code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse('''3.8'''):
import importlib_metadata
else:
import importlib.metadata as importlib_metadata
lo... | 707 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class SCREAMING_SNAKE_CASE ( __lowercase ... | 58 | 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,
)
lowercase_ = {
'''configuration_whisper''': ['''WHISPER_PRETRAINED_CONFIG_A... | 708 | '''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is... | 58 | 0 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import DiffusionPipeline
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diff... | 709 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']... | 58 | 0 |
'''simple docstring'''
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def UpperCamelCase__ ... | 710 | '''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =os.path.join(args.tf_model_dir , 'parame... | 58 | 0 |
'''simple docstring'''
import torch
from diffusers import EulerDiscreteScheduler
from diffusers.utils import torch_device
from .test_schedulers import SchedulerCommonTest
class SCREAMING_SNAKE_CASE ( __lowercase):
"""simple docstring"""
lowercase : List[str] = (EulerDiscre... | 711 | '''simple docstring'''
def UpperCamelCase__ ( a__ = 1_0_0_0 ):
'''simple docstring'''
_lowerCAmelCase =2**power
_lowerCAmelCase =0
while n:
_lowerCAmelCase , _lowerCAmelCase =r + n % 1_0, n // 1_0
return r
if __name_... | 58 | 0 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
lowercase_ = '''examples/'''
lowercase_ = {
'''examples''': (re.compile(r'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(r'''^__version__\... | 712 | '''simple docstring'''
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =set()
# To detect a back edge, keep track of vertices currently in the recursion stack
_lowerCAmelCase =set()
return any(
node not in visited an... | 58 | 0 |
'''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_tf_weig... | 713 | '''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase_ = logging.get_logger(__name__)
lowerca... | 58 | 0 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def UpperCamelCase__ ( a__ = 1_0_0_0_0_0_0 , a__ = 1_0 ):
'''simple docstring'''
_lowerCAmelCase =defaultdict(a__ )
for outer_width in range(3 , (t_limit // 4... | 714 | '''simple docstring'''
lowercase_ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''... | 58 | 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(level=logging.INFO)
lowercase_ ... | 715 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''facebook/data2vec-text-base''': '''https:... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( a__ , a__ ):
'''simple docstring'''
_lowerCAmelCase =[]
create_all_state(1 , a__ , a__ , [] , a__ )
return result
def UpperCamel... | 716 | '''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processo... | 58 | 0 |
'''simple docstring'''
import argparse
import os
import re
lowercase_ = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
lowercase_ = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
lowercase_ = re.compile(r'''^\s*"([^"]+)":''')
# Patter... | 717 | '''simple docstring'''
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
def UpperCamelCase__ ( self ) -> Optional[Any]:
_lowerCAmelCase =0
_lowerCAmelCase =[0]
... | 58 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
lowercase_ = {'''configuration_dpt''': ['''DPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPTConfig'''... | 718 | '''simple docstring'''
lowercase_ = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/tran... | 58 | 0 |
'''simple docstring'''
import numpy as np
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 719 | '''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from tra... | 58 | 0 |
'''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compu... | 720 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compu... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
lowercase : int
lowercase : TreeNode | None = None
lowercase : TreeNode | No... | 721 | '''simple docstring'''
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , __A ) -> None:
_lowerCAmelCase =num_of_nodes
_lowerCAmelCase =[]
_lowerCAmelCase ... | 58 | 0 |
'''simple docstring'''
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
return 1 / (1 + np.exp(-z ))
def UpperCamelCase__ ( a__ , a__ ):
'''simple ... | 700 | '''simple docstring'''
from PIL import Image
def UpperCamelCase__ ( a__ , a__ ):
'''simple docstring'''
def brightness(a__ ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 255.0:
raise ValueError('level must be be... | 58 | 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 PretrainedConfig
fr... | 701 | '''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 tran... | 58 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
lowercase_... | 702 | '''simple docstring'''
from __future__ import annotations
lowercase_ = 10
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =1
_lowerCAmelCase =max(a__ )
while placement <= max_digit:
# declare and initializ... | 58 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
lowerca... | 703 | '''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_AND_AUTO_VALUES,
ENV_VARS_TRU... | 58 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase_ = logging.get_logger(__name__)
lowerca... | 704 | '''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =len(a__ ) // 2
# choose the middle 3 elements
_lowerCAmelCase =lst[m - 1 : m + 2]
# if middle element is peak... | 58 | 0 |
import numpy
# List of input, output pairs
lowercase_ = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowercase_ = (((515, 22, 13), 555), ((61, 35, 49), 150))
lowercase_ = [2, 4, 1, 5]
lowercase_ = len(train_data)
lowercase_ ... | 705 | '''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_convbert import ConvBertTokenizer
lowercase_ = logging.get_logger(__name__)
lowercase_... | 58 | 0 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE ( __lowercase):
"""simple docstring"""
lowercase : Any = ['image_processor', 'tokenizer']
lowercase : ... | 706 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE ( __lowercase):
"""simple docstring"""
lowercase : Any = ['image_processor', 'tokenizer']
lowercase : An... | 58 | 0 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def UpperCamelCase__ ( a__ , a__ ):
'''simple docstring'''
_lowerCAmelCase =int(a__ )
assert noofclusters < len(a__ )
# Find out the dimension... | 707 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class SCREAMING_SNAKE_CASE ( __lowercase ... | 58 | 0 |
'''simple docstring'''
import pprint
import requests
lowercase_ = '''https://zenquotes.io/api'''
def UpperCamelCase__ ( ):
'''simple docstring'''
return requests.get(API_ENDPOINT_URL + '/today' ).json()
def UpperCamelCase__ ( ):
'''simple docstring''... | 708 | '''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is... | 58 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import re... | 709 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']... | 58 | 0 |
'''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
def ... | 710 | '''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =os.path.join(args.tf_model_dir , 'parame... | 58 | 0 |
'''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
fro... | 711 | '''simple docstring'''
def UpperCamelCase__ ( a__ = 1_0_0_0 ):
'''simple docstring'''
_lowerCAmelCase =2**power
_lowerCAmelCase =0
while n:
_lowerCAmelCase , _lowerCAmelCase =r + n % 1_0, n // 1_0
return r
if __name_... | 58 | 0 |
'''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 712 | '''simple docstring'''
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =set()
# To detect a back edge, keep track of vertices currently in the recursion stack
_lowerCAmelCase =set()
return any(
node not in visited an... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
lowercase_ = TypeVar('''KT''')
lowercase_ = TypeVar('''VT''')
class SCREAMING_SNAKE_CASE ( Generic[KT, VT]):
"""simple docstring"""
def __init__( self , ... | 713 | '''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase_ = logging.get_logger(__name__)
lowerca... | 58 | 0 |
'''simple docstring'''
import argparse
import json
import subprocess
def UpperCamelCase__ ( a__ , a__ ):
'''simple docstring'''
_lowerCAmelCase =[]
_lowerCAmelCase =(
F'''curl -H "Accept: application/vnd.github+json" -H "Authorization: Be... | 714 | '''simple docstring'''
lowercase_ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''... | 58 | 0 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class SCREAMING_SNAKE_CASE ( __lowercase , __lowercase):
"""simple docstring"""
... | 715 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''facebook/data2vec-text-base''': '''https:... | 58 | 0 |
'''simple docstring'''
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu... | 716 | '''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processo... | 58 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
assert isinstance(a__ , a__ ), F'''The input value of [n={number}] is not an integer'''
if number == 1:
return 2
elif number < 1:
_lowerCAmelCase =F'... | 717 | '''simple docstring'''
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
def UpperCamelCase__ ( self ) -> Optional[Any]:
_lowerCAmelCase =0
_lowerCAmelCase =[0]
... | 58 | 0 |
'''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_warmup, set_seed
from accelerate... | 718 | '''simple docstring'''
lowercase_ = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/tran... | 58 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase_ = {'''configuration_swin''': ['''SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''SwinConfig''', '''SwinOnnxConfig''']}
try:
if not is_torc... | 719 | '''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from tra... | 58 | 0 |
'''simple docstring'''
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class SCREAMING_SNAKE_CASE ( __lowercase):
"""simple... | 720 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compu... | 58 | 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 UpperCamelCase__ ( a__ ):
'''simple do... | 721 | '''simple docstring'''
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , __A ) -> None:
_lowerCAmelCase =num_of_nodes
_lowerCAmelCase =[]
_lowerCAmelCase ... | 58 | 0 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
def UpperCamelCase__ ( self ) -> None:
... | 700 | '''simple docstring'''
from PIL import Image
def UpperCamelCase__ ( a__ , a__ ):
'''simple docstring'''
def brightness(a__ ) -> float:
return 1_2_8 + level + (c - 1_2_8)
if not -255.0 <= level <= 255.0:
raise ValueError('level must be be... | 58 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageResamp... | 701 | '''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 tran... | 58 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( a__ , a__ ):
'''simple docstring'''
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modu... | 702 | '''simple docstring'''
from __future__ import annotations
lowercase_ = 10
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =1
_lowerCAmelCase =max(a__ )
while placement <= max_digit:
# declare and initializ... | 58 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
if is_flax_available():
import jax
from transformers.models.auto.modeling_flax_auto ... | 703 | '''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_AND_AUTO_VALUES,
ENV_VARS_TRU... | 58 | 0 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
lowercase_ = [
'''good first issue''',
'''good second issue''',
'''good difficult issue''',
'''feature request''',
'''new model''',
'''wip''',
]
def UpperCamelCase__ ( ):
... | 704 | '''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =len(a__ ) // 2
# choose the middle 3 elements
_lowerCAmelCase =lst[m - 1 : m + 2]
# if middle element is peak... | 58 | 0 |
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
lowercase_ = '''scheduler_config.json'''
class SCREAMING_SNAKE_CASE ( __lowercase):
... | 705 | '''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_convbert import ConvBertTokenizer
lowercase_ = logging.get_logger(__name__)
lowercase_... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , __A ) -> None:
_lowerCAmelCase =num_of_nodes
_lowerCAmelCase =[]
_lowerCAmelCas... | 706 | '''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class SCREAMING_SNAKE_CASE ( __lowercase):
"""simple docstring"""
lowercase : Any = ['image_processor', 'tokenizer']
lowercase : An... | 58 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerCo... | 707 | '''simple docstring'''
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class SCREAMING_SNAKE_CASE ( __lowercase ... | 58 | 0 |
'''simple docstring'''
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def UpperCamelCase__ ( self , __A ) -> List[Any]:
raise No... | 708 | '''simple docstring'''
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not is... | 58 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_lowerCAmelCase =1
_lowerCAmelCase =1
while repunit:
_lowerCAmelCase =(1_0 * repunit + 1... | 709 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowercase_ = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ViTMAEConfig''']... | 58 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ... | 710 | '''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =os.path.join(args.tf_model_dir , 'parame... | 58 | 0 |
'''simple docstring'''
lowercase_ = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface... | 711 | '''simple docstring'''
def UpperCamelCase__ ( a__ = 1_0_0_0 ):
'''simple docstring'''
_lowerCAmelCase =2**power
_lowerCAmelCase =0
while n:
_lowerCAmelCase , _lowerCAmelCase =r + n % 1_0, n // 1_0
return r
if __name_... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def UpperCamelCase__ ( a__ , a__ , a__ ):
'''simple docstring'''
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError('One and only one argument must... | 712 | '''simple docstring'''
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
_lowerCAmelCase =set()
# To detect a back edge, keep track of vertices currently in the recursion stack
_lowerCAmelCase =set()
return any(
node not in visited an... | 58 | 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 tran... | 713 | '''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowercase_ = logging.get_logger(__name__)
lowerca... | 58 | 0 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def UpperCamelCase__ ( a__ ):
'''simple docstring'''
def decorator(a__ ):
_lowerCAmelCase =getattr(a__ , 'handle_key' , [] )
handle +... | 714 | '''simple docstring'''
lowercase_ = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '''N''... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCamelCase__ ( a__ ) -> int:
'''simple docstring'''
_lowerCAmelCase =len(a__ ) // 2
# choose the middle 3 elements
_lowerCAmelCase =lst[m - 1 : m + 2]
# if middle el... | 715 | '''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase_ = logging.get_logger(__name__)
lowercase_ = {
'''facebook/data2vec-text-base''': '''https:... | 58 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
lowercase_ = {
'''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ErnieConfig''', '''ErnieOnnxConfig'''],
}
try... | 716 | '''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processo... | 58 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase__ ( a__ , a__ , a__ ):
... | 717 | '''simple docstring'''
import unittest
from knapsack import knapsack as k
class SCREAMING_SNAKE_CASE ( unittest.TestCase):
"""simple docstring"""
def UpperCamelCase__ ( self ) -> Optional[Any]:
_lowerCAmelCase =0
_lowerCAmelCase =[0]
... | 58 | 0 |
'''simple docstring'''
import collections
import os
import re
from pathlib import Path
lowercase_ = '''src/transformers'''
# Matches is_xxx_available()
lowercase_ = re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
lowercase_ = re.compile(r'''^_import_stru... | 718 | '''simple docstring'''
lowercase_ = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+https://github.com/huggingface/tran... | 58 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_di... | 719 | '''simple docstring'''
import argparse
import os
import sys
from unittest.mock import patch
import pytorch_lightning as pl
import timeout_decorator
import torch
from distillation import SummarizationDistiller, distill_main
from finetune import SummarizationModule, main
from transformers import MarianMTModel
from tra... | 58 | 0 |
'''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_availab... | 720 | '''simple docstring'''
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import glue_compu... | 58 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf impo... | 721 | '''simple docstring'''
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self , __A ) -> None:
_lowerCAmelCase =num_of_nodes
_lowerCAmelCase =[]
_lowerCAmelCase ... | 58 | 0 |
from math import ceil, sqrt
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int = 1_000_000 ):
SCREAMING_SNAKE_CASE__ = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
SCREAMING_SNAKE_CASE__ = max(ceil(sqrt(outer_wid... | 59 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 1 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Union[str, Any] ):
for param in module.parameters():
SCREAMING_SNAKE_CASE__ = False
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMI... | 59 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 1 |
import numpy as np
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: np.array ):
return 1 / (1 + np.exp(-vector ))
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: np.array ):
return vector * sigmoid(1.7_0_2 * vector )
if __name__ == "__main__":... | 59 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 1 |
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('.')
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Tuple ):
SCREAMING_SNAKE_CASE__ = test_file.split(os... | 59 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 1 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'Salesforce/blip-vqa-base': 'https://huggingface.co/Salesforce/blip-vqa-base/resolve/main/confi... | 59 |
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_transfo_xl import CORPUS... | 59 | 1 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
_lowerCamelCase = transforms.Co... | 59 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder impo... | 59 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 1 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 1 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list , UpperCamelCase__: list ):
_validate_point(UpperCamelCase__ )
_validate_point(UpperCamelCase__ )
if len(UpperCamelCase__ ) != len(UpperCamelCase__ ):
raise ValueError("""Both points must be in the same ... | 59 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 1 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ... | 59 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 1 |
import qiskit
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int , UpperCamelCase__: int ):
SCREAMING_SNAKE_CASE__ = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
SCREAMING_SNAKE_CASE__ = qiskit.Q... | 59 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 59 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 59 |
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 PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 59 | 1 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
_lowerCamelCase = TypeVar('T')
class UpperCamelCase_ ( Generic[T] ):
def __init__( self :Tuple , __A :list[T] , __A :Callable[[T, ... | 59 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-textcaps... | 59 | 1 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_comm... | 59 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCamelCase_ ( unittest.TestCase ):
def ... | 59 | 1 |
from typing import List
import numpy as np
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: dict ):
SCREAMING_SNAKE_CASE__ = {key: len(UpperCamelCase__ ) for key, value in gen_kwargs.items() if isinstance(UpperCamelCase__ , UpperCamelCase__ )}
if len(set(lists_... | 59 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CONFIG_A... | 59 | 1 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config.json',
# See a... | 59 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_whisper': ['WHISPER_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Whi... | 59 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 1 |
import argparse
import os
import numpy as np
import tensorflow as tf
import torch
from transformers import BertModel
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: BertModel , UpperCamelCase__: str , UpperCamelCase__: str ):
SCREAMING_SNAKE_CASE__ = ... | 59 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 59 | 1 |
import random
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: List[str] , UpperCamelCase__: str , UpperCamelCase__: str ):
SCREAMING_SNAKE_CASE__ = a[left_index]
SCREAMING_SNAKE_CASE__ = left_index + 1
for j in range(left_index + 1 , ... | 59 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase__ )
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = fi... | 59 | 1 |
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessin... | 59 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 59 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_mobilebert': [
'MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mob... | 59 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
lowerCamelCase_ = "timm_backbone"
def __init__( self :Union[str, Any] ... | 59 | 1 |
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 OptionalDependencyNotAvailable()
except Option... | 59 |
from math import pow, sqrt
def SCREAMING_SNAKE_CASE__ ( *UpperCamelCase__: float ):
SCREAMING_SNAKE_CASE__ = len(UpperCamelCase__ ) > 0 and all(value > 0.0 for value in values )
return result
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: ... | 59 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by app... | 59 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'shi-labs/nat-mini-in1k-224': 'https://hugg... | 59 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
_lowerCamelCase = {
'configuration_swiftformer': [
'SWIFTFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'SwiftFormerConfig',
'SwiftFormerOnnxConfig'... | 59 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 | 1 |
_lowerCamelCase = '\n# Installazione di Transformers\n! pip install transformers datasets\n# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e\n# rimuovi la modalità commento al comando seguente.\n# ! pip install git+https://github.com/huggingface/transformers... | 59 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase__ ):
def __init__( self :List[Any] , *__A :Tuple , ... | 59 | 1 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .dataclasses import ... | 59 |
import unittest
from datasets import load_dataset
from transformers.pipelines import pipeline
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_torch, slow
@is_pipeline_test
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
@require_torch
... | 59 | 1 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ ( metaclass=UpperCamelCase__ ):
lowerCamelCase_ = ["note_seq"]
def __init__( self :Any , *__A :Union[str, Any] , **__A :Optional[Any] ) -> Any:
... | 59 |
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_transfo_xl import CORPUS... | 59 | 1 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: int ):
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod() | 59 |
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transformers.utils import logging
... | 59 | 1 |
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
@require_torch
class UpperCamelCase_ ( unittest.TestC... | 59 |
import os
from pathlib import Path
from unittest.mock import patch
import pytest
import zstandard as zstd
from datasets.download.download_config import DownloadConfig
from datasets.utils.file_utils import (
OfflineModeIsEnabled,
cached_path,
fsspec_get,
fsspec_head,
ftp_get,
ftp_head,
... | 59 | 1 |
import argparse
import os
import torch
from transformers.utils import WEIGHTS_NAME
_lowerCamelCase = ['small', 'medium', 'large']
_lowerCamelCase = 'lm_head.decoder.weight'
_lowerCamelCase = 'lm_head.weight'
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: st... | 59 |
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
_lowerCamelCase = logging.getLogger(__name__)
def SCREAMING_SNAKE_CASE__ ( ):
SCREAMING_SNAKE_CASE__ = argparse.ArgumentParser(
description="""Pr... | 59 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'bigcode/gpt_bigcode-santacoder': 'https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json',
}
class UpperCamelCas... | 59 |
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: list[list[float]] ):
SCREAMING_SNAKE_CASE__ = []
for data in source_data:
for i, el in enumerate(UpperCamelCase__ ):
if len(UpperCamelCase__ ) < i + 1:
data_lists.append([] )
data_lists[i].append(fl... | 59 | 1 |
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers import (
AutoConfig,
... | 59 |
import warnings
from functools import wraps
from typing import Callable
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: Callable ):
@wraps(UpperCamelCase__ )
def _inner_fn(*UpperCamelCase__: Dict , **UpperCamelCase__: Any ):
warnings.warn(
(f'... | 59 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
_lowerCamelCase = {'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
_lowerCamelCase ... | 59 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_... | 59 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {'vocab_file': ... | 59 |
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 PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProcessor
from transformers.utils im... | 59 | 1 |
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import AutoTokenizer, BarkProcessor
from transformers.testing_utils import require_torch, slow
@require_torch
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self ... | 59 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/pix2struct-textcaps-base': (
'https://huggingface.co/google/pix2struct-textcaps... | 59 | 1 |
import math
import os
import unittest
from transformers import MegatronBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import Confi... | 59 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class UpperCamelCase_ ( unittest.TestCase ):
def ... | 59 | 1 |
_lowerCamelCase = {
'Pillow': 'Pillow<10.0.0',
'accelerate': 'accelerate>=0.20.3',
'av': 'av==9.2.0',
'beautifulsoup4': 'beautifulsoup4',
'black': 'black~=23.1',
'codecarbon': 'codecarbon==1.2.0',
'cookiecutter': 'cookiecutter==1.7.3',
'dataclasses': 'dataclasses',
'dat... | 59 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCamelCase = {
'configuration_layoutlmv3': [
'LAYOUTLMV3_PRETRAINED_CONFIG_A... | 59 | 1 |
from __future__ import annotations
from math import pi
def SCREAMING_SNAKE_CASE__ ( UpperCamelCase__: float , UpperCamelCase__: float , UpperCamelCase__: float ):
if (inductance, frequency, reactance).count(0 ) != 1:
raise ValueError("""One and onl... | 59 |
import inspect
import unittest
class UpperCamelCase_ ( unittest.TestCase ):
def _snake_case ( self :str ) -> Union[str, Any]:
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
assert... | 59 | 1 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
from dataset... | 59 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutpu... | 59 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {'configuration_fnet': ['FNET_PRETRAINED_CONFIG_ARCHIVE_MAP', 'FNetConfig']}
try:
if no... | 59 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 59 | 1 |
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