code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...tes... | 20 |
'''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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class __A ( UpperCamelCase__ ):
UpperCamelCase = (IPNDMScheduler,)
UpperCamelCase = (("""num_inference_steps""", 50),)
... | 21 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''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/licenses/... | 22 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
# We ignore warnings about stepping the scheduler since we step it ourselves during gradient accumulation
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings("""ignore""", category=UserWarning, module="""torch.optim.lr_scheduler""")
class _a ... | 23 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCAmelCase_ : int = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[Any] = {
'''google/umt5... | 24 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion_safe i... | 25 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...on... | 26 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
def __lowerCAmelCase( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> float:
"""simple docstring"""
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modul... | 27 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A )
class lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
'''simple docstring'''
from random import randint, random
def lowercase__( __UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: int ,__UpperCamelCase: bool = False ,__UpperCamelCase: bool = False ,__UpperCamelCase: int = 5 ,)... | 28 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
"""simple docstring"""
import random
def lowercase ( lowerCAmelCase__ ):
lowerCamelCase_ = num - 1
lowerCamelCase_ = 0
while s % 2 == 0:
lowerCamelCase_ = s // 2
t += 1
for _ in range(5 ):
lowerCamelCase_ = random.randrange(2 ,num - 1 )
... | 29 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
import math
import sys
def lowerCamelCase__ ( _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : List[str] = ''''''
try:
with open(_lowercase , '''rb''' ) as binary_file:
UpperCAmelCase_ : Dict = binary_file.read()
fo... | 30 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Any = {
'microsoft/git-base': 'https://huggingface.co/mi... | 31 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
import baseaa
def A__ ( SCREAMING_SNAKE_CASE_ : str ) -> bytes:
"""simple docstring"""
return baseaa.baaencode(string.encode('''utf-8''' ) )
def A__ ( SCREAMING_SNAKE_CASE_ : bytes ) -> str:
"""simple docstring"""
... | 32 |
'''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,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE ( __lowerCAmelCase , __lowerCAmelCase = None , __lowerCAmelCase = None ) -> None:
if start is None:
snake_case__ = 0
if end is None:
snake_case__ = len(__lowerCAmelCase ) - 1
i... | 33 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
"""simple docstring"""
def __snake_case ( _lowercase = 100_0000 ):
"""simple docstring"""
UpperCamelCase = set(range(3 ,_lowercase ,2 ) )
primes.add(2 )
for p in range(3 ,_lowercase ,2 ):
if p not in primes:
continue
... | 34 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 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 torc... | 35 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import numpy as np
def lowercase ( __A : np.array ) -> np.array:
'''simple docstring'''
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 36 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Optional[int] = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""tiiuae/falcon-40b""": """https://huggingface.co/tiiuae/falcon-40b/resolve/main/config.json"""... | 37 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
A_ : List[str] = logging.getLogger(__name__)
class __snake_case ( __SCREAMING_SNAKE_CASE ):
... | 38 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transforme... | 39 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFAutoModel, is_tensorflow_text_available, is_tf_available
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.testing_utils import require_tensorflow_text, requi... | 40 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 41 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
fr... | 42 |
'''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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
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 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''simple docstring'''
import argparse
import copy
def A_ ( _lowerCAmelCase : str ):
"""simple docstring"""
_lowerCamelCase : Optional[Any] = {}
with open(_lowerCAmelCase ) as f:
for line in f:
if line.split()[0] not i... | 44 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
import numpy as np
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModelWithProjection, PreTrainedModel
from ...utils import logging
UpperCamelCase = logging.get_logger(__name__)
class lowerCAmelCase_ ( lowercase ):
"""simple docstring"""
... | 45 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
"""simple docstring"""
from PIL import Image
def lowerCamelCase_( _lowerCamelCase ) -> Image:
'''simple docstring'''
_lowerCamelCase, _lowerCamelCase : Optional[Any] = image.size
_lowerCamelCase : List[Any] = 0
_lowerCamelCase : ... | 46 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
import math
from numpy import inf
from scipy.integrate import quad
def UpperCAmelCase__ ( lowerCamelCase_ : float ):
if num <= 0:
raise ValueError('math domain error' )
return quad(lowerCamelCase_ , 0 , lowerCamelCase_ , args=(lowerCamelCase_... | 47 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCAmelCase__ : Tuple = logging.get_logger(__name__)
UpperCAmelCase__ : List[str] = {
"google/umt5-small... | 48 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
"""simple docstring"""
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def lowercase__ ( snake_case_ :Dataset , snake_case_ :Dict... | 49 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A )
class lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
'''simple docstring'''
def A__ ( __lowerCAmelCase : int ):
lowerCamelCase__ = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 50 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
'''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... | 51 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
A = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
author = "Snover, Matthew ... | 52 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def a_ ( lowerCAmelCase_ : List[str], lowerCAmelCase_ : str ):
# ===== initialization =====
__lowerCAmelCase = Mock(... | 53 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
from __future__ import annotations
import os
from collections.abc import Mapping
__lowercase : List[str] =tuple[int, int]
class A :
def __init__( self: Any , _lowerCAmelCase: set[int] , _lowerCAmelCase: Mapping[EdgeT, int] ) -> None:
... | 54 |
'''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,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
import asyncio
import os
import re
import sys
import tempfile
import unittest
from contextlib import contextmanager
from copy import deepcopy
from distutils.util import strtobool
from enum import Enum
from importlib.util import find_spec
from pathlib import Path
from unittest.mock import patch
import pyarrow as pa
im... | 55 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_comm... | 56 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
A_ : Optional[Any] = False
try... | 57 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDim... | 58 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIPModel, CLIPTokenizerFast
fr... | 59 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
def lowerCamelCase_ ( _UpperCamelCase ) -> Any:
"""simple docstring"""
snake_case_ : Dict = []
snake_case_ : int = set({'''(''', '''[''', '''{'''} )
snake_case_ : Dict = set({''')''', ''']''', '''}'''} )
... | 60 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_config... | 61 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def lowerCamelCase__ ( lowercase , lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : List[Any] = F'''{sampling_rate}'''
SCREAMING_SNAKE_CASE ... | 62 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
a : Any = ... | 63 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class _lowerCamelCase ( UpperCamelCase_ ):
@require_torch
def UpperCamelCase_ ( self ) -> Any:
# this tes... | 64 |
'''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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase ( __UpperCamelCase = 100 ):
'''simple docstring'''
return sum(int(__UpperCamelCase ) for x in str(factorial(__UpperCamelCase ) ) )
if __name__ == "__main__":
print(solution(int(input('Enter t... | 65 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
import argparse
import os
import re
UpperCamelCase = "src/diffusers"
# Pattern that looks at the indentation in a line.
UpperCamelCase = re.compile(r"^(\s*)\S")
# Pattern that matches `"key":" and puts `key` in group 0.
UpperCamelCase = re.compile(r"^\s*\"([^\"]+)\":")
# Pattern that m... | 66 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
def SCREAMING_SNAKE_CASE__ ( snake_case__ :int , snake_case__ :int ) -> int:
return number | (1 << position)
def SCREAMING_SNAKE_CASE__ ( snake_case__ :int , snake_case__ :int ) -> int:
return number & ~(1 << position)
def SCREAMING_SNAKE_CASE_... | 67 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def lowercase__ ( A_: List[str] , A_: Optional[Any]=1000 ) -> List[str]:
"""simple docstring"""
if n < 2:
return False
if n % 2 == 0:
return n == 2
# ... | 68 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
'''simple docstring'''
import numpy as np
def __UpperCAmelCase ( _UpperCAmelCase : np.array ) -> np.array:
return (2 / (1 + np.exp(-2 * vector ))) - 1
if __name__ == "__main__":
import doctest
doctest.testmod()
| 69 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class A( UpperCamelCase ):
'''simple docstring'''
Upp... | 70 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _snake_case (__SCREAMING_SNAKE_CASE):
@staticmethod
@abstractmethod
def UpperCamelCase__ ( _snake_case ):
raise NotImplementedError()
@abstractmetho... | 71 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A )
class lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
'''simple docstring'''
import os
# Precomputes a list of the 100 first triangular numbers
_UpperCAmelCase : int = [int(0.5 * n * (n + 1)) for n in range(1, 1_01)]
def UpperCamelCase ( ) -> Tuple:
'''simple docstring'''
lowercase =os.path.dirname(os.path.realpath(lowercase_ ) )
... | 72 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
a_ : Optional[Any] = re.compile(R'\b(a|an|the)\b', re.UNICODE)
a_ : List[str] = None
def lowerCamelCase__ ():
SCREAMING_SNAKE_CASE = argpa... | 73 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
from a... | 74 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
'''simple docstring'''
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCamelCase_ ( __a ):
lowerCAmelCase__ = ['image_processor', 'tokenizer']
lowerCAmelCase__ = 'AutoImageProcessor'
lowerCAmelCas... | 75 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/b... | 76 |
'''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,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
"""simple docstring"""
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase , UpperCamelCase ) -> Tuple:
"""simple docstring"""
__Up... | 77 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
'''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_mvp import ... | 78 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
SCREAMING_SNAKE_CASE__ : int = logging.get_logger(__name__)
def _lowerCamelCase ( __lowerCamelC... | 79 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from ..onnx_utils import OnnxRunti... | 80 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 81 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
"""simple docstring"""
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
lowerCamelCase = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
... | 82 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
"""simple docstring"""
import unittest
from transformers import is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
if is_flax_available():
import optax
from flax.training.common_utils import onehot
from transformer... | 83 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
import argparse
import re
from typing import Dict
import torch
from datasets import Audio, Dataset, load_dataset, load_metric
from transformers import AutoFeatureExtractor, pipeline
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase = args.log_ou... | 84 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : int = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Optional[Any] = {
"abeja/gpt-neox-japanese-2.7b": "https://huggingface.co/abeja/gpt-neox-japanese... | 85 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipel... | 86 |
'''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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
from __future__ import annotations
import requests
_lowerCamelCase : str = set(
"""approved_at_utc approved_by author_flair_background_color
author_flair_css_class author_flair_richtext author_flair_template_id author_fullname
author_premium can_mod_post category clicked content_categories c... | 87 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from .formatting impo... | 88 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
SCREAMING_SNAKE_CASE : List[Any] = logging.get_logger(__... | 89 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
'''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/licen... | 90 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def _snake_case ( snake_case__ : np.ndarray ):
A , A = np.shape(snake_case__ )
if rows != columns:
A = (
'\'table\' has to be of square shaped array but got a '
F'{rows}x{columns} array:\n{table}'... | 91 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
'''simple docstring'''
import re
import jax.numpy as jnp
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.random import PRNGKey
from ..utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
def _lowerCAmelCase ( __magic_name__ : List[str]... | 92 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = ... | 93 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A )
class lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
'''simple docstring'''
from statistics import mean
import numpy as np
def lowercase_ ( __A : list , __A : list , __A : list , __A : int ) -> list:
"""simple docstring"""
lowercase : Dict =0
# Number of pro... | 94 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
"""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... | 95 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
from math import sqrt
def a ( __UpperCAmelCase : int ) -> bool:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ) and (
number >= 0
), "'number' must been an int and positive"
__magic_name__... | 96 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
from typing import Dict, Optional
import numpy as np
import datasets
__a = '\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. For binary (two classes) or multi-class segmentat... | 97 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowercase__ : Any = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvail... | 98 |
'''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,
)
UpperCAmelCase = {
'''configuration_owlvit''': [
... | 119 | 0 |
from ...processing_utils import ProcessorMixin
class __UpperCAmelCase ( __A ):
"""simple docstring"""
_lowerCamelCase = """WhisperFeatureExtractor"""
_lowerCamelCase = """WhisperTokenizer"""
def __init__( self , __A , __A ):... | 99 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
Up... | 119 | 0 |
# 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
#
# Unless required by app... | 100 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( lowercase__ : float, lowercase__ : float, lowercase__ : float ):
'''simple docstring'''
if (voltage, current, resistance).count(0 ) != 1:
raise ValueError('One and on... | 119 | 0 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowerCAmelCase__ : Dict =(3, 9, -11, 0, 7, 5, 1, -1)
lowerCAmelCase__ : Optional[int] =(4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __lowercase ... | 101 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : list[int] ):
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
__lowercase =sum(lowercase__ ) / len(lowercase__ ) # Calculate ... | 119 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_avai... | 102 |
'''simple docstring'''
import string
def __UpperCamelCase ( lowercase__ : str ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__lowercase =''
for symbol in message:
if symbol in string.ascii_uppercase:
... | 119 | 0 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s''',
datefmt='''%m/%d/%Y %H:%M:%S''',
level=logging... | 103 |
'''simple docstring'''
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto... | 119 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase = {
"""configuration_nllb_moe""": [
"""NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""NllbMoeConfig""... | 104 |
'''simple docstring'''
class lowerCAmelCase :
def __init__( self : List[Any] , __lowercase : str , __lowercase : Any , __lowercase : str ):
"""simple docstring"""
__lowercase =name
__lowercase ... | 119 | 0 |
from __future__ import annotations
import math
class lowerCAmelCase_ :
def __init__( self ,snake_case__ ):
SCREAMING_SNAKE_CASE_ : List[Any] = size
# approximate the overall size of segment tree with given value
SCREAMING_SNAKE_CASE_ : Union[st... | 105 |
'''simple docstring'''
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoFeatureExtractor, WavaVecaFeatureExtractor
from transformers.testing_utils... | 119 | 0 |
import pickle
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, XGLMTokenizer, XGLMTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 106 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''shi-labs/dinat-mini-in1k-224... | 119 | 0 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 107 |
'''simple docstring'''
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
fr... | 119 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__a: str = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__a: List[Any] = [file for file in filepaths if f... | 108 |
'''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
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmel... | 119 | 0 |
'''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,
MusicgenForConditionalGenerati... | 109 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
logging.set_verbosit... | 119 | 0 |
'''simple docstring'''
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, ... | 331 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_available... | 119 | 0 |
"""simple docstring"""
def __snake_case ( _lowercase ):
"""simple docstring"""
UpperCamelCase = 0
while len(lowercase__ ) > 1:
UpperCamelCase = 0
# Consider two files with minimum cost to be merged
for _ in range(2 ):
... | 34 |
'''simple docstring'''
import os
from collections.abc import Iterator
def __UpperCamelCase ( lowercase__ : str = "." ):
'''simple docstring'''
for dir_path, dir_names, filenames in os.walk(lowercase__ ):
__lowercase =[d for d in dir_names if d != 'scripts' a... | 119 | 0 |
'''simple docstring'''
from math import ceil
def _UpperCAmelCase ( _lowerCamelCase : int = 10_01 ) -> str:
_lowerCAmelCase : Any = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_lowerCAmelCase : Optional[int] = 2 * i + 1
_lowerCAmelCase ... | 384 |
'''simple docstring'''
from collections import defaultdict
from math import gcd
def __UpperCamelCase ( lowercase__ : int = 1_50_00_00 ):
'''simple docstring'''
__lowercase =defaultdict(lowercase__ )
__lowercase =2
while 2 * euclid_m * (euclid_m + 1) <... | 119 | 0 |
def __UpperCAmelCase ( __a : int ) -> Optional[Any]:
"""simple docstring"""
_a : Tuple = 0
while num > 0:
digit_sum += num % 10
num //= 10
return digit_sum
def __UpperCAmelCase ( __a : int = 100 ) ... | 14 |
'''simple docstring'''
# Function to print upper half of diamond (pyramid)
def __UpperCamelCase ( lowercase__ : Optional[Any] ):
'''simple docstring'''
for i in range(0, lowercase__ ):
for _ in range(0, n - i - 1 ): # printing spaces
p... | 119 | 0 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def a__ ( __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ) -> List[str]:
__lowerCAmelCase: Optional[Any] ... | 346 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils imp... | 119 | 0 |
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
TEXT_GUIDED_IMAGE_... | 658 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=A )
class lowerCAmelCase ( A ):
# `task` is not a ClassVar since we want it to be part of the `asdict` output for JSO... | 119 | 0 |
from typing import Any
def UpperCamelCase__ ( lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,lowerCAmelCase__ ,):
_validation(
lowercase__ ,lowercase__ ,lowercase__ ,lowercase__ ,lowercase__ ,)
# Creat... | 428 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if n == 1 or not isinstance(lowercase__, lowercase__ ):
return 0
elif n == 2:
return 1
else:
__lowercase =[0, 1]
for i in r... | 119 | 0 |
import tensorflow as tf
from ...tf_utils import shape_list
class __lowercase ( tf.keras.layers.Layer ):
def __init__( self : int , __lowerCamelCase : int , __lowerCamelCase : str , __lowerCamelCase : Tuple , __lowerCamelCase ... | 604 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : List[str], lowercase__ : Tuple ):
'''simple docstring'''
__lowercase =[0 for i in range(r + 1 )]
# nc0 = 1
__lowercase =1
for i in range(1, n + 1 ):
# to comput... | 119 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2... | 82 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase ( unittest.TestCase ):
... | 119 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_a : Tuple = logging.get_logger(__name__)
_a : Optional[Any] = {
"""huggingface/informer-tourism-monthly""": (
"""https://huggingface.co/huggingface/in... | 145 |
'''simple docstring'''
def __UpperCamelCase ( lowercase__ : int ):
'''simple docstring'''
if upper_limit < 0:
raise ValueError('Limit for the Catalan sequence must be ≥ 0' )
__lowercase =[0] * (upper_limit + 1)
# Base case: C(0) = C(1) = 1
__... | 119 | 0 |
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