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 |
|---|---|---|---|---|
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __versi... | 90 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 1 |
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import AudioPipelineOutput, B... | 90 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 1 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
lowercase__ ='\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Method for Automatic Evalua... | 90 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
__a : str = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__a : Optional[Any] = n - k
# Calculate C(n,k)
for i in range(lowerCAmelCase__ ):
resul... | 90 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 1 |
from manim import *
class UpperCamelCase__ ( __lowercase ):
def lowerCAmelCase (self : Union[str, Any] ):
__a : Union[str, Any] = Rectangle(height=0.5 , width=0.5 )
__a : str = Rectangle(height=0.46 , width=0.46 ).set_stroke(width=0 )
_... | 90 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 1 |
from __future__ import annotations
import time
import numpy as np
lowercase__ =[8, 5, 9, 7]
lowercase__ =[
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
lowercase__ =[
[3, 2, 1, 4],
[0, 2, 5, 2],
[5, 1, 0, 5],
[1, 5, 3, 0],
... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
import sys
from collections import defaultdict
class UpperCamelCase__ :
def __init__(self : Optional[Any] ):
__a : str = []
def lowerCAmelCase (self : int , snake_case_ : List[Any] ):
return self.node_position[vertex]
def lowerCAmelCase (self : L... | 90 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 1 |
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
lowercase__ ={
'linear': PIL.Image.Resampling.BILINEAR,
'bilinear': PIL.Image.Resampling.BILINEAR,
... | 90 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 1 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
'huggingface/informer-tourism-monthly': (
'https://huggingface.co/huggingface/informer-tourism-monthly/res... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_common import BackboneTester... | 90 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTest... | 90 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : Union[str, Any] ):
__a : str = len(lowerCAmelCase__ )
while cur > 1:
# Find the maximum number in arr
__a : Dict = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
__a : Tuple = arr[mi::-1] + arr[mi + 1 : len(l... | 90 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 1 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Dict = ["image_processor", "tokenizer"]
_SCREAMING_SNAKE_CASE : Union[str, Any] = "AutoImageProcessor"
_... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 6_0_0_8_5_1_4_7_5_1_4_3 ):
try:
__a : Tuple = int(lowerCAmelCase__ )
except (TypeError, ValueError):
raise TypeError('''Parameter n must be int or castable to int.''' )
if n <= 0:
raise ValueError('''Parameter n must be greate... | 90 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
lowercase__ ='src/diffusers'... | 90 |
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.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : int ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 90 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 1 |
import io
import json
import fsspec
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.json import JsonDatasetReader, JsonDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __UpperCamelCase ( l... | 90 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 1 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigT... | 90 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 1 |
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResampling,
get_image_siz... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 1 |
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 import CORPUS_NAME... | 90 |
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
lowercase... | 90 | 1 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def __UpperCamelCase ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : List[str] , ... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('''socket.socket''' )
@patch('''builtins.open''' )
def __UpperCamelCase ( lowerCAmelCase__ : List[Any] , lowerCAmelCase__ : int ):
# ===== initialization =====
__a : int =... | 90 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 1 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( __lowercase ):
def __init__(self : List[Any] , snake_case_ : Callable , snake_case_ : Optional[Features... | 90 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 1 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def __UpperCamelCase ( lowerCAmelCase__ : Any , lowerCAmelCase__ : int , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[An... | 90 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 1 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='%(asctime)s - %(levelname)s - %(name)s - %(message)s', datefmt='%m/%d/%Y %H:%M:%S', level=logging.INFO
)
lowercase__ ... | 90 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 1 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class UpperCamelCase__ :
_SCREAMING_SNAKE_CASE : torch.Tensor # [batch_size x 3]
_SCREAMING_SNAKE_CASE : torch.Tensor # [batch_size x 3]
_SCREAMING_SNAKE_CASE : torch.Tenso... | 90 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 1 |
lowercase__ ={
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': 'dataclasses',
'datasets': '... | 90 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 1 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowercase__ =200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation and must be smaller than... | 90 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 1 |
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 UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.models.w... | 90 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : Optional[Any] ):
stooge(lowerCAmelCase__ , 0 , len(lowerCAmelCase__ ) - 1 )
return arr
def __UpperCamelCase ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Any , lowerCAmelCase__ ... | 90 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 1 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequenceCla... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_common import BackboneTester... | 90 | 1 |
import multiprocessing
from typing import TYPE_CHECKING, Optional, Union
from .. import Dataset, Features, config
from ..formatting import query_table
from ..packaged_modules.sql.sql import Sql
from ..utils import logging
from .abc import AbstractDatasetInputStream
if TYPE_CHECKING:
import sqlitea
impo... | 90 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 1 |
from math import factorial
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : float ):
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''' )
if trials < 0 or successes < 0:
r... | 90 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 1 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Tuple = "EncodecFeatureExtractor"
_SCREAMING_SNAKE_CASE : Union[str, Any] = ... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ ={
'configuration_xlm_roberta_xl': [
'XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XLMRobertaXLConfig',
'XLMRobertaXLOnnxConfig',
],
}
try:
... | 90 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 1 |
from math import ceil, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0_0_0_0 ):
__a : Union[str, Any] = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
__a : List[str] = max(ceil(sqrt(outer_width**2 - limit ) ) ... | 90 |
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.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 1 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class UpperCamelCase__ :
def __init__(self : Any , snake_case_ : Any ):
__a : Any = data
__a : Node | None = None
class UpperCamelCase__ :
def __init__(self : Opt... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 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 (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 90 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 1 |
import os
def __UpperCamelCase ( lowerCAmelCase__ : str = "input.txt" ):
with open(os.path.join(os.path.dirname(lowerCAmelCase__ ) , lowerCAmelCase__ ) ) as input_file:
__a : Any = [
[int(lowerCAmelCase__ ) for element in line.split(''',''' )]
for line i... | 90 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 1 |
from math import ceil
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_1 ):
__a : Union[str, Any] = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
__a : List[str] = 2 * i + 1
__a : str = 2 * i
__a : Dict = total + 4 * odd**2 - 6 * ev... | 90 |
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
lowercase... | 90 | 1 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 1 |
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, InputFeatures, SingleSentenceClassificati... | 90 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 1 |
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
get_constant_schedule,
... | 90 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 1 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTest... | 90 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ ={
'configuration_roformer': ['ROFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'RoFormerCo... | 90 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 1 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__vers... | 90 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
lowercase__ =get_tests_dir('fixtures/test_sentenc... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_u... | 90 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 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... | 90 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 1 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_common import BackboneTester... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_common import BackboneTester... | 90 | 1 |
from collections.abc import Sequence
def __UpperCamelCase ( lowerCAmelCase__ : Sequence[float] , lowerCAmelCase__ : float ):
return sum(c * (x**i) for i, c in enumerate(lowerCAmelCase__ ) )
def __UpperCamelCase ( lowerCAmelCase__ : Sequence[floa... | 90 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 1 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def __UpperCamelCase ( lowerCAmelCase__ : dict ):
return (data[... | 90 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 1 |
import math
def __UpperCamelCase ( lowerCAmelCase__ : int ):
__a : str = 0
__a : Union[str, Any] = 0
while num > 0:
__a : Dict = num % 8
__a : Optional[Any] = octal + (remainder * math.floor(math.pow(1_0 , lowerCAmelCase__ ) ))
counter +... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 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 (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 90 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 1 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def __UpperCamelCase ( lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : bool = True , lowerCAmelCase__ : float = math.inf , lowerCAmelCase__ : flo... | 90 |
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.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 1 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 1 |
from __future__ import annotations
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : list[str] | None = None , lowerCAmelCase__ : dict[str, float] | None = None , lowerCAmelCase__ : bool = False , ):
__a : Tuple ... | 90 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
__a : str = len(lowerCAmelCase__ )
for i in range(1 , lowerCAmelCase__ ):
__a : Optional[int] = collection[i]
__a : int = 0
__a : Dict = i - 1
while low <= high:
__a : Any = (lo... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 1 |
import itertools
import math
def __UpperCamelCase ( lowerCAmelCase__ : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All pri... | 90 |
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
lowercase... | 90 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 1 |
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
lowercase__ =logging.get_logger(__name__)
lowercase__ ='▁'
lowercase__ ={... | 90 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 1 |
import argparse
import gc
import json
import os
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Accelerator... | 90 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 1 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCamelCase... | 90 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 1 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 1 |
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
lowercase__ =logging.get_logger(__name__)
class UpperCam... | 90 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 1 |
import os
def __UpperCamelCase ( lowerCAmelCase__ : int ):
__a : Optional[int] = len(grid[0] )
__a : Optional[int] = len(lowerCAmelCase__ )
__a : Tuple = 0
__a : int = 0
__a : int = 0
# Check vertically, horizontally, diagonally at the ... | 90 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : int ):
if index == number_of_items:
return 0
__a : int = 0
__a : Union... | 90 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegmentation,
... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
lowercase__ =argparse.ArgumentParser()
parser.add_argument(
'--checkpoint_path', default=None, type=str, required=True, help='Path to t... | 90 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : int = ["image_processor", "tokenizer"]
_SCREAMING_SNAKE_CASE : Union[str, Any] = "CLIPImag... | 90 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 1 |
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.modeli... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_common import BackboneTester... | 90 | 1 |
import tensorflow as tf
from ...tf_utils import shape_list
class UpperCamelCase__ ( tf.keras.layers.Layer ):
def __init__(self : List[str] , snake_case_ : Optional[Any] , snake_case_ : int , snake_case_ : Optional[Any] , snake_case_ : Optional[Any] , snake_case_ : str=1 , snak... | 90 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...... | 90 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 1 |
import math
import os
import sys
def __UpperCamelCase ( lowerCAmelCase__ : str ):
__a : str = ''''''
try:
with open(lowerCAmelCase__ , '''rb''' ) as binary_file:
__a : int = binary_file.read()
for dat in data:
__a : Tuple = f"{dat:08b}"
resu... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 1 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
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_co... | 90 |
from math import pi, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : float ):
if num <= 0:
raise ValueError('''math domain error''' )
if num > 1_71.5:
raise OverflowError('''math range error''' )
elif num - int(lowerCAmelCase__ ) not in (0, 0.5):
raise NotImplementedError('''num ... | 90 | 1 |
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : List[str] = "MCTCTFeatureExtractor"
_SCREAMING_SNAKE_CASE : int = "AutoTokenizer"
def __init__(self ... | 90 |
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.
lowercase__ =10
def __UpperCamelCase ( lowerCAmelCase__ : int , lowerCAmelCase__ : int ... | 90 | 1 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
lowercase__ =list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
lowercase__ =[file for file in filepaths if file != file.... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0 ):
__a : int = -1
__a : Any = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__a : List[Any] = (n * n - 2 * a * n) // (2 * n - 2 * a)
__a : ... | 90 | 1 |
from collections import deque
from math import floor
from random import random
from time import time
class UpperCamelCase__ :
def __init__(self : Dict ):
__a : List[str] = {}
def lowerCAmelCase (self : int , snake_case_ : List[Any] , snake_case_ : int , snake_ca... | 90 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 1 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def __UpperCamelCase ( lowerCAmelCase__ : Optional[Any] ):
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unif... | 90 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.modeling_mbart impor... | 90 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list[list[int | float]] ):
__a : int = len(lowerCAmelCase__ )
__a : Dict = len(matrix[0] )
__a : Union[str, Any] = min(lowerCAmelCase__ , lowerCAmelCase__ )
for row in range(lowerCAmelCase__ ):
# Check if dia... | 90 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ =logging.get_logger(__name__)
lowercase__ ={
'shi-labs/nat-mini-in1k-224': 'https://huggingface.co/sh... | 90 |
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
lowercase... | 90 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository c... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
def merge(lowerCAmelCase__ : list , lowerCAmelCase__ : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from left
yield from right
re... | 90 | 1 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils impo... | 90 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def __UpperC... | 90 | 1 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
lowercase__ =logging.getLogger()
def __UpperCamelCase... | 90 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
@require_sentencepiece
@requi... | 90 | 1 |
from math import sqrt
def __UpperCamelCase ( lowerCAmelCase__ : int ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All primes num... | 90 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase__ ={
'configuration_layoutlmv2': ['LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LayoutLMv2Config'],
'... | 90 | 1 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 |
import argparse
import os
import re
import packaging.version
lowercase__ ='examples/'
lowercase__ ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULTILINE), '__ve... | 90 | 1 |
import unittest
from transformers import 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_tensor
from .... | 90 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 90 | 1 |
def __UpperCamelCase ( lowerCAmelCase__ : list ):
if len(lowerCAmelCase__ ) <= 1:
return [tuple(lowerCAmelCase__ )]
__a : List[Any] = []
def generate(lowerCAmelCase__ : int , lowerCAmelCase__ : list ):
if k == 1:
res.append(tuple(arr[:] ) )
... | 90 |
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class UpperCamelCase__ ( __lowercase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = CustomTokenizer
pass
| 90 | 1 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
lowercase__ =(720, 1280) # Height, Width
lowercase__ =(0.4, 0.6) # if height or width lower than this scale, drop it.
lowercase__ =1 / 100
lowercase__ =''
l... | 90 |
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
C... | 90 | 1 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowercase__ =(3, 9, -11, 0, 7, 5, 1, -1)
lowercase__ =(4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class UpperCamelCase__ :
_SCREAMING_SNAKE_CASE : int
_SCREAMING_SNAKE_... | 90 |
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( __lowercase ,unittest.TestCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = Ph... | 90 | 1 |
import baseaa
def __UpperCamelCase ( lowerCAmelCase__ : str ):
return baseaa.baaencode(string.encode('''utf-8''' ) )
def __UpperCamelCase ( lowerCAmelCase__ : bytes ):
return baseaa.baadecode(lowerCAmelCase__ ).decode('''utf-8''' )
if __name__ == "__main_... | 90 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ =50000
lowercase__ =5000
lowercase__ , lowercase__ =os.path.split(__file__)
lowercase__ =os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENA... | 90 | 1 |
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 import ... | 90 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ ={
'configuration_data2vec_audio': ['DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Data2VecAudioConfig'],
'configuration_data2vec_text': [
'DA... | 90 | 1 |
from collections import defaultdict
from math import ceil, sqrt
def __UpperCamelCase ( lowerCAmelCase__ : int = 1_0_0_0_0_0_0 , lowerCAmelCase__ : int = 1_0 ):
__a : defaultdict = defaultdict(lowerCAmelCase__ )
for outer_width in range(3 , (t_limit // 4) ... | 90 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
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_backbone_common import BackboneTester... | 90 | 1 |
import warnings
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 UpperCamelCase__ ( __lowercase ):
_SCREAMING_... | 90 |
import os
import sys
import unittest
lowercase__ =os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
get_model_to_t... | 90 | 1 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /home/niels/... | 90 |
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
lowercase__ =logging.get_logger(__name__)
lowercase__ ={'vocab_file': 'vocab.json', 'merges_file': 'merges.txt', ... | 90 | 1 |
import pytest
lowercase__ ='__dummy_dataset1__'
lowercase__ ='\nimport json\nimport os\n\nimport datasets\n\n\nREPO_URL = "https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/"\nURLS = {"train": REPO_URL + "wikiann-bn-train.jsonl", "validation": REPO_URL + "wikiann-bn-vali... | 90 |
def __UpperCamelCase ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ):
__a : Any = len(lowerCAmelCase__ )
__a : Union[str, Any] = []
for i in range(len(lowerCAmelCase__ ) - pat_len + 1 ):
__a : List[Any] = True
for j in range(lowerCAmelCas... | 90 | 1 |
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