code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _A ( lowerCAmelCase_ : ... | 61 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__... | 58 | 0 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class SCREAMING_SNAKE_CASE ( lowerC... | 62 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
... | 58 | 0 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_co... | 63 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 | 0 |
import string
from math import logaa
def A__ ( snake_case_ : str , snake_case_ : str ):
SCREAMING_SNAKE_CASE__: Optional[int]= document.translate(
str.maketrans('''''' , '''''' , string.punctuation ) ).replace('''\n''' , '''''' )
SCREAMI... | 64 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionMode... | 58 | 0 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_v... | 65 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : str , __UpperCamelCase : Any ):
'''simple docstring'''
... | 58 | 0 |
def __magic_name__ ( SCREAMING_SNAKE_CASE ) -> int:
_lowercase : Optional[int] = abs(SCREAMING_SNAKE_CASE )
_lowercase : Dict = 0
while n > 0:
res += n % 10
n //= 10
return res
def __magic_name__... | 66 |
"""simple docstring"""
__lowerCAmelCase : Tuple = '''
# 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.
# ... | 58 | 0 |
from manim import *
class A_ ( UpperCAmelCase ):
"""simple docstring"""
def __UpperCAmelCase ( self : str ) -> Union[str, Any]:
_lowercase = Rectangle(height=0.5 ,width=0.5 )
_lower... | 67 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
__lowerCAmelCase : Tuple = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title ... | 58 | 0 |
def lowercase__ ( A_: int = 1 , A_: int = 1000 ) -> int:
"""simple docstring"""
__UpperCAmelCase =1
__UpperCAmelCase =0
for divide_by_number in range(A_ , digit + 1 ):
__UpperCAmelCase =[]
... | 68 |
"""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_inp... | 58 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( _UpperCAmelCase : int , _UpperCAmelCase : float , _UpperCAmelCase : float ) -> float:
return round(float(moles / volume ) * nfactor )
def __UpperCAmelCase ( _UpperCAmelCase : float , _UpperCAmelCase ... | 69 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : int = TypeVar('''KT''')
__lowerCAmelCase : Union[str, Any] = TypeVar('''VT''')
class _lowerC... | 58 | 0 |
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_availa... | 70 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[Any] = '''examples/'''
__lowerCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]... | 58 | 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 .utils import loggin... | 71 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0... | 58 | 0 |
'''simple docstring'''
class __magic_name__ :
def __init__( self , snake_case_ , snake_case_ ):
lowercase =name
lowercase =val
def __str__( self ):
return f'{self.__class__.__name__}({self.name}, {self.val})'
def __lt__( self , snake_ca... | 72 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
... | 58 | 0 |
import numpy as np
def lowerCamelCase__ (_UpperCAmelCase , _UpperCAmelCase , _UpperCAmelCase = 1e-12 , _UpperCAmelCase = 100 , ):
assert np.shape(_UpperCAmelCase)[0] == np.shape(_UpperCAmelCase)[1]
# Ensure proper dimensionality.
assert np.shape(_UpperC... | 73 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_STAR... | 58 | 0 |
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def a__ ( snake_case , snake_case , snake_case ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE : Optional[Any] = {
'''en''': '''Machine learning is great, isn\'t it?''',
... | 74 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''... | 58 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
UpperCamelCase__ = logging.get_logger(__name__)
class lowerCamelCase_ ( __a ):
def __init__( self : int , *_... | 75 |
"""simple docstring"""
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
__lowerCAmelCase : Tuple ... | 58 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main/config.json',
}
clas... | 76 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_t... | 58 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
A = {"""configuration_mmbt""": ["""MMBTConfig"""]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 77 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : list[list[int]] , __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : list[int] ):
'''simple docstring'''
if graph[path[cur... | 58 | 0 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_tr... | 78 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput... | 58 | 0 |
def _lowerCamelCase ( __lowerCamelCase , __lowerCamelCase , __lowerCamelCase , __lowerCamelCase ) -> str:
'''simple docstring'''
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
UpperCAmelCase__... | 79 |
"""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/licen... | 58 | 0 |
from __future__ import annotations
import numpy as np
def snake_case ( lowerCamelCase ):
'''simple docstring'''
return np.maximum(0 , lowerCamelCase )
if __name__ == "__main__":
print(np.array(relu([-1, 0, 5]))) # --> [0, 0, 5]
| 80 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__low... | 58 | 0 |
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_... | 81 |
"""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
__lowerCAmelCase : ... | 58 | 0 |
"""simple docstring"""
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
lowerCamelCase = re.compile(r"""\b(a|an|the)\b""", re.UNICODE)
lowerCamelCase = None
def a__ ( ):
UpperCAmelCase_ = ... | 82 |
"""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 _lowerCAmelCa... | 58 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def snake_case_ ( A_ : Optional[int] ):
... | 83 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__... | 58 | 0 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,
... | 84 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
... | 58 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE__ : List[Any] = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : Optional[Any] = {
"ut/deta": "https://huggin... | 85 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 | 0 |
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, ViTModel
from transformers.utils import l... | 86 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionMode... | 58 | 0 |
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> list:
"""simple docstring"""
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
A__ = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 87 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : str , __UpperCamelCase : Any ):
'''simple docstring'''
... | 58 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDeco... | 88 |
"""simple docstring"""
__lowerCAmelCase : Tuple = '''
# 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.
# ... | 58 | 0 |
import math
import time
from typing import Dict, List, Optional
from torch.utils.data import Dataset
from transformers import SeqaSeqTrainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_mod... | 89 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
__lowerCAmelCase : Tuple = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title ... | 58 | 0 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
__UpperCAmelCase = logging.get_logger(__name__)
__UpperCAmelCase... | 90 |
"""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_inp... | 58 | 0 |
"""simple docstring"""
from math import sqrt
def _snake_case ( snake_case__ : int ):
A = 0
for i in range(1 , int(sqrt(snake_case__ ) + 1 ) ):
if n % i == 0 and i != sqrt(snake_case__ ):
total += i + n // i
elif i == sqrt(snake_case__ ):
total += i
return total - n
... | 91 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : int = TypeVar('''KT''')
__lowerCAmelCase : Union[str, Any] = TypeVar('''VT''')
class _lowerC... | 58 | 0 |
'''simple docstring'''
from string import ascii_lowercase, ascii_uppercase
def _lowerCAmelCase ( __magic_name__ : str ) -> str:
if not sentence:
return ""
lowercase : Tuple =dict(zip(__magic_name__ , __magic_name__ ) )
return lo... | 92 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[Any] = '''examples/'''
__lowerCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]... | 58 | 0 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
__A = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_copies # noqa: E402
... | 93 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0... | 58 | 0 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokeniza... | 94 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
... | 58 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils im... | 95 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_STAR... | 58 | 0 |
"""simple docstring"""
from __future__ import annotations
def a ( __UpperCAmelCase : list[float] ) -> bool:
if len(__UpperCAmelCase ) < 2:
raise ValueError("""Monogons and Digons are not polygons in the Euclidean space""" )
if any(i... | 96 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''... | 58 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEA... | 97 |
"""simple docstring"""
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
__lowerCAmelCase : Tuple ... | 58 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase__ : Dict = {
'facebook/vit-mae-base': 'https://huggingface.co/facebook/vit-mae-base/resolve/main/config.j... | 98 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_t... | 58 | 0 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("""repo_id""" , ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path""" , ["""filename.csv""", """filename with blanks.csv"""] )
@p... | 99 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : list[list[int]] , __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : list[int] ):
'''simple docstring'''
if graph[path[cur... | 58 | 0 |
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_A : str = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH AH QH""",
"""TS KS 5S 9S AC""",
"""KD 6S... | 100 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput... | 58 | 0 |
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
lowerCAmelCase__ : Op... | 101 |
"""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/licen... | 58 | 0 |
"""simple docstring"""
from itertools import permutations
def UpperCamelCase (SCREAMING_SNAKE_CASE ):
if num[3] % 2 != 0:
return False
if (num[2] + num[3] + num[4]) % 3 != 0:
return False
if num[5] % 5 != 0:
return False
... | 102 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__low... | 58 | 0 |
"""simple docstring"""
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCAmelCase ( __SCREAMING_SNAKE_CASE ):
def __init__( self : ... | 103 |
"""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
__lowerCAmelCase : ... | 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
UpperCamelCase = ... | 104 |
"""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 _lowerCAmelCa... | 58 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Image
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase_ )
class lowerCAmelCase_ ( lowerCamelCase_ ):
__a : str = ... | 105 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__... | 58 | 0 |
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
__snake_case :Dict =logging.get_logger(__name__)
__snake_case :Any ={'vo... | 106 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
... | 58 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFor... | 107 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 | 0 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
@slow
@requ... | 108 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionMode... | 58 | 0 |
'''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
fro... | 109 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : str , __UpperCamelCase : Any ):
'''simple docstring'''
... | 58 | 0 |
"""simple docstring"""
import os
import re
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
UpperCamelCase__ = logging.get_logger(__name__)
UpperCam... | 110 |
"""simple docstring"""
__lowerCAmelCase : Tuple = '''
# 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.
# ... | 58 | 0 |
import datasets
from .evaluate import evaluate
_lowerCAmelCase : Tuple ='''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.062... | 113 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
__lowerCAmelCase : Tuple = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title ... | 58 | 0 |
"""simple docstring"""
import numpy
# List of input, output pairs
__UpperCamelCase : List[str] = (
((5, 2, 3), 1_5),
((6, 5, 9), 2_5),
((1_1, 1_2, 1_3), 4_1),
((1, 1, 1), 8),
((1_1, 1_2, 1_3), 4_1),
)
__UpperCamelCase : List[Any] = (((5_1_5, 2_2, 1_3), 5_5_5), ((6_1, ... | 450 |
"""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_inp... | 58 | 0 |
import os
from pathlib import Path
def lowerCamelCase ( a_ , a_ , a_ ) -> List[str]:
lowerCAmelCase_ = {
"""en""": """Machine learning is great, isn't it?""",
"""ru""": """Машинное обучение - это здорово, не так ли?""",
"""d... | 318 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : int = TypeVar('''KT''')
__lowerCAmelCase : Union[str, Any] = TypeVar('''VT''')
class _lowerC... | 58 | 0 |
"""simple docstring"""
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowerCamelCase__ ( __snake_case, __snake_case, __snake_case, __snake_case, __snake_case, __snake_case, __snake_case, __snake_case, __snake_case, ) -> Optional[Any]:
""... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[Any] = '''examples/'''
__lowerCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]... | 58 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class lowerCAmelCase__ :
"""simple docstring"""
lowerCAmelCase__ = 42
lowerCAmelCase__ = None
lowerCAmelCase__ = None
UpperCAmelCase ... | 627 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0... | 58 | 0 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
def a (self : List[Any] ):
"""simple docstring"""
... | 592 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
... | 58 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ = logging.get_logger(__name__)
lowercase__ = {
'''shi-labs/dinat-m... | 581 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_STAR... | 58 | 0 |
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,
to_channel_dimension_... | 243 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''... | 58 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
UpperCamelCase_ : Optional[int] = {
'''configuration_ernie''': ['''ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Erni... | 115 |
"""simple docstring"""
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
__lowerCAmelCase : Tuple ... | 58 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ = {'''configuration_mmbt''': ['''MMBTConfig''']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
e... | 74 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_t... | 58 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_... | 676 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : list[list[int]] , __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : list[int] ):
'''simple docstring'''
if graph[path[cur... | 58 | 0 |
import argparse
import torch
from transformers import FunnelBaseModel, FunnelConfig, FunnelModel, load_tf_weights_in_funnel
from transformers.utils import logging
logging.set_verbosity_info()
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ):
UpperC... | 113 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput... | 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
_... | 450 |
"""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/licen... | 58 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
lowerCamelCase_ = {'''configuration_dpt''': ['''DPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''DPTConfig''']}... | 318 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__low... | 58 | 0 |
"""simple docstring"""
class _UpperCAmelCase:
def __init__( self , __a , __a , __a) -> Union[str, Any]:
'''simple docstring'''
_UpperCamelCase = None
_UpperCamelCase = None
_UpperCamelCa... | 19 |
"""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
__lowerCAmelCase : ... | 58 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : List[str] = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 627 |
"""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 _lowerCAmelCa... | 58 | 0 |
def lowerCamelCase__ ( snake_case_ : list[list[int]] , snake_case_ : int , snake_case_ : int , snake_case_ : list[int] ) -> Dict:
if graph[path[curr_ind - 1]][next_ver] == 0:
return False
# 2. Validate that next vertex is no... | 592 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__... | 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 PretrainedC... | 581 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
... | 58 | 0 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test... | 243 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 | 0 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_imag... | 115 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionMode... | 58 | 0 |
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_ = {
'''junnyu/roformer_chinese_small''': '''https://huggingface.co/junn... | 74 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : str , __UpperCamelCase : Any ):
'''simple docstring'''
... | 58 | 0 |
'''simple docstring'''
class __UpperCamelCase ( SCREAMING_SNAKE_CASE__ ):
pass
class __UpperCamelCase ( SCREAMING_SNAKE_CASE__ ):
pass
class __UpperCamelCase :
def __init__( self ):
"""simple docstring"""
... | 676 |
"""simple docstring"""
__lowerCAmelCase : Tuple = '''
# 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.
# ... | 58 | 0 |
import requests
_lowerCAmelCase : int ='''https://newsapi.org/v1/articles?source=bbc-news&sortBy=top&apiKey='''
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Dict = requests.get(_NEWS_API + bbc_news_api_key ).json()
# each article in the list is a dict
for i, article in ... | 113 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
__lowerCAmelCase : Tuple = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title ... | 58 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
requir... | 450 |
"""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_inp... | 58 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class a_ ( unittest.TestCase , SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def _lowercase ( self ) -> Union[str, Any]:
... | 318 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : int = TypeVar('''KT''')
__lowerCAmelCase : Union[str, Any] = TypeVar('''VT''')
class _lowerC... | 58 | 0 |
"""simple docstring"""
import math
from collections.abc import Iterator
from itertools import takewhile
def lowerCamelCase__ ( __snake_case ) -> Dict:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[Any] = '''examples/'''
__lowerCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]... | 58 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_a... | 627 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0... | 58 | 0 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase__ ( snake_case_ : int , snake_case_ : int , snake_case_ : float = 1 / sqrt(2 ) ) -> List[str]:
__snake_case = tau * frequency / sam... | 592 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
... | 58 | 0 |
"""simple docstring"""
import random
def __magic_name__ ( _lowerCamelCase : int , _lowerCamelCase : float , _lowerCamelCase : bool = False ):
__a : dict = {i: [] for i in range(__UpperCamelCase )}
# if probability is g... | 581 |
"""simple docstring"""
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_STAR... | 58 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_UpperCamelCase = logging.get_logger(__name__)
_UpperCamelCase = {
'''kssteven/ibert-roberta-base''': '''https://hu... | 243 |
"""simple docstring"""
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''... | 58 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=SCREAMING_SNAKE_CASE__ ):
"""simple docstring"""
snake_case = ["torch"]
def __init__( self : List[str] , *_snake_case : List[A... | 115 |
"""simple docstring"""
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
__lowerCAmelCase : Tuple ... | 58 | 0 |
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_tf_available() and not... | 74 |
"""simple docstring"""
from __future__ import absolute_import, division, print_function, unicode_literals
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers import RobertaConfig
from transformers.file_utils import add_start_docstrings, add_start_docstrings_t... | 58 | 0 |
'''simple docstring'''
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a_ ( __snake_case : bytes , __snake_case : int ) -> Dict:
"""simple docstring"""
lowerCamelCase_ =F'''{sampling_rate}'''
... | 676 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : list[list[int]] , __UpperCamelCase : int , __UpperCamelCase : int , __UpperCamelCase : list[int] ):
'''simple docstring'''
if graph[path[cur... | 58 | 0 |
from typing import Union
import fire
import torch
from tqdm import tqdm
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE = "cpu" ,SCREAMING_SNAKE_CASE = None ):
UpperCAmelCase__: str = torch.load(__UpperCamelCase ,map_location=__UpperCamelCase )
for k, v in tqdm(state_dict.items() ... | 113 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput... | 58 | 0 |
"""simple docstring"""
import argparse
import os
import re
__UpperCamelCase : Any = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
__UpperCamelCase : Any = re.compile(R'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
__UpperCamelCase ... | 450 |
"""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/licen... | 58 | 0 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class a_ ( SCREAMING_SNAKE_CASE__ ):
'''simple docstring'''
def __init__( ... | 318 |
"""simple docstring"""
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__low... | 58 | 0 |
"""simple docstring"""
_a = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''-... | 19 |
"""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
__lowerCAmelCase : ... | 58 | 0 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
assert isinstance(__UpperCamelCase , __UpperCamelCase ), F'The input value of [n={number}] is not an integer'
if number == 1:
return 2
elif number < 1:
__SCREAMING_SNAKE_CASE = F'The in... | 627 |
"""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 _lowerCAmelCa... | 58 | 0 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
'''BridgeTower/bridgetower-base''': '''https://huggingface.co/BridgeTower/... | 592 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__lowerCAmelCase : List[Any] = logging.get_logger(__name__)
__... | 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,
... | 581 |
"""simple docstring"""
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
... | 58 | 0 |
def lowerCAmelCase__( lowercase : float , lowercase : float ) -> Dict:
if mass < 0:
raise ValueError("The mass of a body cannot be negative" )
return 0.5 * mass * abs(__UpperCamelCase ) * abs(__UpperCamelCase )
if __name__ == "__main__":
impo... | 243 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if mass < 0:
raise ValueError("""The mass of a body cannot be negative""" )
return 0.5 ... | 58 | 0 |
"""simple docstring"""
import torch
from ..models.speechta import SpeechTaForTextToSpeech, SpeechTaHifiGan, SpeechTaProcessor
from ..utils import is_datasets_available
from .base import PipelineTool
if is_datasets_available():
from datasets import load_dataset
class __lowerCAmelCase ( SCREAMING_... | 115 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionMode... | 58 | 0 |
from __future__ import annotations
import unittest
from transformers import FunnelConfig, is_tf_available
from transformers.testing_utils import require_tf
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor, random_attention_mask
from ...test_... | 74 |
"""simple docstring"""
# Usage:
# ./gen-card-facebook-wmt19.py
import os
from pathlib import Path
def __lowerCAmelCase ( __UpperCamelCase : int , __UpperCamelCase : str , __UpperCamelCase : Any ):
'''simple docstring'''
... | 58 | 0 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
a_ : Tuple = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved ... | 676 |
"""simple docstring"""
__lowerCAmelCase : Tuple = '''
# 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.
# ... | 58 | 0 |
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 _A ( SCREAMING_SNAKE_CASE=None ,SCREAMIN... | 113 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
__lowerCAmelCase : Tuple = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title ... | 58 | 0 |
"""simple docstring"""
from collections import defaultdict
from math import ceil, sqrt
def __SCREAMING_SNAKE_CASE ( A_ = 1_00_00_00 , A_ = 10 ):
lowerCAmelCase__ : defaultdict = defaultdict(__UpperCamelCase )
for outer_width in range(3 , (t_limit // 4) + 2 ):
if ou... | 450 |
"""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_inp... | 58 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase_ = {
'''configuration_bigbird_pegasus''': [
'''BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''BigBirdPegasusConfig''',
'''... | 318 |
"""simple docstring"""
from __future__ import annotations
from random import random
from typing import Generic, TypeVar
__lowerCAmelCase : int = TypeVar('''KT''')
__lowerCAmelCase : Union[str, Any] = TypeVar('''VT''')
class _lowerC... | 58 | 0 |
"""simple docstring"""
import warnings
from functools import wraps
from typing import Callable
def lowerCamelCase__ ( __snake_case ) -> Dict:
"""simple docstring"""
@wraps(__UpperCamelCase )
def _inner_fn(*__snake_case, **__snake_case ... | 19 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
__lowerCAmelCase : Optional[Any] = '''examples/'''
__lowerCAmelCase : Union[str, Any] = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]... | 58 | 0 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""" )
return (bulk_modulus / density) ** 0.5
if _... | 627 |
"""simple docstring"""
def __lowerCAmelCase ( __UpperCamelCase : float , __UpperCamelCase : float ):
'''simple docstring'''
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0... | 58 | 0 |
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_available... | 592 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def __lowerCAmelCase ( __UpperCamelCase : int ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
... | 58 | 0 |
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