code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
fro... | 64 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE_ ( ) -> Any:
"""simple docstring"""
a_ : Optional[Any] = HfArgumentParser(__A )
a_ : Optional[int] = parser.par... | 32 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case =logging.get_logger(__name__)
__snake_case ={
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.json""",
"""google/f... | 55 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester... | 55 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase : Tuple = {
"""configuration_autoformer""": [
"""AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AutoformerConf... | 20 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ :Dict = logging.get_logger(__name__)
lowercase__ :Optional[int] = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json",
# See a... | 101 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class __lowerCAmelCase ( A ):
def __init__( self : List[str] , A : List[Any] , A : Any , A : List[Any]) -> O... | 290 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerTokenizer
from .tokeni... | 290 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 53 |
'''simple docstring'''
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def lo... | 53 | 1 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
_UpperCAmelCase = False
try:
_UpperCAmelCase ... | 192 | from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNotAvailable()
... | 192 | 1 |
'''simple docstring'''
def __magic_name__( lowerCamelCase):
__lowerCAmelCase = len(lowerCamelCase)
for _ in range(lowerCamelCase):
for i in range(_ % 2, arr_size - 1, 2):
if arr[i + 1] < arr[i]:
__lowerCAmelCase , __... | 174 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from... | 174 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
lowerCamelCase_ = tuple[int, int]
class __A:
"""simple docstring"""
def __init__(self , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase__ = vertices
U... | 178 |
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowerCamelCase_ = logging.get_logger(__name__)
class __A( __lowerCamelCase ):
"""simple docstring"""
def __init__(self , *SCREAMING_SNAKE_CASE_ , **SCREAMING... | 178 | 1 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, rand... | 317 |
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():
... | 317 | 1 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
Wava... | 360 |
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
class _lowerCAmelCase( UpperCAm... | 292 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import requests
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
... | 145 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at ht... | 145 | 1 |
from __future__ import annotations
import time
from collections.abc import Sequence
from random import randint
from matplotlib import pyplot as plt
def _UpperCAmelCase (UpperCamelCase_ : Sequence[float] , UpperCamelCase_ : int , UpperCamelCase_ : int ):
'''simple docstring'''
... | 159 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def _UpperCAmelCase (UpperCamelCase_ : Tuple , UpperCamelCase_ : Dict ):
'''simple docstring'''
_lowerCAmelCase : ... | 159 | 1 |
'''simple docstring'''
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_u... | 1 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
UpperCAmelCase_ = logging.... | 346 | 0 |
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_RECORDS_FILENAME, RealmRe... | 70 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase : int = logging.get_logger(__name__)
_lowerCAmelCase : Dict = {
'''microsoft/git-base''': '''https://huggingface.co/microsoft/git-base/resol... | 70 | 1 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
Au... | 85 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def UpperCamelCase_( snake_case : Callable ):
'''simple docstring'''
@wraps(snake_case )
def _inner_fn(*snake_case : Optional[int] , **snak... | 85 | 1 |
"""simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threa... | 354 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNotAvailable... | 200 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"facebook/xlm-roberta-xl": "https://huggingface.co/face... | 177 | """simple docstring"""
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase ) -> int:
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
lowercase__... | 177 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ... | 335 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
@register_to_config
def __init__(self , *,
__a = 4 , __a ... | 335 | 1 |
"""simple docstring"""
import warnings
from functools import wraps
from typing import Callable
def _snake_case ( _snake_case : Callable ):
@wraps(_snake_case )
def _inner_fn(*_snake_case : Optional[int] , **_snake_case : str ):
warnings.warn(
(f'''\'{fn... | 60 |
"""simple docstring"""
def _snake_case ( _snake_case : list ):
def merge(_snake_case : list , _snake_case : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
y... | 60 | 1 |
"""simple docstring"""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
__SCREAMING_SNAK... | 367 |
"""simple docstring"""
import copy
import tempfile
import unittest
from transformers import MaMaaaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from transformers.utils import cached_property
from ...generation.test_uti... | 233 | 0 |
'''simple docstring'''
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def __magic_name__( lowerCamelCase):
monkeypatch.setattr('''datasets.utils.deprecation_utils._emitted_deprecation_warnings''', set())
@pytest.fixture
def __magic_... | 174 |
"""simple docstring"""
import os
def snake_case ( ):
with open(os.path.dirname(A__ ) + "/grid.txt" ) as f:
UpperCAmelCase_ : Any = [] # noqa: E741
for _ in range(20 ):
l.append([int(A__ ) for x in f.readline().split()] )
UpperCAm... | 268 | 0 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _UpperCAmelCase ( SCREAMING_SNA... | 358 |
from __future__ import annotations
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
if b == 0:
return (1, 0)
((__UpperCamelCase) , (__UpperCamelCase)) =extended_euclid(SCREAMING_SNAKE_CASE__ , a % ... | 117 | 0 |
"""simple docstring"""
from typing import 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 ...... | 109 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : List[str] = {
"google/pix2st... | 93 | 0 |
'''simple docstring'''
import numpy as np
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
return 1 / (1 + np.exp(-vector ))
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
return vector * sigmoid(1.702 * vector )
if __name__ == "__main__":
import doctes... | 361 |
'''simple docstring'''
from __future__ import annotations
import typing
from collections import Counter
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE ):
_snake_case = Counter()
for base in range(1 , max_perimeter + 1 ):
for perpendicular in range(_SCREAMI... | 270 | 0 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowerCamelCase__ ( _a , _a , _a , _a):
SCREAMING_SNAKE_CASE : Any = {
"en": "Machine learning is great, isn't it?",
"ru": "Машинное обучение - это здорово, не так ли?",
"de"... | 76 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowerCamelCase__ ( _a):
SCREAMING_SNAKE_CASE : int = {}
SCREAMING_SNAKE_CASE : Any = token... | 76 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase = {
'''configuration_pix2struct''': [
'''PIX2STRUCT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''Pix2Str... | 350 |
'''simple docstring'''
def a__ ( _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(_SCREAMING_SNAKE_CASE : int , _SCREAMING_SN... | 67 | 0 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@requi... | 159 |
def _lowerCAmelCase ( lowerCAmelCase_ :int | float | str )->tuple[int, int]:
'''simple docstring'''
try:
snake_case_ = float(lowerCAmelCase_ )
except ValueError:
raise ValueError("Please enter a valid number" )
snake_case_ = ... | 159 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
_SCREAMING_SNAKE_CASE = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
impor... | 350 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.or... | 3 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __UpperCAmelCase ( A__ ):
'''simple docstring'''
__lowerCAmelCase = (DDPMParallelScheduler,)
def A (self : Lis... | 258 |
"""simple docstring"""
import sys
import turtle
def lowercase (_lowerCAmelCase , _lowerCAmelCase ):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowercase (_lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , ):
my_pen.up()... | 301 | 0 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data impo... | 354 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase = "cpu" , _UpperCamelCase = None ):
'''simple docstring'''
__lowerCAmelCase = torch.load(_UpperCamelCase , map_location... | 259 | 0 |
import os
def lowerCamelCase__ ( ):
'''simple docstring'''
__lowerCamelCase = os.path.dirname(os.path.realpath(A__ ) )
__lowerCamelCase = os.path.join(A__ , """triangle.txt""" )
with open(A__ ) as f:
__lowerCamelCase = f... | 12 |
'''simple docstring'''
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
a_ : Dict ... | 55 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowercase : Tuple = logging.getLogger(__name__)
def snake_case__ ( ):
"""simple docstring"""
lowerCamelCase__ : Any ... | 272 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __SCREAMING_SNAKE_CASE ( metaclass=lowerCAmelCase_ ):
'''simple docstring'''
_a = ['torch', 'torchsde']
def __init__( self : Union[str, Any], *lowerCamelCase ... | 272 | 1 |
import pytest
import datasets
# Import fixture modules as plugins
lowerCAmelCase_ = ['''tests.fixtures.files''', '''tests.fixtures.hub''', '''tests.fixtures.fsspec''']
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
# Mark tests as "unit" by d... | 8 |
import argparse
from tax import checkpoints
from transformers import AutoConfig, FlaxAutoModelForSeqaSeqLM
def lowerCAmelCase__ ( a__: Tuple , a__: Optional[Any] , a__: Any ) -> List[Any]:
'''simple docstring'''
_UpperCAmelCase = AutoConfig.from_pretrained(a__ ... | 329 | 0 |
'''simple docstring'''
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from toke... | 190 |
'''simple docstring'''
import itertools
import math
def _lowerCAmelCase ( __snake_case : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Ne... | 190 | 1 |
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import TEXT_GUIDED_IM... | 26 |
import math
def snake_case_ ( 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
... | 233 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSD... | 352 |
"""simple docstring"""
def a__ ( __lowercase , __lowercase ) -> float:
_validate_point(__lowercase )
_validate_point(__lowercase )
if len(__lowercase ) != len(__lowercase ):
raise ValueError("Both points must be in the same n-dimensional space" )... | 163 | 0 |
def lowerCamelCase__ ( a__ : str ) -> str:
UpperCamelCase_ = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def lowerCamelCase__ ( a__ : str ) ... | 122 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase_ = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Con... | 201 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class lowerCAmelCase__ ( UpperCAmelCase__ ):
def lowerCAmelCase__ ( self : Tupl... | 367 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
... | 322 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase__ : List[str] = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokeni... | 324 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[str] = logging.get_logger(__name__)
lowercase__ : Optional[int] = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/as... | 324 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowercase ( __UpperCAmelCase ):
lowercase_ = ['image_processor', 'tokenizer']
lowercase_ = 'ChineseCLIPImageProcessor'
lowercase_ = ... | 367 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
... | 205 | 0 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
_lowerCAmelCase = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snover, Matthew an... | 37 |
import numpy as np
# Importing the Keras libraries and packages
import tensorflow as tf
from tensorflow.keras import layers, models
if __name__ == "__main__":
# Initialising the CNN
# (Sequential- Building the model layer by layer)
_snake_case : Any = models.Sequential()
# Step 1 - Convol... | 123 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers impo... | 280 |
'''simple docstring'''
# Lint as: python3
import itertools
import os
import re
lowercase__ = re.compile(r"([A-Z]+)([A-Z][a-z])")
lowercase__ = re.compile(r"([a-z\d])([A-Z])")
lowercase__ = re.compile(r"(?<!_)_(?!_)")
lowercase__ = re.compile(r"(_{2... | 280 | 1 |
def A ( _lowercase ):
SCREAMING_SNAKE_CASE : List[Any] = 0
SCREAMING_SNAKE_CASE : Any = len(snake_case__ )
for i in range(n - 1 ):
for j in range(i + 1 , snake_case__ ):
if arr[i] > arr[j]:
... | 182 |
'''simple docstring'''
class A :
def __init__( self , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Tuple:
"""simple docstring"""
A : Any = None
A : Optio... | 3 | 0 |
"""simple docstring"""
lowerCamelCase__ = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
... | 357 |
"""simple docstring"""
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowerCamelCase__ = "%20".join(argv[1:]) if len(argv) > 1 else quote(str(input("Search... | 310 | 0 |
"""simple docstring"""
def UpperCAmelCase__ (snake_case__ : int ):
"""simple docstring"""
if not isinstance(snake_case__ , snake_case__ ):
_snake_case : Tuple = F"Input value of [number={number}] must be an integer"
raise TypeError(snake_case... | 64 |
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
... | 159 | 0 |
"""simple docstring"""
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
_lowerCAmelCase : List[str] = ... | 371 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
_lowerCAmelCase : List[str] ... | 340 | 0 |
import math
from numpy import inf
from scipy.integrate import quad
def UpperCAmelCase_ ( __lowerCAmelCase ) -> float:
if num <= 0:
raise ValueError('''math domain error''' )
return quad(__lowerCAmelCase , 0 , __lowerCAmelCase , args=(__lowerCAmelCase) )[0]
... | 156 |
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.configuration_utils impo... | 156 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class UpperCamelCase_ ( _lowerCamelCase ... | 295 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
@property
def lowerCAmelCase ( self )... | 295 | 1 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A : Optional[int] = logging.get_logger(__name__)
A : Optional[Any] = {
"xlnet-base-cased": "https://huggingface.co/xlnet-base-cased/resolve/main/config.json",
... | 57 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(_UpperCamelCase , _UpperCamelCas... | 57 | 1 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowerCamelCase : Any = "\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Huma... | 358 |
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's easier to use for... | 208 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slo... | 284 |
'''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
__A =namedtuple(
'_TestCommandArgs',
[... | 163 | 0 |
from collections import defaultdict
from math import gcd
def lowerCamelCase ( UpperCAmelCase__ : int = 1500000 ) -> int:
lowercase_ : defaultdict = defaultdict(UpperCAmelCase__ )
lowercase_ : Any = 2
while 2 * euclid_m * (euclid_m + 1) <= li... | 364 | '''simple docstring'''
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_lowercase : Union[str, Any] ... | 21 | 0 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def UpperCAmelCase_ ( __lowerCamelCase : int ,__lowerCamelCase : int ,__lowerCamelCase : int ,__lowerCamelCase : int ,__lowerCame... | 223 |
'''simple docstring'''
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import VideoMAEConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow,... | 223 | 1 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class _a ( _lowercase):
_a : List[str] = (DDIMParallelScheduler,)
_a : str = (('''eta''', 0.0), ('''num_inference_steps''', 50))
def ... | 352 |
import math
class _a :
def __init__( self : List[Any] , _SCREAMING_SNAKE_CASE : Any=0 )-> Optional[Any]: # a graph with Node 0,1,...,N-1
lowerCAmelCase__ : Optional[int] = n
lowerCAmelCase__ : List[Any] = [
[math.inf fo... | 211 | 0 |
class __lowerCAmelCase :
def __init__( self ) -> Optional[int]:
'''simple docstring'''
a__ : int =0
a__ : Union[str, Any] =0
a__ : int ={}
def _lowe... | 95 |
"""simple docstring"""
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 a__ ... | 202 | 0 |
from sklearn.metrics import matthews_corrcoef
import datasets
_A = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true and false positive... | 369 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_A = {
"configuration_lilt": ["LILT_PRETRAINED_CONFIG_ARCHIVE_MAP", "LiltConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except Op... | 137 | 0 |
"""simple docstring"""
import torch
from diffusers import StableDiffusionPipeline
__lowercase = """path-to-your-trained-model"""
__lowercase = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
__lowercase = ... | 40 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
a_ = logging.get_logger(__name__)
a_ = {name: getattr(transformers, name + '''Fast''') for name in SLOW_TO_FAST_CONVERTERS}
de... | 340 | 0 |
import sys
__UpperCAmelCase : Dict = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'668966489504452445231617318... | 353 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__UpperCAmelCase : Optional[int] = ""
__UpperCAmelCase : Union[str, Any] = ""
__UpperCAmelCase : Optional[int] = ""
__UpperCAmelCase : Any = 1 # (0 is vertical, 1 is horizontal)
de... | 315 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCAmelCase_ ( nn.Module ):
"""simple docstring"""
UpperCAmelCase__ : int... | 235 |
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
a__ = logging.get_logger(__name__)
def __UpperCAmelCase ( __a : Dict ) -> Tuple:
"""simple docstring"""
_a ... | 235 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase ( a_ ):
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
... | 370 |
"""simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
_A = logging.getLogger(__name__)
class _lowercase :
def __init__( self ) ... | 205 | 0 |
_snake_case = {}
def _UpperCamelCase ( snake_case__, snake_case__, snake_case__ ) -> int:
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed any other rules,
# we have a prize string
... | 157 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_enabled(False)
def... | 340 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_com... | 365 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_utils import is... | 278 | 0 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
lowerCAmelCase_ = {
'''config''': [
'''EXTERNAL_DATA_FORMAT_SIZE_LIMIT''',
'''OnnxConfig''',
'''OnnxConfigWithPast''',
'''OnnxSeq2SeqConfigWithPast''',
'''PatchingSpec''',
],
'... | 8 |
def snake_case_ ( snake_case ) -> int:
if n == 1 or not isinstance(snake_case , snake_case ):
return 0
elif n == 2:
return 1
else:
lowercase__: Optional[Any] = [0, 1]
for i in range(2 , ... | 196 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...im... | 366 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS... | 292 | 0 |
"""simple docstring"""
from timeit import timeit
def a_ ( _lowerCAmelCase : int ):
'''simple docstring'''
if number < 0:
raise ValueError('the value of input must not be negative' )
lowercase__ : Any = 0
while number:
... | 77 | """simple docstring"""
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( _lowerCAmelCase : Tuple , _lowerCAmelCase : Optional[int] , _lo... | 77 | 1 |
"""simple docstring"""
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _a :
"""simple docstring"""
UpperCamelCase__ = None
UpperCamelCase__ = False
UpperCamelCase__ = False
Upper... | 368 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class _a ( lowerCAmelCase , unittest.TestCase):
"""simple docstring... | 326 | 0 |
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase : Any = "\nThe F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:\nF1 = 2 * (precision * recall) / (precision + recall)\n"
UpperCAmelCase : List[Any] = "\nArgs:\n ... | 280 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE : str = {
"configuration_llama": ["LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP"... | 21 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def A ( a_ = True ,*a_ ,**a_ ) -> Dict:
if not is_tqdm_available():
raise ImportError('Accelerat... | 245 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import... | 245 | 1 |
'''simple docstring'''
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
__UpperCAmelCase ="\\n@misc{wu2016googles,\n title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n ... | 67 | '''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .token... | 67 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision... | 367 |
'''simple docstring'''
from __future__ import annotations
def _A ( snake_case , snake_case = None , snake_case = None ) -> None:
if start is None:
_lowercase : Dict = 0
if end is None:
_lowercase : List[Any] = l... | 199 | 0 |
__snake_case : Dict = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(10_00_00)]
def _UpperCAmelCase ( a__):
'''simple docstring'''
a_ : str = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.
sum_of_digit... | 248 |
'''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_c... | 298 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=lowerCAmelCase_ ):
_lowerCamelCase : Optional[Any] = ["""speech"""]
def __init__( self : List[str] , *snake_case_ : int , **snake_case_ : Dict ):
... | 156 |
'''simple docstring'''
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 156 | 1 |
'''simple docstring'''
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
... | 271 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMSchedu... | 202 | 0 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class SCREAMING_SNAKE_CASE__ ( pl.LightningModule ):
"""simple docstring"""
def __init__( self : Any , __A ... | 369 |
import sys
__lowerCamelCase : List[str] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""... | 286 | 0 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffusers.sche... | 222 |
import inspect
import unittest
from math import floor
from transformers import CvtConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common import Confi... | 222 | 1 |
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
lowerCAmelCase : Any = logging.getLogger()
def A_( A... | 354 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
lowerCAmelCase : str = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4:... | 251 | 0 |
'''simple docstring'''
import os
import sys
import unittest
lowercase__ : Optional[Any] = 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_te... | 190 |
'''simple docstring'''
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.c... | 190 | 1 |
from collections.abc import Sequence
from queue import Queue
class lowerCamelCase :
'''simple docstring'''
def __init__( self , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase , _UpperCamelCase=None , _UpperCamelCase=None ) -> ... | 350 |
from __future__ import annotations
def lowercase__ ( __snake_case : list[int] , __snake_case : int ):
'''simple docstring'''
if len(__snake_case ) < k or k < 0:
raise ValueError('Invalid Input' )
UpperCAmelCase_ : int ... | 145 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_UpperCamelCase : Optional[int] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP'... | 304 | from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_te... | 143 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case : Optional[int] = {'''configuration_mbart'''... | 366 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transformers.utils import... | 109 | 0 |
'''simple docstring'''
from math import ceil
def snake_case_ ( _lowerCAmelCase : Optional[int] , _lowerCAmelCase : List[str] ) -> Tuple:
UpperCAmelCase : List[Any] = list(range(0 , _lowerCAmelCase ) )
UpperCAmelCase :... | 23 |
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
i... | 154 | 0 |
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : list) -> list:
'''simple docstring'''
__UpperCamelCase : str = len(_SCREAMING_SNAKE_CASE)
for _ in range(_SCREAMING_SNAKE_CASE):
for i in range(_ % 2 , arr_size - 1 ... | 351 |
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
lowercase : List[str] = logging.get_logger(__name__)
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : ... | 151 | 0 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
_A : Union[str, Any] = logging.get_logger(__name__)
_A : Optional[Any] = {
'''goog... | 229 | '''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_A : str = logging.get_logger(__name__)
_A : str = [
['''a... | 229 | 1 |
def __UpperCamelCase ( UpperCAmelCase ):
if not isinstance(UpperCAmelCase , UpperCAmelCase ):
raise ValueError('''multiplicative_persistence() only accepts integral values''' )
if num < 0:
raise ValueError('''multiplicative_persistence() does not accept negative values''' )
low... | 356 | '''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenizatio... | 214 | 0 |
"""simple docstring"""
import cva
import numpy as np
class __A :
"""simple docstring"""
def __init__( self , __A , __A ) -> int:
if k in (0.04, 0.06):
a =k
a =window_size
else:
raise V... | 81 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinvaConfig, SwinvaForImageClassification
def _A ( ... | 81 | 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_big_bird import BigB... | 367 |
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_... | 141 | 0 |
def __snake_case ( _lowerCAmelCase : float , _lowerCAmelCase : float ) -> float:
if density <= 0:
raise ValueError("Impossible fluid density" )
if bulk_modulus <= 0:
raise ValueError("Impossible bulk modulus" )
return (bulk_modulus / density) ** 0.5
... | 300 |
from typing import 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 ....file_utils import Pa... | 300 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase (__UpperCamelCase : Union[str, Any] , __UpperCamelCase : Optional[Any] , __UpperCamelCase : int ):
"""simple docstring"""
if len(lowerCamelCase_ ) == 0:
raise ValueError('''find... | 368 | """simple docstring"""
def lowerCAmelCase (__UpperCamelCase : Dict , __UpperCamelCase : Optional[Any] ):
"""simple docstring"""
__UpperCamelCase =[0 for i in range(r + 1 )]
# nc0 = 1
__UpperCamelCase =1
for i in range(1 , n + 1 ):
... | 85 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 330 |
from math import sqrt
def lowerCAmelCase ( lowerCAmelCase_ )-> bool:
assert isinstance(lowerCAmelCase_ , lowerCAmelCase_ ) and (
number >= 0
), "'number' must been an int and positive"
lowerCAmelCase_ : List[Any] = True
# 0 and 1 are ... | 262 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake... | 371 | """simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
IMAG... | 64 | 0 |
"""simple docstring"""
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
... | 33 |
"""simple docstring"""
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..... | 260 | 0 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxC... | 359 |
"""simple docstring"""
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from i... | 226 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE :List[Any] = {
''... | 159 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def _lowerCAmelCase ( )->Any:... | 159 | 1 |
"""simple docstring"""
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowerCamelCase__ ( unittest.TestCase ):
... | 341 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__A = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a Met... | 341 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch_available():
... | 110 |
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
AutoMode... | 110 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
a_ = {'configuration_speech_encoder_decoder': ['SpeechEncoderDecoderConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 50 | import math
import flax.linen as nn
import jax.numpy as jnp
def __lowercase ( lowerCamelCase : jnp.ndarray , lowerCamelCase : int , lowerCamelCase : float = 1 , lowerCamelCase : float = 1 , lowerCamelCase : float = 1.0e4 , lowerCamelCase : bool = False , lowerCa... | 50 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : List[Any] = ... | 77 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require... | 151 | 0 |
"""simple docstring"""
from __future__ import annotations
import time
lowerCAmelCase__ = list[tuple[int, int]]
lowerCAmelCase__ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
... | 355 |
"""simple docstring"""
def snake_case_ ( A_ : int ):
'''simple docstring'''
return 1 if digit in (0, 1) else (digit * factorial(digit - 1 ))
def snake_case_ ( A_ : int ):
'''simple docstring'''
_lowerCamelCase : str = ... | 175 | 0 |
'''simple docstring'''
UpperCamelCase__ : Optional[int] = '0.18.2'
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_a... | 344 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 345 | 0 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
snake_case : Tuple = argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', default=None, type=str, requir... | 370 |
def __lowercase ( __lowerCAmelCase : Optional[Any] ):
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
5: [2, 6, 8],
6: [5, 7],
7... | 109 | 0 |
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