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 |
|---|---|---|---|---|
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
__A : List[Any] = logging.get_logger(__name__)
class __A ( lowerCAmelCase__ ):
def __init__( self : int , *UpperCAmelCase_ : List[str] , **UpperCAmelCase_ ... | 138 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def __UpperCamelCase ( _A : Optional[Any] , _A : List[str]=7 ) ->str:
"""simple docstring"""
lowerCamelCase_ =None
if token is not None:
... | 154 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',... | 302 |
"""simple docstring"""
from typing import Optional
import torch
import torch.utils.checkpoint
from torch import Tensor, nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_... | 302 | 1 |
'''simple docstring'''
from manim import *
class A_ ( _snake_case ):
'''simple docstring'''
def UpperCAmelCase_ ( self : List[Any] ) -> Optional[int]:
UpperCAmelCase : List[str] = Rectangle(height=0.5 , w... | 151 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer... | 151 | 1 |
__UpperCAmelCase = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader impo... | 354 |
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__UpperCAmelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa: E402... | 145 | 0 |
"""simple docstring"""
import math
def _lowerCAmelCase ( ):
UpperCAmelCase = input('Enter message: ' )
UpperCAmelCase = int(input(F"""Enter key [2-{len(lowercase_ ) - 1}]: """ ) )
UpperCAmelCase = input('Encryption/Decr... | 78 |
import importlib
import math
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Tuple, Union
import flax
import jax.numpy as jnp
from ..utils import BaseOutput
_a = '''scheduler_config.json'''
class A_ ( snake_cas... | 322 | 0 |
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.stable_diffusion.pipeline_stable_diffus... | 351 |
from __future__ import annotations
from PIL import Image
# Define glider example
UpperCAmelCase_ : Optional[Any] = [
[0, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0],
[1, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0],
... | 62 | 0 |
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from accelera... | 73 |
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .utils import require_lza, require_zsta... | 281 | 0 |
"""simple docstring"""
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@datac... | 367 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 209 | 0 |
def _UpperCAmelCase ( snake_case ):
"""simple docstring"""
if not isinstance(snake_case , snake_case ):
_lowerCAmelCase = F'Input value of [number={number}] must be an integer'
raise TypeError(snake_case )
if number < 0:
return False
... | 82 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, TensorType... | 355 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def _SCREAMING_SNAKE_CASE (__lowerCAmelCase ) -> tuple[np.ndarray, np.ndarray]:
'''simple docstring'''
lowercase_ , lowercase_ = np.shape(__lowerCAmelCase )
if rows !... | 313 | 0 |
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 = {
'''roberta-base''': '''https://huggingface... | 188 |
"""simple docstring"""
import os
import sys
import unittest
__snake_case = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_t... | 320 | 0 |
import unittest
import numpy as np
import torch
from diffusers import DDIMPipeline, DDIMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, slow, torch_device
from ..pipeline_params import UNCONDITIONAL_IMAGE_GENERATION_BATCH_PARAMS, UNCONDITIONAL_IMAGE_GEN... | 356 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def _UpperCAmelCase ( ):
print('Making key files...' )
make_key_files('rsa' , 10_24 )
print('Key files generation succes... | 117 | 0 |
'''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 i... | 250 |
'''simple docstring'''
import os
import pytest
from attr import dataclass
_snake_case = 'us-east-1' # defaults region
@dataclass
class a__ :
_SCREAMING_SNAKE_CASE : str
_SCREAMING_SNAKE_CASE : str = 'arn:aws:iam::558105141721:role/sagemaker_execution_role'
_SCREAMING... | 250 | 1 |
"""simple docstring"""
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
load_... | 371 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import add_start_docstrings
lowerCamelCase__ = R"\n [`RagConfig`] stores the configuration of a *RagModel*. Configuration objects inherit from [`PretrainedConfig`] and\n can be used to control... | 310 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.ut... | 10 |
"""simple docstring"""
import numpy
class lowercase_ :
'''simple docstring'''
def __init__( self : Dict , _UpperCAmelCase : numpy.ndarray , _UpperCAmelCase : numpy.ndarray ):
_A = input_array
# Random initial weigh... | 315 | 0 |
"""simple docstring"""
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
lowerCamelCase_ = datasets.load_iris()
lowerCamelCase_ = np.array(data['''data'''])
lowerCamelCase_ = np.array(data['''ta... | 253 |
"""simple docstring"""
import re
import string
import numpy as np
import datasets
lowerCamelCase_ = '''
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
'''
lowerCamelCase_ = '''
Args... | 253 | 1 |
'''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 __UpperCamelCase ( lowerCamelCa... | 75 | """simple docstring"""
import argparse
import json
import subprocess
def UpperCAmelCase__ ( lowerCAmelCase__ :Tuple , lowerCAmelCase__ :List[Any] ) -> Optional[Any]:
'''simple docstring'''
lowercase = []
lowercase = (
... | 197 | 0 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollator... | 361 |
'''simple docstring'''
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class lowerCamelCase ( lowercase_ ):
'''simple docstring'''
def lowercase__ ( self : Any , lowerCAmelCase_ : ... | 136 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( _UpperCamelCase : int ) -> int:
"""simple docstring"""
if a < 0:
raise ValueError('Input value must be a positive integer' )
elif isinstance(_UpperCamelCase , _UpperCamelCase ):
raise Typ... | 47 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCAmelCase ( ) -> Any:
"""simple docstring"""
_SCREAMING_SNAKE_CASE =ArgumentPar... | 47 | 1 |
"""simple docstring"""
import os
from datetime import datetime as dt
from github import Github
lowercase__ = [
'good first issue',
'good second issue',
'good difficult issue',
'enhancement',
'new pipeline/model',
'new scheduler',
'wip',
]
def __a ( ) ->str:... | 203 | """simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
lowercase__ = logging.get_logger(__name__)... | 203 | 1 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
D... | 155 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise OptionalDependencyNotAvai... | 30 | 0 |
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 impor... | 362 |
import inspect
import os
import torch
from transformers import AutoModel
from transformers.testing_utils import mockenv_context
from transformers.trainer_utils import set_seed
import accelerate
from accelerate.accelerator import Accelerator
from accelerate.state import AcceleratorState
from a... | 330 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
_UpperCamelCase = logging.get_logger(__name__)
@datacla... | 275 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
from collections.abc import Sequence
from dataclasses import dataclass
from typing import Any
@dataclass
class _UpperCAmelCase :
a__ : int
a__ : Node | None = None
a_... | 332 | 0 |
"""simple docstring"""
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from... | 57 |
"""simple docstring"""
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
... | 57 | 1 |
"""simple docstring"""
import flax.linen as nn
import jax
import jax.numpy as jnp
class __A ( nn.Module ):
_UpperCamelCase : int
_UpperCamelCase : jnp.dtype = jnp.floataa
def __A ( self ):
_lowerCAmelCase : str = nn.Conv(
... | 44 |
"""simple docstring"""
from __future__ import annotations
import os
from collections.abc import Mapping
_lowerCAmelCase :Tuple = tuple[int, int]
class _UpperCAmelCase :
'''simple docstring'''
def __init__( self , A , A ) -> None:
_Upper... | 263 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase : List[Any] = {
"configuration_squeezebert": [
"SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP",
"SqueezeBertCo... | 208 |
import argparse
import pathlib
import fairseq
import torch
from fairseq.models.roberta import RobertaModel as FairseqRobertaModel
from fairseq.modules import TransformerSentenceEncoderLayer
from packaging import version
from transformers import XLMRobertaConfig, XLMRobertaXLForMaskedLM, XLMRobertaX... | 208 | 1 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ):
snake_case : List[Any] = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=__lowerCamelCase , default="biencoder-nq... | 59 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers... | 59 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : List[Any] = {
'configuration_mvp': ['MVP_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MvpConfig', 'MvpOnnxConfig'],
... | 86 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class _Up... | 86 | 1 |
import pytest
from datasets import inspect_metric, list_metrics, load_metric
@pytest.fixture
def a ( A__ : List[Any] ) -> List[Any]:
"""simple docstring"""
monkeypatch.setattr('datasets.utils.deprecation_utils._emitted_deprecation_warnings' , set()... | 205 |
def _SCREAMING_SNAKE_CASE ( a , a = 0 ) -> list:
__A : int = length or len(a )
__A : str = False
for i in range(length - 1 ):
if list_data[i] > list_data[i + 1]:
__A , __A : Optional[int] = list_dat... | 280 | 0 |
"""simple docstring"""
def _lowerCamelCase(__UpperCamelCase ) -> str:
_lowerCAmelCase =int(__UpperCamelCase )
if decimal in (0, 1): # Exit cases for the recursion
return str(__UpperCamelCase )
_lowerCAmelCase , _lowerCAmelCase =divmod(__UpperCamelCase , 2 )
return... | 353 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__A = {
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CONFIG_ARCHIVE_MAP... | 341 | 0 |
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
A__ = """src/transformers"""
# This is to make sure the transformers... | 82 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_pr... | 24 | 0 |
'''simple docstring'''
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,
... | 358 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def _UpperCamelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int , SCREAMING_SNAKE_CASE__ : List[str] , SCREAMING_SNAKE_CASE__ ... | 61 | 0 |
def lowerCAmelCase__ ( lowerCamelCase_ : Tuple):
'''simple docstring'''
lowerCAmelCase__ : Tuple = 1
lowerCAmelCase__ : Dict = 2
while i * i <= n:
lowerCAmelCase__ : Tuple = 0
while n % i == 0:
... | 129 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'''distilbert-base-uncased''': '''https://huggingface.co/distilbert-... | 214 | 0 |
"""simple docstring"""
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A_ = logging.get_logger(__name__)
A_ = {
'''microsoft/xprophetnet-large-wiki100-cased''': (
'''https://huggingface.co/micro... | 296 |
"""simple docstring"""
import os
from distutils.util import strtobool
def _lowerCAmelCase ( UpperCAmelCase__ : List[Any], UpperCAmelCase__ : Optional[Any] ) ->List[str]:
for e in env_keys:
A__ : List[Any] = int(os.environ.get(UpperCAme... | 296 | 1 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
__lowerCAmelCase = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, type=str, ... | 271 |
'''simple docstring'''
class UpperCAmelCase__ :
"""simple docstring"""
def __init__( self : Dict ):
'''simple docstring'''
_a : Dict = {}
def __lowercase ( self : Union[str, Any] ):
'''simple docstring'''
print(self.vert... | 271 | 1 |
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 102 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"""alibaba-damo/mgp-str-base""": """https://huggingface.co/alibaba-damo/mgp-str-base/resolve/main/config.json""",
}
class a__ ... | 102 | 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
f... | 16 |
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 import logging
logging... | 236 | 0 |
'''simple docstring'''
import argparse
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
... | 190 |
'''simple docstring'''
import os
from pathlib import Path
import numpy as np
import pytest
from pack_dataset import pack_data_dir
from parameterized import parameterized
from save_len_file import save_len_file
from torch.utils.data import DataLoader
from transformers import AutoTokenize... | 190 | 1 |
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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resi... | 29 |
"""simple docstring"""
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, re... | 144 | 0 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import BatchEncoding, PreTrainedTokenizer
from ...utils import logging
__A = logging.get_logger(__name__)
__A = ... | 352 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
__A = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE ( snake_case ):
"""simple docstring"""
def __init__( self: List[Any] , *__A: Union[str, An... | 75 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
from transformers.util... | 302 |
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
@require_torch
@require_optimum
@slow
class SC... | 302 | 1 |
'''simple docstring'''
lowerCamelCase__ = {
"joule": 1.0,
"kilojoule": 1_000,
"megajoule": 1_000_000,
"gigajoule": 1_000_000_000,
"wattsecond": 1.0,
"watthour": 3_600,
"kilowatthour": 3_600_000,
"newtonmeter": 1.0,
"calorie_nutr": 4_186.8,
"kiloc... | 322 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
lowerCamelCase__ = list[list[float | int]]
def __lowerCAmelCase (__lowerCAmelCase , __lowerCAmelCase ):
_UpperCAmelCase : int = len(__lowerCAmelCase )
_Up... | 322 | 1 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
_snake_case : Tuple = "\\n@inproceedings{snover-etal-2006-study,\n title = \"A Study of Translation Edit Rate with Targeted Human Annotation\",\n author = \"Snover, Matthew and\n Dorr, Bonnie ... | 123 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore,
)
from transfor... | 123 | 1 |
'''simple docstring'''
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class _SCREAMING_SNAKE_CASE ( __a ,__a ):
__SCREAMI... | 98 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threa... | 98 | 1 |
"""simple docstring"""
import numpy as np
import qiskit
def _snake_case ( lowercase__ = 8 , lowercase__ = None ):
_lowerCamelCase : str = np.random.default_rng(seed=lowercase__ )
# Roughly 25% of the qubits will contribute to the key.
... | 96 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
from transfor... | 260 | 0 |
from __future__ import annotations
def _A ( lowerCAmelCase_ : int = 4 ):
"""simple docstring"""
lowerCAmelCase__ = abs(lowerCAmelCase_ ) or 4
return [[1 + x + y * row_size for x in range(lowerCAmelCase_ )] for y in range(lowerCAmelCase... | 221 |
from math import pi, sqrt
def _A ( lowerCAmelCase_ : float ):
"""simple docstring"""
if num <= 0:
raise ValueError("math domain error" )
if num > 171.5:
raise OverflowError("math range error" )
elif num - int(lowerCAme... | 221 | 1 |
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
lowercase : str = logging.get_logger(__name__)
def A_ ( A__ , A__ ) -> L... | 99 |
'''simple docstring'''
import argparse
import json
from tqdm import tqdm
def UpperCamelCase__ ( ):
"""simple docstring"""
_lowerCAmelCase = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
... | 70 | 0 |
"""simple docstring"""
import math
import unittest
def _lowerCAmelCase ( UpperCAmelCase__ : int ) ->bool:
assert isinstance(UpperCAmelCase__, UpperCAmelCase__ ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
... | 296 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, 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_... | 296 | 1 |
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
Trainer,
TrainerCallback,
... | 32 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : Union[str, Any] = {
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
... | 32 | 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
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps... | 356 |
'''simple docstring'''
from __future__ import annotations
def __UpperCamelCase ( _UpperCAmelCase ):
if not nums:
raise ValueError("List is empty" )
return sum(_UpperCAmelCase ) / len(_UpperCAmelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 37 | 0 |
"""simple docstring"""
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSe... | 96 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ = {
'configuration_mask2former': [
'MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mask2FormerConfig',
],
}
tr... | 308 | 0 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import ... | 364 |
'''simple docstring'''
lowercase__ : Any = {'''a''': ['''c''', '''b'''], '''b''': ['''d''', '''e'''], '''c''': [], '''d''': [], '''e''': []}
lowercase__ : List[Any] = ['''a''', '''b''', '''c''', '''d''', '''e''']
def _lowerCAmelCase ( __snake_case : s... | 190 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
_A : int = logging.get_logger(__name__)
class _lowercase ( UpperCAmelCase__ ):
'''simple docstring'''
def __init__( ... | 229 | '''simple docstring'''
from __future__ import annotations
from dataclasses import dataclass
@dataclass
class _lowercase :
'''simple docstring'''
_SCREAMING_SNAKE_CASE : float
_SCREAMING_SNAKE_CASE : TreeNode | None = None
_SCREAMING_SNA... | 229 | 1 |
"""simple docstring"""
# Copyright (c) 2021-, NVIDIA CORPORATION. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/L... | 108 |
"""simple docstring"""
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class snake_case ( pl.LightningModule ):
def __init__( self : str , UpperCamelC... | 108 | 1 |
"""simple docstring"""
lowerCamelCase_ = "Alexander Joslin"
import operator as op
from .stack import Stack
def __lowerCamelCase ( a_ : str ) -> int:
__SCREAMING_SNAKE_CASE :str = {'''*''': op.mul, '''/''': op.truediv, '''+''': op.add, '''-'... | 191 |
"""simple docstring"""
def __lowerCamelCase ( a_ : list ) -> list:
if len(a_ ) < 2:
return collection
def circle_sort_util(a_ : list , a_ : int , a_ : int ) -> bool:
__SCREAMING_SNAKE_CASE :int ... | 191 | 1 |
'''simple docstring'''
class lowerCAmelCase__ :
def __init__( self , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowercase_ : str ... | 358 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class lowerCAmelCase__ :
def __init__( self , __SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowercase_ : str ... | 264 | 0 |
'''simple docstring'''
from math import pow
def _SCREAMING_SNAKE_CASE ( UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase , UpperCamelCase , ):
"""simple docstring"""
if current_sum == needed_sum:
# If the sum of the... | 37 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( UpperCamelCase ):
"""simple docstring"""
lowerCAmelCase__ : Tuple = abs(UpperCamelCase )
lowerCAmelCase__ : List[Any] = 0
while n > 0:
res += n % 10
n //= 10
return res... | 37 | 1 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase_ ( metaclass=lowerCamelCase__ ):
'''simple docstring'''
__snake_case = ["sentencepiece"]
def __init__( self , *_UpperCAmelCase , **_UpperCAmelCase ):
requires_backends(self , ['''sentencep... | 267 |
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class lowerCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase__ ( self ):
snake_ca... | 267 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForOb... | 81 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''SenseTime/deformable-detr''': '''https://huggingface.co/sensetime/deformable-detr/resolve/main/config... | 43 | 0 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
import... | 28 |
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 ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils import logging
logging.set_verbosity_info()
__U... | 28 | 1 |
from collections import namedtuple
import requests
from lxml import html # type: ignore
__UpperCAmelCase : Tuple = namedtuple("covid_data", "cases deaths recovered")
def A__ ( SCREAMING_SNAKE_CASE__ = "https://www.worldometers.info/coronavirus/") -> covid_data:
... | 111 |
import argparse
import glob
import logging
import os
from argparse import Namespace
from importlib import import_module
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 111 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleCho... | 359 |
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _a ( *UpperCAmelCase , UpperCAmelCase = None , UpperCAmelCase=True , UpperCAmelCase=2 ) -> str:
"""simple docstring"""
from .. import __version__
... | 265 | 0 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_tr... | 1 |
import copy
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
from ..auto import CONFIG_MAPPING
lowerCamelCase : Tuple =loggin... | 189 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCAmelCase : List[str] ={
"configuration_llama": ["LLAMA_PRETRAIN... | 123 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase ( UpperCamelCase__ ):
__lowercase = (PNDMScheduler,)
__lowercase = (("""num_inference_steps""", 50),)
def ... | 123 | 1 |
'''simple docstring'''
class lowercase__ :
def __init__( self : Dict ,lowerCamelCase__ : Optional[int] ,lowerCamelCase__ : List[Any] ,lowerCamelCase__ : Union[str, Any] ):
'''simple docstring'''
_UpperCamelCase : int = name
_UpperCamelC... | 83 |
'''simple docstring'''
from typing import Callable, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ : Optional[Any] = logging.get_logger(__name__)
snake_case_ : int = {
'microsoft/xprophetnet-large-wiki100-cased': (
'http... | 83 | 1 |
"""simple docstring"""
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_=1024 ):
__SCREAMING_SNAKE_CASE ,__SCREAMING_SNAKE... | 255 |
"""simple docstring"""
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
__magic_name__ = {
... | 255 | 1 |
'''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Tuple = {
'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec... | 267 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ..... | 222 |
'''simple docstring'''
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'vocab_file': 'vocab.json',
'merg... | 222 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_UpperCamelCase = {
'configuration_blenderbot': [
'BLENDERBOT_PRETRAINED_CONFIG_ARCHIVE_MAP... | 275 |
'''simple docstring'''
import unittest
from knapsack import greedy_knapsack as kp
class lowercase__ ( unittest.TestCase ):
'''simple docstring'''
def UpperCAmelCase_ ( self ):
_SCREAMING_SNAKE_CASE : str = [10, 20, 30, 40, 50, 60]
... | 200 | 0 |
from __future__ import annotations
import numpy as np
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> Optional[int]:
'''simple docstring'''
SCREAMING_SNAKE_CASE, SCREAMING_SNAKE_CASE = np.shape(_SCREAMING_SNAKE_CASE )
if rows != colum... | 354 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
SCREAMING_SNAKE_CASE_ = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""... | 193 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class __A ... | 44 | """simple docstring"""
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threade... | 44 | 1 |
"""simple docstring"""
from __future__ import annotations
class _lowerCamelCase :
"""simple docstring"""
def __init__( self , _SCREAMING_SNAKE_CASE )->Any:
'''simple docstring'''
A_ : List[str] = TypeError(
'''Matrices must... | 361 |
from __future__ import annotations
import math
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE ):
if num <= 0:
A_ : Optional[int] = f'''{num}: Invalid input, please enter a positive integer.'''
raise ValueError(SCREAMING_SNAKE_CASE )
A_ : Union[str, Any] = [True] * (... | 65 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}
try:
if not is_torch_available():
raise OptionalDependencyNotAvail... | 76 |
def __lowercase ( _UpperCamelCase = 4000000 ) ->int:
"""simple docstring"""
lowercase : int = []
lowercase , lowercase : str = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(_UpperCamelCase )
... | 337 | 0 |
'''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 a__ ( _SCREAMING_SNAKE_CASE : dict ) ... | 67 |
'''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 a__ ( _SCREAMING_SNAKE_CASE : Optional[Any] , _SCREAMING... | 67 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi
def a__ ( SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float , SCREAMING_SNAKE_CASE : float ):
'''simple docstring'''
if (inductance, frequency, reactance).count(... | 108 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_t... | 231 | 0 |
def __UpperCAmelCase ( snake_case_ : Any ) -> List[str]:
"""simple docstring"""
_lowerCAmelCase = len(snake_case_ )
_lowerCAmelCase = sum(snake_case_ )
_lowerCAmelCase = [[False for x in range(s + 1 )] for y in range(n ... | 357 |
"""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... | 317 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE__ = {"configuration_xlnet": ["XLNET_PRE... | 46 |
'''simple docstring'''
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
_snake_case = logging.getLogg... | 250 | 0 |
def UpperCamelCase__( UpperCamelCase__ : str )->str:
A__ = ''''''
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def UpperCamelCase__( UpperCamelCase__ ... | 39 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def UpperCamelCase ( self ):
A__ = [
'''safety_checker/pytorch_model.bin''',
... | 39 | 1 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 68 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers... | 305 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
... | 247 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCAmelCase_ ( ) -> List[str]:
UpperCamelCase__ : List[str] = {
'''repo_name''': ['''test_repo1''', '''te... | 247 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
A: List[str] = logging.get_logger(__name... | 109 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase__ : List[Any] = {
'''configuration_distilbert''': [
... | 264 | 0 |
def A ( lowercase ) -> int:
'''simple docstring'''
UpperCamelCase = abs(lowercase )
UpperCamelCase = 0
while n > 0:
res += n % 10
n //= 10
return res
def A ( lowercase ) -> int:
'''simple docstring'''
UpperCamelCase = abs(lowe... | 110 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokenizer... | 110 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_fl... | 335 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
SCREAMING_SNAKE_CASE_ : str = parse(importlib.metadata.version('torch'))
def _snake_case ( Uppe... | 335 | 1 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
lowerCAmelCase_ = [
# (stable-diffusion, HF Diffusers)
(... | 302 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transfor... | 302 | 1 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class lowerCAmelCase__ ( UpperCAmelCase__ ):
... | 234 |
'''simple docstring'''
from __future__ import annotations
lowerCamelCase__ = 'Muhammad Umer Farooq'
lowerCamelCase__ = 'MIT'
lowerCamelCase__ = '1.0.0'
lowerCamelCase__ = 'Muhammad Umer Farooq'
lowerCamelCase__ = 'contact@muhammadumerfarooq.me'
lowerCamelCase__ = '... | 234 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__:Optional[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__:Union[str, Any] = {
"""facebook/xglm-564M""": """https://huggingface.co/facebook/xglm-564M/resolve/main/config.... | 268 | """simple docstring"""
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from... | 268 | 1 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def __lowerCamelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __UpperCamelCase ) -> List[Any]:
"""simple docstring"""
lowerCAmelCase_ : Any ... | 241 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
lowercase__ = TypeVar("""_T""")
class __lowerCamelCase ( Generic[_T] ):
'''simple docstring'''
def __init__( self : Optional[int] , a_ : Iterable[_T] | None = No... | 241 | 1 |
"""simple docstring"""
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
_UpperCamelCase = l... | 350 |
"""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,
)
_UpperCamelCase = {"""configu... | 234 | 0 |
"""simple docstring"""
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_... | 72 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''microsoft/unispeech-large-1500h-cv''': (
'''https://huggingface.c... | 72 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase__ = 5_0_0_0_0_0
lowercase__ , lowercase__ = os.path.split(__file__)
lowercase__ = os.path.join(RESULTS_... | 83 |
'''simple docstring'''
from collections.abc import Generator
def _UpperCamelCase ( ) -> Generator[int, None, None]:
'''simple docstring'''
snake_case ,snake_case : Tuple = 0, 1
while True:
snake_case ,snake_case : List[Any] = b, a + b
yie... | 83 | 1 |
"""simple docstring"""
from maths.is_square_free import is_square_free
from maths.prime_factors import prime_factors
def _snake_case ( lowercase__ : int ) -> int:
'''simple docstring'''
lowerCAmelCase_ :str = prime_factors(lowercase__ )
... | 84 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax... | 84 | 1 |
from math import pow
def lowerCAmelCase__ ( _a : int , _a : int , _a : int , _a : int , _a : int , ):
if current_sum == needed_sum:
# If the sum of the powers is equal to needed_sum, then we have a solution.
solutions_count += 1
r... | 36 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyN... | 36 | 1 |
import gc
import inspect
import unittest
import torch
from parameterized import parameterized
from diffusers import PriorTransformer
from diffusers.utils import floats_tensor, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_mod... | 306 |
def __lowerCamelCase ( snake_case__ ) -> list:
"""simple docstring"""
def merge(snake_case__ ,snake_case__ ) -> list:
def _merge():
while left and right:
yield (left if left[0] <= right[... | 306 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simp... | 355 |
"""simple docstring"""
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__UpperCamelCase : Union[str, Any] = logging.get_logger(__name__)
__... | 309 | 0 |
"""simple docstring"""
from __future__ import annotations
SCREAMING_SNAKE_CASE__ = list[tuple[int, int]]
SCREAMING_SNAKE_CASE__ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0,... | 46 |
"""simple docstring"""
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__) # pylint: disable=invalid-name
... | 46 | 1 |
'''simple docstring'''
import os
lowercase__ : Any = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 1_00, '''D''': 5_00, '''M''': 10_00}
def _lowerCAmelCase ( __snake_case : str ) -> int:
__A : str = 0
__A ... | 190 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : Optional[Any] = logging.get_logger(__name__)
lowercase__ : ... | 190 | 1 |
'''simple docstring'''
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common... | 4 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicab... | 195 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def __lowerCAmelCase (__lowerCAmelCase ):
# This defines a "chinese character" as anything in the CJK Unicode block:
... | 364 |
'''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
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_ou... | 322 | 0 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_numpy_array, valid_i... | 188 |
lowerCamelCase : Optional[Any] = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
def snake_case_ ( ):
__lowercase : List[str] = input("""Enter message: """ )
__lowercase : int = input("""Enter key [alphanumeric]: """ )
__lowercase : ... | 233 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTra... | 346 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCAmelCase_ : Union[str, Any] = None
try:
import msvcrt
except ImportError:
lowerCAmelCase_ : Tuple = None
try:
import fcntl
e... | 346 | 1 |
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