code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from itertools import permutations
def __magic_name__ ( _lowerCamelCase: tuple ) -> bool:
'''simple docstring'''
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowerCAmelCase ... | 535 |
"""simple docstring"""
UpperCAmelCase = 8.3_144_598
def __magic_name__ ( _lowerCamelCase: float, _lowerCamelCase: float ) -> float:
'''simple docstring'''
if temperature < 0:
raise Exception('''Temperature cannot be less than 0 K''' )
if molar_mass <= 0:
raise Exce... | 535 | 1 |
'''simple docstring'''
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class __UpperCAmelCase ( __a ):
def __init__( self , _lowerCamelCase... | 717 | '''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from de... | 606 | 0 |
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTeste... | 216 | import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__lowerCamelCase : str = get_logger(__name__)
class a__ ( enum.Enum ):
A = 'all_checks'
A = 'basic_checks'
A ... | 216 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCamelCase( UpperCamelCase__ : int ) -> list[int]:
if num <= 0:
A : str = F'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(UpperCamelCase__ ... | 537 |
'''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
... | 537 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase : str = {
"""configuration_blenderbot""": [
... | 142 |
"""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 OptionalDependenc... | 142 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_com... | 468 |
"""simple docstring"""
import argparse
import shlex
import runhouse as rh
if __name__ == "__main__":
# Refer to https://runhouse-docs.readthedocs-hosted.com/en/latest/api/python/cluster.html#hardware-setup for cloud access
# setup instructions, if using on-demand hardware
# If us... | 468 | 1 |
'''simple docstring'''
def lowercase__ ( __UpperCamelCase : list ):
'''simple docstring'''
__lowercase = False
while is_sorted is False: # Until all the indices are traversed keep looping
__lowercase = True
for i in range(0 , len(__... | 566 |
'''simple docstring'''
from string import ascii_uppercase
snake_case : List[str] = {str(ord(c) - 55): c for c in ascii_uppercase}
def lowercase__ ( __UpperCamelCase : int , __UpperCamelCase : int ):
'''simple docstring'''
if isinstance(__UpperCamelCase ,... | 566 | 1 |
class __lowerCAmelCase : # Public class to implement a graph
"""simple docstring"""
def __init__( self : Optional[Any] , _snake_case : int , _snake_case : int , _snake_case : list[list[bool]] ):
"""simple do... | 704 |
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__":
SCREAMING_SNAKE_CASE__ = '''%20'''.join(argv[1:]) if len(argv) > 1 else quote(str(input('''Search: ''')))
... | 52 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mobilebert import MobileBertTokenizer
lowerCamelCase : List[Any] =logging.get_l... | 228 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension... | 228 | 1 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
s... | 712 |
'''simple docstring'''
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.dat... | 355 | 0 |
def __SCREAMING_SNAKE_CASE ( lowercase_ ) -> List[Any]:
'''simple docstring'''
__UpperCAmelCase : Optional[Any] = set()
# edges = list of graph's edges
__UpperCAmelCase : List[Any] = get_edges(lowercase_ )
# While there ... | 462 |
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from .... | 62 | 0 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_acc... | 708 |
class _UpperCamelCase:
def __init__( self : List[Any] , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE__ : Union[str, Any] ):
'''simple docstring'''
__a : List[A... | 577 | 0 |
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
A__ : int = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full BertForMaskedLM or RObertaForMaskedLM for Transfer Learned"""
"""... | 233 |
import doctest
import glob
import importlib
import inspect
import os
import re
from contextlib import contextmanager
from functools import wraps
from unittest.mock import patch
import numpy as np
import pytest
from absl.testing import parameterized
import datasets
from datasets import load_metric
from .utils import... | 233 | 1 |
'''simple docstring'''
from __future__ import annotations
import copy
import inspect
import json
import math
import os
import tempfile
import unittest
from importlib import import_module
import numpy as np
from transformers import ViTMAEConfig
from transformers.file_utils import cached_property, is_tf_ava... | 575 |
'''simple docstring'''
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 _SCREAMING_SNAKE_CASE :
"""simple docstring"""
... | 575 | 1 |
'''simple docstring'''
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# full voca... | 614 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase : Union[str, Any] ... | 242 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_senten... | 703 | '''simple docstring'''
def _lowerCamelCase ( lowerCamelCase_ : str , lowerCamelCase_ : int ):
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(lowerCamelCase_ ) - ngram_size + 1 )]
if __name__ == "__main__":
from docte... | 389 | 0 |
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,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
Wav... | 112 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction_utils import FeatureExtra... | 112 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.util... | 292 |
"""simple docstring"""
def lowercase_ ( _lowercase : list , _lowercase : int , _lowercase : int = 0 , _lowercase : int = 0 ):
'''simple docstring'''
UpperCAmelCase : Tuple = right or len(_lowercase ) - 1
if le... | 292 | 1 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDE... | 87 |
"""simple docstring"""
from math import factorial
class A__ :
'''simple docstring'''
def __init__( self: str , _SCREAMING_SNAKE_CASE: Tuple , _SCREAMING_SNAKE_CASE: Any) -> str:
"""simple docstring"""
__lowerCAmelCa... | 293 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_a : str = logging.get_logger(__name__)
_a : Any = {
"""andreasmadsen/efficient_mlm_m0.40""": (
... | 111 |
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_warmup, set_seed
from accelerate import Accelerator... | 111 | 1 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
__snake_case :Tuple =True
... | 106 |
"""simple docstring"""
def UpperCAmelCase ( A : list[int] , A : list[int] ):
'''simple docstring'''
if not len(A ) == len(A ) == 3:
raise ValueError('Please enter a valid equation.' )
if equationa[0] == equationa[1] == equationa... | 573 | 0 |
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers import VQDiffusionScheduler
from ...utils ... | 721 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def _a ( SCREAMING_SNAKE_CASE : Namespace ):
"""simple docstring"""
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch_dump_output , ar... | 106 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_distilbert import DistilBertTokenizer
A : Dict = logging.get_logger(__name__)
A :... | 15 |
"""simple docstring"""
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, ... | 196 | 0 |
'''simple docstring'''
import math
import random
def lowerCamelCase__ ( a , a = False ):
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
_lowercase = 0.02
def lowerCamelCase__ ( a , a ):
... | 705 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuration_co... | 427 | 0 |
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, slow, torch_device
f... | 639 |
"""simple docstring"""
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from acce... | 674 | 0 |
"""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.dat... | 616 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_fea... | 616 | 1 |
'''simple docstring'''
import math
from numpy import inf
from scipy.integrate import quad
def a__ ( a__ ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(a__ , 0 , a__ , args=(a__) )[0]
def a__ ... | 627 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCAmelCase : List[str] = {
'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}
try:
if not is_torch_available():
... | 164 | import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__lowerCAmelCase : Tuple = logging.get_logger(__name__)
__lowerCAmelCase : ... | 164 | 1 |
'''simple docstring'''
from math import factorial
def __snake_case ( _UpperCAmelCase : int = 20):
UpperCamelCase = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCamelCase = n // 2
return int(factorial(_UpperCAmelCas... | 212 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProc... | 212 | 1 |
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sqlalchemy
def _lowerCAmelCase (_lowerCAme... | 709 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _lowercase (a_ ):
'''simple docstring'''
lowercase__ = (CMStochasticIterativeScheduler,)
lowercase__ = 10
def _lowerCamelC... | 504 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InformerConfig''',
],
}
try:
... | 157 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE ):
A__ : str = '''bert-generation'''
def __init__( self : Tuple , __lowerCamelCase : Optional[int]=5_0_3_5_8 ... | 103 | 0 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def snake_case (A_ :Any , A_ :int , A_ :Optional[int] , A_ :Optional[int] ):
'''simple docstring'''
a : int = s.r... | 118 |
"""simple docstring"""
def snake_case (A_ :int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
a : Any = [0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
a : Optional[int] = 1
... | 118 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandins... | 452 |
'''simple docstring'''
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sente... | 72 | 0 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
W... | 706 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make... | 78 | 0 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configurat... | 151 |
def UpperCAmelCase_ ( __UpperCamelCase ):
if len(__UpperCamelCase ) <= 1:
return lst
SCREAMING_SNAKE_CASE__ =1
while i < len(__UpperCamelCase ):
if lst[i - 1] <= lst[i]:
i += 1
else:
SCREAMING_SNAKE_CASE__ , ... | 151 | 1 |
def A__ ( lowercase: float, lowercase: 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
if ... | 700 | _lowercase : Dict ='''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import ... | 661 | 0 |
"""simple docstring"""
import ast
import os
import re
import shutil
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.test_utils.examples import compare_against_test
from accelerate.test_utils.testing import TempDirTestCase, require_trackers, run_command, slow
from accel... | 682 |
"""simple docstring"""
def snake_case ( _a: list , _a: int = 0 )-> list:
'''simple docstring'''
lowerCamelCase__ = length or len(_a )
lowerCamelCase__ = False
for i in range(length - 1 ):
if list_data[i] > list_data[i +... | 510 | 0 |
"""simple docstring"""
import itertools
import string
from collections.abc import Generator, Iterable
def a_ ( _lowerCAmelCase : Iterable[str] , _lowerCAmelCase : int ):
'''simple docstring'''
lowercase__ : Any = iter(_lowerCAmelCase )
... | 645 | """simple docstring"""
from __future__ import annotations
def a_ ( _lowerCAmelCase : float , _lowerCAmelCase : float , _lowerCAmelCase : float , ):
'''simple docstring'''
if (stress, tangential_force, area).count(0 ) != 1:
... | 645 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_c... | 366 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase( SCREAMING_SNAKE_CASE_ ,SCREAMING_SNA... | 366 | 1 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_... | 246 | from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=__snake_case )
class a__ ( __snake_case ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output... | 246 | 1 |
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase ) -> Tuple:
UpperCamelCase__ : Tuple = [
"encoder.version",
... | 228 |
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowerCamelCase : Dict =logging.get_logger(__name__)
lowerCamelCase : int =[
['''at... | 228 | 1 |
"""simple docstring"""
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffu... | 690 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class A__( unittest.Tes... | 690 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A__ )
class __UpperCamelCase ( A__ ):
__A : str = field(default="""language-modeling""" , metadata={"""include_i... | 32 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf i... | 460 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 707 |
"""simple docstring"""
import tensorflow as tf
from ...tf_utils import shape_list
class _UpperCAmelCase ( tf.keras.layers.Layer):
def __init__( self : int , lowercase_ : Tuple , lowercase_ : Union[str, Any] , lowercase_ : Tuple , lowercase_ : List[Any] , lowercase_ : Tuple... | 485 | 0 |
'''simple docstring'''
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def A_( A : Dataset , A : Dict[str, str]):
UpperCamelCase... | 3 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xfor... | 435 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_toke... | 701 | """simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from ... | 674 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A : List[str] = logging.g... | 231 |
"""simple docstring"""
import functools
from typing import Any
def lowerCamelCase__ ( _lowerCamelCase : str , _lowerCamelCase : list[str] ) -> bool:
# Validation
if not isinstance(_lowerCamelCase , _lowerCamelCase )... | 549 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"BAAI/AltCLIP": "https://huggingface.co/BAAI/AltCLIP/resolve/main/c... | 700 |
"""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... | 480 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_fea... | 93 |
"""simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditi... | 93 | 1 |
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 SCREAMING_SNAKE_CASE__ ( lowercase ) -> ... | 684 |
def SCREAMING_SNAKE_CASE__ ( lowercase ) -> list:
for i in range(len(lowercase ) - 1 ,0 ,-1 ):
snake_case : Any = False
for j in range(lowercase ,0 ,-1 ):
if unsorted[j] < unsorted[j - 1]:
snake_case , snake_case : Option... | 684 | 1 |
"""simple docstring"""
a_ = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import StreamingD... | 437 | """simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokeni... | 586 | 0 |
"""simple docstring"""
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
@require_tokenizers... | 713 |
"""simple docstring"""
import os
import unittest
from transformers import FunnelTokenizer, FunnelTokenizerFast
from transformers.models.funnel.tokenization_funnel import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@re... | 190 | 0 |
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny model through reduction of a normal pre-trained model, but keeping the
# full vocab, merges file, and ... | 175 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class __lowerCAmelCase ( lowerCAmelCase__ ):
def __init__( self , __UpperCAmelCase , __UpperCAmelCase = None ... | 175 | 1 |
'''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,
req... | 666 |
'''simple docstring'''
import re
import string
import numpy as np
import datasets
__lowerCAmelCase = '\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n'
__lo... | 666 | 1 |
import numpy as np
__A : Dict = [
["a", "b", "c", "d", "e"],
["f", "g", "h", "i", "k"],
["l", "m", "n", "o", "p"],
["q", "r", "s", "t", "u"],
["v", "w", "x", "y", "z"],
]
class A_ :
def __init__( self ):
'''simple docstring'''
Upp... | 130 |
'''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_torch_available():
import ... | 310 | 0 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
de... | 711 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokenize... | 425 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A =logging.get_logger(__name__)
class _snake_case ( a__ ):
lowerCAmelCase :Any = '''timm_backbone'''
def __init__( self , _lowerCame... | 407 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
if exponent == 1:
return base
if exponent % 2 == 0:
UpperCAmelCase__ : List[str] = _modexpt(UpperCamelCase__ , exponent // 2 , UpperCamelCase... | 407 | 1 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
lowerCamelCase__ : Optional[Any] = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def UpperC... | 495 |
def UpperCamelCase ( lowercase_ = 10_00 ) -> int:
'''simple docstring'''
return sum(2 * a * ((a - 1) // 2) for a in range(3 , n + 1 ) )
if __name__ == "__main__":
print(solution())
| 495 | 1 |
"""simple docstring"""
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ... | 123 |
"""simple docstring"""
# This script creates a super tiny model that is useful inside tests, when we just want to test that
# the machinery works, without needing to the check the quality of the outcomes.
#
# This version creates a tiny vocab first, and then a tiny model - so the outcome is truly tiny -
# all file... | 123 | 1 |
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=__lowerCAmelCase ):
'''simple docstring'''
_snake_case = ['torch', 'transformers', 'onnx']
def __init__( self : List[str] , *_UpperCamelCase : Li... | 718 | import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __snake_case ( unittest.TestCase ):
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (... | 15 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"""h... | 346 | '''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase :List[Any] = logging.get_logger(__name__)
_lowerCAmelCase :Tuple = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resolve/main/config.j... | 251 | 0 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE = {'UserAgent': UserAgent().random}
def a (lowerCAmelCase__ ):
__a = script.contents[0]
__a ... | 209 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOut... | 209 | 1 |
'''simple docstring'''
def _snake_case ( _SCREAMING_SNAKE_CASE : list , _SCREAMING_SNAKE_CASE : int , _SCREAMING_SNAKE_CASE : int = 0 , _SCREAMING_SNAKE_CASE : int = 0 ) -> int:
"""simple docstring"""
lowerCAmelCase = right or len(... | 433 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'microsoft/git-base': 'https://huggingfa... | 433 | 1 |
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class UpperCamelCase__ :
"""simple docstring"""
UpperCAmelCase_ =None
def _UpperCamelCase ( self ) -> Tuple:
SCREA... | 712 |
from math import factorial
def A__ ( __lowerCamelCase = 20 ):
SCREAMING_SNAKE_CASE_ = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
SCREAMING_SNAKE_CASE_ = n // 2
return int(factorial(__lowerCamelCase ) / (factorial(__lowerCamelCase ) * factoria... | 597 | 0 |
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won't be considered
# since th... | 187 |
from jiwer import compute_measures
import datasets
A = '\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL to MER and WIL: improved evaluation measures for connected spe... | 187 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import random
class lowerCAmelCase :
'''simple docstring'''
def __init__( self , lowerCAmelCase__ = None ) -> List[str]:
SCREAMING_SNAKE_CASE = value
... | 327 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from... | 327 | 1 |
'''simple docstring'''
import os
def lowercase_ ( __A : Any ) -> Tuple:
"""simple docstring"""
lowercase : List[str] =len(grid[0] )
lowercase : Union[str, Any] =len(__A )
lowercase : List[str] =0
lowercase : Union... | 94 |
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowercase_ ( __A : str ) -> Union[str, Any]:
"""simple docstring"""
return x + 2
class UpperCAmelCase_ ... | 94 | 1 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe imp... | 701 | # Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 316 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
from a... | 74 | 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... | 64 | 0 |
from math import factorial
def lowerCAmelCase_ (lowercase__ : List[str] , lowercase__ : List[str] ) -> Any:
'''simple docstring'''
if n < k or k < 0:
raise ValueError('''Please enter positive integers for n and k where n >= k''' )
return ... | 711 |
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
_UpperCAmelCase : List[Any] = logging.getLogger()
@unittest.skip('Temporarily disable the doc t... | 288 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class lowercase ( SCREAMING_SNAKE_CASE_)... | 352 |
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_dimensi... | 352 | 1 |
"""simple docstring"""
UpperCamelCase_ : int = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def A_ ():
'''simple docstring'''
A_ = input("Enter message: " )
A_ = input("Enter key [alphanumeric]: " )
A_ = input("Encrypt/Decrypt [e/d]: " )
... | 482 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
UpperCamelCase_ : Tuple = 637_8137.0
UpperCamelCase_ : List[str] = 635_6752.31_4245
UpperCamelCase_ : Dict = 637_8137
def A_ (__a , __a ,... | 482 | 1 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
UpperCAmelCase_ = logging.get_logger(__name__)
UpperC... | 32 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable_full_deter... | 690 | 0 |
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..models.auto.modeling_auto impor... | 709 | '''simple docstring'''
def __UpperCamelCase ( UpperCAmelCase , UpperCAmelCase ):
_enforce_args(UpperCAmelCase , UpperCAmelCase )
if n == 0:
return 0
lowercase__ : Optional[int] = float('''-inf''' )
for i in range(1 , n + 1 ):
lowercase__ : str = max(
... | 428 | 0 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by ap... | 456 |
import tensorflow as tf
from ...tf_utils import shape_list
class _a (tf.keras.layers.Layer ):
'''simple docstring'''
def __init__( self , A__ , A__ , A__ , A__ , A__=1 , A__=False , **A__ ):
super().__init__(**A_... | 456 | 1 |
import numpy as np
def UpperCAmelCase__ ( lowerCamelCase ):
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 711 |
def UpperCAmelCase__ ( lowerCamelCase ):
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowercase :str = 1
lowercase :Tuple = 1
while repunit:
lowercase :Dict = (10 * repunit + 1) % divisor
repunit_index += 1
return repunit_index
de... | 453 | 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
_snake_case : Union[str, Any] = logging.get_logger(__name__)
_snake_case : Tuple ... | 81 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.tes... | 81 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
'microsoft/biogpt': 'https://huggingface.co/microsoft/biogpt/resolve/main/config.json',
# See all BioGPT models at https://hugg... | 720 | import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
_SCREAMING_SNAKE_CASE = {
'vocab_file': 'vocab.jso... | 83 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decod... | 4 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', ... | 4 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# U... | 291 |
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCamelCase ( snake_case__ : str ,snake_case__ : Dict ,snake_case__ ... | 291 | 1 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
A : str = logging.get_logger(__name__)
A : str = {
'post_extract_proj': 'feature_projecti... | 15 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class _a :
"""simple docstring"""
def __init__( self : int , __UpperCamelCase : list[str] )->Dict:
_UpperCAmelCase = []
self.adlist.append(
... | 602 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase = logging.get_logger(__name__)
lowercase = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json"""... | 711 | import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
lowercase = logging.get_logger(__name__)
lowercase = {
"""post_extract_proj""": """feature_pr... | 591 | 0 |
'''simple docstring'''
def a ( __a ) -> bool:
'''simple docstring'''
UpperCamelCase__ :List[Any] = [int(__a ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(__a ) == 4 and all(0 <= int(__a ) <= 254 for octet in octets )
if __name__ == "__... | 189 |
'''simple docstring'''
from __future__ import annotations
import math
def a ( __a , __a , __a , __a , __a ) -> int:
'''simple docstring'''
if depth < 0:
raise ValueError('''Depth cannot be less than 0''' )
if len(__a ) == 0:
... | 189 | 1 |
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
snake_case_ : List[Any] = logging.get_logger(__name__)
class __snake_case ( a ):
Upp... | 169 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class __snake_case :
def __init__( self : Dict , _snake_case : Optional[int] , _snake_case : int , _snake_case : int):
"""simple docstring"""
if ds... | 169 | 1 |
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.t... | 328 |
import os
import sys
import unittest
__UpperCamelCase : List[str] = 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_dummies # noqa: E402
from check_dummies import create_dummy_f... | 328 | 1 |
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
lowercase = {"UserAgent": UserAgent().random}
def __UpperCAmelCase ( a_):
snake_case_ = script.contents[0]
snake_case_ =... | 707 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
lowercase = logging.getLogger(__name__)
@dataclass
class UpperCamelCase_ ( snake_case_ ):
'''simp... | 607 | 0 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# 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 ... | 291 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def A ( lowercase__ : dict ) -> tuple:
return (data["data"], d... | 45 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT... | 443 |
import argparse
import os
import re
UpperCAmelCase_ : List[Any] = 'src/transformers'
# Pattern that looks at the indentation in a line.
UpperCAmelCase_ : Any = re.compile(R'^(\s*)\S')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCAmelCase_ : str... | 443 | 1 |
import math
from collections import defaultdict
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 KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def __UpperCAmelCase( ... | 114 |
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_tokenization_common import To... | 114 | 1 |
"""simple docstring"""
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class a__ :
snake_case__ = 4_2
snake_case__ = None
snake_case__ = None
def UpperCAmelCase ( snake_case : Optional[int] )... | 714 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
UpperCamelCase__ = logging.get_logger(__name__)
class a__ ( UpperCamelCase_ ):
def __init__( self : Dict ,*a__ : List[s... | 439 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def _A ( _a : Sequence[float] , _a : float ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(_a ) )
def _A ( _a : Sequence[float] , _a : ... | 617 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase ={
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"... | 617 | 1 |
__UpperCAmelCase = "Tobias Carryer"
from time import time
class a_:
"""simple docstring"""
def __init__( self : Optional[Any] , lowerCAmelCase__ : str , lowerCAmelCase__ : Union[str, Any] , lowerCAmelCase__ : str , lowerCAmelCase__ ... | 720 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TextClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
from .test_pipeli... | 259 | 0 |
"""simple docstring"""
def lowerCAmelCase_ ( SCREAMING_SNAKE_CASE__, SCREAMING_SNAKE_CASE__ ) -> int:
return int((input_a, input_a).count(1 ) != 0 )
def lowerCAmelCase_ ( ) -> None:
assert or_gate(0, 0 ) == 0
assert or_gate(0, 1 ) == 1
... | 237 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__: Optional[int] = logging.get_logger(__name__)
lowerCAmelCase__: List[Any] = {
"uclanlp/visualbert-vqa": "https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json",
"uclanl... | 345 | 0 |
def lowerCamelCase__ ( a : list[list] ) -> list[list]:
"""simple docstring"""
a__ :Any = current_set.copy()
for row_index, row in enumerate(a ):
a__ :List[str] = row[0]
for column_index, column in enumerate(a ):
if magnitude == 0:
... | 373 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
from ... | 373 | 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, ids_tensor,... | 464 |
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 = logging.get_logger(__name__)
lowerCamelCase = '▁'
lowerCamelCase = {'vocab_file': 'pr... | 464 | 1 |
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTe... | 711 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase = {
"microsoft/wavlm-base": "https://huggingface.co/microsoft/wavlm-base/resolve/main/config.json",
# See all ... | 597 | 0 |
'''simple docstring'''
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPM... | 288 |
'''simple docstring'''
import os
import sys
import unittest
__lowerCamelCase = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, c... | 288 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
... | 372 |
from typing import Optional, Tuple, Union
import torch
from einops import rearrange, reduce
from diffusers import DDIMScheduler, DDPMScheduler, DiffusionPipeline, ImagePipelineOutput, UNetaDConditionModel
from diffusers.schedulers.scheduling_ddim import DDIMSchedulerOutput
from diffusers.schedule... | 372 | 1 |
from __future__ import annotations
from collections.abc import Iterator
class lowercase__ :
def __init__( self : Dict , UpperCamelCase__ : int ):
'''simple docstring'''
SCREAMING_SNAKE_CASE : List[str... | 248 | import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
__U... | 248 | 1 |
def lowerCamelCase_ ( A : list ):
"""simple docstring"""
def merge(A : list , A : list ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[0] else right).pop(0 )
yield from le... | 413 |
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnxruntime as ort
_snak... | 413 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.