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 __future__ import annotations
def UpperCamelCase_( lowerCamelCase_ , lowerCamelCase_ ) -> float:
_lowercase : Optional[int] = sorted(numsa + numsa )
_lowercase , _lowercase : int = divmod(len(lowerCamelCase_ ) , 2 )
if mod =... | 21 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str ) -> list:
if n_term == "":
return []
_a = []
for temp in range(int(lowercase ) ):
series.append(F'1/{temp + 1}' if series else "1" )
return series
if __name__ == "__main_... | 63 | 0 |
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.TestCase ):
def _UpperCAmelCase ( sel... | 368 |
from typing import Any
class a :
def __init__( self , A_ ):
'''simple docstring'''
_UpperCAmelCase : List[Any] = data
_UpperCAmelCase : Any = None
class a :
def __init__( self ):
... | 189 | 0 |
import os
from distutils.util import strtobool
def A ( _UpperCAmelCase : Tuple , _UpperCAmelCase : Union[str, Any] ) -> Dict:
'''simple docstring'''
for e in env_keys:
_UpperCAmelCase = int(os.environ.get(a_ , -1 ) )
if val >= ... | 339 |
from torch import nn
class __A ( nn.Module ):
"""simple docstring"""
def __init__( self , lowerCamelCase__ , lowerCamelCase__ ):
"""simple docstring"""
super().__init__()
__UpperCamelCase : ... | 71 | 0 |
class UpperCamelCase__ :
def __init__(self : Tuple ):
__a : Tuple = {}
def lowerCAmelCase (self : Union[str, Any] ):
print(self.vertex )
for i in self.vertex:
print(lowerCAmelCase__ , ''' -> ''' , ''' -> '''.join([str(lowerCAmelCase__ ) for ... | 367 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArguments
| 90 | 0 |
"""simple docstring"""
from cva import destroyAllWindows, imread, imshow, waitKey
def lowercase_ ( _snake_case ):
# getting number of pixels in the image
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ : List[str] = img.shape[0], img.shape[1]
... | 25 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase__ : str = logging.get_logger(__nam... | 25 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__magic_name__: str = logging.get_logger(__name__)
__magic_name__: Any = {
"facebook/nllb-moe-54B": "https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json",
}
class snake_case... | 138 |
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=logging.INFO
)
__magic_n... | 138 | 1 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin... | 226 | def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : int ):
"""simple docstring"""
while b:
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : int = b, a % b
return a
def _snake_case ( lowerCAmelCase : int , lowerCAmelCase : ... | 18 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class a_ ( a__ ):
"""simple docstring"""
def __lowerCAmelCase ( self , _lowerCamelCase=None , _lowerCamelCase=None , _lowerCamelCase=None , **_lowerCamelCase ) ->int:
... | 19 |
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__ : Tuple = '''▁'''
a__ : List[Any] = {'''vocab_file''': '''spiece.... | 19 | 1 |
"""simple docstring"""
from __future__ import annotations
def a__ ( SCREAMING_SNAKE_CASE : int | float | str , SCREAMING_SNAKE_CASE : int | float | str ):
'''simple docstring'''
if nth_term == "":
return [""]
lowerCAmelCase : Optional[int] = ... | 108 |
"""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.version impor... | 108 | 1 |
'''simple docstring'''
from __future__ import annotations
def _snake_case ( A , A ) -> list[tuple[int, int]]:
lowerCAmelCase__ , lowerCAmelCase__ = position
lowerCAmelCase__ = [
(y + 1, x + 2),
(y - 1, x + ... | 356 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCAmelCase ... | 228 | 0 |
"""simple docstring"""
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
_a = ... | 17 | """simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
... | 150 | 0 |
from ...configuration_utils import PretrainedConfig
a : Dict = {
'google/tapas-base-finetuned-sqa': (
'https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'
),
'google/tapas-base-finetuned-wtq': (
'https://huggingface.co/google/tap... | 82 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _a ( unittest.TestCase , _lowerCAmelCase ):
def __snake_case (self ) -> Optional[int]:
UpperCAmelCase_: Optional[int] = l... | 82 | 1 |
"""simple docstring"""
import os
from distutils.util import strtobool
def lowercase ( __snake_case : List[Any] , __snake_case : List[str] ):
for e in env_keys:
lowercase_ : Optional[int] = int(os.environ.get(_A , -1 ) )
if val >= 0:
... | 33 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMSche... | 297 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowercase = {'''configurat... | 85 | """simple docstring"""
import itertools
import json
import os
import unittest
from transformers import AddedToken, LongformerTokenizer, LongformerTokenizerFast
from transformers.models.longformer.tokenization_longformer import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
... | 85 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor
from ..... | 109 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def _snake_case ( UpperCamelCase : int = 1000000 , UpperCamelCase : int = 10 ):
UpperCAmelCase : defaultdict = defaultdict(UpperCamelCase )
for outer_width in range(3 , (t_limit... | 109 | 1 |
import warnings
from ...utils import logging
from .image_processing_beit import BeitImageProcessor
lowerCamelCase__ = logging.get_logger(__name__)
class __magic_name__ (__lowercase ):
def __init__( self , *_a , **_a ) -> None:
warnings.warn(
"The clas... | 366 |
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 notes:
# - tqdm must be checked before to... | 22 | 0 |
"""simple docstring"""
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
lowerCamelCase_ : Union[str, Any] = list(good_file_paths())
assert filepaths, "good_file_path... | 81 |
'''simple docstring'''
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(import... | 321 | 0 |
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def SCREAMING_SNAKE_CASE__ ( __a ):
snake_case_ : Option... | 352 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_SCREAMING_SNAKE_CASE = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],
"""tokenization_... | 88 | 0 |
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
__UpperCAmelCase = '\\n@INPROCEEDINGS{Papineni02bleu:a,\n author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},\n title = {BLEU: a ... | 29 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_SCREAMING_SNAKE_CASE : Optional[Any... | 85 | 0 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class __snake_case ( unittest.TestCase ):
"""simple docstring"""
def UpperCamelCase__( self ):
'''simple docstring'''
... | 361 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
a_ = logging.get_logger(__name__)
a_ = {
"""shi-labs/dinat-mini-in1k-224""": """https:... | 291 | 0 |
import argparse
from collections import defaultdict
import yaml
A__ = """docs/source/en/_toctree.yml"""
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
_lowerCAmelCase = defaultdict(snake_case )
_lowerCAmelCase = []
_lowerCAmelCase ... | 82 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A__ = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""tokenization_mvp""": ["""MvpToken... | 82 | 1 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_a... | 357 |
'''simple docstring'''
import inspect
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_lowercase = """src/transformers"""
# This is to make... | 229 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( _UpperCamelCase : list[list[int]] , _UpperCamelCase : int , _UpperCamelCase : int , _UpperCamelCase : list[int] ) -> bool:
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:
... | 150 | """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 transformers.image_... | 150 | 1 |
"""simple docstring"""
import argparse
import re
from pathlib import Path
import requests
import torch
from PIL import Image
from torchvision.transforms import CenterCrop, Compose, Normalize, Resize, ToTensor
from transformers import (
EfficientFormerConfig,
EfficientFormerForImageClassificationWithTea... | 253 |
"""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
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = ... | 253 | 1 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : List[Any] ):
'''simple docstring'''
_UpperCAmelCase = len(_SCREAMING_SNAKE_CASE )
while cur > 1:
# Find the maximum number in arr
_UpperCAmelCase = arr.index(m... | 260 |
"""simple docstring"""
def lowercase ( ):
'''simple docstring'''
_UpperCAmelCase = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
_UpperCAmelCase = 6
_UpperCAmelCase = 1
_UpperCAmelCase = 1901
_UpperCAmelCase ... | 260 | 1 |
"""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: Tuple = ... | 363 |
"""simple docstring"""
UpperCAmelCase: str = """
# 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.g... | 336 | 0 |
'''simple docstring'''
import os
import unittest
from transformers import LxmertTokenizer, LxmertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 141 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFImgaImgSuperResolutionPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params ... | 141 | 1 |
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = False ):
if n == 2:
return True
if not n % 2 or n < 2:
return False
if n > 5 and n % 10 not in (1, 3, 7, 9): # can quickly check last digit
return False
if n > 3_317_044_064_679_887_385_961_981 and not allow... | 65 |
from manim import *
class _lowerCamelCase ( UpperCamelCase ):
"""simple docstring"""
def _snake_case ( self )->Tuple:
'''simple docstring'''
A_ : Optional[int] = Rectangle(height=0.5 , width=0.5 )
A_ : Union[str, Any] ... | 65 | 1 |
'''simple docstring'''
def _A ( snake_case ) -> Optional[Any]:
if not all(x.isalpha() for x in string ):
raise ValueError("String must only contain alphabetic characters." )
_lowercase : List[Any] = sorted(string.lower() )
return len(lowercase__ ) == le... | 250 |
'''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class lowerCAmelCase ( A ):
def __init__( self : Optional[Any] , *__lowercase : str , **__lowercase : Union[str, Any] ):
"""simple docstrin... | 141 | 0 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def snake_case__ ( __lowerCamelCase : Dict , __lowerCamelCase : float = 0.0 , __lowerCamelCase : float = 1.0 ):
"""simple docstring"""
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) ... | 272 |
"""simple docstring"""
import numpy as np
from PIL import Image
def snake_case__ ( __lowerCamelCase : np.ndarray , __lowerCamelCase : int , __lowerCamelCase : int ):
"""simple docstring"""
lowerCamelCase__ : List[Any] =np.array(__lowerCamelCase ... | 272 | 1 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class snake_case ( unittest.TestCase ):
def UpperCAmelCase__ ( ... | 243 |
'''simple docstring'''
import requests
a_ = 'YOUR API KEY'
def _a( UpperCamelCase__ : str, UpperCamelCase__ : str = giphy_api_key ):
'''simple docstring'''
SCREAMING_SNAKE_CASE__ : Any ='''+'''.join(query.split() ... | 152 | 0 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resize, To... | 341 |
"""simple docstring"""
def _lowerCamelCase(__UpperCamelCase ) -> Optional[Any]:
_lowerCAmelCase =0
_lowerCAmelCase =len(__UpperCamelCase )
for i in range(n - 1 ):
for j in range(i + 1 , __UpperCamelCase ):
if arr[i] > arr[j]:
num_inversions += 1
return num_invers... | 341 | 1 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
snake_case : Optional[int] = object()
# For specifying empty leaf dict `{}`
snake_case : Any = ... | 240 |
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
snake_case : List[Any] = datasets.logging.get_logger(__name__)
snake_case : List[str] = '''\
@InPro... | 240 | 1 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_common impor... | 56 |
"""simple docstring"""
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return number | (1 << position)
def _lowercase ( __lowerCAmelCase , __lowerCAmelCase ) -> int:
return number & ~(1 << position)
def _lowercase ( __lower... | 56 | 1 |
'''simple docstring'''
from math import factorial, pi
def _UpperCamelCase ( __A , __A = 30 ) -> float:
'''simple docstring'''
if not isinstance(__A , (int, float) ):
raise ValueError("maclaurin_sin() requires either an int or float for t... | 80 |
import argparse
import os
import torch
from transformers import (
XLNetConfig,
XLNetForQuestionAnswering,
XLNetForSequenceClassification,
XLNetLMHeadModel,
load_tf_weights_in_xlnet,
)
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
UpperCAmelCase : in... | 95 | 0 |
"""simple docstring"""
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
... | 163 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ConvNextConfig, SegformerImageProcessor, UperNetConfig, UperNetForSemanticSegmentation
def a__ ( __lowerca... | 163 | 1 |
import re
def __UpperCAmelCase ( __a : str ) -> bool:
"""simple docstring"""
_a : List[str] = re.compile(
R'''^(?:0|94|\+94|0{2}94)''' R'''7(0|1|2|4|5|6|7|8)''' R'''(-| |)''' R'''\d{7}$''' )
return bool(re.search(_lowerCamelCase ,_lowerCamelCase ... | 235 |
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor
if is_fl... | 232 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu... | 365 |
"""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... | 100 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase__ = {
"""configuration_gpt_neo""": ["""GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoConfig"""... | 96 |
"""simple docstring"""
import math
def _snake_case ( lowercase__ ):
return math.sqrt(lowercase__ ) * math.sqrt(lowercase__ ) == num
def _snake_case ( lowercase__ ):
_lowerCamelCase : Optional[int] = 0
_lowerCamelCase... | 96 | 1 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowercase : str = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of tha... | 356 |
'''simple docstring'''
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class __UpperCAmelCase :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
if dst_width < ... | 160 | 0 |
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
... | 51 | """simple docstring"""
def __a ( _SCREAMING_SNAKE_CASE = 1000000 ) ->int:
a__: int = limit + 1
a__: Optional[int] = [0] * limit
for first_term in range(1 , _SCREAMING_SNAKE_CASE ):
for n in range(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SN... | 290 | 0 |
'''simple docstring'''
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
SCREAMING_SNAKE_CASE_: Optional[Any] ={'UserAgent': UserAgent().random}
def lowerCAmelCase_ ( snake_case_ : int ) -> dict:
... | 106 | '''simple docstring'''
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib... | 106 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__ : List[str] =logging.get_logger(__name__)
A__ : List[Any] ={
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/mai... | 70 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCAmelCase :
_lowercas... | 70 | 1 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowerCAmelCase__ ( ):
'''simple docstring'''
print('''Making key files...''')
make_key_files('''rsa''' ,1024)
print('''Key f... | 364 |
__snake_case : Any ='\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
__snake_case : Tuple =[{'type':... | 94 | 0 |
'''simple docstring'''
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
lowercase__ = logging.get_logger(__name__)
def UpperCamelCase( UpperCAmelCa... | 151 |
'''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
lowercase__ = logging.get_logger(__name__)
lowercase__ =... | 151 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils impor... | 370 | '''simple docstring'''
def lowerCamelCase ( UpperCAmelCase__ : int = 1000000 ) -> int:
lowercase_ : List[Any] = limit + 1
lowercase_ : Optional[Any] = [0] * limit
for first_term in range(1 , UpperCAmelCase__ ):
for n in r... | 21 | 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_channel... | 31 | '''simple docstring'''
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transform... | 31 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ = logging.get_logger(__name__)
lowerCamelCase__ = {
'''distilbert-base-uncased''': '''http... | 364 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerConfig''... | 22 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__UpperCamelCase = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBert... | 69 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__UpperCamelCase = {
'''configuration_resnet''': ['''RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Re... | 69 | 1 |
from ... import PretrainedConfig
__a = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class __a( _a ):
"""simple docstring"""
lowerCAmelCase = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
lowerCAmelCase ... | 369 |
from collections import defaultdict
def lowerCamelCase__ ( _lowercase , _lowercase ):
'''simple docstring'''
UpperCAmelCase_ : Optional[int] = first_str.lower().strip()
UpperCAmelCase_ : Any = second_str.lower().strip()
... | 235 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase : str =logging.get_logger(__name__)
lowerCamelCase : Any ={
"kssteven/ibert-rob... | 189 |
import functools
def lowerCamelCase__ ( _A , _A ):
'''simple docstring'''
if not isinstance(_A , _A ) or not all(isinstance(_A , _A ) for day in days ):
raise ValueError("The parameter days should be a list of integers" )
... | 187 | 0 |
"""simple docstring"""
__A = {
"joule": 1.0,
"kilojoule": 1000,
"megajoule": 100_0000,
"gigajoule": 10_0000_0000,
"wattsecond": 1.0,
"watthour": 3600,
"kilowatthour": 360_0000,
"newtonmeter": 1.0,
"calorie_nutr": 4186.8,
"kilocalorie_nutr": 418_6800.00,
... | 341 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def _lowerCamelCase(__UpperCamelCase , __UpperCamelCase=1 ) -> Tuple:
if n_shave_prefix_segments >= 0:
return ".".join(path.split(""".""" )[n_shave... | 341 | 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 __UpperCAmelCase ( lowercase ... | 289 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class _snake_case ( _snake_case ... | 94 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musicgen... | 183 |
'''simple docstring'''
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDM... | 183 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from... | 298 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class A ( SCREAMI... | 298 | 1 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_ut... | 159 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
_lowerCamelCase : str = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenag... | 159 | 1 |
'''simple docstring'''
import warnings
from .generation import TFGenerationMixin
class UpperCAmelCase__ ( SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
warnings.warn(
'''Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will '''
'''be... | 271 |
def __UpperCamelCase ( _lowerCAmelCase = 100_0000 ) -> int:
"""simple docstring"""
A : str = limit + 1
A : Tuple = [0] * limit
for first_term in range(1 , _lowerCAmelCase ):
for n in range(_lowerCAmelCase , _lowerCAmelCa... | 116 | 0 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
__lowerCAmelCase = re.compile(r'\b(a|an|the)\b', re.UNICODE)
__lowerCAmelCase = None
def __SCREAMING_SNAKE_CASE ( ):
_snake_case = arg... | 270 |
'''simple docstring'''
def __SCREAMING_SNAKE_CASE ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
if not (isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE )):
raise ValueError("""longest_comm... | 270 | 1 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
__snake_case =logging.get_logger(__name__)
__snake_case ={
"""t5-small""": """https://huggin... | 4 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
_A : Dict ={'''tokenization_herbert''': ['''HerbertTokenizer''']}
try:
if not is_tokenizers_available():
raise Op... | 41 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
def _A ( _a : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number %... | 360 |
"""simple docstring"""
import random
def _A ( _a : list , _a : Any ):
"""simple docstring"""
A , A , A = [], [], []
for element in data:
if element < pivot:
less.append(... | 77 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import torch
import torchaudio
from datasets import load_dataset
from huggingface_hub import hf_hub_download
from transformers import ASTConfig, ASTFeatureExtractor, ASTForAudioClassification
from transformers.utils i... | 113 |
"""simple docstring"""
__UpperCamelCase = frozenset(
[
'''prompt''',
'''height''',
'''width''',
'''guidance_scale''',
'''negative_prompt''',
'''prompt_embeds''',
'''negative_prompt_embeds''',
'''cross_attention_kwargs'... | 113 | 1 |
import logging
from transformers import PretrainedConfig
lowerCamelCase_ = logging.getLogger(__name__)
lowerCamelCase_ = {
'''bertabs-finetuned-cnndm''': '''https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json''',
}
class ... | 370 |
from torch import nn
def UpperCamelCase( lowercase_ ) -> Tuple:
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
return nn.GELU()
else:
raise ValueError(f'''Unsupported acti... | 34 | 0 |
'''simple docstring'''
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
__a: Tuple = logging... | 198 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipe... | 241 | 0 |
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
# import classes
from unilm.wavlm.WavLM im... | 369 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_convbert import ConvBertTokenizer
lowerCAmelCase : Any = logging.get_logger(__name__)
lower... | 127 | 0 |
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase):
return 1 if input_a == input_a else 0
def lowerCamelCase__ ():
assert xnor_gate(0 , 0) == 1
assert xnor_gate(0 , 1) == 0
assert xnor_gate(1 , 0) == 0
assert xnor_gate(1 , 1) == 1
if __n... | 137 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__UpperCAmelCase = 1.054571817e-34 # unit of ℏ : J * s
__UpperCAmelCase = 3e8 # unit of c : m * s^-1
... | 84 | 0 |
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBertForMaskedLM,
Distil... | 360 |
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase__ ( lowerCamelCase_ : ndarray):
'''simple docstring'''
return np.dot(lowerCamelCase_ ,lowerCamelCase_)
class lowerCamelCase__ :
'''simple docstri... | 94 | 0 |
class A__ :
def __init__( self , A_ , A_=None , A_=None ):
'''simple docstring'''
UpperCamelCase : List[str] = data
UpperCamelCase : Optional[int] = previous
UpperCamelCase : Optional[Any] ... | 52 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__lowerCamelCase = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
'''ClapConfig'... | 162 | 0 |
"""simple docstring"""
import math
import sys
import cva
import numpy as np
def __UpperCAmelCase ( __lowerCamelCase , __lowerCamelCase ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
lowercase__ : Optional[Any... | 302 |
"""simple docstring"""
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(... | 302 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class __UpperCamelCase :
A_ = field(
metadata={"help": "The out... | 27 |
"""simple docstring"""
def lowercase (_lowerCAmelCase = 100_0000 ):
__lowerCAmelCase = [i - 1 for i in range(limit + 1 )]
for i in range(2 , limit + 1 ):
if phi[i] == i - 1:
for j in range(2 * i , limit + 1 , _lowerCAmelCase ):
... | 301 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_A = logging.get_logger(__name__)
_A = {
"caidas/swin2sr-classicalsr-x2-64": (
"https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/main/config.json"
),
}
class lowerCa... | 362 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_A = logging.get_logger(__name__)
_A = {"vocab_file": "vocab.txt", "... | 137 | 0 |
'''simple docstring'''
import numpy
class __UpperCAmelCase :
'''simple docstring'''
def __init__(self : Any , _lowerCAmelCase : numpy.ndarray , _lowerCAmelCase : numpy.ndarray ):
A = input_array
# Random initial weights are... | 258 |
'''simple docstring'''
def __a ( UpperCAmelCase , UpperCAmelCase ) ->float:
"""simple docstring"""
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""" )
return (bulk_modulus / densit... | 258 | 1 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.uti... | 242 |
'''simple docstring'''
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
lowercase =logging.getLogger(__name__)
class __magic_name__ ( lowerCAmelCase ):
... | 242 | 1 |
'''simple docstring'''
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transfo... | 27 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
lowerCamelCase : Tuple =False
class __a ( unittest.TestCase ... | 189 | 0 |
"""simple docstring"""
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_BLOCK_... | 364 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfig
from ..... | 202 | 0 |
from __future__ import annotations
_UpperCAmelCase : Union[str, Any] ='''#'''
class snake_case__:
'''simple docstring'''
def __init__( self ) -> Dict:
lowerCAmelCase_ : dict = {}
def lowercase_ ( self , __lowercase ... | 262 |
"""simple docstring"""
import sys
lowercase__ : Dict = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''... | 264 | 0 |
"""simple docstring"""
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from tr... | 355 |
"""simple docstring"""
def __SCREAMING_SNAKE_CASE ( lowercase__ = 600_851_475_143 ):
"""simple docstring"""
try:
A = int(lowercase__ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 57 | 0 |
"""simple docstring"""
def _A (__a = 1_00_00_00 ) -> int:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : str = 1
SCREAMING_SNAKE_CASE_ : str = 1
SCREAMING_SNAKE_CASE_ : List[str] = {1: 1}
for inputa in range(2 ... | 91 | """simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
BertE... | 44 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_lowerCAmelCase : Optional[int] = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
else:
... | 70 |
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
_lowerCAmelCase : Any = (3, 9, -11, 0, 7, 5, 1, -1)
_lowerCAmelCase : Any = (4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class __magic_name__ :
"""simple docstrin... | 70 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils i... | 57 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class __magic_name__ :
def __init__( self : str , lowercase_ : Dict ):
if isinst... | 239 | 0 |
from itertools import zip_longest
import requests
from bsa import BeautifulSoup
from pandas import DataFrame
def __lowerCamelCase ( UpperCAmelCase_ : str = "laptop" ):
"""simple docstring"""
a :Optional[int] = F'''https://www.amazon.in/laptop/s?k={product}'''... | 281 |
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
snake_case : List[Any] = get_tests_dir('''fixtures/test_sentenc... | 281 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils... | 83 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get... | 42 | 0 |
'''simple docstring'''
# Copyright 2021 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/lice... | 179 |
'''simple docstring'''
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def snake_case_ (UpperCamelCase : Dict ):
'''simple docstring'''
_a = {}
_a = job['''started_at''']
... | 179 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES, XLMTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( _lowerCamelCase , unittest... | 69 |
'''simple docstring'''
from __future__ import annotations
import queue
class lowercase :
"""simple docstring"""
def __init__( self ,a_ ) -> str:
_UpperCAmelCase : Optional[Any] = data
_UpperCAmelCase : Optional[int] = None
... | 215 | 0 |
import numpy as np
def lowerCAmelCase_ ( __UpperCAmelCase: np.array ) -> np.array:
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 247 |
from __future__ import annotations
import bisect
def lowerCAmelCase_ ( __UpperCAmelCase: list[int] , __UpperCAmelCase: int , __UpperCAmelCase: int = 0 , __UpperCAmelCase: int = -1 ) -> int:
if hi < 0:
UpperCamelCase__ : ... | 247 | 1 |
import argparse
from collections import defaultdict
import yaml
__UpperCamelCase : List[Any] = "docs/source/en/_toctree.yml"
def __A ( __lowerCamelCase ) -> Tuple:
a = defaultdict(_SCREAMING_SNAKE_CASE )
for doc in model_doc:
... | 228 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__A = {"""configuration_reformer""": ["""REFORMER_PRETRAINED_CONFIG_ARCHIVE_... | 293 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A : List[Any] = logging.get_logger(__name__)
__A : Any = {
"google/fnet-base": "https://huggingface.co/google/fnet-base/resolve/main/config.json",
"... | 354 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licen... | 89 | 0 |
import random
from typing import Any
def __lowerCamelCase ( UpperCAmelCase_ : list ):
"""simple docstring"""
for _ in range(len(UpperCAmelCase_ ) ):
a :str = random.randint(0 , len(UpperCAmelCase_ ) - 1 )
a :... | 94 |
'''simple docstring'''
from sklearn.metrics import fa_score
import datasets
_UpperCamelCase = '''
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)
'''
_UpperCamelCase = '''
Args:
... | 254 | 0 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def __lowerCamelCase ( lowerCAmelCase__ ):
return sum(param.float().sum() if 'encoder.embeddings' n... | 366 | import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
from transformers.models.wa... | 119 | 0 |
"""simple docstring"""
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state im... | 109 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from... | 189 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A_ ( lowerCAmelCase_ ... | 156 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from .... | 156 | 1 |
'''simple docstring'''
import functools
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase ):
"""simple docstring"""
if not isinstance(UpperCamelCase , UpperCamelCase ) or not all(isinstance(UpperCamelCase , UpperCamelCase ) for day in days ... | 37 |
"""simple docstring"""
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
UpperCAmelCase__ = '... | 288 | 0 |
def lowerCamelCase_ ( _UpperCamelCase ) -> int:
"""simple docstring"""
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise TypeError('''only integers accepted as input''' )
else:
snake_case_ : Any = str(abs(_UpperCamelCas... | 369 |
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ ... | 279 | 0 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
d... | 298 |
from __future__ import annotations
UpperCAmelCase__ = list[list[int]]
# assigning initial values to the grid
UpperCAmelCase__ = [
[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, 6, 3, 0, 0, 5],
... | 339 | 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
snake_case_ = logging.get_logger(__name__)
snake_case_ ... | 181 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
if not isinstance(lowercase_ , lowercase_ ):
UpperCAmelCase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase_ )
if number < 1:
... | 181 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avail... | 347 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( __A = 1_000_000 ) -> int:
_snake_case = limit + 1
_snake_case = [0] * limit
for first_term in range(1 , __A ):
for n in range(__A , __A , __A ):
_snake_case = first_term + n / first_term
if commo... | 42 | 0 |
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate(
'stable diffusion controlnet',
'0.22.0',
'Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diffusion.flax_pipeline_stable_di... | 369 |
'''simple docstring'''
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : int ):
'''simple docstring'''
while b:
UpperCAmelCase__ , UpperCAmelCase__ = b, a % b
return a
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : ... | 61 | 0 |
'''simple docstring'''
import math
def lowercase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float ):
"""simple docstring"""
if (
not isinstance(lowerCAmelCase__ , (int, float) )
or power_factor < -1
or power_fac... | 254 |
'''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_in... | 254 | 1 |
import itertools
import json
import os
import unittest
from transformers import AddedToken, RobertaTokenizer, RobertaTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import... | 176 |
import warnings
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimen... | 176 | 1 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
UpperCAmelCase__ = logging.get_logger(__name__)
class lowerCAmelCase__ ( A_ ):
def __init__( self : Optional[Any] , _lowerCamelCase : Opt... | 288 |
"""simple docstring"""
def _UpperCAmelCase ( __lowerCamelCase : list , __lowerCamelCase : int = 0 ) -> list:
_snake_case = length or len(__lowerCamelCase )
_snake_case = False
for i in range(length - 1 ):
if list_data[i] > lis... | 288 | 1 |
"""simple docstring"""
from math import ceil
def A_ ( snake_case_ : int = 1_0_0_1 ):
'''simple docstring'''
UpperCamelCase : str = 1
for i in range(1 ,int(ceil(n / 2.0 ) ) ):
UpperCamelCase : Optional[Any] = ... | 27 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
__A : int = {
'''configuration_gpt_bigcode''': ['''GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTBigCodeConfig'''],
}
try:... | 27 | 1 |
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