 0 |
import numpy as np
UpperCamelCase_ =[
['a', 'b', 'c', 'd', 'e'],
['f', 'g', 'h', 'i', 'k'],
['l', 'm', 'n', 'o', 'p'],
['q', 'r', 's', 't', 'u'],
['v', 'w', 'x', 'y', 'z'],
]
class _a :
def __init__( self : Optional[Any] ) ... | 367 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
UpperCamelCase_ ="""examples/"""
UpperCamelCase_ ={
"""examples""": (re.compile(r"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
... | 128 | 0 |
'''simple docstring'''
import warnings
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_ : List[str] = logging.get_lo... | 63 |
'''simple docstring'''
import math
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def UpperCamelCase__ ( self : List[str] , __a : list[list[float]] , __a : list[int] ):
_a = 0.0
_a = 0.0
fo... | 63 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s",
datefmt="%m/%d/%Y %H:%M:%S",
level=logging.INFO,
)
l... | 352 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
... | 11 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A ={
'configuration_groupvit': [
'GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'GroupViTConfig',
'GroupViTOnnxConfig',
... | 34 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : List[str] = logging.get_logger(__name__)
lowerCamelCase__ : List[str] = {
'facebook/s2t-small-librispeech-asr': (
'https://huggingface.co/facebook/s2t-small-librispeech-asr/res... | 225 | 0 |
import math
from collections.abc import Callable
def lowerCamelCase_ ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ) -> int:
"""simple docstring"""
snake_case_ : float = xa
snake_case_ : float = xa
while True:... | 350 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMix... | 279 | 0 |
'''simple docstring'''
from bisect import bisect
from itertools import accumulate
def __a(SCREAMING_SNAKE_CASE_ : Any , SCREAMING_SNAKE_CASE_ : List[str] , SCREAMING_SNAKE_CASE_ : Dict , SCREAMING_SNAKE_CASE_ : Union[str, Any] ):
'''simple docstri... | 158 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
class lowerCAmelCase_ :
def __init__( self , _lowerCAmelCase ) -> Optional[int]:
_lowerCAmelCase = []
self.adlist.append(
{"value": "", "next_states": [], "fail_stat... | 158 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import Tokenize... | 255 |
"""simple docstring"""
import inspect
import unittest
class SCREAMING_SNAKE_CASE_ ( unittest.TestCase ):
"""simple docstring"""
def snake_case_ ( self):
try:
import diffusers # noqa: F401
except ImportError:
assert False
def snake_case_ ... | 255 | 1 |
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