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 os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,... | 567 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase : Optional[Any] = {
"configuration_mega": ["MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP", "MegaConfig", "MegaOnnxConfig... | 567 | 1 |
'''simple docstring'''
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
__UpperCAmelCase = logging.get_logger(__name_... | 220 |
'''simple docstring'''
import numpy as np
def SCREAMING_SNAKE_CASE_ ( snake_case_ : np.array ) -> np.array:
return 1 / (1 + np.exp(-vector ))
def SCREAMING_SNAKE_CASE_ ( snake_case_ : np.array ) -> np.array:
return vector * sigmoid(1.7... | 220 | 1 |
'''simple docstring'''
from PIL import Image
def _A ( A__ , A__ ):
"""simple docstring"""
__lowercase = (259 * (level + 255)) / (255 * (259 - level))
def contrast(A__ ) -> int:
return int(128 + factor * (c - 128) )
return img.point(A__ )
if __name__ == "__main__... | 41 | """simple docstring"""
__A : Union[str, Any] = {str(digit): digit**5 for digit in range(10)}
def lowercase ( UpperCamelCase : int ):
"""simple docstring"""
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(UpperCamelCase ) )
def lowercase ( ):
... | 656 | 0 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokeniza... | 713 |
'''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()
__A : Any... | 398 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
__A = logging.get_logger(__name__)
class UpperCAmelCase (__A ):
"""simple docstring"""
def __init__( self , *_UpperCAmelCase , ... | 586 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
... | 94 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_size,
rescale,
... | 707 |
'''simple docstring'''
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
... | 419 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, Timeste... | 8 |
'''simple docstring'''
import argparse
import os
import re
lowercase__ : Optional[int] = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase__ : Dict = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and pu... | 8 | 1 |
"""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 a_ ( _UpperCAmelCase ):
a ... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
a : str = '''examples/'''
a : List[str] = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__... | 19 | 1 |
"""simple docstring"""
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils i... | 543 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def a__ ( snake_case__ ) -> list[list[float]]:
lowerCamelCase = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implementati... | 543 | 1 |
'''simple docstring'''
def lowerCamelCase_ ( A_ , A_ ):
assert x is not None
assert y is not None
__lowerCamelCase = len(A_ )
__lowerCamelCase = len(A_ )
# declaring the array for storing the dp values
__lowerCamelCase = [[0] * (n + 1) for _... | 575 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
_UpperCamelCase : Any =parse(importlib.metadata.version("torch"))
def lowerCamelCase_ ( A_ , A_ , ... | 575 | 1 |
def _lowercase ( __UpperCamelCase : int = 50 ):
snake_case__ = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):
... | 214 |
from math import ceil
def _lowercase ( __UpperCamelCase : int = 1001 ):
snake_case__ = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
snake_case__ = 2 * i + 1
snake_case__ = 2 * i
snake_case__ = tot... | 214 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( _A = 50 ):
a : Tuple = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 195 |
'''simple docstring'''
def lowerCamelCase__ ( _A = 6008_5147_5143 ):
try:
a : Optional[int] = int(_A )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter n must be greater ... | 195 | 1 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertEncod... | 269 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
BarkCoarseConfig,
... | 269 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : int = {
'''configuration_roformer''': ['''ROFORMER_PRETRAINED_CONFIG_... | 714 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_lowerCamelCase : Optional[Any] = logging.get_logger(__name__)
class lowerCAmelCase__ ( __magic_name__ ):
'''simple docstring'''
def __init__( self , ... | 516 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE = {
'dist... | 94 |
"""simple docstring"""
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class ... | 554 | 0 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __A( __lowerCamelCase , __lowerCamelCase ):
"""simple docstring"""
@register_to_config
de... | 86 |
import os
from datetime import datetime as dt
from github import Github
lowerCamelCase_ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''enhancement''',
'''new pipeline/model''',
'''new scheduler''',
'''wip''',
]
def __magic_name__ ( ... | 86 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import TimesformerConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, ... | 19 |
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_mps
from ..pipeline_params import UNCONDITIONA... | 285 | 0 |
"""simple docstring"""
import math
from numpy import inf
from scipy.integrate import quad
def _A ( __lowercase ):
"""simple docstring"""
if num <= 0:
raise ValueError("""math domain error""" )
return quad(__lowercase , 0 , __l... | 718 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def _A ( __lowercase , __lowercase , __lowercase , __lowercase=None ):
"""simple docstring"""
lowerCamelCase__ = (path or []) + [u]
for v in graph[u]:
... | 258 | 0 |
import os
def SCREAMING_SNAKE_CASE_ ( ) -> List[str]:
with open(os.path.dirname(UpperCAmelCase_ ) + '''/p022_names.txt''' ) as file:
SCREAMING_SNAKE_CASE_ : Any =str(file.readlines()[0] )
SCREAMING_SNAKE_CASE_ : List[Any] =names.rep... | 443 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase_ ( A ):
__lowerCamelCase = (DDIMParallelScheduler,)
__lowerCamelCase = (("eta", 0.0), ("num_inference_steps", 5_0))
... | 443 | 1 |
'''simple docstring'''
import math
from collections.abc import Callable
def lowerCamelCase__ ( __lowerCamelCase : Callable[[float], float] , __lowerCamelCase : float , __lowerCamelCase : float ):
'''simple docstring'''
_UpperCAmelCase : float ... | 331 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase =logging.get_logger(__name__)
lowercase ={
'facebook/dpr-ctx_encoder-single-nq-base': (
'https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/confi... | 331 | 1 |
import string
import numpy
def __UpperCamelCase ( lowercase__ : int , lowercase__ : int ) -> int:
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , lowercase__ )
class __a :
__snake_case : int = s... | 600 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("""socket.socket""" )
@patch("""builtins.open""" )
def __UpperCamelCase ( lowercase__ : List[Any] , lowercase__ : str ) -> str:
'''simple docstring'''
lowerC... | 600 | 1 |
"""simple docstring"""
from __future__ import annotations
def __lowercase ( a : list[int] ) -> list[int]: # This function is recursive
__snake_case : str =len(a )
# If the array contains only one element, we return it (it's the stop condition of
# recu... | 497 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ : Optional[int] = logging.get_logger(__name__)
UpperCamelCase_ : Union[str, Any] = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
cla... | 497 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {}
class __lowercase ( _A ):
lowercase = 'llama'
lowercase = ['past_key_values']
def __init__( self ... | 604 | import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...tes... | 604 | 1 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
lowerCAmelCase_ = numpy.array([0, 0])
lowerCAmelCase_ = numpy.array([0.5, 0.8_66_02_54])
lowerCAmelCase_ = numpy.array([1, 0])
lowerCAmelCase_ = [VE... | 470 |
def __lowerCAmelCase ( UpperCamelCase ) -> bool:
if not isinstance(UpperCamelCase , UpperCamelCase ):
raise ValueError('''Input series is not valid, valid series - [2, 4, 6]''' )
if len(UpperCamelCase ) == 0:
raise ValueError('''Input list must be a non empty lis... | 470 | 1 |
'''simple docstring'''
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class lowercase__ ( unittest.TestCase ):
def UpperCamelCase_ ( self : Optional[int] ):
... | 195 |
'''simple docstring'''
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is... | 195 | 1 |
'''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_availa... | 245 |
'''simple docstring'''
from collections.abc import Callable
def UpperCamelCase ( a , a , a ) -> float:
'''simple docstring'''
__magic_name__ = a
__magic_name__ = b
if function(a ) == 0: # one of the a or b is a root for the function
... | 245 | 1 |
from sklearn.metrics import matthews_corrcoef
import datasets
_lowerCAmelCase = "\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 account true and false... | 10 |
'''simple docstring'''
# DISCLAIMER: This code is strongly influenced by https://github.com/pesser/pytorch_diffusion
# and https://github.com/hojonathanho/diffusion
import math
from dataclasses import dataclass
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from diffusers.confi... | 131 | 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 a... | 246 | import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
lowerCamelCase_ : Dict = logging.get_logger(__name__)
class a__ ( __snake_case ):
def __init__( self , *UpperCAmelCase , **UpperCAmelCase ) -> None:
w... | 246 | 1 |
from math import factorial
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase = 100 ) -> int:
'''simple docstring'''
return sum(int(A__ ) for x in str(factorial(A__ ) ) )
if __name__ == "__main__":
print(solution(int(input('''Enter the Number: ''').strip())))
| 343 |
"""simple docstring"""
import torch
from diffusers import DDPMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __lowercase( lowercase__ ):
'''simple docstring'''
__a : int = (DDPMParallelScheduler,)
def snake_case_ ( self , **__a... | 594 | 0 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
... | 716 |
"""simple docstring"""
from __future__ import annotations
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE = TypeVar("""T""")
class __a ( Generic[T] ):
def __init__( self : List[Any] , UpperCAmelCase_ : T )-> None:
... | 556 | 0 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class SCREAMING... | 62 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundfile_availble, i... | 151 | 0 |
'''simple docstring'''
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availa... | 415 | '''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
... | 415 | 1 |
from __future__ import annotations
class A :
def __init__( self , lowercase_ ) -> Union[str, Any]:
'''simple docstring'''
_snake_case : Optional[int] = TypeError(
'''Matrices must be formed from a list of zero or more l... | 326 |
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 transformers import Aut... | 326 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import AutoProcessor, BertTokeniz... | 703 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
UpperCAmelCase_ : Optional[int] = '\\n\n'
UpperCAmelCase_ : Tuple = '\nPerplexity ... | 540 | 0 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaXLForSequ... | 97 |
from __future__ import annotations
def a ( snake_case__: Optional[int] , snake_case__: Optional[int] , snake_case__: Any , snake_case__: Optional[int] ): # noqa: E741
'''simple docstring'''
while r - l > 1:
lowercase_ = (l + r) // 2
if v[m] >=... | 97 | 1 |
from __future__ import annotations
import os
from collections.abc import Mapping
lowercase : Union[str, Any] = tuple[int, int]
class A__ :
"""simple docstring"""
def __init__( self , lowercase , lowercase) -> None:
'''simple docstri... | 705 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase : List[str] = logging.get_logger(__name__)
lowercase : Any = {
"""huggingface/time-series-transformer-tourism-monthly""": (
"""https://hugging... | 392 | 0 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
... | 53 |
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def a_ ( ):
__lowerCAmelCase = ArgumentParser(
description=(
'PyTorch TPU distributed training launch '
... | 53 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_... | 702 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
__lowerCAmelCase = logging.get_logger(__name__)
class UpperCAmelCase__ ( lowercase__ ):
"""simple docstring"""
def __init__( self : Any ,*_a ... | 319 | 0 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : Dict ) -> Tuple:
'''simple docstring'''
UpperCAmelCase_ = int(snake_case_ )
... | 78 |
'''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 ... | 442 | 0 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
UpperCAmelCase_ = 1.054571817E-34 # unit of ℏ : J * s
UpperCAmelCase_ = 3E8 # unit of c : m * s^-1
def UpperCAmelCase__ ( ... | 704 |
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 664 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transformer import... | 544 | from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def _snake_case ( snake_case__ : ArgumentParser ) -> Tuple:
... | 544 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelerate ... | 710 | """simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"files" , [
["full:README.md", "dataset_infos.json"],
["empty:README.md", "dataset_info... | 132 | 0 |
def __magic_name__ ( lowercase_ ) -> int:
'''simple docstring'''
UpperCamelCase = hex_num.strip()
if not hex_num:
raise ValueError("No value was passed to the function" )
UpperCamelCase = hex_num[0] == "-"
if is_negati... | 606 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
__a : Tuple = logging.getLogger(__name__)
def __magic_name__ ( ) -> Optional[Any]:
'''simple docstring'''
UpperCamelCase ... | 606 | 1 |
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_=1024 , lowercase_=1024 , lowercase_=False , ... | 675 |
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 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class lowercase_ ( unittest.TestCase ):
'''simple docstring'''
... | 447 |
'''simple docstring'''
from io import BytesIO
from typing import List, Union
import requests
from ..utils import add_end_docstrings, is_decord_available, is_torch_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_decord_available():
import numpy as np
from decord i... | 447 | 1 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class A (SCREAMING_SNAKE_CASE ):
'''simple docstring... | 713 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
A : Dict = datasets.logging.get_logger(__name__)
A : Optional[Any] = '''\
@InProceedings{moosavi2019... | 247 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( a , a , a , a , a ):
if index == number_of_items:
return 0
__snake_case = 0
__snake_case = 0
__snake_case = knapsack(snake_case__ , snake_case__ , snake_case__ , snake_c... | 356 |
import os
import pytest
from attr import dataclass
__UpperCAmelCase = '''us-east-1''' # defaults region
@dataclass
class lowerCAmelCase_ :
UpperCAmelCase__ : str
UpperCAmelCase__ : Tuple = "arn:aws:iam::558105141721:role/sagemaker_execution_role"
Up... | 40 | 0 |
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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILImageResampling... | 713 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 540 | 0 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowerCAmelCase__ = TypeVar('''KEY''')
lowerCAmelCase__ = TypeVar('''VAL''')
@dataclass(frozen=lowerCamelCase__ , slots=lowerCamelCase... | 41 | import unittest
from pathlib import Path
from tempfile import NamedTemporaryFile, TemporaryDirectory
from transformers import BertConfig, BertTokenizerFast, FeatureExtractionPipeline
from transformers.convert_graph_to_onnx import (
convert,
ensure_valid_input,
generate_identified_filename,
infer_shapes... | 216 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
_lowerCAmelCase = logging.get_logger(__nam... | 711 |
'''simple docstring'''
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
def UpperCamelCase ( a=None , a=None ) -> Union[str, ... | 245 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ : Tuple = {'configuration_fnet': [... | 527 |
'''simple docstring'''
from math import pow
def UpperCAmelCase ( A : int , A : int , A : int , A : int , A : int , ):
if current_sum == needed_sum:
# If the sum of the powers is equal to needed_sum, then we have a so... | 527 | 1 |
# Function to print upper half of diamond (pyramid)
def lowercase ( __A : List[str] ) -> Any:
'''simple docstring'''
for i in range(0 , __A ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(""" """ , end="""""" )
... | 710 |
from math import factorial
def lowercase ( __A : int = 20 ) -> int:
'''simple docstring'''
snake_case : str = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
snake_case : str = n // 2
return... | 315 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
if is_onnx_available():
... | 553 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load... | 553 | 1 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__SCREAMING_SNAKE_CASE : List[Any] = re.compile(R'''\b(a|an|the)\b''', re.UNICODE)
__SCREAMING_SNAKE_CASE : Optional[Any] = None
def ... | 623 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
__SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
class lowerCamelCase_( A__ ):
'''simple docstring'''
def __init__( self , lowerCamelCase__... | 623 | 1 |
"""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/LICENS... | 346 |
"""simple docstring"""
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def ... | 346 | 1 |
UpperCamelCase_ = "\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers.git\n"
Up... | 376 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_available():
... | 376 | 1 |
'''simple docstring'''
from collections.abc import Callable
class A_ :
'''simple docstring'''
def __init__( self , A_ = None ):
_UpperCamelCase = []
# Stores indexes of each item for supporting updates and deletion.
_UpperCamelCase = {}
... | 138 |
"""simple docstring"""
import baseaa
def lowerCamelCase ( _UpperCamelCase : str ) -> bytes:
'''simple docstring'''
return baseaa.baaencode(string.encode("""utf-8""" ) )
def lowerCamelCase ( _UpperCamelCase : bytes ) -> str:
'''simple docstring... | 139 | 0 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class lowerCamelCase ( __lowercase ):
'''simple docstring'''
lowerCAmelCase__ = (EulerDiscreteScheduler,)
lo... | 713 | '''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase ( lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = 42
lowerCAmelCase__ = 42
def __lowerCamelCase ( _UpperCamelCase : str ):
... | 43 | 0 |
"""simple docstring"""
def lowercase__ ( lowerCAmelCase : str ) -> bool:
"""simple docstring"""
UpperCAmelCase = [int(lowerCAmelCase ) for i in ip_va_address.split('.' ) if i.isdigit()]
return len(lowerCAmelCase ) == 4 and all(0 ... | 373 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers impo... | 373 | 1 |
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import... | 702 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
"ut/deta": "https://huggingface.co/ut/deta/resolve/main/config.json",
}
class lowerCAmelC... | 202 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ ... | 645 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCamelCase : Dict ={"configuration_focalnet": ["FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP", "FocalNetConfig"]}
t... | 316 | 0 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
__A : Optional[Any] = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex an... | 75 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
__A : int = '%20'.join(argv[1:]) if len(argv) > 1 else quote(str(input('Search: ')))
print('Googling.....')
__A... | 75 | 1 |
from statistics import mean
import numpy as np
def _a ( lowercase__ : list , lowercase__ : list , lowercase__ : list , lowercase__ : int ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Union[str, Any] = 0
# Number of processes finished... | 85 |
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
cen... | 206 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase : Union[str, Any] ={
'configuration_roformer': ['ROFO... | 693 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
lowerCAmelCase : List[Any] = 4
lowerCAme... | 693 | 1 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
lowercase__ = [int(0.5 * n * (n + 1)) for n in range(1, 101)]
def __magic_name__ ( ):
__a : List[str] = os.path.dirname(os.path.realpath(_lowerCamelCase ) )
... | 581 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase__ = logging.get_logg... | 581 | 1 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _snake_case ( ) -> str:
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
... | 455 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format='''%(asctime)s - %(levelname)s - %(name)s - %(message)s''', datefmt='''%m/%d/%Y %H:%M:%S''', level=logging.INFO
)
__lo... | 455 | 1 |
from collections.abc import Iterable
from typing import Any
class UpperCamelCase :
def __init__( self : int ,_lowerCAmelCase : int | None = None ):
"""simple docstring"""
__snake_case = value
__snake_case = None # Added in ord... | 524 | #
# This a `torch.distributed` diagnostics script that checks that all GPUs in the cluster (one or
# many nodes) can talk to each other via nccl and allocate gpu memory.
#
# To run first adjust the number of processes and nodes:
#
# python -m torch.distributed.run --nproc_per_node 2 --nnodes 1 torch-distributed-gpu-tes... | 524 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
from dat... | 700 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowerCamelCase :int = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER... | 686 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case = {
"""configuration_roberta_prelayernorm""": [
"""ROBERTA_PRELAYERNORM_PRETRAI... | 378 |
'''simple docstring'''
from cva import destroyAllWindows, imread, imshow, waitKey
def UpperCAmelCase_ ( lowerCamelCase_ ):
"""simple docstring"""
lowerCAmelCase__ , lowerCAmelCase__ : Tuple = img.shape[0], img.shape[1]
# converting each pixel's color to its negative
for i in... | 378 | 1 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def lowerCamelCase__ ( A__ : Tuple , A__ : str , A__ : List[str] ):
'''simple docstring'''
__lowerCamelCase = ("""dense.weigh... | 703 |
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
UpperCAmelCase_ = get_tests_dir('fixtures/test_sentencepiece... | 80 | 0 |
"""simple docstring"""
from collections import namedtuple
import requests
from lxml import html # type: ignore
__lowerCamelCase = namedtuple('covid_data', 'cases deaths recovered')
def a ( __UpperCAmelCase : str = "https://www.worldometers.info/coronavirus... | 96 | from ...configuration_utils import PretrainedConfig
class snake_case__ ( _UpperCamelCase ):
_SCREAMING_SNAKE_CASE : Union[str, Any] = "bert-generation"
def __init__( self : Optional[int] , A__ : List[Any]=5_03_58 , A__ : Any=10_24 , ... | 666 | 0 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class SCREAMING_SNAKE_CASE... | 713 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
... | 212 | 0 |
"""simple docstring"""
import comet # From: unbabel-comet
import torch
import datasets
_A = datasets.logging.get_logger(__name__)
_A = """\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},
title = {Unbabel's... | 299 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
_A = TypeVar("""T""")
_A = TypeVar("""U""")
class _lowerCamelCase ( Generic[T, U] ):
def __init__( self : List[Any] , Uppe... | 299 | 1 |
import numpy as np
import datasets
SCREAMING_SNAKE_CASE__ = '''
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.
It was in... | 702 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_DEFAULT_STD
torch.set_grad_e... | 577 | 0 |
'''simple docstring'''
import argparse
import torch
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_from_original_stable_diffusion_ckpt
if __name__ == "__main__":
SCREAMING_SNAKE_CASE_ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=No... | 517 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
SCREAMING_SNAKE_CASE_ = ""
SCREAMING_SNAKE_CASE_ = ""
SCREAMING_SNAKE_CASE_ = ""
SCREAMING_SNAKE_CASE_ = 1 # (0 is vertical, 1 is horizontal)
def lowerCamelCase__ ( ) -> ... | 517 | 1 |
from math import loga
def a__ ( _UpperCamelCase : int ):
if a < 0:
raise ValueError('''Input value must be a positive integer''' )
elif isinstance(_UpperCamelCase ,_UpperCamelCase ):
raise TypeError('''Input value must be a \'int\' type''' )
return 0 if (a ==... | 622 |
import torch
from diffusers import StableDiffusionPipeline
a_ = """path-to-your-trained-model"""
a_ = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("""cuda""")
a_ = """A photo of sks dog in a bucket"""
a_ = pipe(prompt, num_inference_steps=50, guidance_s... | 622 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ... | 96 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : Optional[Any] = {
"microsoft/markuplm-base": "https://huggingface.co/microsoft/markuplm-bas... | 698 | 0 |
'''simple docstring'''
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowerCAmelCase : Dict = logging.getLogger(__name__)
class SCREAMING_SNAKE_CASE_... | 432 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers im... | 432 | 1 |
'''simple docstring'''
import argparse
import os
import re
_lowerCamelCase = """src/diffusers"""
# Pattern that looks at the indentation in a line.
_lowerCamelCase = re.compile(R"""^(\s*)\S""")
# Pattern that matches `"key":" and puts `key` in group 0.
_lowerCamelCase ... | 71 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 603 | 0 |
'''simple docstring'''
from math import isqrt, loga
def _UpperCamelCase ( SCREAMING_SNAKE_CASE_ ):
lowercase_ : List[Any] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 438 | '''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from .... | 438 | 1 |
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_ = {
'junnyu/roformer_chinese_small': 'https://huggingface.co/junnyu/roformer_c... | 417 | import argparse
import requests
import torch
from PIL import Image
from torchvision.transforms import Compose, Normalize, Resize, ToTensor
from transformers import SwinaSRConfig, SwinaSRForImageSuperResolution, SwinaSRImageProcessor
def __lowercase ( lowerCamelCase : str ):
UpperCamelCase_ : Any ... | 417 | 1 |
"""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,
)
a_ = {
'''configuration_xlm_roberta''... | 718 |
"""simple docstring"""
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __lowercase :
"""simple docstring"""
def __init__(self , lowercase__ ):
snake_case_ : Union[str, Any] = data
s... | 48 | 0 |
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
lowerCAmelCase_ = collections.namedtuple('''_Datasets''', ['''train'... | 60 |
from __future__ import annotations
def lowerCamelCase_ ( _UpperCamelCase ) -> list:
"""simple docstring"""
if len(_UpperCamelCase ) == 0:
return []
snake_case_ , snake_case_ : Dict = min(_UpperCamelCase ), max(_UpperCamelCase ... | 60 | 1 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartForSe... | 349 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixi... | 349 | 1 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached... | 79 |
'''simple docstring'''
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCamelCase__ ( A : str = "isbn/0140328726" ):
'''simple docstring'''
UpperCAmelCase = olid.strip().strip('''/''' ) # Remove leading/tr... | 210 | 0 |
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append(".")
def UpperCamelCase_( lowerCamelCase_ ) -> Optional[Any]:
_lowercase : int = test_file.split(os.path.sep )
... | 717 |
import unittest
from transformers import DebertaVaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
fro... | 354 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_... | 38 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : Optional[Any] ) -> Dict:
"""simple docstring"""
A__ = []
A__ = set({"(", "[", "{"} )
A__ = set({")", "]", "}"} )
A__ ... | 104 | 0 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transformers... | 430 |
"""simple docstring"""
from statistics import mean
import numpy as np
def _UpperCAmelCase ( __lowerCamelCase : list , __lowerCamelCase : list , __lowerCamelCase : list , __lowerCamelCase : int ) -> list:
_snake_case = 0
# Number of proce... | 430 | 1 |
import torch
import torch.nn as nn
from transformers import CLIPConfig, CLIPVisionModel, PreTrainedModel
from ...utils import logging
lowercase : int = logging.get_logger(__name__)
def _SCREAMING_SNAKE_CASE ( _lowerCamelCase : Dict , _lowerCamelCase : Li... | 557 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
im... | 557 | 1 |
"""simple docstring"""
from __future__ import annotations
import requests
lowerCamelCase : Union[str, Any] =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... | 237 | """simple docstring"""
import math
def _lowercase ( _SCREAMING_SNAKE_CASE : int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 237 | 1 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils impo... | 167 | import requests
__lowercase = '''''' # <-- Put your OpenWeatherMap appid here!
__lowercase = '''https://api.openweathermap.org/data/2.5/'''
def lowerCamelCase ( SCREAMING_SNAKE_CASE = "Chicago" , SCREAMING_SNAKE_CASE = APPID ):
'''simple docstring'''
return reques... | 167 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
Wav... | 711 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHead... | 344 | 0 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
cached_file,
get_fi... | 496 |
def __snake_case ( _UpperCamelCase ) -> list:
_a = len(_UpperCamelCase )
for i in range(1 , _UpperCamelCase ):
_a = collection[i]
_a = 0
_a = i - 1
while low <= high:
_a = (low + high) // 2
if val < collection[mid]:
_a = mi... | 487 | 0 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 719 |
import copy
from typing import Dict, List, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
UpperCAmelCase : Tuple = {
'''facebook/mask2former-swin-small-coco-instance''': (
'''https://huggingface.co/facebook/... | 77 | 0 |
'''simple docstring'''
def _snake_case ( A_ : Union[str, Any] = 1000 ):
"""simple docstring"""
a_ : str = 3
a_ : Any = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
... | 577 |
from numpy import exp, pi, sqrt
def UpperCAmelCase ( a_ , a_ = 0.0 , a_ = 1.0 ) -> int:
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 55 | 0 |
from math import factorial
def lowerCAmelCase_ ( A_ ,A_):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter positive... | 711 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
A__: str = namedtuple('''covid_data''', '''cases deaths recovered''')
def lowerCAmelCase_ ( A_ = "https://www.worldometers.info/coronavirus/"):
UpperCamelCase__: Union[str,... | 221 | 0 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Train... | 272 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
lowercase = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
lowercase = [... | 272 | 1 |
def a__ ( A_, A_ ):
'''simple docstring'''
__magic_name__ = len(A_ )
__magic_name__ = len(A_ )
__magic_name__ = [[False for _ in range(m + 1 )] for _ in range(n + 1 )]
__magic_name__ = True
for i in range(A_ ):
... | 76 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def a__ ( A_, A_ ):
'''simple docstring'''
assert i... | 76 | 1 |
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : int ,A : List[Any] ):
__A = val
__A = None
__A = None
def UpperCamelCase_ ( self : List[str] ,A : Dict ):
if self.val:
... | 55 |
"""simple docstring"""
from collections import namedtuple
UpperCAmelCase = namedtuple("""from_to""", """from_ to""")
UpperCAmelCase = {
"""cubicmeter""": from_to(1, 1),
"""litre""": from_to(0.001, 1_0_0_0),
"""kilolitre""": from_to(1, 1),
"""gallon""": from_to(0.00_454, 264.... | 535 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {"""configuration_encoder_decoder""": ["""EncoderDecoderConfig"""]}
try:
... | 719 |
from functools import reduce
UpperCamelCase = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66... | 152 | 0 |
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