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 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
class lowerCAmelCase_:
'''simple docstring'''
def __init__( self ,__UpperCAmelCase ) -> Optional[Any]:
lowerCAmelCase__ : Optional[int] = data
lowerCAmelCase__ : Any = None
... | 565 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 676 | 0 |
"""simple docstring"""
import numpy as np
import torch
from ..models.clipseg import CLIPSegForImageSegmentation
from ..utils import is_vision_available, requires_backends
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class _lowerCAmelCase ( lowerCamelCase__ )... | 93 |
'''simple docstring'''
import functools
def a_ ( __snake_case : str , __snake_case : str ) -> int:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
@functools.cache
def min_distance(__sna... | 676 | 0 |
import bza
import gzip
import lzma
import os
import shutil
import struct
import tarfile
import warnings
import zipfile
from abc import ABC, abstractmethod
from pathlib import Path
from typing import Dict, List, Optional, Type, Union
from .. import config
from .filelock import FileLock
from .lo... | 311 |
'''simple docstring'''
def a_ ( __snake_case : int ) -> bool:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
raise TypeError(__snake_case )
... | 676 | 0 |
'''simple docstring'''
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline # noqa: F401
deprecate(
'''stable diffusion controlnet''',
'''0.22.0''',
'''Importing `Stabl... | 370 |
'''simple docstring'''
from __future__ import annotations
a_ : int = list[list[int]]
# assigning initial values to the grid
a_ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8... | 676 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__A = {"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
__A = _LazyModule(__name__, globals()[... | 484 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Tuple = {
"""huggingface/informer-tourism-monthly""": (
"""https://hugg... | 676 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_sub... | 560 |
'''simple docstring'''
from __future__ import annotations
def a_ ( __snake_case : int ) -> list[int]:
"""simple docstring"""
lowerCamelCase_ =[True] * limit
lowerCamelCase_ =False
lowerCamelCase_ =False
lowerCamelCase_ =True
for i i... | 676 | 0 |
def __lowerCAmelCase ( A_ : int , A_ : int ) -> str:
if not isinstance(__snake_case , __snake_case ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(__snake_case , __snake_case ) or not number >= 1:
raise ValueErr... | 221 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __UpperCamelCase ( lowerCamelCase__ ):
def __i... | 676 | 0 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase : Optional[int] = """\
@inproceedings{kakwani2020indicnlpsuite,
title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks ... | 284 |
'''simple docstring'''
from maths.prime_check import is_prime
def a_ ( __snake_case : int ) -> int:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
... | 676 | 0 |
'''simple docstring'''
UpperCamelCase__ : dict[str, float] = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kilo... | 614 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 676 | 0 |
'''simple docstring'''
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class UpperCAmelCase ( datasets.BuilderConfig ):
_A : Optional[datasets.Feat... | 126 |
'''simple docstring'''
def a_ ( __snake_case : int , __snake_case : int ) -> str:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(__snak... | 676 | 0 |
"""simple docstring"""
from string import ascii_uppercase
__magic_name__ = {char: i for i, char in enumerate(ascii_uppercase)}
__magic_name__ = dict(enumerate(ascii_uppercase))
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
lowe... | 129 |
'''simple docstring'''
from typing import List
import numpy as np
def a_ ( __snake_case : dict ) -> int:
"""simple docstring"""
lowerCamelCase_ ={key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case )}
if le... | 676 | 0 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_lowerCAmelCase = """
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
"""
_lowerCAmelCase = """
Args:
pred... | 565 |
'''simple docstring'''
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""... | 676 | 0 |
"""simple docstring"""
from math import isqrt
def __A (_SCREAMING_SNAKE_CASE ) ->bool:
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(__snake_case ) + 1 ) )
def __A (_SCREAMING_SNAKE_CASE = 10**6 ) ->int:
"""simple... | 93 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : str = logging.get_logger(__name__)
a_ : int = {
"""RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}
class __Uppe... | 676 | 0 |
from __future__ import annotations
import math
from collections.abc import Callable
def A ( _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE = 100 ,) -> float:
lowerCamelCase : List[Any] = x_start
lowerCamel... | 311 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ : int = logging.get_logger(__name__)
a_ : str = {"""vocab... | 676 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def snake_case__ ( _A: Optional[int] , _A: Union[str, Any] , _A: Any ) ->... | 370 |
'''simple docstring'''
from collections.abc import Sequence
def a_ ( __snake_case : Sequence[float] , __snake_case : float ) -> float:
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(__snake_case ) )
def a_ ( __snake_case : Se... | 676 | 0 |
import numpy as np
def __A ( _lowercase ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def __A ( _lowercase ):
'''simple docstring'''
return vector * sigmoid(__snake_case )
if __name__ == "__main__":
import doctest
doct... | 484 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( lowerCamelCase__ ):
lowercase : Optional[int] =['image_processor', 'tokenizer']
lowercase : ... | 676 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamelCase ) -> float:
return sum(c * (x**i) for i, c in enumerate(__snake_case ) )
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamel... | 560 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 676 | 0 |
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, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder, V... | 221 |
'''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( __snake_case : Optional[int] , __snake_case : Union[str, Any] , __sn... | 676 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_UpperCamelCase : Tuple = logging.get_logger(__name__)
_UpperCamelCase : int = {
"""microsoft/unispeech-sat-base-100h-libri-ft... | 284 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Optional[int] = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltC... | 676 | 0 |
'''simple docstring'''
def __UpperCamelCase( _A : list[list[float]] ):
'''simple docstring'''
UpperCAmelCase__ : Optional[Any] = []
for data in source_data:
for i, el in enumerate(__snake_case ):
if len(__snake_case ) < i + 1:
data_lists.append([] ... | 614 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 676 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class UpperCAmelCase ( lowerCamelCase__ ):
def __lowerCamelCase ( self ):
return [
{"col_1": 3, "col_2": "a"},
{"col_... | 126 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
a_ :... | 676 | 0 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_imag... | 129 |
'''simple docstring'''
def a_ ( __snake_case : str , __snake_case : str ) -> str:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =(
first_str_length if first_str_length... | 676 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json"""}
class lowerCAmelCase_( lo... | 565 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 676 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwritten/resolve/main/con... | 93 |
'''simple docstring'''
import functools
def a_ ( __snake_case : str , __snake_case : str ) -> int:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
@functools.cache
def min_distance(__sna... | 676 | 0 |
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
SCREAMING_SNAKE_CASE__ : Dict = logging.get_logger(__name__)
class UpperCamelCase__ (lowerCamelCase__ ):
'''simple docstring'''
def __init__( ... | 311 |
'''simple docstring'''
def a_ ( __snake_case : int ) -> bool:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
raise TypeError(__snake_case )
... | 676 | 0 |
'''simple docstring'''
def snake_case__ ( _A: str , _A: str ) -> bool:
'''simple docstring'''
lowerCAmelCase = len(__snake_case )
lowerCAmelCase = len(__snake_case )
lowerCAmelCase = [[False for _ in range(m + 1 )] for _ in range(n + 1 ... | 370 |
'''simple docstring'''
from __future__ import annotations
a_ : int = list[list[int]]
# assigning initial values to the grid
a_ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8... | 676 | 0 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.convert_swi... | 484 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Tuple = {
"""huggingface/informer-tourism-monthly""": (
"""https://hugg... | 676 | 0 |
"""simple docstring"""
def __UpperCAmelCase ( __lowerCamelCase ) -> list:
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError('''The given input must be positive''' )
# get the generated string sequence
lowercase__ : ... | 560 |
'''simple docstring'''
from __future__ import annotations
def a_ ( __snake_case : int ) -> list[int]:
"""simple docstring"""
lowerCamelCase_ =[True] * limit
lowerCamelCase_ =False
lowerCamelCase_ =False
lowerCamelCase_ =True
for i i... | 676 | 0 |
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def __lowerCAmelCase ( ... | 221 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __UpperCamelCase ( lowerCamelCase__ ):
def __i... | 676 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelT... | 284 |
'''simple docstring'''
from maths.prime_check import is_prime
def a_ ( __snake_case : int ) -> int:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
... | 676 | 0 |
'''simple docstring'''
def __UpperCamelCase( _A : list ):
'''simple docstring'''
if not grid or not grid[0]:
raise TypeError('''The grid does not contain the appropriate information''' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1... | 614 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 676 | 0 |
'''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class UpperCAmelCase ( lowerCamelC... | 126 |
'''simple docstring'''
def a_ ( __snake_case : int , __snake_case : int ) -> str:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(__snak... | 676 | 0 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
__magic_name__ = namedtuple(
"""_TestCommandArgs""... | 129 |
'''simple docstring'''
from typing import List
import numpy as np
def a_ ( __snake_case : dict ) -> int:
"""simple docstring"""
lowerCamelCase_ ={key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case )}
if le... | 676 | 0 |
'''simple docstring'''
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowerCAmelCase_( lowerCamelCase__ ):
''... | 565 |
'''simple docstring'''
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""... | 676 | 0 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class _lowerCAmelCase ( lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
@register_to_config
def ... | 93 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : str = logging.get_logger(__name__)
a_ : int = {
"""RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}
class __Uppe... | 676 | 0 |
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
SCREAMING_SNAKE_CASE__ : Any = logging.getLogger()
@unittest.skip("""Temporari... | 311 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ : int = logging.get_logger(__name__)
a_ : str = {"""vocab... | 676 | 0 |
'''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
__lowercase = """1"""
__lowercase = """0"""
__lowercase = """1"""
__lowercase = ort.SessionOptions()
__lowercase = ort.GraphOptimizationLevel.ORT_DISABLE_ALL
print('''Creat... | 370 |
'''simple docstring'''
from collections.abc import Sequence
def a_ ( __snake_case : Sequence[float] , __snake_case : float ) -> float:
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(__snake_case ) )
def a_ ( __snake_case : Se... | 676 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json""",
# See all AltCLIP models a... | 484 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( lowerCamelCase__ ):
lowercase : Optional[int] =['image_processor', 'tokenizer']
lowercase : ... | 676 | 0 |
"""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 ... | 560 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 676 | 0 |
from typing import List
import numpy as np
def __lowerCAmelCase ( A_ : dict ) -> int:
__UpperCAmelCase = {key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case )}
if len(set(lists_lengths.values() ) ... | 221 |
'''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( __snake_case : Optional[int] , __snake_case : Union[str, Any] , __sn... | 676 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class _snake_case ( lowerCamelCase__ ):
def __init__( self , ... | 284 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Optional[int] = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltC... | 676 | 0 |
'''simple docstring'''
import requests
UpperCamelCase__ : int = """""" # <-- Put your OpenWeatherMap appid here!
UpperCamelCase__ : List[Any] = """https://api.openweathermap.org/data/2.5/"""
def __UpperCamelCase( _A : str = "Chicago" , _A : str = APPID ... | 614 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 676 | 0 |
'''simple docstring'''
_A: Dict = frozenset(
[
"""prompt""",
"""height""",
"""width""",
"""guidance_scale""",
"""negative_prompt""",
"""prompt_embeds""",
"""negative_prompt_embeds""",
"""cross_attention_kwargs""",
]
)
... | 126 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
a_ :... | 676 | 0 |
"""simple docstring"""
import json
import sys
def _A ( __lowercase , __lowercase ):
"""simple docstring"""
with open(__snake_case , encoding="""utf-8""" ) as f:
lowerCamelCase__ = json.load(__snake_case )
lowerCamel... | 129 |
'''simple docstring'''
def a_ ( __snake_case : str , __snake_case : str ) -> str:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =(
first_str_length if first_str_length... | 676 | 0 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
_low... | 565 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 676 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__A = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
__A = _LazyModule(__name__, globals()["""__... | 93 |
'''simple docstring'''
import functools
def a_ ( __snake_case : str , __snake_case : str ) -> int:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
@functools.cache
def min_distance(__sna... | 676 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging
... | 311 |
'''simple docstring'''
def a_ ( __snake_case : int ) -> bool:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
raise TypeError(__snake_case )
... | 676 | 0 |
'''simple docstring'''
import functools
from typing import Any
def snake_case__ ( _A: str , _A: list[str] ) -> bool:
'''simple docstring'''
if not isinstance(__snake_case , __snake_case ) or len(__snake_case ) == 0:
raise ValueError("""the string should be... | 370 |
'''simple docstring'''
from __future__ import annotations
a_ : int = list[list[int]]
# assigning initial values to the grid
a_ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8... | 676 | 0 |
import math
import random
def __A ( _lowercase , _lowercase = False ):
'''simple docstring'''
if deriv:
return value * (1 - value)
return 1 / (1 + math.exp(-value ))
# Initial Value
__A = 0.02
def __A ( _lowercase , _l... | 484 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Tuple = {
"""huggingface/informer-tourism-monthly""": (
"""https://hugg... | 676 | 0 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""Visual-Attention-Network/van-base""": (
"""https://huggingface.co/Visual-Attention-Network... | 560 |
'''simple docstring'''
from __future__ import annotations
def a_ ( __snake_case : int ) -> list[int]:
"""simple docstring"""
lowerCamelCase_ =[True] * limit
lowerCamelCase_ =False
lowerCamelCase_ =False
lowerCamelCase_ =True
for i i... | 676 | 0 |
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from... | 221 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __UpperCamelCase ( lowerCamelCase__ ):
def __i... | 676 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from ut... | 284 |
'''simple docstring'''
from maths.prime_check import is_prime
def a_ ( __snake_case : int ) -> int:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
... | 676 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
UpperCamelCase__ : Optional[Any] = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pil... | 614 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 676 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_c... | 126 |
'''simple docstring'''
def a_ ( __snake_case : int , __snake_case : int ) -> str:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(__snak... | 676 | 0 |
"""simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionMod... | 129 |
'''simple docstring'''
from typing import List
import numpy as np
def a_ ( __snake_case : dict ) -> int:
"""simple docstring"""
lowerCamelCase_ ={key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case )}
if le... | 676 | 0 |
'''simple docstring'''
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
_lowerCAmelCase = logging.get_logger(__name__)
class lowerCAmelCase_:
'''simple docs... | 565 |
'''simple docstring'''
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""... | 676 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@... | 93 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : str = logging.get_logger(__name__)
a_ : int = {
"""RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}
class __Uppe... | 676 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
SCREAMING_SNAKE_CASE__ : Union[str, Any... | 311 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ : int = logging.get_logger(__name__)
a_ : str = {"""vocab... | 676 | 0 |
'''simple docstring'''
from maths.prime_check import is_prime
def snake_case__ ( _A: int ) -> int:
'''simple docstring'''
if not isinstance(__snake_case , __snake_case ):
lowerCAmelCase = f"Input value of [number={number}] must be an integer"
raise Typ... | 370 |
'''simple docstring'''
from collections.abc import Sequence
def a_ ( __snake_case : Sequence[float] , __snake_case : float ) -> float:
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(__snake_case ) )
def a_ ( __snake_case : Se... | 676 | 0 |
def __A ( _lowercase ):
'''simple docstring'''
if len(__snake_case ) <= 1:
return [tuple(__snake_case )]
_A = []
def generate(_lowercase , _lowercase ):
if k == 1:
res.append(tuple(arr[:] ) )
... | 484 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase ( lowerCamelCase__ ):
lowercase : Optional[int] =['image_processor', 'tokenizer']
lowercase : ... | 676 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ = {"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}
try:
if not is_tor... | 560 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 676 | 0 |
from __future__ import annotations
import numpy as np
def __lowerCAmelCase ( A_ : list[float] ) -> str:
return np.maximum(0 , __snake_case )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 221 |
'''simple docstring'''
import argparse
import torch
from transformers import BertConfig, BertForPreTraining, load_tf_weights_in_bert
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( __snake_case : Optional[int] , __snake_case : Union[str, Any] , __sn... | 676 | 0 |
'''simple docstring'''
from __future__ import annotations
_UpperCamelCase : List[Any] = 1.6_0_2_1e-1_9 # units = C
def snake_case ( snake_case : float , snake_case : float , snake_case : float , ) -> tuple[str, float]:
"""simple docstring"""
... | 284 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Optional[int] = {
"""BAAI/AltCLIP""": """https://huggingface.co/BAAI/AltC... | 676 | 0 |
'''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__ : int = {
"""configurati... | 614 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import Mo... | 676 | 0 |
'''simple docstring'''
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 Backbo... | 126 |
'''simple docstring'''
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .utils import logging
a_ :... | 676 | 0 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from ..mo... | 129 |
'''simple docstring'''
def a_ ( __snake_case : str , __snake_case : str ) -> str:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =(
first_str_length if first_str_length... | 676 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor
... | 565 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
... | 676 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
__A = 5_0000
__A = 5000
__A = os.path.split(__file__)
__A = os.path.join(RESULTS_BASEPATH, """results""", RESUL... | 93 |
'''simple docstring'''
import functools
def a_ ( __snake_case : str , __snake_case : str ) -> int:
"""simple docstring"""
lowerCamelCase_ =len(__snake_case )
lowerCamelCase_ =len(__snake_case )
@functools.cache
def min_distance(__sna... | 676 | 0 |
from __future__ import annotations
def A ( _SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,_SCREAMING_SNAKE_CASE ,) -> None:
lowerCamelCase : Optional[Any] = len(__snake_case )
# If row is equal to... | 311 |
'''simple docstring'''
def a_ ( __snake_case : int ) -> bool:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
raise TypeError(__snake_case )
... | 676 | 0 |
'''simple docstring'''
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
impor... | 370 |
'''simple docstring'''
from __future__ import annotations
a_ : int = list[list[int]]
# assigning initial values to the grid
a_ : Matrix = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8... | 676 | 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 = {
"""iou_prediction_head.layers... | 484 |
'''simple docstring'''
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Tuple = {
"""huggingface/informer-tourism-monthly""": (
"""https://hugg... | 676 | 0 |
"""simple docstring"""
import functools
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamelCase ) -> int:
lowercase__ : List[str] = len(__snake_case )
lowercase__ : Optional[Any] = len(__snake_case )
@funct... | 560 |
'''simple docstring'''
from __future__ import annotations
def a_ ( __snake_case : int ) -> list[int]:
"""simple docstring"""
lowerCamelCase_ =[True] * limit
lowerCamelCase_ =False
lowerCamelCase_ =False
lowerCamelCase_ =True
for i i... | 676 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 221 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __UpperCamelCase ( lowerCamelCase__ ):
def __i... | 676 | 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 snake_case ( snake_case : Dataset , snake_case : Dict[str, str] ) -> Optiona... | 284 |
'''simple docstring'''
from maths.prime_check import is_prime
def a_ ( __snake_case : int ) -> int:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
lowerCamelCase_ =F'''Input value of [number={number}] must be an integer'''
... | 676 | 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 PreTrainedTokenizer
from ...utils import logging
UpperCamelCase__ : int = logging.get_logger(__name__)
UpperCamelCase__ : ... | 614 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import B... | 676 | 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 (
ChannelDimension,
PILIm... | 126 |
'''simple docstring'''
def a_ ( __snake_case : int , __snake_case : int ) -> str:
"""simple docstring"""
if not isinstance(__snake_case , __snake_case ):
raise ValueError('''iterations must be defined as integers''' )
if not isinstance(__snak... | 676 | 0 |
"""simple docstring"""
import itertools
import os
import re
__magic_name__ = re.compile(R"""([A-Z]+)([A-Z][a-z])""")
__magic_name__ = re.compile(R"""([a-z\d])([A-Z])""")
__magic_name__ = re.compile(R"""(?<!_)_(?!_)""")
__magic_name__ = re.compile(R"""(_{2,})""")
... | 129 |
'''simple docstring'''
from typing import List
import numpy as np
def a_ ( __snake_case : dict ) -> int:
"""simple docstring"""
lowerCamelCase_ ={key: len(__snake_case ) for key, value in gen_kwargs.items() if isinstance(__snake_case , __snake_case )}
if le... | 676 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import... | 565 |
'''simple docstring'''
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""... | 676 | 0 |
"""simple docstring"""
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configur... | 93 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : str = logging.get_logger(__name__)
a_ : int = {
"""RUCAIBox/mvp""": """https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json""",
}
class __Uppe... | 676 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ : List[str] = {
"""configuration_groupvit""": [
"""GROUPVIT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""GroupViTConfig""",... | 311 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ : int = logging.get_logger(__name__)
a_ : str = {"""vocab... | 676 | 0 |
"""simple docstring"""
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize('''repo_id''' , ['''canonical_dataset_name''', '''org-name/dataset-name'''])
@pytest.mark.parametrize('''path''' , ['''filename.csv''', '''filename with bl... | 677 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import ... | 677 | 1 |
"""simple docstring"""
# 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 __... | 677 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 677 | 1 |
"""simple docstring"""
def lowerCamelCase (a_ :Tuple , a_ :int , a_ :Tuple , a_ :List[Any]) -> str:
if height >= 1:
move_tower(height - 1 , a_ , a_ , a_)
move_disk(a_ , a_)
move_tower(... | 677 |
"""simple docstring"""
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowerCamelCase (a_ :int)... | 677 | 1 |
"""simple docstring"""
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''google/pix2struct-textcaps-base''': (
'''https://huggingface.... | 677 |
"""simple docstring"""
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def ... | 677 | 1 |
"""simple docstring"""
from typing import Dict
import numpy as np
import torch
from . import residue_constants as rc
from .tensor_utils import tensor_tree_map, tree_map
def lowerCamelCase (a_ :Dict[str, torch.Tensor]) -> Dict[str, torch.Tensor]:
lowercase :Dict = []
... | 677 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase = {
'''configuration_blenderbot''': [
'''BLE... | 677 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class ... | 677 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# ... | 677 | 1 |
"""simple docstring"""
# using dfs for finding eulerian path traversal
def lowerCamelCase (a_ :int , a_ :Tuple , a_ :Union[str, Any] , a_ :Any=None) -> Dict:
lowercase :Optional[Any] = (path or []) + [u]
for v in graph[u]:
... | 677 |
"""simple docstring"""
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
UpperCAmelCase = version.parse(vers... | 677 | 1 |
"""simple docstring"""
class __magic_name__ :
def __init__( self : Union[str, Any] , snake_case__ : Tuple , snake_case__ : List[Any] , snake_case__ : Tuple ):
'''simple docstring'''
lowercase :Any = None
lo... | 677 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data... | 677 | 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... | 677 |
"""simple docstring"""
def lowerCamelCase (a_ :Tuple , a_ :int , a_ :Tuple , a_ :List[Any]) -> str:
if height >= 1:
move_tower(height - 1 , a_ , a_ , a_)
move_disk(a_ , a_)
move_tower(... | 677 | 1 |
"""simple docstring"""
import warnings
warnings.warn(
'''memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: '''
'''`from accelerate import find_executable_batch_size` to avoid this warning.''',
FutureWarning,
)
| 677 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
UpperCAmelCase = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and B... | 677 | 1 |
"""simple docstring"""
UpperCAmelCase = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
UpperCAmelC... | 677 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __magic_name__ ( __UpperCAmelCase ):
@staticmethod
@abstractmethod
def __snake_case ( snake_case__ : ArgumentParser ):
'''simple docstring'''
... | 677 | 1 |
"""simple docstring"""
import itertools
import json
import linecache
import os
import pickle
import re
import socket
import string
from collections import Counter
from logging import getLogger
from pathlib import Path
from typing import Callable, Dict, Iterable, List
import git
import torch
from torch.utils.data... | 677 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
UpperCAmelCase = {
'''configuration_encodec''': [
'''ENCODEC_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''EncodecConfig''',
],
... | 677 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchF... | 677 |
"""simple docstring"""
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... | 677 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ..... | 677 |
"""simple docstring"""
UpperCAmelCase = {
'''A''': ['''B''', '''C''', '''E'''],
'''B''': ['''A''', '''D''', '''E'''],
'''C''': ['''A''', '''F''', '''G'''],
'''D''': ['''B'''],
'''E''': ['''A''', '''B''', '''D'''],
'''F''': ['''C'''],
'''G''': ['''C'''],
}
def lowerCam... | 677 | 1 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformer... | 677 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from tempfile import TemporaryDirectory
from typing import List, Optional
import faiss
import torch
from datasets import Features, Sequence, Value, load_dataset
from tr... | 677 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def lowerCamelCase (a_ :str) -> None:
lowercase , lowercase :str = analyze_text(a_)
lowercase :int = list('... | 677 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCAmelCase = {
'''configuration_longt5''': ['''LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LongT5Config''', '''LongT5OnnxConfig'''],
}... | 677 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 677 |
"""simple docstring"""
import uuid
from typing import Any, Dict, List, Optional, Union
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
if is_torch_available():
import torch
Upp... | 677 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
class __magic_name__ :
def __init__( self : str , snake_case__ : int ):
'''simple docstring'''
lowercase :str = size
# approximate the overall si... | 677 |
"""simple docstring"""
def lowerCamelCase (a_ :int = 100) -> int:
lowercase :Union[str, Any] = set()
lowercase :List[Any] = 0
lowercase :Dict = n + 1 # maximum limit
for a in range(2 , a_):
for b in ... | 677 | 1 |
"""simple docstring"""
# HF Trainer benchmarking tool
#
# This tool can be used to run and compare multiple dimensions of the HF Trainers args.
#
# It then prints a report once in github format with all the information that needs to be shared
# with others and second time in a console-friendly format, so it's eas... | 677 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
'''microsoft/xprophetnet-large-wiki100-cased''': (
'''https://hugg... | 677 | 1 |
"""simple docstring"""
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowerCamelCase (a_ :int)... | 677 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase = {
'''configurati... | 677 | 1 |
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