code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_E... | 21 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase_ ( __lowercase : list[float] , __lowercase : list[float] ) -> float:
'''simple docstring'''
_UpperCAmelCase = sorted(numsa + numsa )
_UpperCAm... | 22 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available... | 294 | 0 |
'''simple docstring'''
from itertools import product
def snake_case_ ( _lowerCAmelCase : int , _lowerCAmelCase : int ) -> list[int]:
UpperCAmelCase : Union[str, Any] = sides_number
UpperCAmelCase : Optional[Any] = ... | 23 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_I... | 294 | 0 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'post_extract_proj': 'feature_projection.pro... | 24 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap im... | 294 | 0 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_cop... | 25 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCamelCase ( snake_case_ ):
def __init__( self : Any ... | 294 | 0 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class lowercase :
def __init__( self , _a ) -> Union[str, Any]:
_A : Tuple = list_of_points
# Degree determines the flexibility of the curve.
... | 26 |
"""simple docstring"""
import unittest
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = None , ):
'''simple docstring'''
_a : List[Any] = np.shape(UpperCame... | 294 | 0 |
'''simple docstring'''
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
__lowercase : List[str] = datasets.logging.get_logger(__name__)
__lowercase : List[str] = '\\n@inproceedings{bleurt,\n title={BLEURT: Learning Robust Me... | 27 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
... | 294 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=_a )
class SCREAMING_SNAKE_CASE ( _a ):
"""simple docstring"""
_SC... | 28 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
'configuration_perceiver': ['PERCEIVER_... | 294 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__UpperCAmelCase = {
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'Vis... | 29 |
"""simple docstring"""
import cva
import numpy as np
class UpperCamelCase :
def __init__( self : Optional[int] , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> Dict:
if k in (0.0_4, 0.0_6):
... | 294 | 0 |
import torch
from torch import nn
class lowercase__( nn.Module ):
"""simple docstring"""
def __init__( self : Union[str, Any] , SCREAMING_SNAKE_CASE_ : List[Any] , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : List[str] ... | 30 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
# Check if the input is valid
if not len(UpperCamelCase__ ) == len(UpperCamelCase__ ) == 3:
raise ValueError("""Please enter a valid equation... | 294 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCamelCase_ (unittest.TestC... | 31 |
"""simple docstring"""
_snake_case = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.gi... | 294 | 0 |
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenizer
from transformers.models.mbart.mode... | 32 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',... | 294 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionMode... | 33 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_snake_case = logging.getLogger(__name__)
class UpperCamelCase ( snak... | 294 | 0 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
A =WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def snake_case_ (_a : Tuple... | 34 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
_snake_case = [8, 5, 9, 7]
_snake_case = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_snake_case = [
[3... | 294 | 0 |
'''simple docstring'''
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():
rai... | 35 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
_snake_case = TypeVar('_T')
class UpperCamelCase ( Generic[_T] ):
def __init__( self : Optional[int] , UpperCAmelCase__ : Iter... | 294 | 0 |
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_tokenizers
class UpperC... | 36 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_snake_case = False
... | 294 | 0 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ : Union[str, Any] = img.shape[0], img.shape[1]
# converting each pi... | 37 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {'vocab_file': 'vocab.json'}
_snake_ca... | 294 | 0 |
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : int , __magic_name__ : int , __magic_name__ : int ) -> float:
"""simple docstring"""
UpperCamelCase :Tuple = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
# formula for sum of... | 38 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase ( snake_case_ ):
UpperCamelCase : int = (IPNDMScheduler,)
UpperCamelCase : ... | 294 | 0 |
from __future__ import annotations
def __A ( __lowerCAmelCase , __lowerCAmelCase )-> list[tuple[int, int]]:
"""simple docstring"""
_UpperCAmelCase , _UpperCAmelCase = position
_UpperCAmelCase = [
(y + 1, x + 2),
... | 39 |
"""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
_snake_ca... | 294 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedTo... | 40 |
"""simple docstring"""
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_s... | 294 | 0 |
'''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 mod... | 41 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(UpperCamelCase__ ):
prin... | 294 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase : Optional[Any] = {
"configuration_resnet": ["RESNET_PRETRAINED_CONFIG_ARCH... | 42 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'... | 294 | 0 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimens... | 43 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_a ... | 44 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available... | 294 | 0 |
"""simple docstring"""
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available(... | 45 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_I... | 294 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE... | 46 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap im... | 294 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTVaConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_conf... | 47 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCamelCase ( snake_case_ ):
def __init__( self : Any ... | 294 | 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
#
# Unles... | 48 |
"""simple docstring"""
import unittest
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = None , ):
'''simple docstring'''
_a : List[Any] = np.shape(UpperCame... | 294 | 0 |
from collections.abc import Generator
from math import sin
def __snake_case ( _UpperCAmelCase ):
if len(_UpperCAmelCase ) != 32:
raise ValueError('''Input must be of length 32''' )
__a = b''''''
for i in [3, 2, 1, 0]:
little_endian += string_aa[8 * i ... | 49 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
... | 294 | 0 |
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_video_inputs
if is_torch_available():
import t... | 50 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
'configuration_perceiver': ['PERCEIVER_... | 294 | 0 |
snake_case_ : Dict = {
"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",
"huggingfa... | 51 |
"""simple docstring"""
import cva
import numpy as np
class UpperCamelCase :
def __init__( self : Optional[int] , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> Dict:
if k in (0.0_4, 0.0_6):
... | 294 | 0 |
class A__ :
def __init__( self , A_ , A_=None , A_=None ):
'''simple docstring'''
UpperCamelCase : List[str] = data
UpperCamelCase : Optional[int] = previous
UpperCamelCase : Optional[Any] ... | 52 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
# Check if the input is valid
if not len(UpperCamelCase__ ) == len(UpperCamelCase__ ) == 3:
raise ValueError("""Please enter a valid equation... | 294 | 0 |
'''simple docstring'''
import torch
from transformers import AutoModel
class snake_case ( torch.nn.Module ):
"""simple docstring"""
def __init__( self : Optional[int] , __A : List[Any]="sayef/fsner-bert-base-uncased" ):
super(__A , sel... | 53 |
"""simple docstring"""
_snake_case = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.gi... | 294 | 0 |
"""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/LICENS... | 54 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',... | 294 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
... | 55 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_snake_case = logging.getLogger(__name__)
class UpperCamelCase ( snak... | 294 | 0 |
'''simple docstring'''
import importlib.util
import json
import os
import warnings
from dataclasses import dataclass, field
import torch
from ..training_args import TrainingArguments
from ..utils import cached_property, is_sagemaker_dp_enabled, logging
a : List[Any] = logging.get_logger(__name__)... | 56 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
_snake_case = [8, 5, 9, 7]
_snake_case = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_snake_case = [
[3... | 294 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_... | 57 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
_snake_case = TypeVar('_T')
class UpperCamelCase ( Generic[_T] ):
def __init__( self : Optional[int] , UpperCAmelCase__ : Iter... | 294 | 0 |
'''simple docstring'''
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
... | 58 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_snake_case = False
... | 294 | 0 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObjectDetection,
ConditionalDetrForSegm... | 59 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {'vocab_file': 'vocab.json'}
_snake_ca... | 294 | 0 |
"""simple docstring"""
snake_case__ : Optional[Any] = {str(digit): digit**5 for digit in range(10)}
def _snake_case ( _snake_case : int ):
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_snake_case ) )
def _snake_case ( ):
return sum(
number
for num... | 60 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase ( snake_case_ ):
UpperCamelCase : int = (IPNDMScheduler,)
UpperCamelCase : ... | 294 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a = {'configuration_focalnet': ['FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FocalNetConfig']}
try:
if not is_torc... | 61 |
"""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
_snake_ca... | 294 | 0 |
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
_A = HfArgumentParser(InitializationArguments)
_A = parser.parse_args()
# Load codeparrot tokenizer trained for Python code tokenizati... | 62 |
"""simple docstring"""
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_s... | 294 | 0 |
'''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 user passe... | 63 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(UpperCamelCase__ ):
prin... | 294 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.util... | 64 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'... | 294 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCas... | 65 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
"MIT/ast-finetuned-audioset-10-10-0.4593": (
"https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/config.json"
... | 66 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available... | 294 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase ={
"configuration_mobilevit": ["MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "Mo... | 67 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_I... | 294 | 0 |
# 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 import Config... | 68 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap im... | 294 | 0 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase = {
'''asapp/sew-tiny-100k''': '''https://huggingface.co/asapp/sew-tiny-100k/resolve/mai... | 69 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCamelCase ( snake_case_ ):
def __init__( self : Any ... | 294 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCAmelCase :
_lowercas... | 70 |
"""simple docstring"""
import unittest
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = None , ):
'''simple docstring'''
_a : List[Any] = np.shape(UpperCame... | 294 | 0 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class __A ( unittest.TestCase ):
"""simple docstring"""
def __lowercas... | 71 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
... | 294 | 0 |
"""simple docstring"""
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines... | 72 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
'configuration_perceiver': ['PERCEIVER_... | 294 | 0 |
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=SCREAMING_SNAKE_CASE ):
_UpperCAmelCase : List[str] = ['''keras_nlp''']
def __init__( self : Tuple ,*SCREAMING_SNAKE_CASE__ : Any ,**SCREAMING_SNAKE_CASE__ : List[s... | 73 |
"""simple docstring"""
import cva
import numpy as np
class UpperCamelCase :
def __init__( self : Optional[int] , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> Dict:
if k in (0.0_4, 0.0_6):
... | 294 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pow, sqrt
def _snake_case ( snake_case__ : float , snake_case__ : float , snake_case__ : float ):
if (resistance, reactance, impedance).count(0 ) != 1:
raise ValueError('One and only one ... | 74 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
# Check if the input is valid
if not len(UpperCamelCase__ ) == len(UpperCamelCase__ ) == 3:
raise ValueError("""Please enter a valid equation... | 294 | 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 ..auto import CONFIG_MAPPING
a_ : int = logging.ge... | 75 |
"""simple docstring"""
_snake_case = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.gi... | 294 | 0 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
DistilBe... | 76 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',... | 294 | 0 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_... | 77 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_snake_case = logging.getLogger(__name__)
class UpperCamelCase ( snak... | 294 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase = [0] * len(lowercase_ )
for i in range(1 , len(lowercase_ ) ):
# use last results for better performance - dynamic programming
UpperCAmelCase ... | 78 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
_snake_case = [8, 5, 9, 7]
_snake_case = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_snake_case = [
[3... | 294 | 0 |
'''simple docstring'''
def __lowercase ( __lowercase = 50 ) -> int:
'''simple docstring'''
_A = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
... | 79 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
_snake_case = TypeVar('_T')
class UpperCamelCase ( Generic[_T] ):
def __init__( self : Optional[int] , UpperCAmelCase__ : Iter... | 294 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 80 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_snake_case = False
... | 294 | 0 |
"""simple docstring"""
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCamelCase_ : List[Any] = logging.getLogger(__name__)
def _A ( ):
"""simple docstring"""
a... | 81 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {'vocab_file': 'vocab.json'}
_snake_ca... | 294 | 0 |
A__ = """
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
A__ ... | 82 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase ( snake_case_ ):
UpperCamelCase : int = (IPNDMScheduler,)
UpperCamelCase : ... | 294 | 0 |
'''simple docstring'''
from math import pi
def A__ ( UpperCAmelCase_ , UpperCAmelCase_ ):
return 2 * pi * radius * (angle / 3_6_0)
if __name__ == "__main__":
print(arc_length(90, 10))
| 83 |
"""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
_snake_ca... | 294 | 0 |
"""simple docstring"""
import os
def _snake_case ( lowercase__ : str = "matrix.txt" ) -> int:
'''simple docstring'''
with open(os.path.join(os.path.dirname(lowercase__ ) , lowercase__ ) ) as in_file:
lowerCAmelCase_ :str =... | 84 |
"""simple docstring"""
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_s... | 294 | 0 |
'''simple docstring'''
def UpperCamelCase_( snake_case : int ):
'''simple docstring'''
if isinstance(snake_case , snake_case ):
raise TypeError("'float' object cannot be interpreted as an integer" )
if isinstance(snake_case ... | 85 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(UpperCamelCase__ ):
prin... | 294 | 0 |
"""simple docstring"""
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import ... | 86 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'... | 294 | 0 |
import argparse
import os
import re
UpperCamelCase = '''src/transformers'''
# Pattern that looks at the indentation in a line.
UpperCamelCase = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCamelCase = re.compile(R'''^\s*"... | 87 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 0 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .logging im... | 88 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available... | 294 | 0 |
'''simple docstring'''
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 = loggin... | 89 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_I... | 294 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow... | 90 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap im... | 294 | 0 |
"""simple docstring"""
from __future__ import annotations
import typing
from collections.abc import Iterable
import numpy as np
UpperCAmelCase_ : int = typing.Union[Iterable[float], Iterable[int], np.ndarray] # noqa: UP007
UpperCAmelCase_ : str = typing.Union[np.floataa, int, float] # no... | 91 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCamelCase ( snake_case_ ):
def __init__( self : Any ... | 294 | 0 |
def _a ( SCREAMING_SNAKE_CASE_ : Tuple , SCREAMING_SNAKE_CASE_ : Any ):
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def _a ( SCREAMING_SNAKE_CASE_ : Dict , SCREAMING_SNAKE_CASE_ : Union[str, Any]=0 ... | 92 |
"""simple docstring"""
import unittest
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = None , ):
'''simple docstring'''
_a : List[Any] = np.shape(UpperCame... | 294 | 0 |
'''simple docstring'''
def snake_case_ ( __SCREAMING_SNAKE_CASE : Optional[int] ):
"""simple docstring"""
lowercase_ : List[str] = [0] * len(__SCREAMING_SNAKE_CASE )
lowercase_ : Union[str, Any] = ... | 93 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
... | 294 | 0 |
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
snake_case : str = get_te... | 94 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
'configuration_perceiver': ['PERCEIVER_... | 294 | 0 |
from __future__ import annotations
class __lowerCAmelCase :
def __init__( self , lowerCAmelCase__ ) -> int:
'''simple docstring'''
a__ : Optional[Any] =TypeError(
"Matrices must be f... | 95 |
"""simple docstring"""
import cva
import numpy as np
class UpperCamelCase :
def __init__( self : Optional[int] , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> Dict:
if k in (0.0_4, 0.0_6):
... | 294 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def _snake_case ( lowercase__ , lowercase__ ... | 96 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
# Check if the input is valid
if not len(UpperCamelCase__ ) == len(UpperCamelCase__ ) == 3:
raise ValueError("""Please enter a valid equation... | 294 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare... | 97 |
"""simple docstring"""
_snake_case = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.gi... | 294 | 0 |
"""simple docstring"""
from __future__ import annotations
import typing
from collections import Counter
def a_ ( lowerCamelCase ):
UpperCAmelCase__ = Counter()
for base in range(1 , max_perimeter + 1 ):
for perpendicular in range(lowerCamelCase ... | 98 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',... | 294 | 0 |
import inspect
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_config_docstrings.py
lowercase : str = """src/transformers"""
# This is to make... | 99 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_snake_case = logging.getLogger(__name__)
class UpperCamelCase ( snak... | 294 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
is... | 100 |
"""simple docstring"""
from __future__ import annotations
import time
import numpy as np
_snake_case = [8, 5, 9, 7]
_snake_case = [
[2, 0, 1, 1],
[0, 1, 2, 1],
[4, 0, 0, 3],
[0, 2, 1, 0],
[1, 0, 3, 0],
]
_snake_case = [
[3... | 294 | 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_bert import BertTokenizer
lowercase__ :List[Any] = logging.get_logger(__name__)
lowercase__ :Optional[Any] ... | 101 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
_snake_case = TypeVar('_T')
class UpperCamelCase ( Generic[_T] ):
def __init__( self : Optional[int] , UpperCAmelCase__ : Iter... | 294 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE : Tuple = {"""configuration_beit""": ["""BEIT_PRETRAINED_CONFIG_ARCHIVE_M... | 102 |
"""simple docstring"""
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
_snake_case = False
... | 294 | 0 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class __snake_case ( unittest.TestCase ):
_a = JukeboxTokenizer
_a = {
'''artist''': '''Zac Brown Band''',
'''genres''': '''Country... | 103 |
"""simple docstring"""
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {'vocab_file': 'vocab.json'}
_snake_ca... | 294 | 0 |
'''simple docstring'''
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
lowerCAmelCase__ = logging.getLogger(__name__)
lowerCAmelCase__ ... | 104 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase ( snake_case_ ):
UpperCamelCase : int = (IPNDMScheduler,)
UpperCamelCase : ... | 294 | 0 |
"""simple docstring"""
import argparse
import copy
def _SCREAMING_SNAKE_CASE ( _lowercase : List[Any] ) ->int:
'''simple docstring'''
a : int = {}
with open(_lowercase ) as f:
for line in f:
if line.split()[0] not ... | 105 |
"""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
_snake_ca... | 294 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__UpperCamelCase : int = {
'''configuration_maskformer''': ['''MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MaskFormerConf... | 106 |
"""simple docstring"""
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_s... | 294 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoi... | 107 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
print(F"""Vertex\tShortest Distance from vertex {src}""" )
for i, d in enumerate(UpperCamelCase__ ):
prin... | 294 | 0 |
"""simple docstring"""
class SCREAMING_SNAKE_CASE__ :
"""simple docstring"""
def __init__( self , snake_case__ = "" , snake_case__ = False ):
"""simple docstring"""
lowerCAmelCase : dict[str, RadixNode] = {}
... | 108 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'... | 294 | 0 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def _snake_case ( UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : int , UpperCamelCase : int... | 109 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , ):
'''simple docstring'''
_a : Optional[Any] = [redshift, radiation_density, matter_... | 294 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__SCREAMING_SNAKE_CASE : Tuple = {
'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_... | 347 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available... | 294 | 0 |
"""simple docstring"""
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 ... | 136 |
"""simple docstring"""
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_I... | 294 | 0 |
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def A__ ( SCREAMING_SNAKE_CASE__) -> Tuple:
__snake_case: int = int(number**0.5)
return number == sq * sq
def A__ ( SCREAMING_SNAKE_CASE__ , SCREAMING_SN... | 111 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap im... | 294 | 0 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscre... | 259 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_clip import CLIPImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCamelCase ( snake_case_ ):
def __init__( self : Any ... | 294 | 0 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase_ ( __A ) -> str:
'''simple docstring'''
UpperCAmelCase__ = FileLock(str(tmpdir / "foo.lock" ) )
UpperCAmelCase__ ... | 65 |
"""simple docstring"""
import unittest
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = None , ):
'''simple docstring'''
_a : List[Any] = np.shape(UpperCame... | 294 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import loggi... | 139 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
... | 294 | 0 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import r... | 340 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
'configuration_perceiver': ['PERCEIVER_... | 294 | 0 |
"""simple docstring"""
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_mode... | 148 |
"""simple docstring"""
import cva
import numpy as np
class UpperCamelCase :
def __init__( self : Optional[int] , UpperCAmelCase__ : float , UpperCAmelCase__ : int ) -> Dict:
if k in (0.0_4, 0.0_6):
... | 294 | 0 |
"""simple docstring"""
import unittest
import numpy as np
def A_ ( _lowerCAmelCase : List[Any], _lowerCAmelCase : List[Any], _lowerCAmelCase : int, _lowerCAmelCase : Union[str, Any] = None, ):
"""simple docstring"""
_a = np.shape(UpperCamelCase__... | 320 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
# Check if the input is valid
if not len(UpperCamelCase__ ) == len(UpperCamelCase__ ) == 3:
raise ValueError("""Please enter a valid equation... | 294 | 0 |
"""simple docstring"""
def _SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ ) -> int:
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or not n... | 247 |
"""simple docstring"""
_snake_case = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.gi... | 294 | 0 |
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentenc... | 159 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',... | 294 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.