code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _snake_case (__lowercase , __lowercase):
return math.sqrt(sum(pow(a - b , 2) for a, b in zip(__lowercase , __lowercase)))
def _snake_case... | 23 |
'''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 ...test_modeling_tf_common im... | 261 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE : Union[str, Any] = {
'configuration_whisper': ['WHISPER_PRETRA... | 55 |
import numpy as np
_SCREAMING_SNAKE_CASE : Any = [
['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 UpperCamelCase__ :
'''simple docstring'''
def __init__( self... | 55 | 1 |
from collections import Counter
from timeit import timeit
def A__ (snake_case : str = "" , ) -> List[str]:
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ) < 2
def A__ (snake_case : str = "" ) -> ... | 279 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization... | 256 | 0 |
def A_ ( A__ = 100_0000 ) -> int:
a__ : Optional[Any] = limit + 1
a__ : Any = [0] * limit
for first_term in range(1 , A__ ):
for n in range(A__ , A__ , A__ ):
a__ : List[Any] = first_term + n... | 392 |
from collections import namedtuple
lowercase : List[str] = namedtuple("""from_to""", """from_ to""")
lowercase : Tuple = {
"""cubicmeter""": from_to(1, 1),
"""litre""": from_to(0.001, 1_0_0_0),
"""kilolitre""": from_to(1, 1),
"""gallon""": from_to(0.00_454, 264.172),
... | 392 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
import torch
... | 74 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : int = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Info... | 591 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimension_format,
)... | 307 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/config.json',
'xlnet-large-cased': 'https://huggingface.c... | 307 | 1 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCAmelCase_ :
def __init__( self ,snake_case__ ):
SCREAMING_SNAKE_CASE_ : Union[str, Any] = value
SCREAMING_SNAKE_CASE_ : Node | None = None
SCREAMING_... | 105 |
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class UpperCamelCase_ ( __UpperCamelCase ... | 479 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
lowerCAmelCase = False
class lowerCamelCase ( unittest.TestCase ):
def A( self ... | 675 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase = """sshleifer/bart-tiny-random"""
lowerCAme... | 675 | 1 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def A_ ( lowercase_ , lowercase_=False ) -> List[str]:
_snake_case : Union[str, Any] = OmegaConf.load(lowercase_ )
if display:
print(... | 326 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import Aut... | 326 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {"vocab_f... | 391 |
__magic_name__ = "ABCDEFGHIJKLMNOPQRSTUVWXYZ"
def _lowerCAmelCase ( ):
'''simple docstring'''
UpperCAmelCase = input('''Enter message: ''' )
UpperCAmelCase = input('''Enter key [alphanumeric]: ''' )
UpperCAmelCase =... | 391 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
UpperCamelCase__ : Optional[Any] = 6_378_137.0
UpperCamelCase__ : Union[str, Any] = 6_356_752.314_245
UpperCamelCase__ : int = 6_378_137
def SCREAMING_SNAKE_CASE__ ( snake_case_, s... | 387 |
'''simple docstring'''
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_i... | 561 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class __lowercase ... | 703 |
import numpy
class __lowercase :
def __init__( self : Union[str, Any] , __lowerCamelCase : numpy.ndarray , __lowerCamelCase : numpy.ndarray ) -> None:
"""simple docstring"""
... | 627 | 0 |
from ...processing_utils import ProcessorMixin
class __lowercase ( __snake_case ):
_A = "WhisperFeatureExtractor"
_A = "WhisperTokenizer"
def __init__(self : List[Any] , snake_case : Union[str, Any] , snake_case : Union[str, Any] ) -> List[Any]:
... | 461 |
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, r... | 461 | 1 |
"""simple docstring"""
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
A = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
from .safilesystem import SaFileSys... | 147 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class _UpperCamelCase ( metaclass=lowerCamelCase__ ):
"""simple docstring"""
snake_case_ = ['note_seq']
def __init__( self : List[Any] , *snake_case : Any , **snake_case : Any... | 147 | 1 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class lowercase ( __A , unittest.T... | 35 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__SCREAMING_SNAKE_CASE = {'tokenization_bertweet': ['BertweetTokenizer']}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
__SCREAMING_SNAKE_CASE = _Laz... | 220 | 0 |
"""simple docstring"""
import numpy as np
def lowerCamelCase ( _snake_case ):
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 254 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class a :
UpperCamelCase : int
UpperCamelCase : int
class a :
def __init__( ... | 254 | 1 |
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def lowerCamelCase__ (_UpperCAmelCase):
return getitem, k
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return setitem, k, v
def ... | 73 |
"""simple docstring"""
import string
def A_ ( snake_case_ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
UpperCamelCase : Optional[int] = """"""
for symbol in message:
if symbol in string.... | 499 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_util... | 185 |
def UpperCamelCase_( _A :str )-> int:
UpperCamelCase__ = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function" )
UpperCamelCase__ = hex_num[0] == "-"
if is_negative:
UpperCamelCase__ = hex_num[1:]
try:
Up... | 185 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPanoramaPipeline,
U... | 478 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import Au... | 65 | 0 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_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 check_copies # noqa: E402
# ... | 704 |
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
_lowercase = {
'''tiny.en''': '''https://openaipublic.azureedge.net/main/whisper/models/d3dd5... | 96 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
__UpperCAmelCase = logging.get_logger(__name__)
class lowercase_ ( a_ ):
def __init__( self : Dict , *_lowerc... | 308 |
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
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)... | 300 | 0 |
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def a ( lowerCamelCase_ , lowerCamelCase_=None ):
'''simple docstring'''
lowercase__ = None
if token is not None:
... | 671 |
from itertools import count
def a ( lowerCamelCase_ = 50 ):
'''simple docstring'''
lowercase__ = [1] * min_block_length
for n in count(lowerCamelCase_ ):
fill_count_functions.append(1 )
for block_length in range(lowerCamelCase_ , ... | 671 | 1 |
def lowercase_ ( __snake_case : int , __snake_case : str ) -> Union[str, Any]:
'''simple docstring'''
snake_case__ :int = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
... | 241 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowercase_ ( __snake_case : Optional[Any] ) -> List[Any]:
'''simple docstring'''
if (
(... | 241 | 1 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class a__ :
A = 42
A = None
A = None
__lowerCamelCase : int = namedtuple('''CoinsDistribResult''', '''moves excess''')
... | 702 | import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class a__ ( A__ , unittest.TestCase ):
A = Bi... | 316 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''facebook/data2vec-text-base'''... | 146 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Union[str, Any] ... | 65 | 0 |
'''simple docstring'''
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def lowerCamelCase__ ():
_SCREAMING_SNAKE_CASE : Tuple = [randint(-1000, 1000 ) for i in range(10 )]
_SCREAMING_S... | 717 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowerCAmelCase__:
'''simple docstring'''
def __init__( self , __lowerCamelCase ) -> Tuple:
_SCREAMING_SNAKE_CASE : List[str] = list_of_po... | 381 | 0 |
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE__ ( __lowerCAmelCase ):
snake_case__ = F"""https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"""
return requests.get(__lowerCAmelCase ).json()
def SCREAMING_SNAKE_CASE__ ... | 276 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = {
'''vocab_file''': '''vocab.json''',
'''merges_file''': '''merges.t... | 276 | 1 |
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... | 709 |
import os
import string
import sys
__a = 1 << 8
__a = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,
'left': 68 + ARROW_KEY_FLAG,
'mod_int': 91,
'undefined': ... | 300 | 0 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class lowerCAmelCase_ :
def __init__( self , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase=0.2 , _lower... | 18 |
'''simple docstring'''
import argparse
import json
import math
import os
import time
import traceback
import zipfile
from collections import Counter
import requests
def __a(SCREAMING_SNAKE_CASE_ : Any , SCREAMING_SNAKE_CASE_ : Tuple=None ):
'''simple docstring'''
... | 18 | 1 |
'''simple docstring'''
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
__lowerCAmelCase = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH AH QH""",
... | 716 |
'''simple docstring'''
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def UpperCAmelCase_ (__a : Dict , __a : Any=7 ):
"""simple docstring"""
_a : Dict = None
if token is not None:... | 319 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase : List[str] = {
"""configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],... | 543 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
lowerCAmelCase : Dict = namedtuple(
"""_TestC... | 543 | 1 |
def __A ( _A ):
"""simple docstring"""
if bit_count < 0:
raise ValueError("The given input must be positive" )
# get the generated string sequence
__a = gray_code_sequence_string(_A )
#
# convert them to integers
for i in range(len(_A ) ):
__a = int... | 713 | def __A ( _A = 100_0000 ):
"""simple docstring"""
__a = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , _A ):
phi[j] -= phi[j] // i
return sum(phi[2 : limit ... | 525 | 0 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ : Tuple = logging.get_logger(__name__)
class __lowerCAmelCase ( __magic_... | 98 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_... | 179 | 0 |
from __future__ import annotations
from math import pi
def UpperCAmelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError("One and only one argument must... | 716 |
from multiprocessing import Lock, Pipe, Process
# lock used to ensure that two processes do not access a pipe at the same time
snake_case_ : Optional[Any] =Lock()
def UpperCAmelCase ( lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase__ , lowerCAmelCase_... | 205 | 0 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
cla... | 96 |
from __future__ import annotations
__magic_name__ = list[list[int]]
# assigning initial values to the grid
__magic_name__ = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0, 0, 5],... | 254 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
_UpperCamelCase : Union[str, Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/ma... | 645 | """simple docstring"""
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_ba... | 645 | 1 |
"""simple docstring"""
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
_lowerCAmelCase = '\\n@inproceedings{wang2019glue,\n title={{GLUE}: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding},\n ... | 264 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
__UpperCAmelCase : Any = {
'vocab_file': 'vocab.json',... | 471 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
__A : Dict = True
except (ImportError, ModuleNotFoundError):
__A : Union[str, Any] = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
nltk.download('punkt', qu... | 701 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, r... | 281 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
_snake_case : str = argparse.ArgumentParser(
description=(
"Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"
" Distilla... | 81 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_snake_case : Optional[int] = logging.get_logger(__name__)
class a (_lowerCAmelCase ):
"""simple docstring"""
def __init__( self : Optional[Any] , ... | 81 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {'''configuration_timm_backbone''': ['''TimmBackboneConfig''']}
try:
if not is_torch_available():
raise OptionalDependencyNo... | 713 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resol... | 494 | 0 |
def UpperCamelCase_ ( __a , __a , __a , __a ) -> int:
a__, a__ : Union[str, Any] = len(__a ), len(grid[0] )
if (
min(__a , __a ) < 0
or row == row_length
or col == col_length
or (row, col) in visit
or... | 37 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def UpperCamelCase_ ( __a , __a , __a ) -> Optional[Any]:
a__ : Union[str, Any] = ("dense.weight", "attention.self.query", "attention.self.key", "attention.sel... | 37 | 1 |
"""simple docstring"""
def _UpperCAmelCase ( __lowerCamelCase : int = 10 , __lowerCamelCase : int = 10_00 , __lowerCamelCase : bool = True ) -> int:
assert (
isinstance(__lowerCamelCase , __lowerCamelCase )
and isinstance(__lowerCamelCas... | 717 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 430 | 0 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from ja... | 467 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
__lower... | 467 | 1 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator,
... | 496 | '''simple docstring'''
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data impo... | 496 | 1 |
"""simple docstring"""
from math import pow, sqrt
def _A ( *_a : float ):
"""simple docstring"""
A = len(_a ) > 0 and all(value > 0.0 for value in values )
return result
def _A ( _a : float , _a : float ):
... | 617 |
"""simple docstring"""
import unittest
from knapsack import greedy_knapsack as kp
class lowerCamelCase__ ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase__ ( self ) -> Any:
A = [1_0, 2_0, 3_0, 4_0, 5_0, 6_0]
A... | 617 | 1 |
import numpy as np
def _A ( __A: np.ndarray ,__A: np.ndarray ,__A: float = 1e-12 ,__A: int = 1_0_0 ,):
'''simple docstring'''
assert np.shape(__A )[0] == np.shape(__A )[1]
# Ensure proper dimensionality.
assert np.shape(__A )[0] == np.shap... | 714 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property
from ...test_t... | 501 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
_lowercase : Any = logging.get_logger(__name__)
def lowercase__ ( snake_case_ :Union[tf.Tensor, np.ndarray] ):... | 49 | """simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowercase__( __SCREAMING_SNAKE_CASE : An... | 425 | 0 |
"""simple docstring"""
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
_A = argparse.ArgumentParser()
parser.add_argument("""--dump_path""", default=None, t... | 718 |
"""simple docstring"""
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
_A = {
... | 507 | 0 |
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ... | 521 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_auto import TF... | 521 | 1 |
'''simple docstring'''
def _a( UpperCamelCase__ : list[list[float]] ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : list[list[float]] =[]
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
... | 665 |
'''simple docstring'''
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_... | 665 | 1 |
"""simple docstring"""
def _lowercase ( __snake_case ,__snake_case ) -> List[Any]:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def _lowercase ( __snake_case ,__snake_case=0 ) -> Tuple:
return sorted(__snake_case ,ke... | 293 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin... | 293 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
... | 61 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is... | 61 | 1 |
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 i... | 428 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
__SCREAMING_SNAKE_CASE : Union[str, Any] =False
class A_ ( unittest... | 428 | 1 |
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transformers.testing_utils imp... | 38 |
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
__lowerCamelCase : Dict ... | 38 | 1 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def _lowercase ( lowerCamelCase__ : str, lowerCamelCase__ : float | Decimal, lowerCamelCase__ : float = 10**-10 ):
_a = a
... | 131 |
'''simple docstring'''
import unittest
from transformers import XLMConfig, 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 im... | 131 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
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 Backbo... | 282 |
"""simple docstring"""
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... | 282 | 1 |
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
__lowerCAmelCase = logging.get_logger(__name__)
__lowerCAmelCase = """T5Config"""
class lowerCamelCase_ ( lowercase ):
... | 147 |
from ..utils import DummyObject, requires_backends
class lowerCamelCase_ ( metaclass=lowercase ):
__lowercase : str = ["note_seq"]
def __init__( self , *lowerCamelCase_ , **lowerCamelCase_ ) -> List[str]:
"""simple docstring"""
re... | 147 | 1 |
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,... | 253 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def __a ( __UpperCAmelCase : List[Any] , __UpperCAmelCase : Tuple=() , __UpperCAmelCase : List[str]=None ... | 253 | 1 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case_, snake_case_, snake_case_ ) -> float:
"""simple docstring"""
if days_between_payments <= 0:
raise ValueError('''days_between_payments must be > 0''' )
if daily_interest_rate < 0:
raise ValueErr... | 387 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class lowerCamelCase_ ( tf.keras.optimizers.schedules... | 387 | 1 |
import operator
def A__ ( snake_case_ : list , snake_case_ : bool = False , snake_case_ : list | None = None ):
SCREAMING_SNAKE_CASE__: List[Any]= operator.lt if reverse else operator.gt
SCREAMING_SNAKE_CASE__: Union[str, Any]= solution or []
if not arr:
retu... | 107 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase_ : List[str] = {
'configuration_maskformer': ['MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MaskFormerConfig'],
'configuration_maskformer_swin': ['M... | 107 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
"""configuratio... | 178 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_m... | 678 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCAmelCase : Union[str, Any] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 700 |
'''simple docstring'''
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
__UpperCAmelCase = 'http://... | 220 | 0 |
# 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_util... | 304 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def A__( __lowerCAmelCase ):
_snake_case : Dict = [
'decoder.version',
'decoder.output_projection.weight',
'_float... | 304 | 1 |
'''simple docstring'''
import qiskit
def __lowerCamelCase ( _lowercase , _lowercase ) -> qiskit.result.counts.Counts:
UpperCAmelCase : Any = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
UpperCAmelCase... | 707 |
'''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():
fr... | 672 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType
_lowerCamelCase = logging... | 6 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenizatio... | 465 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from diffusers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionPipeline,
PNDMScheduler,
)
from diffusers.uti... | 700 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=a_ ):
SCREAMING_SNAKE_CASE : List[str] = ['''torch''', '''torchsde''']
def __init__( self , *_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_CASE ):
'''si... | 514 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CA... | 369 |
def lowerCAmelCase__ ( lowerCamelCase_ : Dict ,lowerCamelCase_ : Optional[int]):
'''simple docstring'''
lowerCAmelCase__ : int = (boundary[1] - boundary[0]) / steps
lowerCAmelCase__ : Optional[int] = boundary[0]
lowerCAmelCase__ : ... | 647 | 0 |
UpperCAmelCase_ = 65_521
def __magic_name__ ( lowercase ) -> int:
"""simple docstring"""
lowercase_ : Tuple = 1
lowercase_ : int = 0
for plain_chr in plain_text:
lowe... | 715 |
import math
def __magic_name__ ( lowercase ) -> bool:
"""simple docstring"""
lowercase_ : Optional[Any] = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowercase ... | 436 | 0 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
'''simple docstring'''
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 65 | '''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class A ( UpperCAmelCase , UpperCAm... | 262 | 0 |
__lowerCamelCase = {
'''meter''': '''m''',
'''kilometer''': '''km''',
'''megametre''': '''Mm''',
'''gigametre''': '''Gm''',
'''terametre''': '''Tm''',
'''petametre''': '''Pm''',
'''exametre''': '''Em''',
'''zettametre''': '''Zm''',
'''yottametre''': '''Ym''',
}
# Expone... | 702 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class snake_case_ (lowercase__ ):
"""simple docstring"""
_lowerCamelCase = """ClapFeatureExtractor"""
_lowerCamelCase = ("""RobertaTokenizer""", """RobertaTokeniz... | 455 | 0 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class __lo... | 468 |
def _UpperCamelCase ( lowerCAmelCase_ ) ->Any:
UpperCAmelCase = 0
UpperCAmelCase = len(lowerCAmelCase_ )
for i in range(n - 1 ):
for j in range(i + 1 , lowerCAmelCase_ ):
if arr[i] > arr[j]:
num_inversions += 1
return num_invers... | 377 | 0 |
import jax.numpy as jnp
from ...utils import logging
from ..ta.modeling_flax_ta import FlaxTaEncoderModel, FlaxTaForConditionalGeneration, FlaxTaModel
from .configuration_mta import MTaConfig
_snake_case = logging.get_logger(__name__)
_snake_case = '''T5Config'''
def lowercase_(... | 231 |
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowercase_( SCREAMING_SNAKE_CASE_ = "isbn/0140328726" ):
'''simple docstring'''
lowerCamelCase : List[Any] = olid.strip().strip("/" ) # Remove leading... | 231 | 1 |
'''simple docstring'''
import math
def lowercase__ ( __lowercase : list , __lowercase : int = 0 , __lowercase : int = 0 ) -> list:
"""simple docstring"""
__UpperCamelCase = end or len(__lowercase )
for i in range(__lowercase , ... | 399 |
'''simple docstring'''
def lowercase__ ( __lowercase : int , __lowercase : Tuple , __lowercase : Tuple ) -> Any:
"""simple docstring"""
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(__lowerca... | 399 | 1 |
"""simple docstring"""
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, Test... | 141 |
"""simple docstring"""
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class _UpperCAm... | 141 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@requ... | 387 |
from collections.abc import Sequence
def SCREAMING_SNAKE_CASE__ ( snake_case_, snake_case_ ) -> float:
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(snake_case_ ) )
def SCREAMING_SNAKE_CASE__ ( snake_case_, snake_case_ ) -> float:
"""s... | 387 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json",
"microsoft/markuplm-large": "ht... | 714 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"studio-ousia/luke-base": "https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json",
"studio-ousia/luke-large": "https... | 548 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=_lowercase )
class lowerCamelCase_ ( _lowercase ):
# `task` is not a ClassVar since we want it to be part of the `asdict` outpu... | 17 |
def __SCREAMING_SNAKE_CASE ( a__ : int ) -> int:
if not isinstance(a__ ,a__ ):
raise TypeError("""Input value must be an 'int' type""" )
__A : Union[str, Any] = 0
while number:
position += 1
number >>= 1
return position
if __name__ == "__main__":
... | 17 | 1 |
"""simple docstring"""
import numpy as np
def UpperCamelCase_ ( lowerCamelCase : np.ndarray ) -> np.ndarray:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def UpperCamelCase_ ( lowerCamelCase : np.ndarray ) -> np... | 719 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
A = logging.getLogger()
@unittest.skip('Temporarily disable the doc tests.' )
@require... | 147 | 0 |
def _snake_case (_snake_case : Optional[int] , _snake_case : Tuple , _snake_case : Dict , _snake_case : Dict , _snake_case : Tuple , _snake_case : str) -> Dict:
if index == r:
for j in range(_snake... | 181 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class SCREAMING_SNAKE_CASE_ ( unittest.Te... | 181 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ba... | 441 |
from __future__ import annotations
def UpperCamelCase ( _a , _a = None , _a = None ) -> None:
'''simple docstring'''
if start is None:
lowercase_ :str = 0
if end is None:
lowercase_ :str = ... | 441 | 1 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagem... | 526 |
'''simple docstring'''
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 a__( lowerCamelCase__ ):
... | 526 | 1 |
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torch_availa... | 716 |
import argparse
import os
import re
A__ : Optional[int] = 'src/transformers'
# Pattern that looks at the indentation in a line.
A__ : Union[str, Any] = re.compile(r'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
A__ : List[str] = re.compil... | 671 | 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
a_ = logging.get_logger(__name__)
a_ = '▁'
a_ = {'vocab_file': 'sentencepiece.bp... | 417 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvNextConfig', 'ConvNextOnnxConfig']
}
tr... | 417 | 1 |
import os
from datetime import datetime as dt
from github import Github
_SCREAMING_SNAKE_CASE = [
'''good first issue''',
'''feature request''',
'''wip''',
]
def _lowerCAmelCase ( ):
__lowercase = Github(os.environ['''GITHUB_TOKEN'''] ... | 704 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _lowerCAmelCase ( ):
__lowercase = ArgumentParser('''Diffusers CLI tool''' , usage='''diffusers-cli <command> [<args>]''' )
__lowercase =... | 56 | 0 |
"""simple docstring"""
def lowercase_ ( _snake_case ):
if edge <= 0 or not isinstance(_snake_case ,_snake_case ):
raise ValueError("""Length must be a positive.""" )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
def lowercase_ ( _snake_case ):... | 223 |
"""simple docstring"""
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration... | 223 | 1 |
import argparse
import os
from accelerate.utils import ComputeEnvironment
from .cluster import get_cluster_input
from .config_args import cache_dir, default_config_file, default_yaml_config_file, load_config_from_file # noqa: F401
from .config_utils import _ask_field, _ask_options, _convert_compute_environmen... | 721 | import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase : Dict = logging.get_logger(__name__)
_lowerCamelCase : List[Any] = '''... | 647 | 0 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_swi... | 0 | import torch
from torch import nn
class UpperCAmelCase__ ( nn.Module ):
"""simple docstring"""
def __init__( self: int , __lowerCAmelCase: List[Any] , __lowerCAmelCase: str , __lowerCAmelCase: int , __lowerCAmelCase: List[Any] ... | 221 | 0 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmu... | 211 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
_UpperCamelCase = input("""Enter image url: """).strip()
print(f'Downloading image from {url} ...')
_UpperCamelCase = BeautifulSoup(requests.get(... | 211 | 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_dimens... | 547 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase__ = {
'''configuration_deberta''': ['''DEBERTA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DebertaConfig''', '''Deb... | 547 | 1 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
_lowercase: List[Any] = logging.get_logger(__name__)
class lowerCamelCase__ ( UpperCAmelCase ):
'''simple docstring'''
def __init__( self : Any , *lowercase__ ... | 716 | def _lowerCamelCase ( snake_case = 50_000_000 ):
_lowerCAmelCase = set()
_lowerCAmelCase = int((limit - 24) ** (1 / 2) )
_lowerCAmelCase = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in ra... | 225 | 0 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class a ( lowercase__ , lowercase__ ):
"... | 63 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import... | 327 | 0 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from tra... | 713 |
'''simple docstring'''
def UpperCamelCase_ ( A__ = 50 ):
a_ = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
different_colour_ways_number[row_length][tile_length... | 511 | 0 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 374 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict impo... | 374 | 1 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
lowerCAmelCase_ : Tuple = "\\n@inproceedings{popovic-2015-chrf,\n title = \"chr{F}: character n-gram {F}-score for automatic {MT} evaluation\",\n author = \"Popovi{\'c}, Maja\",\... | 461 | '''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
from .tokenization_gpta import GPTaTokenize... | 461 | 1 |
def A_ ( a ):
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : Optional[Any] = len(a )
SCREAMING_SNAKE_CASE_ : Tuple = len(matrix[0] )
SCREAMING_SNAKE_CASE_ : int = min(a , a )
for row in range(a ):
# Check if diago... | 511 |
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
lowerCAmelCase : Union[str, Any] = logging.get_logger(__name__)
class _A ( __magic_name__):
def __init__( self , *_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_CASE ):
... | 511 | 1 |
"""simple docstring"""
_a : List[str] = {
'A': ['B', 'C', 'E'],
'B': ['A', 'D', 'E'],
'C': ['A', 'F', 'G'],
'D': ['B'],
'E': ['A', 'B', 'D'],
'F': ['C'],
'G': ['C'],
}
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : dict ,_lowerCamelCase : Any ,_lowerCamel... | 663 | """simple docstring"""
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 OptionalDepen... | 663 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCamelCase_ : Optional[int] = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",
... | 548 |
"""simple docstring"""
import warnings
from diffusers import StableDiffusionInpaintPipeline as StableDiffusionInpaintPipeline # noqa F401
warnings.warn(
"The `inpainting.py` script is outdated. Please use directly `from diffusers import"
" StableDiffusionInpaintPipeline` instead."
)
| 155 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase__ : int = {'''configuration_vit''': ['''VIT_PRETRAINE... | 485 |
"""simple docstring"""
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
class _UpperCAmelCase ( low... | 485 | 1 |
"""simple docstring"""
import functools
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) ->int:
# Validation
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) or not all(isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) ... | 434 | """simple docstring"""
SCREAMING_SNAKE_CASE__ : int =6_5521
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ ) ->int:
_lowerCamelCase : Union[str, Any] = 1
_lowerCamelCase : List[str] = 0
for plain_chr in plain_text:
_lowerCamelCase : Di... | 434 | 1 |
'''simple docstring'''
import argparse
import os
import re
_lowerCAmelCase = '''src/transformers'''
# Pattern that looks at the indentation in a line.
_lowerCAmelCase = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCA... | 399 |
'''simple docstring'''
from collections import deque
from .hash_table import HashTable
class A ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def __init__(self , *_UpperCAmelCase , **_UpperCAmelCase ) -> List[str]:
su... | 399 | 1 |
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