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 |
|---|---|---|---|---|
def __UpperCamelCase ( lowercase__ : Optional[int] , lowercase__ : List[Any] , lowercase__ : Optional[Any] ) -> Optional[Any]:
'''simple docstring'''
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiati... | 600 |
def __UpperCamelCase ( lowercase__ : int , lowercase__ : int , lowercase__ : int ) -> float:
'''simple docstring'''
lowerCAmelCase_ : Tuple = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_diff)
... | 600 | 1 |
"""simple docstring"""
import itertools
import random
import unittest
import numpy as np
from transformers import WAV_2_VEC_2_PRETRAINED_MODEL_ARCHIVE_LIST, WavaVecaConfig, WavaVecaFeatureExtractor
from transformers.testing_utils import require_torch, slow
from ...test_sequence_feature_extraction_common impo... | 714 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCamelCase = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config", "M2M100OnnxConfig"],
... | 190 | 0 |
def A__ ( snake_case_ : Optional[Any] , snake_case_ : Tuple , snake_case_ : Optional[Any] , snake_case_ : Optional[Any] , snake_case_ : int , snake_case_ : List[str] ):
if index == r:
for j in range(snake_case_ ):
print(data[j] ... | 64 |
def lowerCAmelCase( SCREAMING_SNAKE_CASE_ = 4_0_0_0_0_0_0 )-> int:
"""simple docstring"""
UpperCamelCase_ = [0, 1]
UpperCamelCase_ = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
... | 628 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.confi... | 701 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_tran... | 377 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_commo... | 34 |
'''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers impo... | 442 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch_device
from diffusers.... | 701 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokeni... | 45 | 0 |
from pathlib import Path
import fire
def SCREAMING_SNAKE_CASE_ ( _snake_case :str , _snake_case :str , _snake_case :int ) -> int:
_A = Path(_snake_case )
_A = Path(_snake_case )
dest_dir.mkdir(exist_ok=_snake_case )
for path in src_dir.iter... | 2 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Union[str, ... | 567 | 0 |
'''simple docstring'''
def A_ ( ) ->List[Any]:
lowercase_ = []
lowercase_ = 1
while len(SCREAMING_SNAKE_CASE_ ) < 1e6:
constant.append(str(SCREAMING_SNAKE_CASE_ ) )
i += 1
lowercase_ = """""".join(SCREAMING_SNAKE_CASE_ )
return (
int(constant[0] )
* int... | 704 | '''simple docstring'''
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEmb... | 603 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( a , a ):
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(a ) * abs(a )
if __name__ == "__main__":
import doctest
doctest.testmod(verbose=True)
| 356 |
'''simple docstring'''
import argparse
import json
import os
import re
import shutil
import torch
from transformers import BioGptConfig, BioGptForCausalLM
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES
from transformers.tokenization_utils_base import TOKENIZER_CONFIG_FILE
from tra... | 356 | 1 |
def a__ ( __UpperCamelCase ):
if not head:
return True
# split the list to two parts
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ = head.next, head
while fast and fast.next:
SCREAMING_SNAKE_CASE_ = fast.next.next
SCREAMING_SNA... | 707 | import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
A : List[str] = False
class lowerCamelCase (unittest.TestCase ):
... | 356 | 0 |
'''simple docstring'''
def lowercase__( _UpperCamelCase : list )-> list:
"""simple docstring"""
if len(_UpperCamelCase ) < 2:
return collection
def circle_sort_util(_UpperCamelCase : list , _UpperCamelCase : int , _UpperCamelCase : int ) -> bool:
... | 138 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowercase__( _UpperCamelCase : Optional[Any] , _UpperCamelCase : Dict , _UpperCamelCase : int , _UpperCamelCase : Optional[int] )-> List[Any]:
"""simple docstring"""
_... | 138 | 1 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def _lowerCamelCase( a , a = "cpu" , a = None ):
__a = torch.load(a , map_location=a )
for k, v in tqdm(state_dict.items() ):
if ... | 67 | """simple docstring"""
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokeni... | 67 | 1 |
def UpperCAmelCase__( __UpperCAmelCase : List[Any] , __UpperCAmelCase : int , __UpperCAmelCase : Dict=False ):
if isinstance(__UpperCAmelCase , __UpperCAmelCase ) and isinstance(__UpperCAmelCase , __UpperCAmelCase ):
__snake_case : ... | 576 | import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transformers.utils import lo... | 576 | 1 |
from typing import Any
def UpperCamelCase( lowercase_ ) -> list[Any]:
'''simple docstring'''
if not input_list:
return []
snake_case_ = [input_list.count(lowercase_ ) for value in input_list]
snake_case_ = max(lowercase_ ) # Gets the maximum count ... | 161 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowerCamelCase_ = {
'''configuration_transfo_xl''': ['''TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TransfoXLConfig'''],
'''tokenization_transfo_xl''': [''... | 161 | 1 |
import os
import unittest
from transformers import LayoutLMTokenizer, LayoutLMTokenizerFast
from transformers.models.layoutlm.tokenization_layoutlm import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class ... | 10 |
"""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 impo... | 118 | 0 |
"""simple docstring"""
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_... | 190 |
"""simple docstring"""
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict impor... | 190 | 1 |
'''simple docstring'''
from collections import defaultdict
def snake_case__ ( UpperCamelCase ,UpperCamelCase ) -> bool:
_UpperCamelCase : str = first_str.lower().strip()
_UpperCamelCase : Dict = second_str.lower().strip()
# Remove whitespace
_UpperC... | 683 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_att... | 683 | 1 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
_UpperCAmelCase : Union[str, Any] = {
"""E""": 12.70,
"""T""": 9.06,
"""A""": 8.17,
"""O""": 7.51,
"""I""": 6.97,
"""N""": 6.75,
"""S""": 6.33,
"""H""": 6.09,
"""R""": 5.99,
"""D"""... | 108 |
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet impor... | 108 | 1 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def __a ( SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple... | 303 |
def __a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) -> Union[str, Any]:
'''simple docstring'''
__UpperCAmelCase = 0
while b > 0:
if b & 1:
res += a
a += a
b >>= 1
return res
def __a ( SC... | 303 | 1 |
def a__ ( snake_case ):
"""simple docstring"""
if not all(char in '''01''' for char in bin_string ):
raise ValueError('''Non-binary value was passed to the function''' )
if not bin_string:
raise ValueError('''Empty string was passed to the function''' )
__SC... | 131 |
def a__ ( snake_case , snake_case , snake_case=False ):
"""simple docstring"""
if isinstance(snake_case , snake_case ) and isinstance(snake_case , snake_case ):
__SCREAMING_SNAKE_CASE : Dict = len(set_a.intersection(snake_case ) )
... | 131 | 1 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
UpperCa... | 37 |
"""simple docstring"""
def __lowercase ( snake_case_ : list ) ->float:
'''simple docstring'''
__A : Tuple = 0
while len(snake_case_ ) > 1:
__A : List[Any] = 0
# Consider two files with minimum cost to be merged
for _ in ran... | 177 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
UpperCAmelCase__ = {
"""distilbert-base-uncased"... | 717 | """simple docstring"""
import unittest
from knapsack import knapsack as k
class a ( unittest.TestCase ):
def lowerCAmelCase_ ( self : List[Any] ):
_UpperCAmelCase = 0
_UpperCAmelCase = [0]
_UpperCAmelCase = [0]
_UpperCAmelCa... | 275 | 0 |
def _lowerCamelCase ( lowerCamelCase_: int ):
'''simple docstring'''
A : Any = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def _lowerCamelCase ( lowerCamelCase_: int = 100 ):
... | 256 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _SCREAMING_SNAKE_CASE ( snake_case ):
lowerCamelCase_ = (CMStochasticIterativeScheduler,)
lowerCamelCase_ = 1_0
def _UpperCAmelCase ( ... | 256 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
__lowerCamelCase :Any = loggi... | 717 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__lowerCamelCase :str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 42 | 0 |
'''simple docstring'''
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
_a : List[Any] = logging.get_logger(__name__)
def _a (lowe... | 56 |
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
lowerCAmelCase = '\\n@misc{wu2016googles,\n title={Google\'s Neural Machine Translation System: Bridging the Gap between Human and Machine Translation},\n author={Yonghui ... | 43 | 0 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __UpperCamelCase (_SCREAMING_SNAKE_CASE ) -> Dict:
lowercase__ = os.path.join(args.tf_mode... | 705 |
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
lowercase_ = False
class SCREAMING_SNAKE_CASE (unittes... | 45 | 0 |
"""simple docstring"""
from typing import List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
"huggingface/autoformer-tourism-monthly": "https://huggingface.co/huggingface... | 695 |
"""simple docstring"""
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE , unittest.TestCase ):
'''simple ... | 695 | 1 |
lowerCAmelCase__ = {
"Pillow": "Pillow",
"accelerate": "accelerate>=0.11.0",
"compel": "compel==0.1.8",
"black": "black~=23.1",
"datasets": "datasets",
"filelock": "filelock",
"flax": "flax>=0.4.1",
"hf-doc-builder": "hf-doc-builder>=0.3.0",
"huggingface-hub": "huggingface-hu... | 1 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCAmelCase__ = version.parse(importlib_metadata.version("nltk"))
if NLTK_VERSION >= version.Version("3.6.4"):
from nltk import word_tokenize
lowerCAmelCase__ = ... | 1 | 1 |
import comet # From: unbabel-comet
import torch
import datasets
a__ = datasets.logging.get_logger(__name__)
a__ = """\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel's Participation in the WMT20 Metri... | 654 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Union[str, Any] = {
"""microsoft/un... | 116 | 0 |
"""simple docstring"""
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
a : str = logging.get_logger(__name__)
def _SCREAMING_SNAKE_CASE ( _lowe... | 31 |
"""simple docstring"""
import baseaa
def _SCREAMING_SNAKE_CASE ( _lowercase : str ) ->bytes:
'''simple docstring'''
return baseaa.aaaencode(string.encode("utf-8" ) )
def _SCREAMING_SNAKE_CASE ( _lowercase : ... | 31 | 1 |
'''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def UpperCAmelCase_ ( A , A , A = 1 / sqrt(2 ) ):
'''simple docstring'''
_a : List[Any] = tau * frequency / samplerate
_a : Tuple = sin(A )
... | 120 |
'''simple docstring'''
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def UpperCAmelCase_ ( A ):
'''simple docstring'''
_a : Dict = args.pruning_method
_a : Optional[Any] ... | 120 | 1 |
'''simple docstring'''
__lowerCamelCase : Dict = range(2, 20 + 1)
__lowerCamelCase : Optional[Any] = [10**k for k in range(ks[-1] + 1)]
__lowerCamelCase : dict[int, dict[int, list[list[int]]]] = {}
def __UpperCAmelCase ( __magic... | 656 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... | 656 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {
"configuration_autoformer": [
"AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"AutoformerConfig",
],
... | 469 |
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_transfo_xl ... | 469 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase__ = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig",
"PoolFormerOnnxConfig",... | 712 | import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot import Blende... | 594 | 0 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCamelCase_ : Dict = '''\
@misc{chen2021evaluating,
... | 185 |
'''simple docstring'''
from math import factorial
def __a ( _UpperCamelCase: int = 100 ) -> int:
"""simple docstring"""
return sum(map(_UpperCamelCase , str(factorial(_UpperCamelCase ) ) ) )
if __name__ == "__main__":
print(solut... | 185 | 1 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class UpperCamelCase ( unittest.TestCase , lowercase_ ):
def _UpperCAmelCase ( self ) -> Tuple:
'''simple docstring'''
lowercase_ ... | 721 | """simple docstring"""
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCal... | 477 | 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_image_inputs
if is_torch_available():
import torch
... | 20 |
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils import logging
logging.set_verbosity_inf... | 658 | 0 |
from collections.abc import Callable
import numpy as np
def A ( snake_case__ : Callable , snake_case__ : float , snake_case__ : float , snake_case__ : float , snake_case__ : float ) -> Union[str, Any]:
'''simple docst... | 702 |
from __future__ import annotations
UpperCAmelCase__ : Dict = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def A ( snake_case__ : list[list[int]] , snake_case__ : list[int] , snake_case__ : list[in... | 676 | 0 |
"""simple docstring"""
import sys
__UpperCamelCase : Any = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''1254069874715852386305071569329096329522... | 4 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ = {
'configuration_nezha': ['NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'NezhaConfig'],
}
try:
if not is_torch_availabl... | 173 | 0 |
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__lowercase : Tuple = logging.get_logger(__name__)
class _A ( __a ):
'''simple docstring'''
def __init__( self ,*SCREAMING_SNAKE_CASE_ ,**SCREAMING_SNAKE... | 719 |
def lowercase ( __A : int = 100_0000 ) -> int:
'''simple docstring'''
snake_case : Union[str, Any] = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , ... | 315 | 0 |
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available()... | 254 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
... | 254 | 1 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
A__ = TypeVar('''T''')
A__ = Union[List[T], Tuple[T, ...]]
A__ = Union[T, List[T], Dict[str, T]]
A__ = Union[str, bytes, os.PathLike]
| 219 |
def _lowerCAmelCase ( __lowerCAmelCase ) -> float:
"""simple docstring"""
if edge <= 0 or not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) *... | 219 | 1 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__UpperCamelCase : Any = '''\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
t... | 450 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_sim... | 450 | 1 |
"""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_v... | 700 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
"configuration_upernet": ["UperNetConfig"],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
... | 621 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CON... | 83 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a = g... | 350 | 0 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def __A ( lowerCamelCase_ ):
"""simple docstring"""
return getitem, k
def __A ( lowerCamelCase_ , lowerCamelCase_ ):
"""simple docstring... | 706 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
__UpperCAmelCase = """"""
__UpperCAmelCase = """"""
__UpperCAmelCase = """"""
__UpperCAmelCase = 1 # (0 is vertical, 1 is horizontal)
def __A ... | 79 | 0 |
"""simple docstring"""
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_g... | 363 |
"""simple docstring"""
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_ut... | 169 | 0 |
'''simple docstring'''
import re
def _snake_case ( A_ : str ):
"""simple docstring"""
a_ : Tuple = re.compile(R"""^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$""" )
if match := re.search(A_ , A_ ):
return match.string == phone
return ... | 719 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__snake_case: Tuple = logging.get_logger(__name__)
__snake_case: Tuple = {
"t5-small": "https://hugg... | 460 | 0 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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_im... | 85 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ...test_b... | 13 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ = {"configuration_vit_msn": ["VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTMSNConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
... | 716 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"distilbert-base-uncased": "https://huggingface.co/distilbert-b... | 376 | 0 |
'''simple docstring'''
_UpperCAmelCase : Tuple = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .streaming_download_manager import... | 683 |
'''simple docstring'''
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class UpperCA... | 683 | 1 |
'''simple docstring'''
from __future__ import annotations
lowerCAmelCase_ : Optional[Any] = []
def __A ( UpperCAmelCase ,UpperCAmelCase ,UpperCAmelCase ) -> Any:
'''simple docstring'''
for i in range(len(lowerCAmelCase_ ) ):
... | 707 | '''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 l... | 204 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from ...utils import logging
... | 37 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mode... | 129 | 0 |
import unittest
import numpy as np
import torch
from diffusers import ScoreSdeVePipeline, ScoreSdeVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class _SCREAMING_SNAKE_CASE (unittest.TestCase ):
... | 717 |
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class _SCREAMING_SNAKE_CASE (UpperCamelCase ):
def __init__( sel... | 447 | 0 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
_lowerCAmelCase : str = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
_lowerCAmelCase : list[int] = [or... | 46 |
"""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 AddedToken
from ...test... | 46 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ = {
'''configuration_maskformer''': ['''MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MaskFormerConfig'''],
'''configura... | 721 | """simple docstring"""
import argparse
import ast
import logging
import os
import sys
import pandas as pd
import torch
from tqdm import tqdm
from transformers import BartForConditionalGeneration, RagRetriever, RagSequenceForGeneration, RagTokenForGeneration
from transformers import logging as transformers_loggin... | 635 | 0 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 598 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
fro... | 598 | 1 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class a ( UpperCAmelCase ):
_lowercase = ["image_processor", "tokenizer"]
_lowercase = "CLIPImageProcessor"
_lowercase = ("XLMRobertaTokenize... | 703 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifierFreeSamplin... | 467 | 0 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
UpperCAmelCase = logging.get_logger(__name__)
def lowerCamelCase (a_ :Any , a_ ... | 677 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# ... | 677 | 1 |
def _lowerCAmelCase ( _lowerCAmelCase = 1_0_0 ):
'''simple docstring'''
A_ : List[Any] = set()
A_ : List[str] = 0
A_ : Dict = n + 1 # maximum limit
for a in range(2 ,_lowerCAmelCase ):
for b in range(2 ,_lowerCAmelCase ):
... | 481 |
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 DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
logging.set_verb... | 481 | 1 |
"""simple docstring"""
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a ( __UpperCAmelCase : List[Any] ) -> str:
__magic_name__: Union[str, Any] = ... | 96 |
'''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_avai... | 448 | 0 |
'''simple docstring'''
__A ='\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/tra... | 113 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _UpperCamelCase ( UpperCamelCase__ ):
# A local function to see if a dot lands in the circle.
def is_in_circle(UpperCame... | 113 | 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,
is_vision_available,
)
lowercase_ : List[Any] = ... | 572 |
"""simple docstring"""
import os
import re
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase_ : List[str] = logging.g... | 572 | 1 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def lowercase__( __UpperCamelCase: Optional[Any] ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : int = {}
... | 508 |
'''simple docstring'''
from __future__ import annotations
import math
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: bool ,__UpperCamelCase: list[int] ,__UpperCamelCase: float ):
"""simple docstring"""
... | 508 | 1 |
from math import sqrt
def __lowerCamelCase ( __lowerCAmelCase : int ) -> int:
__UpperCamelCase : List[Any] = 0
for i in range(1 , int(sqrt(__lowerCAmelCase ) + 1 ) ):
if n % i == 0 and i != sqrt(__lowerCAmelCase ):
... | 269 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _A ( UpperCAme... | 269 | 1 |
'''simple docstring'''
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
UpperCAmelCase_ = re.compile(r"^(?P<major>\d+)" r"\.(?P<minor>\d+)" r"\.(?P<patch>\d+)$")
@total_ord... | 490 |
'''simple docstring'''
import numpy as np
import datasets
UpperCAmelCase_ = "\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean dis... | 490 | 1 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
cla... | 96 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : Optional[int] = logging.get_logger(__name__)
lowercase : Optional[Any] = {
"""google/pegasus-large""": """https://huggingface.co/... | 116 | 0 |
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 ={
'''google/vit-base-patch16-224''': '''https://huggin... | 713 |
from itertools import count
def lowerCamelCase_ ( lowerCamelCase__ = 5_0 ):
lowerCamelCase_ = [1] * min_block_length
for n in count(lowerCamelCase__ ):
fill_count_functions.append(1 )
for block_length in range(lowerCamelCase__ , n + 1 ):
... | 313 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrainedTokenizerB... | 48 |
"""simple docstring"""
from __future__ import annotations
from typing import Any
def __snake_case ( UpperCamelCase__ ) -> int:
"""simple docstring"""
if not postfix_notation:
return 0
A = {'+', '-', '*', '/'}
A = []
for token in pos... | 690 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__snake_case : str = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MAP', ... | 713 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
__snake_case : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def __init__( self : Tuple... | 687 | 0 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_lowerCamelCase = TypeVar('T')
class UpperCamelCase_ ( Generic[T] ):
def __init__( self :Optional[int] , __A :T ) -> Dict:
"""simple docst... | 6 |
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobertaTokenizerFast,
)
... | 6 | 1 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__SCRE... | 149 |
def snake_case_ ( lowercase__ : list[int] ):
'''simple docstring'''
_lowerCAmelCase =[]
if len(lowercase__ ) == 1:
return [nums.copy()]
for _ in range(len(lowercase__ ) ):
_lowerCAmelCase =nums.pop(0 )
_lowerCAmelCase ... | 149 | 1 |
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : List[str] =(DDPMScheduler,)
def UpperCamelCase_ ( self : Dict , **Uppe... | 411 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class snake_case__(_UpperCamelCase ):
"""simple docstring"""
def __init__( self : str , SCREAMING_SNAKE_CASE : Any , SCREAMING_SNAKE_CASE : List[Any] ):
... | 81 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_utils import FrozenDict
... | 81 | 1 |
import argparse
import torch
from transformers import MobileBertConfig, MobileBertForPreTraining, load_tf_weights_in_mobilebert
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE__ ( snake_case__ :Any , snake_case__ :str , sn... | 67 |
def UpperCAmelCase_ ( _A ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ = int(_A )
if n_element < 1:
SCREAMING_SNAKE_CASE__ = ValueError('''a should be a positive number''' )
raise my_error
SCREAMING_SNAKE_CASE__ ... | 493 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from d... | 717 |
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
WEIGHTS_NAME,
AdamW,
OpenAIG... | 382 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase : Dict = {
"configuration_m2m_100": ["M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP", "M2M100Config",... | 262 | '''simple docstring'''
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
__lowerCAmelCase : int = [
os.path.join(os.path.dirname(__file__), dirname)
... | 262 | 1 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCamelCase_ ( lowerCamelCase : int ) -> bool:
"""simple docstring"""
__magic_name__ : int = int(number**0.5 )
ret... | 721 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A = logging.get_logger(__name__)
A = {
"""microsoft/xprophetnet-large-wiki100-cased""": (
"""https://huggingface.co/microsoft/xprophetnet-large-wiki100... | 147 | 0 |
"""simple docstring"""
from __future__ import annotations
import csv
import requests
from bsa import BeautifulSoup
def __snake_case ( __A = "" ) -> dict[str, float]:
lowercase : Dict = url or """https://www.imdb.com/chart/top/?ref_=nv_mv_250"""
low... | 607 |
"""simple docstring"""
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
lowerCAmelCase: Tuple =logging.get_logger(__name__)
lowerCAmelCase: int ... | 607 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase : Tuple = logging.get_logger(__name__)
_lowerCamelCase : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2-tiny-patch4-wi... | 708 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
... | 407 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowerCAmelCase__ = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvaila... | 626 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCamelCase ( __a = "isbn/0140328726" ):
SCREAMING_SNAKE_CASE_ = olid.strip().strip('''/''' ) # Remove leading/trailing whitespace & slashes
if n... | 626 | 1 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class __snake_case ( __lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = ["""image_processor""", """tokenizer"""]
lowerCAmelCase__ ... | 155 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def A__ ( ) -> Tuple:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
f... | 155 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block,... | 38 |
'''simple docstring'''
def __lowerCamelCase ( A__ , A__ ) -> bool:
"""simple docstring"""
UpperCamelCase = len(A__ )
UpperCamelCase = [[False] * (required_sum + 1) for _ in range(arr_len + 1 )]
# for e... | 430 | 0 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
_UpperCamelCase : Tuple = [
"""kernels/rwkv/wkv_cuda.cu""",
"""kernels/rwkv/wkv_op.cpp""",
"""kernels/deformable_detr/ms_deform_attn.h""",
"""kernels/deformable_detr/cuda/ms... | 341 |
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
MaxLengthCriteria,
MaxNe... | 341 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase__ : Optional[Any] = {
'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}
try:
if not is_torch_availabl... | 105 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE (A ) -> bool:
"""simple docstring"""
lowercase__ = [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__ == "__mai... | 460 | 0 |
lowerCamelCase_ : Optional[Any] = range(2, 20 + 1)
lowerCamelCase_ : Tuple = [10**k for k in range(ks[-1] + 1)]
lowerCamelCase_ : int = {}
def lowerCAmelCase( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ):
__a = s... | 716 | from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from... | 246 | 0 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
UpperCamelCase__ : List[Any] = importlib.util.find_spec('''s3fs''') is not None
if _has_safs:
from .safil... | 105 |
from numpy import exp, pi, sqrt
def UpperCAmelCase ( a_ , a_ = 0.0 , a_ = 1.0 ) -> int:
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 55 | 0 |
import math
def SCREAMING_SNAKE_CASE( __UpperCamelCase ) -> int:
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
a__ : Tuple = F'Input value of [number={number}] must be an integer'
raise TypeError(__UpperCamelCase )
if number < 1:
a... | 207 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE( __UpperCamelCase ) -> list:
if len(__UpperCamelCase ) == 0:
return []
a__ , a__ : int = min(__UpperCamelCase ), max(__UpperCamelCase )
a__ : Optional[int] = int(max_value - min_value ... | 207 | 1 |
'''simple docstring'''
from ..utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_scipy_available,
is_torch_available,
is_torchsde_available,
)
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ..... | 245 |
'''simple docstring'''
from typing import List
import numpy as np
def _A ( snake_case ) -> int:
_lowercase : Optional[int] = {key: len(snake_case ) for key, value in gen_kwargs.items() if isinstance(snake_case , snake_case )}
if len(set(lists_lengths.values() ) ) ... | 245 | 1 |
import doctest
from collections import deque
import numpy as np
class __SCREAMING_SNAKE_CASE :
def __init__( self ):
"""simple docstring"""
lowerCAmelCase__ = [2, 1, 2, -1]
lowerCAmelCase__ = [1, 2, 3, 4]
... | 365 |
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__snake_case : str = [
"""word_embeddings_laye... | 365 | 1 |
import cva
import numpy as np
class snake_case_ :
'''simple docstring'''
def __init__( self : int , _UpperCamelCase : float , _UpperCamelCase : int ) ->int:
if k in (0.04, 0.06):
snake_case_ = k
... | 39 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
_lowercase = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokeniz... | 356 | 0 |
from math import ceil
def lowerCAmelCase_ ( lowercase: int = 1_001 ) -> int:
'''simple docstring'''
_UpperCamelCase: str = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_UpperCamelCase: Any = 2 * i + 1
_UpperCamelCase: Any = 2 * i
_UpperC... | 264 | # Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicabl... | 264 | 1 |
import os
def lowerCAmelCase ( UpperCamelCase__ : Optional[Any] ) -> Optional[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE: Any = len(grid[0] )
__SCREAMING_SNAKE_CASE: Any = len(UpperCamelCase__ )
__SCREAMING_SNAK... | 202 |
import pprint
import requests
lowerCamelCase__ = "https://zenquotes.io/api"
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """/today""" ).json()
def __A() -> list:
"""simple docstring"""
return requests.get(API_ENDPOINT_URL + """... | 612 | 0 |
"""simple docstring"""
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, Scheduler... | 713 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase__ : str = logging.get_logger(__name__)
UpperCAmelCase__ : Dict = {
'microsoft/unispeech-large-1500h... | 545 | 0 |
from manim import *
class _UpperCamelCase ( _lowercase ):
'''simple docstring'''
def _snake_case ( self : Optional[int] ):
'''simple docstring'''
__lowerCamelCase : Union[str, Any] = Rectangle(height=0.5 ... | 519 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 194 | 0 |
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 ConfigT... | 550 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase : Union[str, Any] =logging.get_logger(__name__)
__lowercase : List[Any] ={
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface.co/tanreinama/GPT... | 550 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ = {"""configuration_wavlm""": ["""WAVLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """WavLMConfig"""]}
try:
if not is_torch_available():
... | 92 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __lowercase ( ... | 542 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
UpperCamelCase : int = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalD... | 707 | '''simple docstring'''
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
MusicgenForConditionalGeneration... | 610 | 0 |
"""simple docstring"""
def __lowerCamelCase ( UpperCamelCase__ ): # noqa: E741
"""simple docstring"""
_UpperCAmelCase = len(lowerCAmelCase__ )
_UpperCAmelCase = 0
_UpperCAmelCase = [0] * n
_UpperCAmelCase = [False] * n
_UpperCAmelCase = [False] * n
def dfs(UpperCamel... | 657 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
'stud... | 99 | 0 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowercase : str = argparse.ArgumentParser(
description=(
'''Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer ... | 714 |
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
lowercase : Tuple = '''.'''
# Internal TensorFlow ops th... | 114 | 0 |
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