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 |
|---|---|---|---|---|
"""simple docstring"""
from math import ceil, sqrt
def lowerCAmelCase__ ( UpperCamelCase__ = 1_0_0_0_0_0_0 ):
'''simple docstring'''
_a : List[Any] = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
... | 357 |
"""simple docstring"""
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_comm... | 324 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import Ba... | 358 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set ... | 324 | 0 |
"""simple docstring"""
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_herbert import HerbertTokenizer
_snake_case = logging.get_logger(__name__)
_snake_case = ... | 359 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
... | 324 | 0 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import DeiTConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vis... | 360 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@requ... | 324 | 0 |
"""simple docstring"""
import unittest
from transformers import 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_modeli... | 361 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCamelCase ( snake_case_ ):
def __init__( self : Union[str, ... | 324 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
return "\n".join(
F"""{number} * {i} = {number * i}""" for i in range(1 , number_of_terms + 1 ) )
if __name__ == "__main__... | 362 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_snake_case = HUGGINGFACE_HUB_CACHE
_snake_case = 'config.json'
_snake_case = 'diffusion_pytorch_model.bin'
_snake_case = 'dif... | 324 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.blenderbot_small.tokenization_blenderbot_small import (
VOCAB_FILES_NAMES,
BlenderbotSmallTokenizer,
)
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( snake_case... | 363 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials"... | 324 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''alibaba-damo/mgp-str-base''': '''https://huggingface.co/alibaba-damo/mgp-str-base/resolve/mai... | 364 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a , _a : Dict = len(UpperCamelCase__ ), len(grid[0] )
if (
min... | 324 | 0 |
"""simple docstring"""
import math
class UpperCamelCase :
def __init__( self : Any , UpperCAmelCase__ : Optional[int]=0 ) -> str: # a graph with Node 0,1,...,N-1
_a : Optional[int] = n
_a : Optional[int] = [
[math.inf for j in ra... | 365 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'configuration_vision_encoder_decoder': ['Vision... | 324 | 0 |
from sklearn.metrics import recall_score
import datasets
_snake_case = '\nRecall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:\nRecall = TP / (TP + FN)\nWhere TP is the true positives and FN is the f... | 366 |
"""simple docstring"""
from __future__ import annotations
import time
_snake_case = list[tuple[int, int]]
_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... | 324 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config... | 367 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD... | 324 | 0 |
"""simple docstring"""
import os
import string
import sys
_snake_case = 1 << 8
_snake_case = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 27,
'up': 65 + ARROW_KEY_FLAG,
'down': 66 + ARROW_KEY_FLAG,
'right': 67 + ARROW_KEY_FLAG,
... | 368 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.confi... | 324 | 0 |
"""simple docstring"""
import random
from typing import Any
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
for _ in range(len(_snake_case ) ):
_a : Any = random.randint(0 , len(_snake_case ) - 1 )
_a ... | 369 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteSchedul... | 324 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenizat... | 370 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tenso... | 324 | 0 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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 ...... | 371 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AN... | 324 | 0 |
"""simple docstring"""
_snake_case = {
'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': 41_86.8,
'kilocal... | 350 |
"""simple docstring"""
_snake_case = 8.31_44_62 # Unit - J mol-1 K-1
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueE... | 324 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return "".join(chr(ord(_UpperCAmelCase ) - 3_2 ) if """a""" <= char <= """z""" else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 351 |
"""simple docstring"""
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 tq... | 324 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_uti... | 352 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 324 | 0 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
_snake_case = re.compile(r'\b(a|an|the)\b', re.UNICODE)
_snake_case = None
def lowerCAmelCase__ ( ):
... | 353 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
Channe... | 324 | 0 |
_snake_case = 6_5521
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : Dict = 1
_a : Optional[Any] = 0
for plain_chr in plain_text:
_a : Union[str, Any] = (a + ord(_lowerCAmelCase )) % MOD_ADLER
... | 354 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
cl... | 324 | 0 |
"""simple docstring"""
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gp... | 355 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmu... | 324 | 0 |
"""simple docstring"""
from __future__ import annotations
_snake_case = tuple[int, int, int]
_snake_case = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
_snake_case = 'ABCDEFGHIJKLMNOPQRSTUVWXYZ'
# -... | 356 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return vector * sigmoi... | 324 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, r... | 357 |
"""simple docstring"""
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_comm... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_snake_case = {
'configuration_perceiver': ['PERCEIVER... | 358 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set ... | 324 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenizat... | 359 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
... | 324 | 0 |
"""simple docstring"""
_snake_case = {
'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,
'kilocal... | 360 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@requ... | 324 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow... | 361 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCamelCase ( snake_case_ ):
def __init__( self : Union[str, ... | 324 | 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_modelin... | 362 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_snake_case = HUGGINGFACE_HUB_CACHE
_snake_case = 'config.json'
_snake_case = 'diffusion_pytorch_model.bin'
_snake_case = 'dif... | 324 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/resolve/main/config.json',
'studio-ous... | 363 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials"... | 324 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_D... | 364 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a , _a : Dict = len(UpperCamelCase__ ), len(grid[0] )
if (
min... | 324 | 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 = ... | 365 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'configuration_vision_encoder_decoder': ['Vision... | 324 | 0 |
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__... | 366 |
"""simple docstring"""
from __future__ import annotations
import time
_snake_case = list[tuple[int, int]]
_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... | 324 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 367 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD... | 324 | 0 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_snake_case = 637_8137.0
_snake_case = 635_6752.31_4245
_snake_case = 637_8137
def lowerCAmelCase__ ( UpperCamelCase... | 368 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.confi... | 324 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/l... | 369 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteSchedul... | 324 | 0 |
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,
BertEmbedd... | 370 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tenso... | 324 | 0 |
from numpy import exp, pi, sqrt
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ = 0.0 , UpperCamelCase__ = 1.0 ):
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ == "_... | 371 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AN... | 324 | 0 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def _lowercase ( UpperCAmelCase__ : str ) -> Union[str, Any]:
_a : List[str] = Parti... | 350 |
"""simple docstring"""
_snake_case = 8.31_44_62 # Unit - J mol-1 K-1
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueE... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_snake_case = {
'configuration_vivit': ['VIVIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'VivitConfig... | 351 |
"""simple docstring"""
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 tq... | 324 | 0 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
_snake_case = '\\n@inproceedings{inproceedings,\n author = {Morris, Andrew and Maier, Viktoria and Green, Phil},\n year = {2004},\n month = {01},\n pages = {},\n title = {From WER and RIL ... | 352 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case ... | 353 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
Channe... | 324 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class UpperCamelCase ( lowerCamelCa... | 354 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
cl... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
"configuration_whisper": ["WHISP... | 355 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmu... | 324 | 0 |
"""simple docstring"""
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloy... | 356 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return vector * sigmoi... | 324 | 0 |
"""simple docstring"""
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
_snake_cas... | 357 |
"""simple docstring"""
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_comm... | 324 | 0 |
"""simple docstring"""
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_in... | 358 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set ... | 324 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
fro... | 359 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
... | 324 | 0 |
"""simple docstring"""
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
... | 360 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@requ... | 324 | 0 |
"""simple docstring"""
from random import randint, random
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ = False , UpperCamelCase__ = False , UpperCamelCase__ = 5 , ):
... | 361 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCamelCase ( snake_case_ ):
def __init__( self : Union[str, ... | 324 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
if len(__lowerCAmelCase ) < 2:
return collection
def circle_sort_util(UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ) -> boo... | 362 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_snake_case = HUGGINGFACE_HUB_CACHE
_snake_case = 'config.json'
_snake_case = 'diffusion_pytorch_model.bin'
_snake_case = 'dif... | 324 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from accelerate.commands.config import get_config_parser
from accelerate.commands.env import env_command_parser
from accelerate.commands.launch import launch_command_parser
from accelerate.commands.test import test_command_parser
from accelerate.com... | 363 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials"... | 324 | 0 |
"""simple docstring"""
import argparse
import json
import os
import sys
import tempfile
import unittest
from argparse import Namespace
from dataclasses import dataclass, field
from enum import Enum
from pathlib import Path
from typing import List, Literal, Optional
import yaml
fro... | 364 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a , _a : Dict = len(UpperCamelCase__ ), len(grid[0] )
if (
min... | 324 | 0 |
"""simple docstring"""
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARC... | 365 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'configuration_vision_encoder_decoder': ['Vision... | 324 | 0 |
import csv
import tweepy
# Twitter API credentials
_snake_case = ''
_snake_case = ''
_snake_case = ''
_snake_case = ''
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : Tuple = tweepy.OA... | 366 |
"""simple docstring"""
from __future__ import annotations
import time
_snake_case = list[tuple[int, int]]
_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... | 324 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
_snake_case = 50_0000
_snake_case , _snake_case = os.path.split(__file__)
_snake_case = ... | 367 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD... | 324 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if len(lowerCamelCase_ ) != len(lowerCamelCase_ ):
raise ValueError("""String lengths must match!""" )
_a : Optional[Any] = ... | 368 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.confi... | 324 | 0 |
"""simple docstring"""
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoM... | 369 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteSchedul... | 324 | 0 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def lowerCAmelCase__ ( UpperCamelCase__ , UpperC... | 370 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tenso... | 324 | 0 |
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : Any = set()
# To detect a back edge, keep track of vertices currently in the recursion stack
_a : Optional[Any] = set()
return any(
node not in visited and depth_first_sear... | 371 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AN... | 324 | 0 |
"""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... | 350 |
"""simple docstring"""
_snake_case = 8.31_44_62 # Unit - J mol-1 K-1
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueE... | 324 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=_SCREAMING_SNAKE_CASE ):
UpperCamelCase : Union[str, Any] = ['''note_seq''']
def __init__( self : Tuple , *UpperCAmelCase__ : Optional[int] ,... | 351 |
"""simple docstring"""
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 tq... | 324 | 0 |
"""simple docstring"""
from math import pi, sqrt
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
if num <= 0:
raise ValueError("""math domain error""" )
if num > 1_7_1.5:
raise OverflowError("""math range error""" )
elif num ... | 352 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 324 | 0 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase__ ( UpperCamelCase__ = "isbn/0140328726" ):
'''simple docstring'''
_a : Union[str, Any] = olid.strip().strip... | 353 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
Channe... | 324 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {"openai-gpt": "https://huggingface.co/openai-gpt/resolve/main/config.json"}
class UpperCamelCase ( lowercase_ ... | 354 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
cl... | 324 | 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 AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(_... | 355 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmu... | 324 | 0 |
"""simple docstring"""
from __future__ import annotations
from random import random
class UpperCamelCase :
def __init__( self : Union[str, Any] , UpperCAmelCase__ : Optional[Any] = None ) -> List[str]:
_a : List[str] = valu... | 356 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return vector * sigmoi... | 324 | 0 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
_a : int = int(number**0.5 )
return number == sq * sq
def ... | 357 |
"""simple docstring"""
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_comm... | 324 | 0 |
"""simple docstring"""
import string
import numpy
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
return b if a == 0 else greatest_common_divisor(b % a , _A )
class UpperCamelCase :
... | 358 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set ... | 324 | 0 |
"""simple docstring"""
import os
from pickle import UnpicklingError
from typing import Dict, Tuple
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict, unflatten_dict
import transformers
from .u... | 359 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
... | 324 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if number < 0 or shift_amount < 0:
raise ValueError("""both inputs must be positive integers""" )
_a : str = str(bin(UpperCamelCas... | 360 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@requ... | 324 | 0 |
"""simple docstring"""
import argparse
import re
import torch
from CLAP import create_model
from transformers import AutoFeatureExtractor, ClapConfig, ClapModel
_snake_case = {
"text_branch": "text_model",
"audio_branch": "audio_model.audio_encoder",
"attn"... | 361 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCamelCase ( snake_case_ ):
def __init__( self : Union[str, ... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tok... | 362 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_snake_case = HUGGINGFACE_HUB_CACHE
_snake_case = 'config.json'
_snake_case = 'diffusion_pytorch_model.bin'
_snake_case = 'dif... | 324 | 0 |
"""simple docstring"""
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
_snake_case ... | 363 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials"... | 324 | 0 |
"""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... | 364 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a , _a : Dict = len(UpperCamelCase__ ), len(grid[0] )
if (
min... | 324 | 0 |
"""simple docstring"""
import argparse
import torch
from safetensors.torch import load_file
from diffusers import StableDiffusionPipeline
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase_... | 365 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'configuration_vision_encoder_decoder': ['Vision... | 324 | 0 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
... | 366 |
"""simple docstring"""
from __future__ import annotations
import time
_snake_case = list[tuple[int, int]]
_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... | 324 | 0 |
"""simple docstring"""
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
flip_channel_order,
get_resize_output_image_si... | 367 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD... | 324 | 0 |
"""simple docstring"""
import re
from ..utils import cached_file
# docstyle-ignore
_snake_case = '\nHuman: <<task>>\n\nAssistant: '
_snake_case = 'huggingface-tools/default-prompts'
_snake_case = {'chat': 'chat_prompt_template.txt', 'run': 'run_p... | 368 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.confi... | 324 | 0 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
# bit count represents no. of bits in the gray code
if bit_count < 0:
raise ValueError("""The given input must be positive""" )
# get the generated string sequen... | 369 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteSchedul... | 324 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json',
# See all ViT MAE models ... | 370 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tenso... | 324 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqaSe... | 371 |
"""simple docstring"""
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AN... | 324 | 0 |
"""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, UNetaDConditionM... | 350 |
"""simple docstring"""
_snake_case = 8.31_44_62 # Unit - J mol-1 K-1
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if moles < 0 or kelvin < 0 or volume < 0:
raise ValueE... | 324 | 0 |
"""simple docstring"""
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transform... | 351 |
"""simple docstring"""
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 tq... | 324 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 352 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiec... | 324 | 0 |
"""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_dif... | 353 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
Channe... | 324 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase ( snake_case_ ):
def __init__( self :... | 354 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
cl... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
'configuration_altclip': [
'ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'AltCLIPConfig',
... | 355 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmu... | 324 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_snake_case = {
'configuration_convbert': ['CONVBERT_PRETR... | 356 |
"""simple docstring"""
import numpy as np
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def lowerCAmelCase__ ( UpperCamelCase__ ):
'''simple docstring'''
return vector * sigmoi... | 324 | 0 |
"""simple docstring"""
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
_snake_case = False
class UpperC... | 357 |
"""simple docstring"""
import unittest
from transformers import CamembertTokenizer, CamembertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.utils import is_torch_available
from ...test_tokenization_comm... | 324 | 0 |
"""simple docstring"""
from __future__ import annotations
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a : Optional[int] = 0
_a : List[Any] = len(UpperCamelCase__ ) - 1
while i < j:
... | 358 |
"""simple docstring"""
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set ... | 324 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTImageProcessor, ViTConfig, ViTForImageClassification, ViTImageProcessor, ... | 359 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
... | 324 | 0 |
"""simple docstring"""
import os
import pytest
import yaml
from datasets.features.features import Features, Value
from datasets.info import DatasetInfo, DatasetInfosDict
@pytest.mark.parametrize(
"""files""" , [
["""full:README.md""", """dataset_infos.json"""],
... | 360 |
"""simple docstring"""
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@requ... | 324 | 0 |
"""simple docstring"""
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
_snake_case = 637_8137.0
_snake_case = 635_6752.31_4245
_snake_case = 637_8137
def lowerCAmelCase__ ( UpperCamelCase... | 361 |
"""simple docstring"""
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class UpperCamelCase ( snake_case_ ):
def __init__( self : Union[str, ... | 324 | 0 |
"""simple docstring"""
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig... | 362 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
_snake_case = HUGGINGFACE_HUB_CACHE
_snake_case = 'config.json'
_snake_case = 'diffusion_pytorch_model.bin'
_snake_case = 'dif... | 324 | 0 |
"""simple docstring"""
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 = {
'bert-base-uncased':... | 363 |
"""simple docstring"""
from math import factorial
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
if successes > trials:
raise ValueError("""successes must be lower or equal to trials"... | 324 | 0 |
"""simple docstring"""
from torch import nn
class UpperCamelCase ( nn.Module ):
def __init__( self : Optional[int] , UpperCAmelCase__ : Optional[Any] , UpperCAmelCase__ : Dict ) -> int:
super().__init__()
_a... | 364 |
"""simple docstring"""
def lowerCAmelCase__ ( UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ , UpperCamelCase__ ):
'''simple docstring'''
_a , _a : Dict = len(UpperCamelCase__ ), len(grid[0] )
if (
min... | 324 | 0 |
"""simple docstring"""
import json
import os
import tempfile
import datasets
from utils import generate_example_dataset, get_duration
_snake_case = 5_0000
_snake_case = 5000
_snake_case , _snake_case = os.path.split(__file__)
_snake_case = os.path.join... | 365 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'configuration_vision_encoder_decoder': ['Vision... | 324 | 0 |
import os
import sys
_snake_case = os.path.join(os.path.dirname(__file__), 'src')
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoModelForSequenceCl... | 366 |
"""simple docstring"""
from __future__ import annotations
import time
_snake_case = list[tuple[int, int]]
_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... | 324 | 0 |
"""simple docstring"""
import math
class UpperCamelCase :
def _lowercase ( self : Tuple , UpperCAmelCase__ : list[list[float]] , UpperCAmelCase__ : list[int] ) -> int:
_a : str = 0.0
_a : Optional[int... | 367 |
"""simple docstring"""
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD... | 324 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def lowerCAmelCase__ ( ):
'''simple docstring'''
_a : Tuple = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" ... | 368 |
"""simple docstring"""
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.confi... | 324 | 0 |
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