code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
class __snake_case :
def __init__( self , snake_case__ , snake_case__=None , snake_case__=None ) -> str:
'''simple docstring'''
UpperCAmelCase : Tuple =data
UpperCAmelCase : Union[str, Any] =previous
UpperCAmelCa... | 78 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDepende... | 78 | 1 |
import argparse
import os
import jax as jnp
import numpy as onp
import torch
import torch.nn as nn
from music_spectrogram_diffusion import inference
from tax import checkpoints
from diffusers import DDPMScheduler, OnnxRuntimeModel, SpectrogramDiffusionPipeline
from diffusers.pipelines.spectrogram_diffusion import Spe... | 78 | from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__snake_case = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
'''... | 78 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transformers.utils import I... | 78 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/efficient... | 78 | 1 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : List[str] = (DDIMParallelScheduler,)
__lowerCamelCase : Dict = (("""eta""", 0.0), ("""num_infe... | 78 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI_... | 78 | 1 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 78 | import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_tf,
... | 78 | 1 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils imp... | 78 | import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 78 | 1 |
from ... import PretrainedConfig
__snake_case = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : Dict = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
_... | 78 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 78 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__snake_case = {
'''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMv2Con... | 78 | import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diff... | 78 | 1 |
def lowerCAmelCase_ ( __lowerCAmelCase )-> int:
'''simple docstring'''
UpperCAmelCase : Tuple =abs(__lowerCAmelCase )
UpperCAmelCase : List[Any] =0
while n > 0:
res += n % 10
n //= 10
return res
def low... | 78 | import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__snake_case ... | 78 | 1 |
import numpy
# List of input, output pairs
__snake_case = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
__snake_case = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_50))
__snake_case = [2, 4, 1, 5]
__snake_case = le... | 78 | from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=lowerCamelCase__ ):
__lowerCamelCase : Dict = ["""torch"""]
def __init__( self , *snake_case__ , **snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
... | 78 | 1 |
__snake_case = '''Tobias Carryer'''
from time import time
class __snake_case :
def __init__( self , snake_case__ , snake_case__ , snake_case__ , snake_case__=int(time() ) ) -> List[Any]: # noqa: B008
'''simple docstring'''
Upper... | 78 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],... | 78 | 1 |
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 78 | import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __snake_case ( lowerCamelCase__ ):
@require_torch
def UpperCAmelCase__ ( self ) -> List[str]:
'... | 78 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''facebook/dpr-ctx_encoder-single-nq-base''': (
'''https://huggingface.co/facebook/dpr-ctx_encoder-single-nq-base/resolve/main/config.json'''
... | 78 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https://h... | 78 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diff... | 78 | import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : Union[str, Any] = ["""image_processor""", """tokenizer"""]
__lowerCamelCase : Union[str, Any]... | 78 | 1 |
import inspect
import unittest
from transformers import BitConfig
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_backbone_common import BackboneTesterMixin
from ...test_config... | 78 | from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase_ ( __lowerCAmelCase = "isbn/0140328726" )-> dict:
'''simple docstring'''
UpperCAmelCase : Tuple =olid.strip().strip('''/''' ) # Remove leadi... | 78 | 1 |
import string
def lowerCAmelCase_ ( __lowerCAmelCase )-> str:
'''simple docstring'''
UpperCAmelCase : List[Any] =''''''
for i in sequence:
UpperCAmelCase : str =ord(__lowerCAmelCase )
if 65 <= extract <= 90:
... | 78 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 78 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__snake_case = {
'''configuration_biogpt''': ['''BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''BioGptConfig'''],
'''tokenization_biogpt''': ['''BioGptTokenize... | 78 | from __future__ import annotations
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> list[list[int]]:
'''simple docstring'''
UpperCAmelCase : list[list[int]] =[]
create_all_state(1 , __lowerCAmelCase , __lowerCAmelCase , ... | 78 | 1 |
from math import factorial
class __snake_case :
def __init__( self , snake_case__ , snake_case__ ) -> List[str]:
'''simple docstring'''
UpperCAmelCase : str =real
if isinstance(snake_case__ , snake_case__ ):
Upper... | 78 | import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_ut... | 78 | 1 |
from sklearn.metrics import fa_score
import datasets
__snake_case = '''
The F1 score is the harmonic mean of the precision and recall. It can be computed with the equation:
F1 = 2 * (precision * recall) / (precision + recall)
'''
__snake_case = '''
Args:
predictions (`list` of `int`): Predi... | 78 | import sys
def lowerCAmelCase_ ( __lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : Optional[Any] =len(__lowerCAmelCase )
UpperCAmelCase : List[str] =[[0 for x in range(__lowerCAmelCase )] for x in range(__lowerCAmelCase )]
... | 78 | 1 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokenizers
__snake_... | 78 | import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {'''vocab_file''': '''vocab.json'''}
__snake_case = {
'''vocab_file''': {
... | 78 | 1 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_early_s... | 78 | import colorsys
from PIL import Image # type: ignore
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> float:
'''simple docstring'''
UpperCAmelCase : Any =x
UpperCAmelCase : List[str] =y
for ... | 78 | 1 |
import unittest
from transformers import MPNetConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pipeline_mixin im... | 78 | class __snake_case :
def __init__( self , snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase : Tuple =n
UpperCAmelCase : Any =[None] * self.n
UpperCAmelCase : Tuple =0 # index of the first e... | 78 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''facebook/data2vec-text-base''': '''https://huggingfac... | 78 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDepende... | 78 | 1 |
def lowerCAmelCase_ ( __lowerCAmelCase )-> int:
'''simple docstring'''
assert column_title.isupper()
UpperCAmelCase : str =0
UpperCAmelCase : Optional[Any] =len(__lowerCAmelCase ) - 1
UpperCAmelCase : List[Any] =0
... | 78 | from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__snake_case = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
'''... | 78 | 1 |
def lowerCAmelCase_ ( __lowerCAmelCase )-> list:
'''simple docstring'''
if len(__lowerCAmelCase ) < 2:
return collection
def circle_sort_util(__lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase ) -> bool:
UpperCAmelCase : Tuple ... | 78 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/efficient... | 78 | 1 |
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
__snake_case = [
'''kernels/rwkv/wkv_cuda.cu''',
'''kernels/rwkv/wkv_op.cpp''',
'''kernels/deformable_detr/ms_deform_attn.h''',
'''kernels/deformable_detr/cuda/ms_deform_im2col_cuda.cuh''',... | 78 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI_... | 78 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require_torch
... | 78 | import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_tf,
... | 78 | 1 |
def lowerCAmelCase_ ( __lowerCAmelCase )-> bool:
'''simple docstring'''
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 78 | import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 78 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_big_bird import ... | 78 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 78 | 1 |
def lowerCAmelCase_ ( )-> int:
'''simple docstring'''
return [
a * b * (10_00 - a - b)
for a in range(1 , 9_99 )
for b in range(__lowerCAmelCase , 9_99 )
if (a * a + b * b == (10_00 - a - b) ** 2)
][0]
if __name__ == "__ma... | 78 | import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diff... | 78 | 1 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , **__lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : List[str] =AutoConfig.from_pretraine... | 78 | import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__snake_case ... | 78 | 1 |
from typing import Optional
from urllib.parse import quote
import huggingface_hub as hfh
from packaging import version
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = None )-> str:
'''simple docstring'''
if version.parse(hfh.__version... | 78 | from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=lowerCamelCase__ ):
__lowerCamelCase : Dict = ["""torch"""]
def __init__( self , *snake_case__ , **snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
... | 78 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __snake_case ( lowerCamelCase__ )... | 78 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],... | 78 | 1 |
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> int:
'''simple docstring'''
while a != 0:
UpperCAmelCase , UpperCAmelCase : List[Any] =b % a, a
return b
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelC... | 78 | import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __snake_case ( lowerCamelCase__ ):
@require_torch
def UpperCAmelCase__ ( self ) -> List[str]:
'... | 78 | 1 |
from __future__ import annotations
import pandas as pd
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> list[int]:
'''simple docstring'''
UpperCAmelCase : Optional[Any] =[0] * no_of_processes
UpperCAmelCase ... | 78 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https://h... | 78 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimens... | 78 | import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : Union[str, Any] = ["""image_processor""", """tokenizer"""]
__lowerCamelCase : Union[str, Any]... | 78 | 1 |
def lowerCAmelCase_ ( __lowerCAmelCase=2_81_23 )-> str:
'''simple docstring'''
UpperCAmelCase : Optional[int] =[1] * (limit + 1)
for i in range(2 , int(limit**0.5 ) + 1 ):
sum_divs[i * i] += i
for k in range(i + 1 , limit /... | 78 | from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase_ ( __lowerCAmelCase = "isbn/0140328726" )-> dict:
'''simple docstring'''
UpperCAmelCase : Tuple =olid.strip().strip('''/''' ) # Remove leadi... | 78 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
__snake_case = {
'''albert-base-v1''': '''https://huggingface.co/albert-base-v1/resolve/main/config.json''',
'''albert-large-v1''': '''https://huggingfac... | 78 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 78 | 1 |
__snake_case = tuple[float, float, float]
__snake_case = tuple[float, float, float]
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> Vectorad:
'''simple docstring'''
UpperCAmelCase : List[Any] =end_pointa[0] - end_pointa... | 350 | from __future__ import annotations
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> list[list[int]]:
'''simple docstring'''
UpperCAmelCase : list[list[int]] =[]
create_all_state(1 , __lowerCAmelCase , __lowerCAmelCase , ... | 78 | 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 = logging.get_logger(__name__)
__snake_case = '''▁'''
__snake_case ... | 351 | import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_ut... | 78 | 0 |
from ..models.auto import AutoModelForSeqaSeqLM, AutoTokenizer
from .base import PipelineTool
class __snake_case ( _UpperCAmelCase ):
__lowerCamelCase : str = "philschmid/bart-large-cnn-samsum"
__lowerCamelCase : Dict = (
"This is a tool that summarizes an ... | 352 | import sys
def lowerCAmelCase_ ( __lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : Optional[Any] =len(__lowerCAmelCase )
UpperCAmelCase : List[str] =[[0 for x in range(__lowerCAmelCase )] for x in range(__lowerCAmelCase )]
... | 78 | 0 |
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 BnbQua... | 353 | import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {'''vocab_file''': '''vocab.json'''}
__snake_case = {
'''vocab_file''': {
... | 78 | 0 |
from collections import Counter
from timeit import timeit
def lowerCAmelCase_ ( __lowerCAmelCase = "" , )-> bool:
'''simple docstring'''
return sum(c % 2 for c in Counter(input_str.replace(''' ''' , '''''' ).lower() ).values() ) < 2
def lowerCAmelCas... | 354 | import colorsys
from PIL import Image # type: ignore
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> float:
'''simple docstring'''
UpperCAmelCase : Any =x
UpperCAmelCase : List[str] =y
for ... | 78 | 0 |
import argparse
import math
import os
import torch
from neural_compressor.utils.pytorch import load
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, StableDiffusionPipeline, UNetaDConditionModel
def lowerCAmelCase_ ( )-> List[str]:
... | 355 | class __snake_case :
def __init__( self , snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase : Tuple =n
UpperCAmelCase : Any =[None] * self.n
UpperCAmelCase : Tuple =0 # index of the first e... | 78 | 0 |
def lowerCAmelCase_ ( __lowerCAmelCase )-> bool:
'''simple docstring'''
return credit_card_number.startswith(('''34''', '''35''', '''37''', '''4''', '''5''', '''6''') )
def lowerCAmelCase_ ( __lowerCAmelCase )-> bool:
'''simple docstring'''
Upp... | 356 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDepende... | 78 | 0 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
if is_torc... | 357 | from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__snake_case = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
'''... | 78 | 0 |
__snake_case = 6_55_21
def lowerCAmelCase_ ( __lowerCAmelCase )-> Optional[int]:
'''simple docstring'''
UpperCAmelCase : Optional[Any] =1
UpperCAmelCase : List[Any] =0
for plain_chr in plain_text:
UpperCAmelCase ... | 358 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/efficient... | 78 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
logging.... | 359 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI_... | 78 | 0 |
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> Dict:
'''simple docstring'''
while second != 0:
UpperCAmelCase : Union[str, Any] =first & second
first ^= second
UpperCAmelCase : Tuple =c << 1
... | 360 | import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_tf,
... | 78 | 0 |
from __future__ import annotations
import os
from collections.abc import Mapping
__snake_case = tuple[int, int]
class __snake_case :
def __init__( self , snake_case__ , snake_case__ ) -> Optional[Any]:
'''simple docstring'''
UpperCAmelCase ... | 361 | import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 78 | 0 |
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : Optional[... | 362 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 78 | 0 |
import warnings
from .state import AcceleratorState, GradientState
warnings.filterwarnings('''ignore''', category=UserWarning, module='''torch.optim.lr_scheduler''')
class __snake_case :
def __init__( self , snake_case__ , snake_case__ , snake_case__ = True , snake... | 363 | import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diff... | 78 | 0 |
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_vae_attention_paths,
renew_v... | 364 | import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__snake_case ... | 78 | 0 |
def lowerCAmelCase_ ( __lowerCAmelCase = 1_00_00_00 )-> int:
UpperCAmelCase : List[Any] =set(range(3 , __a , 2 ) )
primes.add(2 )
for p in range(3 , __a , 2 ):
if p not in primes:
continue
primes.diffe... | 365 | from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=lowerCamelCase__ ):
__lowerCamelCase : Dict = ["""torch"""]
def __init__( self , *snake_case__ , **snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
... | 78 | 0 |
"""simple docstring"""
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
__snake_case = version.parse(importlib_metadata.version('''nltk'''))
if NLTK_VERSION >= version.Version('''3.6.4'''):
from nltk import word_toke... | 366 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],... | 78 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__snake_case = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConfig''', '''... | 367 | import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __snake_case ( lowerCamelCase__ ):
@require_torch
def UpperCAmelCase__ ( self ) -> List[str]:
'... | 78 | 0 |
import sys
__snake_case = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'668966489504452445231617318564030987111217223831... | 368 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https://h... | 78 | 0 |
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils import is_torch_available
fr... | 369 | import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : Union[str, Any] = ["""image_processor""", """tokenizer"""]
__lowerCamelCase : Union[str, Any]... | 78 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> Dict: # noqa: E741
'''simple docstring'''
while r - l > 1:
UpperCAmelCase : Dict =(l + r) // 2
... | 370 | from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase_ ( __lowerCAmelCase = "isbn/0140328726" )-> dict:
'''simple docstring'''
UpperCAmelCase : Tuple =olid.strip().strip('''/''' ) # Remove leadi... | 78 | 0 |
import argparse
from pathlib import Path
from transformers import AutoConfig, AutoTokenizer, RagConfig, RagSequenceForGeneration, RagTokenForGeneration
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase = N... | 371 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 78 | 0 |
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : Tuple =len(__a )
UpperCAmelCase : int =[]
for i in range(len(__a ) - pat_len + 1 ):
UpperCAmelCase : Opt... | 350 | from __future__ import annotations
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> list[list[int]]:
'''simple docstring'''
UpperCAmelCase : list[list[int]] =[]
create_all_state(1 , __lowerCAmelCase , __lowerCAmelCase , ... | 78 | 0 |
from __future__ import annotations
from cmath import sqrt
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> Optional[Any]:
'''simple docstring'''
if a == 0:
raise ValueError('''Coefficient \'a\' must not be zero.''' )
... | 351 | import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_ut... | 78 | 0 |
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddings
@maybe_allow_in_graph
clas... | 352 | import sys
def lowerCAmelCase_ ( __lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : Optional[Any] =len(__lowerCAmelCase )
UpperCAmelCase : List[str] =[[0 for x in range(__lowerCAmelCase )] for x in range(__lowerCAmelCase )]
... | 78 | 0 |
import re
import string
import numpy as np
import datasets
__snake_case = """
Returns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.
"""
__snake_case = """
Args:
predictions: List of predicted t... | 353 | import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {'''vocab_file''': '''vocab.json'''}
__snake_case = {
'''vocab_file''': {
... | 78 | 0 |
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 ConfigT... | 354 | import colorsys
from PIL import Image # type: ignore
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> float:
'''simple docstring'''
UpperCAmelCase : Any =x
UpperCAmelCase : List[str] =y
for ... | 78 | 0 |
import math
def lowerCAmelCase_ ( __lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : int =0
UpperCAmelCase : Dict =0
while num > 0:
UpperCAmelCase : List[Any] =num % 8
UpperCAmelCase ... | 355 | class __snake_case :
def __init__( self , snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase : Tuple =n
UpperCAmelCase : Any =[None] * self.n
UpperCAmelCase : Tuple =0 # index of the first e... | 78 | 0 |
import warnings
from functools import wraps
from typing import Callable
def lowerCAmelCase_ ( __lowerCAmelCase )-> Callable:
'''simple docstring'''
@wraps(lowercase__ )
def _inner_fn(*__lowerCAmelCase , **__lowerCAmelCase ):
warnings.warn(
... | 356 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDepende... | 78 | 0 |
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
__snake_case = 4
__snake_case = 3
class __snake_case ( __lowerCamelCase ):
p... | 357 | from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__snake_case = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
'''... | 78 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__snake_case = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''tokenization_xlm''': ['''XLMTokenizer'... | 358 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/efficient... | 78 | 0 |
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torch
from ..state import AcceleratorState, PartialState
from ... | 359 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI_... | 78 | 0 |
from __future__ import annotations
__snake_case = []
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> bool:
'''simple docstring'''
for i in range(len(lowerCAmelCase__ ) ):
if board[row][i] == 1:
... | 360 | import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_tf,
... | 78 | 0 |
import pytest
import datasets
# Import fixture modules as plugins
__snake_case = ['tests.fixtures.files', 'tests.fixtures.hub', 'tests.fixtures.fsspec']
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> List[str]:
'''simple docstring'''
for ite... | 361 | import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 78 | 0 |
import qiskit
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> qiskit.result.counts.Counts:
'''simple docstring'''
UpperCAmelCase : Any =qiskit.Aer.get_backend('''aer_simulator''' )
# Create a Quantum Circuit acting on the q register
... | 362 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 78 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFI... | 363 | import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diff... | 78 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_bert''': ['''BERT_PRETRAINE... | 364 | import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__snake_case ... | 78 | 0 |
from .imports import is_rich_available
if is_rich_available():
from rich.traceback import install
install(show_locals=False)
else:
raise ModuleNotFoundError('''To use the rich extension, install rich with `pip install rich`''')
| 365 | from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=lowerCamelCase__ ):
__lowerCamelCase : Dict = ["""torch"""]
def __init__( self , *snake_case__ , **snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
... | 78 | 0 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class __snake_case ( unittest.TestCase , lowerCamelCase_ ):
def UpperCAmelCase__ ( self ) -> Any:
'''simple docstring'''
UpperC... | 366 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],... | 78 | 0 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, id... | 367 | import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __snake_case ( lowerCamelCase__ ):
@require_torch
def UpperCAmelCase__ ( self ) -> List[str]:
'... | 78 | 0 |
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> int:
'''simple docstring'''
return 1 if input_a == input_a else 0
def lowerCAmelCase_ ( )-> None:
'''simple docstring'''
assert xnor_gate(0 , 0 ) == 1
assert xnor_... | 368 | from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''RWKV/rwkv-4-169m-pile''': '''https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json''',
'''RWKV/rwkv-4-430m-pile''': '''https://h... | 78 | 0 |
from typing import List
import numpy as np
def lowerCAmelCase_ ( __lowerCAmelCase )-> int:
'''simple docstring'''
UpperCAmelCase : Any ={key: len(_snake_case ) for key, value in gen_kwargs.items() if isinstance(_snake_case , _snake_case )}
if len(se... | 369 | import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __snake_case ( lowerCamelCase__ ):
__lowerCamelCase : Union[str, Any] = ["""image_processor""", """tokenizer"""]
__lowerCamelCase : Union[str, Any]... | 78 | 0 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def lowerCAmelCase_ ( __lowerCAmelCase )-> str:
... | 370 | from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def lowerCAmelCase_ ( __lowerCAmelCase = "isbn/0140328726" )-> dict:
'''simple docstring'''
UpperCAmelCase : Tuple =olid.strip().strip('''/''' ) # Remove leadi... | 78 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def lowerCAmelCase_ ( __lowerCAmelCase = True , *__lowerCAmelCase , **__lowerCAmelCase )-> Any:
'''simple docstring'''... | 371 | from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...ut... | 78 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_tf, slo... | 350 | from __future__ import annotations
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> list[list[int]]:
'''simple docstring'''
UpperCAmelCase : list[list[int]] =[]
create_all_state(1 , __lowerCAmelCase , __lowerCAmelCase , ... | 78 | 0 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class __snake_case ( __UpperCamelCase , unittest.TestCa... | 351 | import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import huggingface_hub.utils as hf_hub_ut... | 78 | 0 |
from manim import *
class __snake_case ( lowerCAmelCase_ ):
def UpperCAmelCase__ ( self ) -> Optional[Any]:
'''simple docstring'''
UpperCAmelCase : List[Any] =Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase : List[str] ... | 352 | import sys
def lowerCAmelCase_ ( __lowerCAmelCase )-> Any:
'''simple docstring'''
UpperCAmelCase : Optional[Any] =len(__lowerCAmelCase )
UpperCAmelCase : List[str] =[[0 for x in range(__lowerCAmelCase )] for x in range(__lowerCAmelCase )]
... | 78 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''huggingface/time-series-transformer-tourism-monthly''': (
'''https://huggingface.co/huggingface/ti... | 353 | import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {'''vocab_file''': '''vocab.json'''}
__snake_case = {
'''vocab_file''': {
... | 78 | 0 |
class __snake_case :
def __init__( self , snake_case__ ) -> Dict:
'''simple docstring'''
UpperCAmelCase : List[Any] =val
UpperCAmelCase : List[str] =None
UpperCAmelCase : Tuple =None
def UpperCAmelCas... | 354 | import colorsys
from PIL import Image # type: ignore
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase )-> float:
'''simple docstring'''
UpperCAmelCase : Any =x
UpperCAmelCase : List[str] =y
for ... | 78 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'microsoft/markuplm-base': 'https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json',
'microsoft/markuplm-large': 'https://huggingf... | 355 | class __snake_case :
def __init__( self , snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase : Tuple =n
UpperCAmelCase : Any =[None] * self.n
UpperCAmelCase : Tuple =0 # index of the first e... | 78 | 0 |
from dataclasses import dataclass
from typing import Optional
import numpy as np
import torch
import torch.nn as nn
from ..utils import BaseOutput, is_torch_version, randn_tensor
from .attention_processor import SpatialNorm
from .unet_ad_blocks import UNetMidBlockaD, get_down_block, get_up_block
@dataclass
cla... | 356 | from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {
'''configuration_swinv2''': ['''SWINV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''Swinv2Config'''],
}
try:
if not is_torch_available():
raise OptionalDepende... | 78 | 0 |
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase )-> Dict:
'''simple docstring'''
UpperCAmelCase : int =len(__lowerCAmelCase )
UpperCAmelCase : int =len(__lowerCAmelCase )
UpperCAmelCase : int =(
firs... | 357 | from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
__snake_case = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
'''... | 78 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 358 | from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/efficient... | 78 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipelin... | 359 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
OPENAI_CLIP_MEAN,
OPENAI_... | 78 | 0 |
from pathlib import Path
import torch
from ...utils import is_npu_available, is_xpu_available
from .config_args import ClusterConfig, default_json_config_file
from .config_utils import SubcommandHelpFormatter
__snake_case = '''Create a default config file for Accelerate with only a few flags set.'''
... | 360 | import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_tf,
... | 78 | 0 |
import os
import sys
from contextlib import contextmanager
# Windows only
if os.name == "nt":
import ctypes
import msvcrt # noqa
class __snake_case ( ctypes.Structure ):
# _fields is a specific attr expected by ctypes
__lowerCamelCase : str = [('... | 361 | import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bart.t... | 78 | 0 |
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __s... | 362 | import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
from diffusers.pipeline... | 78 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__snake_case = {'configuration_deit': ['DEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DeiTConfig', 'DeiTOnnxConfig']}
try:
if no... | 363 | import gc
import random
import unittest
import numpy as np
import torch
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torch_device
from diff... | 78 | 0 |
from itertools import permutations
def lowerCAmelCase_ ( __lowerCAmelCase )-> bool:
'''simple docstring'''
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
... | 364 | import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
__snake_case ... | 78 | 0 |
import operator as op
__snake_case = '''scaler.pt'''
__snake_case = '''pytorch_model'''
__snake_case = '''random_states'''
__snake_case = '''optimizer'''
__snake_case = '''scheduler'''
__snake_case = '''pytorch_model.bin'''
__snake_case = '''pytorc... | 365 | from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=lowerCamelCase__ ):
__lowerCamelCase : Dict = ["""torch"""]
def __init__( self , *snake_case__ , **snake_case__ ) -> Union[str, Any]:
'''simple docstring'''
... | 78 | 0 |
"""simple docstring"""
def lowerCAmelCase_ ( __lowerCAmelCase )-> float:
'''simple docstring'''
if edge <= 0 or not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise ValueError('''Length must be a positive.''' )
return 3 * ((25 + 10 * (5 ... | 366 | from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case = {
'''configuration_llama''': ['''LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LlamaConfig'''],... | 78 | 0 |
import unittest
import numpy as np
from transformers import DistilBertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from ... | 367 | import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __snake_case ( lowerCamelCase__ ):
@require_torch
def UpperCAmelCase__ ( self ) -> List[str]:
'... | 78 | 0 |
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