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 |
|---|---|---|---|---|
"""simple docstring"""
from __future__ import annotations
import math
import random
from collections.abc import Collection
from typing import overload
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : Dict , UpperCAmelCase__ : Collection... | 682 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 1 |
"""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, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionModel
f... | 682 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 1 |
"""simple docstring"""
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... | 682 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
fro... | 682 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if len(lowerCAmelCase_ ) <= 1:
return [tuple(lowerCAmelCase_ )]
__SCREAMING_SNAKE_CASE = []
def generate(lowerCAmelCase_ , lowerCAmelCase_ ):
if k == 1:
... | 682 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 1 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 1 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mo... | 682 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a__ : Any = datasets.utils.logging.get_logger(__name__)
@dataclass
class... | 682 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mo... | 682 | 1 |
"""simple docstring"""
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
a__ : Tuple ... | 682 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 1 |
"""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 R... | 682 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 682 | 1 |
"""simple docstring"""
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_co... | 682 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 1 |
"""simple docstring"""
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class UpperCamelCase_ ( UpperCamelCase , UpperCamelCase):
"""simple docstr... | 682 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 1 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
if is_torch_available():
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
@require_torch
... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
a__ : Optional[Any] = {
'''google/tapas-base-finetuned-sqa''': (
'''https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json'''
),
'''google/tapas-base-finetuned-wtq''': (
... | 682 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : List[Any] , UpperCAmelCase__ : Optional[Any]=None ) -> Dict:
__SCREAMING_SNAKE_CASE = data
__SCREAMIN... | 682 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import (
BaseOutput,
OptionalDependencyNotAvailable,
is_flax_available,
is_k_diffusion_available,
is_k_diffusion_version,
... | 682 |
"""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,
PixaStructProcessor,
... | 682 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase_ ( metaclass=UpperCamelCase):
"""simple docstring"""
snake_case__ : Any = ["torch", "torchsde"]
def __init__( self : List[str] , *UpperCAmel... | 682 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 682 | 1 |
"""simple docstring"""
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetVaImageProcessor,
loa... | 682 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 1 |
"""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_... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 1 |
"""simple docstring"""
import string
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
__SCREAMING_SNAKE_CASE = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 682 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 1 |
"""simple docstring"""
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from ... | 682 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bart i... | 682 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 1 |
"""simple docstring"""
import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager im... | 682 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 1 |
"""simple docstring"""
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
requi... | 682 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 1 |
"""simple docstring"""
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchv... | 682 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 1 |
"""simple docstring"""
import os
from glob import glob
import imageio
import torch
import torchvision
import wandb
from img_processing import custom_to_pil, loop_post_process, preprocess, preprocess_vqgan
from loaders import load_vqgan
from PIL import Image
from torch import nn
from transformers import CLIP... | 682 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 1 |
"""simple docstring"""
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
a__ : Dict = '''__DUMMY_TRANSFORMERS_USER__'''
a__ : Optional[int] = '''Dummy User'''
a__ ... | 682 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("multiplicative_persistence() only accepts integral values" )
if num < 0:
raise ValueError("multipl... | 682 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from torch.backends.cuda import sdp_kernel
from diffusers import (
CMStochasticIterativeScheduler,
ConsistencyModelPipeline,
UNetaDModel,
)
from diffusers.utils import randn_tensor, slow, torch_device
from diffusers... | 682 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = 0
while len(lowerCAmelCase_ ) > 1:
__SCREAMING_SNAKE_CASE = 0
# Consider two files with minimum cost to be merged
for _ in ... | 682 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mo... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negati... | 682 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 1 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENS... | 682 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 682 | 1 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( UpperCamelCase... | 682 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 1 |
"""simple docstring"""
from ... import PretrainedConfig
a__ : List[str] = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
snake_case__... | 682 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
a__ : Dict = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst ... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common ... | 682 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 1 |
"""simple docstring"""
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
a__ : Dict = collections.namedtuple(... | 682 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 1 |
"""simple docstring"""
from collections import Counter
from timeit import timeit
def UpperCAmelCase__ (lowerCAmelCase_ = "" , ):
'''simple docstring'''
return sum(c % 2 for c in Counter(input_str.replace(" " , "" ).lower() ).values() ) < 2
def UpperCAmelCase__ (lower... | 682 |
"""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,
PixaStructProcessor,
... | 682 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : int , UpperCAmelCase__ : Any , UpperCAmel... | 682 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 682 | 1 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fa... | 682 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ : List[str] = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDe... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
... | 682 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 1 |
"""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 logging
a__... | 682 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from ... | 682 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
while cur > 1:
# Find the maximum number in arr
__SCREAMING_SNAKE_CASE = arr.index(max(arr[0:cur] ) )
... | 682 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if not nums:
return 0
__SCREAMING_SNAKE_CASE = nums[0]
__SCREAMING_SNAKE_CASE = 0
for num in nums[1:]:
__SCREA... | 682 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_con... | 682 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 1 |
"""simple docstring"""
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class UpperCamelCase_ :
"""simple docstring"""
@pro... | 682 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 1 |
"""simple docstring"""
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch("socket.socket" )
@patch("builtins.open" )
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = Mock(... | 682 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 1 |
"""simple docstring"""
import re
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = re.compile(R"^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$" )
if match := re.search(lowerCAmelCase_ , lowerCAmelCase_ ):
return match.string ==... | 682 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(lowerCAmelCase_ , n - 1 , lowerCAmelCase_ ) * a) % mod
... | 682 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ = 10 ):
'''simple docstring'''
if not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ) or n < 0:
raise ValueError("Invalid input" )
__SCREAMING_SNAKE_CASE = 10**n
__SCREAMING_SNAKE_CASE = ... | 682 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mo... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
... | 682 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 682 | 1 |
"""simple docstring"""
# Imports
import numpy as np
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : List[str] , UpperCAmelCase__ : Optional[Any]=None , UpperCAmelCase__ : List[str]=None , UpperCAmelCase__ :... | 682 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 1 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class UpperCamelCase_ ( unittest.TestCase):
"""simple docstring"""
def UpperCAmelCase_ ( self : int ) ->... | 682 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
__SCREAMING_SNAKE_CASE = []
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAK... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImageProcessor... | 682 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 1 |
"""simple docstring"""
import requests
a__ : List[str] = '''''' # <-- Put your OpenWeatherMap appid here!
a__ : str = '''https://api.openweathermap.org/data/2.5/'''
def UpperCAmelCase__ (lowerCAmelCase_ = "Chicago" , lowerCAmelCase_ = APPID ):
'''sim... | 682 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 1 |
"""simple docstring"""
a__ : int = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
a__ : Optional[Any] = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docst... | 682 |
"""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,
PixaStructProcessor,
... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
if days_between_payments <= 0:
raise ValueError("days_between_payments must be > 0" )
if daily_interest... | 682 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase__ ():
'''simple docstring'''
__SCREAMING_SNAKE_CASE = {}
__SCREAMING_SNAKE_CASE = 2
while True:
__SCREAMING_SNAKE_CASE = fa... | 682 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 1 |
"""simple docstring"""
import math
def UpperCAmelCase__ (lowerCAmelCase_ = 100 ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = sum(i * i for i in range(1 , n + 1 ) )
__SCREAMING_SNAKE_CASE = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Tuple ) -> Tuple:
# test for the above condition
self.test()
def ... | 682 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILIm... | 682 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 1 |
"""simple docstring"""
import warnings
from functools import wraps
from typing import Callable
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
@wraps(lowerCAmelCase_ )
def _inner_fn(*lowerCAmelCase_ , **lowerCAmelCase_ ):
warnings.warn(
... | 682 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 1 |
"""simple docstring"""
import logging
import random
import ray
from transformers import RagConfig, RagRetriever, RagTokenizer
from transformers.models.rag.retrieval_rag import CustomHFIndex
a__ : Dict = logging.getLogger(__name__)
class UpperCamelCase_ :
"""simple docstri... | 682 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 1 |
"""simple docstring"""
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if ... | 682 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 1 |
"""simple docstring"""
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MO... | 682 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 1 |
"""simple docstring"""
from math import asin, atan, cos, radians, sin, sqrt, tan
a__ : Dict = 6_37_81_37.0
a__ : Optional[int] = 6_35_67_52.31_42_45
a__ : Optional[int] = 6_3_7_8_1_3_7
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ... | 682 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 1 |
"""simple docstring"""
import math
from collections.abc import Callable
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = xa
__SCREAMING_SNAKE_CASE = xa
while True:
... | 682 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, NystromformerConfig, 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_tens... | 682 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : str = {
'''nielsr/canine-s''': 2_0_4_8,
}
# Uni... | 682 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mo... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 1 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
a__ : List[Any] = logging.get_logger('''transformers.models.speecht5''')
def UpperCAmelCase__ (lowerCAmelCa... | 682 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 682 | 1 |
"""simple docstring"""
from typing import Dict, Optional
import numpy as np
import datasets
a__ : Optional[int] = '''
IoU is the area of overlap between the predicted segmentation and the ground truth divided by the area of union
between the predicted segmentation and the ground truth. F... | 682 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
a__ : Optional[int] = {'''configuration_unispeech''': ['''UNISPEECH_PRETRAINED_CONFIG_A... | 682 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
import math
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negati... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if collection == []:
return []
# get some information about the collection
__SCREAMING_SNAKE_CASE = len(lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = max(lowerC... | 682 | 1 |
"""simple docstring"""
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... | 682 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a__ : Tuple = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization_... | 682 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docs... | 682 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''xlm-... | 682 | 1 |
"""simple docstring"""
a__ : Optional[int] = '''Alexander Joslin'''
import operator as op
from .stack import Stack
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = {"*": op.mul, "/": op.truediv, "+": op.add, "-": op.... | 682 |
"""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,
PixaStructProcessor,
... | 682 | 1 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 682 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 682 | 1 |
"""simple docstring"""
import argparse
import tensorflow as tf
import torch
from transformers import BertConfig, BertForMaskedLM
from transformers.models.bert.modeling_bert import (
BertIntermediate,
BertLayer,
BertOutput,
BertPooler,
BertSelfAttention,
BertSelfOutput,
)
from transfo... | 682 |
"""simple docstring"""
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAtte... | 682 | 1 |
"""simple docstring"""
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transforme... | 682 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
if edge <= 0 or not isinstance(lowerCAmelCase_ , lowerCAmelCase_ ):
raise ValueError("Length must be a positive." )
return 3 * ((25 + 10 * (5 ** (1 / 2))) ** (1 / 2)) * (edge**2)
... | 682 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : List[str] = logging.get_logger(__name__)
a__ : str = {
'''google/realm-cc-news-pretrained-embedder''': (
'''https://huggingface.co/google/realm-cc-ne... | 682 |
"""simple docstring"""
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = r'''
... | 682 | 1 |
"""simple docstring"""
import argparse
import glob
import logging
import os
import time
from argparse import Namespace
import numpy as np
import torch
from lightning_base import BaseTransformer, add_generic_args, generic_train
from torch.utils.data import DataLoader, TensorDataset
from transformers import g... | 682 |
"""simple docstring"""
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.te... | 682 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
a__ : List[Any] = {'''vocab_file''': '''vocab.txt''', '''tokeni... | 682 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Union[str, Any] = logging.get_logger(__name__)
a__ : Optional[int] = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivi... | 682 | 1 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = []
create_all_state(1 , lowerCAmelCase_ , lowerCAmelCase_ , [] , lowerCAmelCase_ )
... | 682 |
"""simple docstring"""
import numpy as np
from transformers import Pipeline
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = np.max(lowerCAmelCase_ , axis=-1 , keepdims=lowerCAmelCase_ )
__SCREAMING_SNAKE_CASE = ... | 682 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
a__ : Any = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 682 |
"""simple docstring"""
import importlib
import os
import sys
# This is required to make the module import works (when the python process is running from the root of the repo)
sys.path.append('''.''')
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_C... | 682 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
f... | 682 |
"""simple docstring"""
# Copyright 2022 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 682 | 1 |
"""simple docstring"""
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
return 1 if input_a == input_a else 0
def UpperCAmelCase__ ():
'''simple docstring'''
assert xnor_gate(0 , 0 ) == 1
assert xnor_gate(0 , 1 ) ... | 682 |
"""simple docstring"""
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
a__ : int = '''
@inproceedings{xu-etal-2016-optimizing,
title = {Optimizing Statistical Machine Translation for Text Simplif... | 682 | 1 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acc... | 682 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import Generatio... | 682 | 1 |
"""simple docstring"""
# Function to print upper half of diamond (pyramid)
def UpperCAmelCase__ (lowerCAmelCase_ ):
'''simple docstring'''
for i in range(0 , lowerCAmelCase_ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(" " , end=""... | 682 |
"""simple docstring"""
import os
def UpperCAmelCase__ ():
'''simple docstring'''
with open(os.path.dirname(lowerCAmelCase_ ) + "/p022_names.txt" ) as file:
__SCREAMING_SNAKE_CASE = str(file.readlines()[0] )
__SCREAMING_SNAKE_CASE = names.replace... | 682 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
a__ : int = logging.get_logger(__name__)
a__ : Union[... | 682 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ , lowerCAmelCase_ ):
... | 682 | 1 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformers i... | 682 |
"""simple docstring"""
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.mo... | 682 | 1 |
"""simple docstring"""
a__ : str = tuple[float, float, float]
a__ : Dict = tuple[float, float, float]
def UpperCAmelCase__ (lowerCAmelCase_ , lowerCAmelCase_ ):
'''simple docstring'''
__SCREAMING_SNAKE_CASE = end_pointa[0] - end_pointa[... | 682 |
"""simple docstring"""
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_avai... | 682 | 1 |
"""simple docstring"""
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_... | 682 |
"""simple docstring"""
import math
import unittest
from transformers import BioGptConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_... | 682 | 1 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 682 |
"""simple docstring"""
import os
import pytest
from attr import dataclass
a__ : int = '''us-east-1''' # defaults region
@dataclass
class UpperCamelCase_ :
"""simple docstring"""
snake_case__ : str
snake_case__ : Optional[Any] = "arn:a... | 682 | 1 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetParams, RegNet... | 682 |
"""simple docstring"""
import warnings
from ..trainer import Trainer
from ..utils import logging
a__ : Any = logging.get_logger(__name__)
class UpperCamelCase_ ( UpperCamelCase):
"""simple docstring"""
def __init__( self : Any , UpperCAmelCa... | 682 | 1 |
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