code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_ = {"configuration_opt": ["OPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "OPTConfig"]}
... | 360 |
from collections.abc import Sequence
def _snake_case( SCREAMING_SNAKE_CASE__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A__ ... | 282 | 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__":
lowercase_ = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path... | 361 |
def _snake_case( SCREAMING_SNAKE_CASE__ : int = 1000 ) -> int:
'''simple docstring'''
A__ = 3
A__ = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
res... | 282 | 0 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowercase_ = HfApi()
lowercase_ = {}
# fmt: off
lowercase_ = torch.tensor([
-0.7_515, -1.6_883, 0.2_420, 0.0_300, 0.6_347, 1.3_433, -1.1_743, -3.7_467,
1.2_342, -2.2_485, 0.4_636, 0.8_0... | 362 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rou... | 282 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tenso... | 363 |
import random
def _snake_case( SCREAMING_SNAKE_CASE__ : list , SCREAMING_SNAKE_CASE__ : str ) -> tuple:
'''simple docstring'''
A__ , A__ , A__ = [], [], []
for element in data:
if element < pivot:... | 282 | 0 |
def _snake_case( SCREAMING_SNAKE_CASE__ : str ) -> bool:
'''simple docstring'''
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def _snake_case( SCREAMING_SNAKE_CASE__ : str ) -> bool:
... | 364 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class A :
"""simple docstring"""
def __init__( self : Any,lowercase_ : list[tuple[float, float]] )-> Optional[int]:
'''simple docstring'''
... | 282 | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTimestepEmb... | 365 |
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMi... | 282 | 0 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
'kwargs, expected' , [
({'num_shards': 0, 'max_num_jobs': 1}, []),
({'num_shards': 10, 'max_num_jobs': 1}, [range(10 )]),
(... | 366 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
lowercase_ = (3, 9, -11, 0, 7, 5, 1, -1)
lowercase_ = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class A :
"""simple docstring"""
lowerCamelCas... | 282 | 0 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
lowercase_ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("", "|", "|"),
datarow=Data... | 367 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class A ( nn.M... | 282 | 0 |
from typing import List
from .keymap import KEYMAP, get_character
def _snake_case( SCREAMING_SNAKE_CASE__ : str ) -> Optional[int]:
'''simple docstring'''
def decorator(SCREAMING_SNAKE_CASE__ : Optional[Any] ):
A__ = g... | 368 |
import argparse
import struct
import unittest
class A :
"""simple docstring"""
def __init__( self : Any,lowercase_ : bytes )-> None:
'''simple docstring'''
A__ = data
# Initialize hash values
... | 282 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_ = {
"configuration_convbert": ["CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ConvBertConfig", "ConvBe... | 369 |
import numpy as np
from transformers import Pipeline
def _snake_case( SCREAMING_SNAKE_CASE__ : int ) -> int:
'''simple docstring'''
A__ = np.max(SCREAMING_SNAKE_CASE__ , axis=-1 , keepdims=SCREAMING_SNAKE_CASE__ )
A__... | 282 | 0 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class A ( nn.M... | 370 |
import comet # From: unbabel-comet
import torch
import datasets
lowercase_ = datasets.logging.get_logger(__name__)
lowercase_ = "\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C and Lavie, Alon},\n title = {Unbabel's Participatio... | 282 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class A ( unittest.Tes... | 371 |
from __future__ import annotations
from typing import Any
def _snake_case( SCREAMING_SNAKE_CASE__ : list ) -> int:
'''simple docstring'''
if not postfix_notation:
return 0
A__ = {'+', '-', '*', '/'}
A__ = [... | 282 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={'vocab_file': 'vocab.json'}
__A ={
'vocab_file': {
'mgp-str': 'https:/... | 283 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 | 1 |
'''simple docstring'''
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : List[str] = len(UpperCamelCase__ )
UpperCAmelCase__ : List[Any] = sum(UpperCamelCase__ )
UpperCAmelCase__ : List[str] = [[Fals... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( ):
UpperCAmelCase__ : int = []
UpperCAmelCase__ : Dict = 1
while len(UpperCamelCase__ ) < 1e6:
constant.append(str(UpperCamelCase__ ) )
i += 1
UpperCAmelCase__ : ... | 283 |
'''simple docstring'''
import functools
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
# Validation
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or not all(isinstance(UpperCamelCase__ , UpperCamelCase__ ) for day in days ):
raise V... | 283 | 1 |
'''simple docstring'''
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 transformer... | 283 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, i... | 283 | 1 |
'''simple docstring'''
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def _UpperCamelCase ( UpperCamelCase__ = 3 ):
if isinstance(UpperCamelCase__ , UpperCamelCase__ ):
raise Type... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1_0 , UpperCamelCase__ = 2_2 ):
UpperCAmelCase__ : List[str] = range(1 , UpperCamelCase__ )
UpperCAmelCase__ : int = range(1 , UpperCamelCase__ )
return sum(
1 fo... | 283 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def _UpperCamelCase ( UpperCamelCase__ ):
if "model" in orig_key:
UpperCAmelCase__ : List[str] = orig_key.replace("""model.""" , """"""... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A ={
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenizati... | 283 | 1 |
'''simple docstring'''
import requests
__A ='' # <-- Put your OpenWeatherMap appid here!
__A ='https://api.openweathermap.org/data/2.5/'
def _UpperCamelCase ( UpperCamelCase__ = "Chicago" , UpperCamelCase__ = APPID ):
return requests.get(URL_BASE + """weather""" , par... | 283 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__A =logging.get_l... | 283 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transfo... | 283 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake_case ( ... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print('Program to check whether a number is a Perfect number or not...')
__A =int(input('Enter number... | 283 |
'''simple docstring'''
import numpy
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase):
UpperCAmelCase__ : Dict = input_array
# Random initial weights are assigned where first argument is t... | 283 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={
'weiweishi/roc-bert-base-zh': 'https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json',
}
class _snake_case ( ... | 283 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transfo... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 3 , UpperCamelCase__ = 7 , UpperCamelCase__ = 1_0_0_0_0_0_0 ):
UpperCAmelCase__ : List[str] = 0
UpperCAmelCase__ : int = 1
for current_denominator in range(1 , limit + 1 ... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import Au... | 283 | 1 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class _snake_case ( ... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 4_0_0_0_0_0_0 ):
UpperCAmelCase__ : List[str] = [0, 1]
UpperCAmelCase__ : Any = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
... | 283 | 1 |
'''simple docstring'''
import math
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : Dict = []
UpperCAmelCase__ : List[Any] = 2
UpperCAmelCase__ : Union[str, Any] = int(math.sqrt(UpperCamelC... | 283 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A ='\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1_0 ):
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or n < 0:
raise ValueError("""Invalid input""" )
UpperCAmelCase__ : Optional[Any] = 1_0**n
UpperCAmelCase__ : List[s... | 283 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _snake_case ( unittest.TestCase ):
def snake_case__ ( self):
UpperCAmelCase__ : ... | 283 | 1 |
'''simple docstring'''
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
... | 283 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__A =[
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def _Upper... | 283 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _UpperCamelCase ( UpperCamelCase__ , UpperCame... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ... | 283 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def _UpperCamelCase ( UpperCamelCase__ ):
if num <= 0:
UpperCAmelCase__ : List[Any] = f'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError... | 283 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available... | 283 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ... | 283 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ... | 283 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=a__ )
class _snake_case ( a__ ):
# `task` is not a ClassVar since we want it t... | 283 |
'''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, apply_forward_hook
from .modeling_utils import ModelMixin
from .... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1_0 , UpperCamelCase__ = 2_2 ):
UpperCAmelCase__ : List[str] = range(1 , UpperCamelCase__ )
UpperCAmelCase__ : int = range(1 , UpperCamelCase__ )
return sum(
1 fo... | 283 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase__ : List[str] = """"""
for i in table:
res += inp[i - 1]
return res
def _UpperCamelCase ( UpperCamelCase__ ):
return data[... | 283 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase__ : Optional[Any] = x
UpperCAmelCase__ : Optional[int] = ... | 283 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={'vocab_file'... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A ={
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransformerConfig',
'Tab... | 283 | 1 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
__A =WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def _UpperCamelC... | 283 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licens... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : List[str] = len(UpperCamelCase__ )
UpperCAmelCase__ : List[Any] = sum(UpperCamelCase__ )
UpperCAmelCase__ : List[str] = [[Fals... | 283 | 1 |
'''simple docstring'''
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def _UpperCamelCase ( ... | 283 |
'''simple docstring'''
import functools
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
# Validation
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or not all(isinstance(UpperCamelCase__ , UpperCamelCase__ ) for day in days ):
raise V... | 283 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
__A ={}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
... | 283 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, i... | 283 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=a__ ):
lowerCAmelCase :Optional[Any] = ['''torch''']
def __init__( self , *_lowerCamelCase , **_lowerCamelCase):
requires_b... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1_0 , UpperCamelCase__ = 2_2 ):
UpperCAmelCase__ : List[str] = range(1 , UpperCamelCase__ )
UpperCAmelCase__ : int = range(1 , UpperCamelCase__ )
return sum(
1 fo... | 283 | 1 |
'''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, apply_forward_hook
from .modeling_utils import ModelMixin
from .... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A ={
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenizati... | 283 | 1 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
__A =logging.get_logger(__name__)
__A ={
'Visual-Attention-Network/van-base': (
'https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'
),
}
... | 283 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__A =logging.get_l... | 283 | 1 |
'''simple docstring'''
import argparse
import copy
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : Dict = {}
with open(UpperCamelCase__ ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
... | 283 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake_case ( ... | 283 | 1 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _snake_case ( unittest.TestCase ):
def snake_case__ ( self):
UpperCAmelCase__ : ... | 283 |
'''simple docstring'''
import numpy
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase):
UpperCAmelCase__ : Dict = input_array
# Random initial weights are assigned where first argument is t... | 283 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
__A =logging.get_logger(__name__)
class _snake_case ( a__ ):
def __init__( self , *_lowerCamelCase , **_lowerCamelCase)... | 283 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transfo... | 283 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__A =logging.get_logger(__name__)
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = '... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import Au... | 283 | 1 |
'''simple docstring'''
from __future__ import annotations
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : Dict = str(UpperCamelCase__ )
return n == n[::-1]
def _UpperCamelCase ( UpperCamelCase__ = 1_0_0_0_0_0... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 4_0_0_0_0_0_0 ):
UpperCAmelCase__ : List[str] = [0, 1]
UpperCAmelCase__ : Any = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
... | 283 | 1 |
'''simple docstring'''
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
__A ={
'<': operator.lt,
'<=': operator.le,
'==': operator.eq,
'!=': operator.ne,
'>=': operator.ge,
'>': operator.gt,
... | 283 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A ='\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\... | 283 | 1 |
'''simple docstring'''
import re
def _UpperCamelCase ( UpperCamelCase__ ):
if len(re.findall("""[ATCG]""" , UpperCamelCase__ ) ) != len(UpperCamelCase__ ):
raise ValueError("""Invalid Strand""" )
return dna.translate(dna.maketrans("""ATCG""" , """TAGC"... | 283 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _snake_case ( unittest.TestCase ):
def snake_case__ ( self):
UpperCAmelCase__ : ... | 283 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : Union[str, Any] = FileLock(str(tmpdir / """foo.lock""" ) )
Upper... | 283 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__A =[
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def _Upper... | 283 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ... | 283 | 1 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def _UpperCamelCase ( UpperCamelCase__ ):
def decorator(UpperCamelCase__ ):
UpperCAmelCase__ : Optional[Any] = getattr(UpperCamelCase__ , """handle_ke... | 283 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available... | 283 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_availabl... | 283 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ... | 283 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__A =get_tests_dir('fixtures/test... | 283 |
'''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, apply_forward_hook
from .modeling_utils import ModelMixin
from .... | 283 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
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... | 283 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext... | 283 | 1 |
'''simple docstring'''
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class _snake_case ( a__ ):
lowerCAmelCase :int = (UnCLIPScheduler,)
def snake_case__ ( self , **_lowerCamelCase):
... | 283 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase__ : Optional[Any] = x
UpperCAmelCase__ : Optional[int] = ... | 283 | 1 |
'''simple docstring'''
from __future__ import annotations
import queue
class _snake_case :
def __init__( self , _lowerCamelCase):
UpperCAmelCase__ : Union[str, Any] = data
UpperCAmelCase__ : int = None
... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A ={
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransformerConfig',
'Tab... | 283 | 1 |
'''simple docstring'''
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class _snake_case ( a__ ):
lowerCAmelCase :Union[str, Any] = '''M-CLIP'''
def __init__( self , _lowerCamelCase=1024 , _lowe... | 283 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A ={
'configuration_ctrl': ['CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP', 'CTRLConfig'],
'tokenization_ctrl': ['CTRLTokenizer'],
}
t... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : List[str] = len(UpperCamelCase__ )
UpperCAmelCase__ : List[Any] = sum(UpperCamelCase__ )
UpperCAmelCase__ : List[str] = [[Fals... | 283 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def _UpperCamelCase ( UpperCamelCase__ = "AAPL" ):
UpperCAmelCase__ : Optional[Any] = f'''https://in.finance.yahoo.com/quote/{symbol}?s={symbol}'''
UpperCAmelCase__ : Option... | 283 |
'''simple docstring'''
import functools
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
# Validation
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or not all(isinstance(UpperCamelCase__ , UpperCamelCase__ ) for day in days ):
raise V... | 283 | 1 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.... | 283 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, i... | 283 | 1 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=a__ ):
lowerCAmelCase :int = ['''flax''']
def __init__( self , *_lowerCamelCase , **_lowerCamelCase):
requires_backends(sel... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1_0 , UpperCamelCase__ = 2_2 ):
UpperCAmelCase__ : List[str] = range(1 , UpperCamelCase__ )
UpperCAmelCase__ : int = range(1 , UpperCamelCase__ )
return sum(
1 fo... | 283 | 1 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A ={
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenizati... | 283 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import ... | 283 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__A =logging.get_l... | 283 | 1 |
'''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, Ty... | 283 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake_case ( ... | 283 | 1 |
'''simple docstring'''
from typing import List
import numpy as np
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : int = {key: len(UpperCamelCase__ ) for key, value in gen_kwargs.items() if isinstance(UpperCamelCase__ , UpperCamelCase__... | 283 |
'''simple docstring'''
import numpy
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase):
UpperCAmelCase__ : Dict = input_array
# Random initial weights are assigned where first argument is t... | 283 | 1 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase):
if dst_width < 0 or dst_height < 0:
... | 283 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transfo... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
return "".join(chr(ord(UpperCamelCase__ ) - 3_2 ) if """a""" <= char <= """z""" else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod() | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import Au... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ , UpperCAmelCase__ : Dict = [], []
while len(UpperCamelCase__ ) > 1:
UpperCAmelCase__ , UpperCAmelCase__ : Optional[Any] = min(UpperCamelCa... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 4_0_0_0_0_0_0 ):
UpperCAmelCase__ : List[str] = [0, 1]
UpperCAmelCase__ : Any = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : List[str] = len(UpperCamelCase__ )
UpperCAmelCase__ : List[Any] = sum(UpperCamelCase__ )
UpperCAmelCase__ : List[str] = [[Fals... | 283 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A ='\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\... | 283 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A =logging.get_logger(__name__)
__A ={
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
}
class _snake_case ( a__ ):
... | 283 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _snake_case ( unittest.TestCase ):
def snake_case__ ( self):
UpperCAmelCase__ : ... | 283 | 1 |
'''simple docstring'''
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def _UpperCamelCase ( Upper... | 283 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__A =[
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def _Upper... | 283 | 1 |
'''simple docstring'''
class _snake_case :
def __init__( self , _lowerCamelCase):
UpperCAmelCase__ : int = set_counts
UpperCAmelCase__ : Optional[int] = max(_lowerCamelCase)
UpperCAmelCase__ : Lis... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ... | 283 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__A ={
'configuration_vision_encoder_decoder': ['VisionEncoderDecoderConfig', 'Vision... | 283 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or number < 0:
raise ValueError("""Input must be a non-negative integer""" )
UpperCAmelCase__ : Dict = 0
while number:
... | 283 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ... | 283 | 1 |
'''simple docstring'''
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
__A =2_99_79_24_58
# Symbols
__A , __A , __A , __A =symbols('ct x y z')
def _UpperCamelCase ( UpperCamelCase__ ):
if velocity > c:... | 283 |
'''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, apply_forward_hook
from .modeling_utils import ModelMixin
from .... | 283 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test... | 283 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext... | 283 | 1 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warni... | 283 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase__ : Optional[Any] = x
UpperCAmelCase__ : Optional[int] = ... | 283 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiec... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A ={
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransformerConfig',
'Tab... | 283 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaConfig, 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 im... | 283 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 | 1 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class _snake_case ( yaml.SafeLoader ):
def snake_case__ ( self , _lowerCamelCase):
UpperCAmelCase__ : str ... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : List[str] = len(UpperCamelCase__ )
UpperCAmelCase__ : List[Any] = sum(UpperCamelCase__ )
UpperCAmelCase__ : List[str] = [[Fals... | 283 | 1 |
'''simple docstring'''
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _UpperCamelCase ( Up... | 283 |
'''simple docstring'''
import functools
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ ):
# Validation
if not isinstance(UpperCamelCase__ , UpperCamelCase__ ) or not all(isinstance(UpperCamelCase__ , UpperCamelCase__ ) for day in days ):
raise V... | 283 | 1 |
'''simple docstring'''
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class _snake_case ( a__ ):
lowerCAmelCase :Optional[int] = ''''''
lowerCAmelCase :str ... | 283 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, i... | 283 | 1 |
'''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 _snake_case ( ... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 1_0 , UpperCamelCase__ = 2_2 ):
UpperCAmelCase__ : List[str] = range(1 , UpperCamelCase__ )
UpperCAmelCase__ : int = range(1 , UpperCamelCase__ )
return sum(
1 fo... | 283 | 1 |
'''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific no... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__A ={
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', 'M2M100OnnxConfig'],
'tokenizati... | 283 | 1 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.... | 283 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
__A =logging.get_l... | 283 | 1 |
'''simple docstring'''
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, Inpu... | 283 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class _snake_case ( ... | 283 | 1 |
'''simple docstring'''
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 ... | 283 |
'''simple docstring'''
import numpy
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase):
UpperCAmelCase__ : Dict = input_array
# Random initial weights are assigned where first argument is t... | 283 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _UpperCamelCase ( UpperCamelCase__ ):
UpperCAmelCase__ : List[Any] = ... | 283 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transfo... | 283 | 1 |
'''simple docstring'''
import numpy
class _snake_case :
def __init__( self , _lowerCamelCase , _lowerCamelCase):
UpperCAmelCase__ : Dict = input_array
# Random initial weights are assigned where first argument is t... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import Au... | 283 | 1 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 4_0_0_0_0_0_0 ):
UpperCAmelCase__ : List[str] = [0, 1]
UpperCAmelCase__ : Any = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
... | 283 |
'''simple docstring'''
def _UpperCamelCase ( UpperCamelCase__ = 4_0_0_0_0_0_0 ):
UpperCAmelCase__ : List[str] = [0, 1]
UpperCAmelCase__ : Any = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
... | 283 | 1 |
'''simple docstring'''
import warnings
from functools import wraps
from typing import Callable
def _UpperCamelCase ( UpperCamelCase__ ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__ , **UpperCamelCase__ ):
warnings.warn(
(f'''\'{fn.... | 283 |
'''simple docstring'''
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__A ='\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\... | 283 | 1 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
__A ='examples/'
__A ={
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init': (re.compile(R'^__version__\s+=\s+"([^"]+)"\s*$', re.MULT... | 283 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class _snake_case ( unittest.TestCase ):
def snake_case__ ( self):
UpperCAmelCase__ : ... | 283 | 1 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase__ : Optional[Any] = x
UpperCAmelCase__ : Optional[int] = ... | 283 |
'''simple docstring'''
import os
from datetime import datetime as dt
from github import Github
__A =[
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def _Upper... | 283 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, i... | 283 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ... | 283 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_com... | 283 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available... | 283 | 1 |
'''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 packag... | 283 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A =logging.get_logger(__name__)
__A ... | 283 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__A ={'tokenization_bertweet': ['BertweetTokenizer']}
if TYPE_CHECKING:
from .tokenization_bertweet import BertweetTokenizer
else:
import sys
__A =_LazyModule(__name__, globals()['__file__'... | 283 |
'''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, apply_forward_hook
from .modeling_utils import ModelMixin
from .... | 283 | 1 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/ermongroup/ddim
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_confi... | 283 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext... | 283 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import tensorflow as tf
from transformers import Au... | 283 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _UpperCamelCase ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
UpperCAmelCase__ : Optional[Any] = x
UpperCAmelCase__ : Optional[int] = ... | 283 | 1 |
'''simple docstring'''
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
... | 283 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A ={
'configuration_table_transformer': [
'TABLE_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TableTransformerConfig',
'Tab... | 283 | 1 |
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