code stringlengths 82 53.2k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import sys
from collections import defaultdict
class _A :
def __init__( self : List[Any] ) -> Optional[int]:
"""simple docstring"""
__snake_case : Optional[Any] = []
def lowercase__ ( ... | 26 |
'''simple docstring'''
def _a ( _lowerCamelCase ) -> int:
"""simple docstring"""
if not isinstance(_lowerCamelCase , _lowerCamelCase ):
raise TypeError("""only integers accepted as input""" )
else:
__snake_case : List[Any] ... | 26 | 1 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class snake_case (... | 401 |
"""simple docstring"""
import heapq as hq
import math
from collections.abc import Iterator
class snake_case :
def __init__( self :Dict , _lowerCamelCase :List[str] ):
__SCREAMING_SNAKE_CASE : Union[str, Any] = str(id_ )
__SCREAMING_SNAKE_CAS... | 401 | 1 |
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository c... | 219 |
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_accelerate,
require_tf,
require_torch,
requ... | 219 | 1 |
'''simple docstring'''
def __lowerCamelCase ( _UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
UpperCAmelCase_ = F"""Input value of [number={number}] must be an integer"""
raise TypeE... | 43 | '''simple docstring'''
from __future__ import annotations
def __lowerCamelCase ( _UpperCamelCase : tuple[int, int] , _UpperCamelCase : int ):
'''simple docstring'''
UpperCAmelCase_ , UpperCAmelCase_ = position
UpperCAmelCase_ = [
... | 43 | 1 |
def UpperCamelCase ( _A ):
"""simple docstring"""
__magic_name__ : Tuple = set()
# edges = list of graph's edges
__magic_name__ : List[str] = get_edges(_A )
# While there are still elements in edges list, take an arbitrary edge
... | 324 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast
from ...utils import logging
__magic_name__: Dict = logging.ge... | 324 | 1 |
'''simple docstring'''
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precis... | 178 |
'''simple docstring'''
def lowerCAmelCase_ ( _lowerCamelCase: int ):
if number > 0:
raise ValueError("""input must be a negative integer""" )
__SCREAMING_SNAKE_CASE : str = len(bin(_lowerCamelCase )[3:] )
__SCREAMING_SNAKE_CASE : Any = bin(abs(_lowerCamel... | 178 | 1 |
def _UpperCamelCase ( lowerCAmelCase_ = 1_0_0_0_0_0_0 ) ->int:
UpperCAmelCase = set(range(3 , lowerCAmelCase_ , 2 ) )
primes.add(2 )
for p in range(3 , lowerCAmelCase_ , 2 ):
if p not in primes:
continue
primes.difference_update(set(range(p * p... | 377 |
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as met
class __low... | 377 | 1 |
'''simple docstring'''
import gc
import unittest
from diffusers import FlaxStableDiffusionInpaintPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from f... | 721 |
'''simple docstring'''
__lowerCamelCase = range(2, 20 + 1)
__lowerCamelCase = [10**k for k in range(ks[-1] + 1)]
__lowerCamelCase = {}
def UpperCAmelCase__ ( UpperCAmelCase__, UpperCAmelCase__, UpperCAmelCase__, UpperCAmelCase__ ) -> Tuple... | 667 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase : Dict = logging.get_logger(__name__)
_lowerCamelCase ... | 403 | import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class lowercase ( a ):
def __init__( self : Dict , _UpperCamelCase : Optional[int] , _UpperCamelCase : Any , _Upp... | 403 | 1 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCamelCase_ : Union[str, Any] = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that genera... | 670 |
from manim import *
class _UpperCamelCase ( _A ):
'''simple docstring'''
def lowerCAmelCase__ ( self : int ):
UpperCamelCase_: Dict = Rectangle(height=0.5 , width=0.5 )
UpperCamelCase_: Dict = Rectangle(height=0.46 ,... | 670 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A_ : Optional[Any] ={"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}
try:
if not is... | 483 |
# 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 require... | 483 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_te... | 721 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class _a ( unittest.TestCase ):
"""simple docstring"""
... | 26 | 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/LICEN... | 437 |
"""simple docstring"""
def UpperCAmelCase_ ( __a : int ):
'''simple docstring'''
_lowerCamelCase : Optional[Any] = int(__a )
if decimal in (0, 1): # Exit cases for the recursion
return str(__a )
_lowerCamelCase , _lowerCame... | 437 | 1 |
"""simple docstring"""
import math
class __A :
def lowerCamelCase__ ( self : str , __snake_case : list[list[float]] , __snake_case : list[int] ) -> int:
__magic_name__: Dict = 0.0
__magic_name__: ... | 720 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
requ... | 213 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __a ( SCREAMING_SNAKE_C... | 228 |
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import C... | 352 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_A : List[Any] = logging.get_logger(... | 721 |
"""simple docstring"""
import argparse
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoTokenizer, RobertaPreLayerNormConfig, RobertaPreLayerNormForMaskedLM
from transformers.utils import logging
logging.set_verbosity_info()
_A : Optional[Any] = logg... | 518 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileViTConfig
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_commo... | 50 |
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def A_ ( lowercase_ , lowercase_ , lowercase_ ) -> Dict:
# Initialise PyTorch model
_snake_... | 326 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __SCREAMING_SNAKE_CASE ( __a):
@staticmethod
@abstractmethod
def UpperCamelCase__ ( _UpperCamelCase ):
"""simple docstring"""
raise NotImplementedError()
... | 706 |
from collections import deque
from .hash_table import HashTable
class __SCREAMING_SNAKE_CASE ( __lowercase):
def __init__( self , *_UpperCamelCase , **_UpperCamelCase ):
"""simple docstring"""
super().__init__(*_UpperCamelCase , ... | 365 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCAmelCase ( UpperCAmelCas... | 42 |
def lowerCamelCase_ ( _UpperCamelCase , _UpperCamelCase , _UpperCamelCase ) -> list:
"""simple docstring"""
snake_case_ : Tuple = len(_UpperCamelCase )
snake_case_ : Union[str, Any] = [[0] * n for i in range(_Upp... | 60 | 0 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.d... | 721 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data im... | 696 | 0 |
"""simple docstring"""
lowercase__ :str = {str(digit): digit**5 for digit in range(1_0)}
def lowerCamelCase_ ( UpperCAmelCase_ ) ->int:
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(UpperCAmelCase_ ) )
def ... | 522 |
"""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.... | 522 | 1 |
"""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 sepia a... | 533 |
"""simple docstring"""
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase : List[str] = HfApi()
lowerCAmelCase : Tuple = {}
# fmt: off
lowerCAmelCase : List[str] = torch.tensor([... | 533 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def __lowerCamelCase ( self ):
... | 421 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def __lowerCamelCase ( SCREAMING_SNAKE_CASE_ : Optional[Any] ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_, SCREAMING_SNAKE_CASE_ : Optional[int] = img.shape[0], ... | 421 | 1 |
from sklearn.metrics import matthews_corrcoef
import datasets
a : List[str] = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto accou... | 704 |
'''simple docstring'''
a : List[Any] = """Alexander Joslin"""
import operator as op
from .stack import Stack
def __lowerCamelCase ( _lowercase ) -> int:
UpperCAmelCase : Dict = {"""*""": op.mul, """/""": op.truediv, """+""": op.add, """-""": op.sub}
... | 672 | 0 |
"""simple docstring"""
from math import pow, sqrt
def SCREAMING_SNAKE_CASE ( *snake_case):
__snake_case = len(snake_case) > 0 and all(value > 0.0 for value in values)
return result
def SCREAMING_SNAKE_CASE ( snake_case, snake_case):
return (
... | 564 | """simple docstring"""
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__lowercase : str = get_test... | 564 | 1 |
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate import Ac... | 708 |
import tempfile
import unittest
from make_student import create_student_by_copying_alternating_layers
from transformers import AutoConfig
from transformers.file_utils import cached_property
from transformers.testing_utils import require_torch
lowerCAmelCase = """sshleifer/bart-tiny-random"""
lowerCAme... | 675 | 0 |
from __future__ import annotations
import math
def __SCREAMING_SNAKE_CASE ( a__ : int ,a__ : int ,a__ : bool ,a__ : list[int] ,a__ : float ) -> int:
if depth < 0:
raise ValueError("""Depth cannot be less than 0""" )
if not scores:
raise ValueEr... | 17 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def __SCREAMING_SNAKE_CASE ( ) -> Tuple:
__A : List[Any] = ArgumentParser(
description=(
"""PyTorch TPU distributed t... | 17 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase_ : Any = {'''configuration_vit''': ['''VIT_PRETRAINED... | 712 |
'''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 M... | 265 | 0 |
'''simple docstring'''
def __magic_name__ ( __UpperCAmelCase ) -> List[str]:
'''simple docstring'''
return " ".join(
''''''.join(word[::-1] ) if len(lowerCamelCase__ ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
... | 640 | """simple docstring"""
import torch
from torch import nn
from transformers import CLIPPreTrainedModel, CLIPVisionModel
from ...models.attention import BasicTransformerBlock
from ...utils import logging
__lowerCAmelCase : int = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 644 | 0 |
"""simple docstring"""
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_au... | 706 |
"""simple docstring"""
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipelin... | 439 | 0 |
'''simple docstring'''
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,... | 390 | import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
lowercase_ : Optional[int] = logging.get_logger(__name__)
def A__ ( snake_case_ : List[Any] ):
SCREAMING_SNAKE_... | 64 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A__ : Union[str, Any] = {
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransf... | 244 |
"""simple docstring"""
def _snake_case ( lowerCamelCase__ : Dict ) -> Dict:
lowerCamelCase_ : Dict =[0] * len(lowerCamelCase__ )
lowerCamelCase_ : Tuple =[]
lowerCamelCase_ : Optional[int] =[1] * len(lowerCamelCase_... | 244 | 1 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transf... | 545 |
"""simple docstring"""
import argparse
import copy
def A ( __snake_case: Union[str, Any] ) -> Tuple:
"""simple docstring"""
__magic_name__ = {}
with open(__snake_case ) as f:
for line in f:
i... | 545 | 1 |
"""simple docstring"""
a_ = frozenset(
[
"prompt",
"height",
"width",
"guidance_scale",
"negative_prompt",
"prompt_embeds",
"negative_prompt_embeds",
"cross_attention_kwargs",
]
)
a_ = frozen... | 621 |
"""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 | 1 |
from maths.prime_check import is_prime
def _UpperCAmelCase ( UpperCamelCase: int ):
"""simple docstring"""
if not isinstance(UpperCamelCase , UpperCamelCase ):
__lowerCAmelCase = F"Input value of [number={number}] must be an integer"
raise TypeError(UpperCamelCase )
if is_pri... | 611 |
class a :
def __init__( self : Union[str, Any] , snake_case__ : str ):
"""simple docstring"""
__lowerCAmelCase = arr.split("," )
def UpperCAmelCase__ ( self : str ):
"""simple docstring"""
__lowerCAmelCase ... | 611 | 1 |
"""simple docstring"""
import requests
__lowerCAmelCase : Optional[int] = '''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def __lowerCAmelCase ( __UpperCamelCase : str ):
'''simple docstring'''
s... | 714 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : bool = False ):
'''simple docstring'''
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n ... | 21 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applica... | 671 |
from __future__ import annotations
from math import ceil, floor, sqrt
def A_ ( _UpperCAmelCase = 2_00_00_00 ):
SCREAMING_SNAKE_CASE_: list[int] = [0]
SCREAMING_SNAKE_CASE_: int
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ... | 671 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers... | 708 |
"""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 passes --user <us... | 463 | 0 |
def a__ ( lowercase__ = 1 , lowercase__ = 1_0_0_0 ):
'''simple docstring'''
UpperCAmelCase_ =1
UpperCAmelCase_ =0
for divide_by_number in range(lowercase__ , digit + 1 ):
UpperCAmelCase_ =[]
UpperCAmel... | 54 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def a__ ( lowercase__ , lowercase__ , lowercase__=1_0_2_4 , lowercase__=1_0_2_4 , lowercase__=False , ... | 54 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__magic_name__ = {
"""configuration_swiftformer""": [
"""SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""SwiftFormerConfig""",
"""S... | 720 | def UpperCAmelCase__( __UpperCAmelCase : str ):
if not all(x.isalpha() for x in string ):
raise ValueError('String must only contain alphabetic characters.' )
__snake_case : str = sorted(string.lower() )
return len(__UpperCAmelCase ) == len(set(__UpperCAmelCa... | 679 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Union[str, Any] = {
"""configuration_xlm_roberta_xl""": [
"""XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XLMRobert... | 33 |
'''simple docstring'''
from itertools import permutations
def UpperCAmelCase_ ( __lowerCamelCase : tuple ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
lowercase_ :... | 172 | 0 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image... | 380 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
lowercase_ = {'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BeitConfig', 'BeitOnnxConfi... | 380 | 1 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : list[list[str]] = [[] for _ in range(UpperCamelCase )]
lowerCAmelCase__ : List[str] = key - 1
if key <= 0:
... | 565 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
_lowerCAmelCase = '''https://www.indeed.co.in/jobs?q=mobile+app+development&l='''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase = "mumbai" ):
""... | 565 | 1 |
'''simple docstring'''
import cmath
import math
def __magic_name__ ( __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase, __UpperCAmelCase ) -> complex:
'''simple docstring'''
snake_case_ = math.radians(__UpperCAmelCase )
snake_case_ = math.radians(_... | 718 |
'''simple docstring'''
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
a : int = collections.namedtuple('_... | 593 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase = logging.get_logger(__name__)
lowerCamelCase = {
"""edbeeching/decision-transformer-gym-hopper-medium""": (
"""https://huggingface.co/edbeeching/dec... | 82 |
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowercase__( A ):
snake_case__ : List[Any] = {}
snake_case__ : int = tokenizer(exa... | 170 | 0 |
'''simple docstring'''
from collections import Counter
from timeit import timeit
def _lowerCAmelCase( UpperCAmelCase_ : str = "" , ) -> Tuple:
return sum(c % 2 for c in Counter(input_str.replace(""" """ , """""" ).lower() ).values() ) < 2
def _lowerCAmelCase( ... | 718 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
... | 211 | 0 |
"""simple docstring"""
import functools
def SCREAMING_SNAKE_CASE__ ( __UpperCAmelCase , __UpperCAmelCase ) -> int:
lowercase__: Any = len(__UpperCAmelCase )
lowercase__: Any = len(__UpperCAmelCase )
@functools.cache
def min_distance(__UpperCAmelCase , _... | 586 | """simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"distilbert-base-uncased": "https://huggingfa... | 586 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class ... | 543 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from t... | 543 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCAmelCase_ )
class _SCREAMING_SNAKE_CASE ( UpperCAmelCase_ ):
lowerCAmelCase__ = field(default='question-answering-extra... | 463 |
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple ... | 411 | 0 |
"""simple docstring"""
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()
UpperCAmelCase = [
'''word_embedd... | 712 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 475 | 0 |
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import numpy as np
from .import_utils i... | 515 |
from ..utils import DummyObject, requires_backends
class a__ ( metaclass=UpperCamelCase__ ):
a : int = ["""torch""", """scipy"""]
def __init__( self , *A , **A ) -> str:
'''simple docstring'''
requires_b... | 515 | 1 |
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
from transformers.utils im... | 718 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
lowercase_ : List[str] = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
author = "Snover, Matthew and
D... | 652 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
__a = datasets.utils.logging.get_logger(... | 97 |
'''simple docstring'''
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import BatchEncoding, MarianTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import is_sentencepiece_available, is_tf_a... | 56 | 0 |
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def _lowercase ( lowercase__ , lowercase__ , lowercase__ , lowercase__ ):
__lowerCAmelCase : List[str] = {
'''en''': '''Machine learning is great, isn\'t it?''',
'''ru'''... | 583 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase = {
"configuration_luke": ["LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP", "LukeConfig"],
"tokenization_luke": ["LukeTokenizer"],
}
try:
if not is_torch_available():
raise ... | 583 | 1 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def UpperCamelCase__ ( SCREAMING_SNAKE_CASE__ ):
# encoder.embeddings are double copied in original FLAVA
return sum... | 669 |
import math
def UpperCamelCase__( UpperCamelCase__ : int )->list:
A__ = [True] * n
A__ = False
A__ = False
A__ = True
for i in range(3 , int(n**0.5 + 1 ) , 2 ):
A__ = i * 2
wh... | 190 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
lowerCAmelCase_ = 'src/transformers'
# Matches is_xxx_available()
lowerCAmelCase_ = re.compile(R'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
lowerCAmelCase_ = re.com... | 110 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_albert im... | 110 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"facebook/xlm-roberta-xl": "h... | 666 |
from collections.abc import Sequence
def lowerCAmelCase_ ( lowerCamelCase = None ):
if nums is None or not nums:
raise ValueError("""Input sequence should not be empty""" )
__magic_name__ : str =nums[0]
for i in range(1 , len(lowerCamelCase ) ... | 21 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase__ :Optional[Any] = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", ""... | 704 |
'''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 import floats_list
... | 483 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils... | 129 |
"""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 | 1 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( A : Optional[Any] , A : Any ) -> Any:
"""simple docstring"""
while second != 0:
__snake_case : List[Any] = first & second
first ^= second
... | 713 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( A : list ) -> list:
"""simple docstring"""
__snake_case : Tuple = False
while is_sorted is False: # Until all the indices are traversed keep looping
__snake_case : ... | 61 | 0 |
from collections.abc import Callable
class UpperCamelCase_ :
'''simple docstring'''
def __init__( self , UpperCamelCase = None) -> Union[str, Any]:
UpperCamelCase__ : Optional[Any] = []
# Stores indexes of each item for supporting updates an... | 410 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase_ = {
'configuration_transfo_xl': ['TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'TransfoXLConfig'],
'tokenization_tr... | 603 | 0 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
lowerCamelCase_ : Tuple = """__DUMMY_TRANSFORMERS_USER__"""
lowerCamelCase_ : List[Any] = """Dummy User"""
lowerCamelCase_ : Op... | 670 |
# 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 required by applicab... | 670 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
UpperCamelCase__ = tuple[int, int]
class A :
def __init__(self : Any , __UpperCAmelCase : set[int] , __UpperCAmelCase : Mapping[EdgeT, int] ) -> None:
"""simple d... | 486 |
from random import shuffle
import tensorflow as tf
from numpy import array
def _a ( SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ : int ) -> Optional[Any]:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : List[str] ... | 663 | 0 |
"""simple docstring"""
import numpy as np
class _UpperCAmelCase :
"""simple docstring"""
def __init__( self , _lowercase=None , _lowercase=None , _lowercase=None , _lowercase=None , _lowercase=None ) -> Union[str, Any]:
self.set_matricies(red=_... | 719 | """simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : str =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[Any] ={
'asapp/sew-d-tiny-100k': 'https://huggingfa... | 558 | 0 |
'''simple docstring'''
import math
def _SCREAMING_SNAKE_CASE ( __snake_case : int ):
_A = []
_A = 2
_A = int(math.sqrt(__snake_case ) ) # Size of every segment
_A = [True] * (end + 1)
_A = []
while start <= end:
i... | 107 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCAmelCase : str = {
'''configuration_vision_encoder_decoder''': ['''VisionEnco... | 107 | 1 |
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 import floats_list
@require_torchaudio
@require_s... | 711 |
def UpperCAmelCase ( UpperCamelCase__ = 10_00 ) -> int:
'''simple docstring'''
__lowerCAmelCase = -1
__lowerCAmelCase = 0
for a in range(1 , n // 3 ):
# Solving the two equations a**2+b**2=c**2 and a+b+c=N eliminating c
__lowe... | 334 | 0 |
_lowercase = range(2, 20 + 1)
_lowercase = [10**k for k in range(ks[-1] + 1)]
_lowercase = {}
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
lowerCAmelCase_ : str = sum(a_i[j] for j in range(snake_case__ , ... | 659 |
"""simple docstring"""
def lowercase__(A ) ->bool:
"""simple docstring"""
return credit_card_number.startswith(("34", "35", "37", "4", "5", "6") )
def lowercase__(A ) ->bool:
"""simple docstring"""
lowerca... | 218 | 0 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTok... | 705 |
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def UpperCAmelCase ( lowerCAmelCase__ ):
'''simple docstring'''
return "".join(sorted(lowerCAmelCase__ ) )
def UpperCAmelCase ( lowerCAmelCase__ ):
'''simple d... | 205 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ ):
"""s... | 327 |
def UpperCAmelCase_ (_lowerCAmelCase : int = 60_08_51_47_51_43 ):
try:
__UpperCamelCase : Optional[Any] = int(_lowerCAmelCase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
raise ValueError("Parameter... | 327 | 1 |
'''simple docstring'''
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def _lowerCAmelCase ( lowercase : int , lowercase : Any=1 ) ->Any:
"""simple docstring"""
if ... | 720 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase = {}
try:
if not is_sentencepiece_availabl... | 318 | 0 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class __magic_name__ :
"""simple docstring"""
def __init__( self : Tuple , _lowercase : Tuple ):
"""simple docstring"""
_UpperCamelCase: Any = data
_Up... | 271 |
"""simple docstring"""
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->list[str]:
"""simple docstring"""
return [sentence[i : i + ngram_size] for i in range(len(_SCREAMING_SNAKE_CASE ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
... | 93 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ :Any = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig"""... | 720 |
"""simple docstring"""
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCamelCase_ ( UpperCAmelCase_ , UpperCAmelCase_ ... | 374 | 0 |
'''simple docstring'''
def UpperCamelCase ( _lowerCamelCase : str ):
A__ = [int(_lowerCamelCase ) for i in ip_va_address.split("." ) if i.isdigit()]
return len(_lowerCamelCase ) == 4 and all(0 <= int(_lowerCamelCase ) <= 2_54 for octet in octets )
if __name__ == "__... | 440 |
'''simple docstring'''
# 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
#
... | 440 | 1 |
import os
from typing import BinaryIO, Optional, Union
import numpy as np
import pyarrow.parquet as pq
from .. import Audio, Dataset, Features, Image, NamedSplit, Value, config
from ..features.features import FeatureType, _visit
from ..formatting import query_table
from ..packaged_modules import _PACKAGED_DATASETS_M... | 345 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BlipaProcessor, BlipImageProcessor, GPTa... | 345 | 1 |
import collections
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = '▁'
_lowerCamel... | 144 |
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_lowerCamelCase = {
'text_branch': 'text_model',
'audio_branch': 'audio_model.audio_encoder',
'attn': 'attention.self',
'self.pro... | 144 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCAmelCase : str = logging.get_logger(__name__)
_UpperCAmelCase : List[str] = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# See all Cvt models ... | 702 |
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_image_inputs
if is_to... | 108 | 0 |
"""simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
... | 160 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
A: Tuple = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase__ ):
def __init__( self , *_SCREAMING_SNAKE_CASE , **_SCREAMING_SNAKE_CA... | 160 | 1 |
'''simple docstring'''
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def SCREAMING_SNAKE_CASE__ ( __A = "laptop" ) -> Optional[int]:
_snake_case = F'https://www.amazon.in/laptop/s?k={product}'
_snake_case = {... | 713 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Model... | 542 | 0 |
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 = logging.get_logger(__name__)
... | 230 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import T... | 230 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_tor... | 569 |
import numpy as np
def __lowerCamelCase ( snake_case__ ) -> np.array:
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 569 | 1 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
BertTokenizerFast,
CTRL... | 321 | from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class snake_case :
"""simple docstring"""
__lowerCAmelCase = 42
__lowerCAmelCase = None
__lowerCAmelCase = None
lowerCAmelCase__ =... | 321 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
... | 711 | '''simple docstring'''
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase ( UpperCAmelCase__ : int , UpperCAmelCase__ : int , UpperCAmelCase__ : float = 1 / sqrt(2 ) ) -> IIRFilter:
lowercase_ : str ... | 30 | 0 |
from collections import deque
from .hash_table import HashTable
class __a( _a ):
"""simple docstring"""
def __init__( self ,*_SCREAMING_SNAKE_CASE ,**_SCREAMING_SNAKE_CASE ) -> List[Any]:
super().__init__(*_SCREAMING_SNAKE_CASE ,**_SCREAMING_SNAKE_CASE )
... | 30 |
def lowerCamelCase__ ( ):
'''simple docstring'''
UpperCAmelCase_ : Dict = 0
for i in range(1 , 1001 ):
total += i**i
return str(_lowercase )[-10:]
if __name__ == "__main__":
print(solution()) | 30 | 1 |
"""simple docstring"""
import math
def _lowerCAmelCase ( lowerCamelCase__ : str, lowerCamelCase__ : str ) -> Union[str, Any]:
'''simple docstring'''
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
r... | 703 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax ... | 295 | 0 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# al... | 128 |
'''simple docstring'''
from math import factorial
def lowerCAmelCase__ ( lowerCamelCase : int ,lowerCamelCase : int ,lowerCamelCase : float ):
if successes > trials:
raise ValueError('successes must be lower or equal to trials' )
if trials < 0 or ... | 128 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
SCREAMING_SNAKE_CASE__ = tuple[int, int]
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self : Optional[int] , _snake_case : set[int] , _snake... | 721 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 52 | 0 |
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 import floats_list
@require_torchaudio
@requir... | 53 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
__magic_name__ = TypeVar('''T''')
class _SCREAMING_SNAKE_CASE ( Generic[T] ):
def __init__( self , lowerCamelCase ):
snake_case__ = data
sna... | 276 | 0 |
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 imp... | 703 |
'''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from t... | 499 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_availa... | 128 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def lowerCAmelCase__ ( lowerCamelCase : Callable[[int | float], int | float] ,lowerCamelCase : int | float ,lowerCamelCase : int | float ,lowerCamelCase : int = 100 ,):
... | 128 | 1 |
'''simple docstring'''
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
lowercase__ =logging.getLogger(__name__)
if is_torch_tpu_available... | 511 |
'''simple docstring'''
import json
from typing import 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_roberta import ... | 511 | 1 |
'''simple docstring'''
from __future__ import annotations
def __snake_case (__UpperCAmelCase , __UpperCAmelCase ):
"""simple docstring"""
# Checks if the entire collection has been sorted
if len(__UpperCAmelCase ) <= 1 or n <= 1:
return
insert_next(__UpperCAmelCase ... | 501 |
'''simple docstring'''
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__lowerCamelCase... | 501 | 1 |
__UpperCamelCase : Optional[Any] = {
'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.... | 641 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__UpperCamelCase : str = {
'configuration_x_clip': [
'XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'XCLIPConfig',
'XCLIPTextConfig',
'... | 641 | 1 |
"""simple docstring"""
import os
def __A ( ) -> Tuple:
with open(os.path.dirname(a_) + '''/grid.txt''') as f:
__a : Dict = [] # noqa: E741
for _ in range(20):
l.append([int(a_) for x in f.readline().split()])
__a ... | 52 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common imp... | 397 | 0 |
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
__A : str = 5_0_0_0_0
__A : Optional[Any] = 5_0_0_0
__A : Union[str, Any] = os.path.split(__file__)
__A : int = os.path.join(RESULTS_BASEPATH, 'results', RESULTS_FILENAME.re... | 718 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokenizer, Bl... | 698 | 0 |
import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTokenizer
else:
a... | 35 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCamelCase ( a ):
"""simple docstring"""
UpperCAmelCase_ : Dict ="ClapFeatureExtractor"
UpperCAmelCase_ : Union[str, Any] =("RobertaToken... | 243 | 0 |
"""simple docstring"""
from typing import Dict, Optional
import numpy as np
import datasets
UpperCAmelCase : Tuple = "\nIoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union\nbetween the predicted segmentation and the ground truth. Fo... | 712 |
"""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 : Any = {... | 100 | 0 |
'''simple docstring'''
from __future__ import annotations
class UpperCAmelCase :
"""simple docstring"""
def __init__( self , _snake_case , _snake_case ) -> Optional[Any]:
_UpperCamelCase, _UpperCamelCase : int = text, pattern
_UpperCamelCase, ... | 683 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | 683 | 1 |
def A ( _lowercase ):
if n_term == "":
return []
SCREAMING_SNAKE_CASE : Optional[int] = []
for temp in range(int(_UpperCamelCase ) ):
series.append(f"""1/{temp + 1}""" if series else '''1''' )
return series
if __name__ == "__... | 715 | import os
import re
import warnings
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_ta import TaTokenizer
e... | 34 | 0 |
'''simple docstring'''
from typing import List, Union
import numpy as np
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, logging
from .base import PIPELINE_INIT_ARGS, ArgumentHandler, ChunkPipeline
lowercase__ : Dict = log... | 8 |
'''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_i... | 585 | 0 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.c... | 242 |
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torc... | 242 | 1 |
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