code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llam... | 289 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 289 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : Union[str, Any] = {
"""facebook/wav2vec2-base-960h... | 289 |
"""simple docstring"""
import baseaa
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bytes:
"""simple docstring"""
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase_ ( lowerCAmelCase__ : bytes ) ... | 289 | 1 |
"""simple docstring"""
from sklearn.metrics import recall_score
import datasets
lowercase__ : Any = """
Recall is the fraction of the positive examples that were correctly labeled by the model as positive. It can be computed with the equation:
Recall = TP / (TP + FN)
Where T... | 289 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
from __future__ import annotations
from random import choice
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] ) -> int:
"""simple docstring"""
return choice(lowerCAmelCase__ )
def UpperCamelCase_ ( lo... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Optional[int] = logging.get_logger(__name__)
... | 289 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : Optional[int] = logging.get_logger(__name__)
lowercase__ : Optional[Any] = {
"""naver-clova-ix/donut-base""": """https://huggingface.co/n... | 289 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
def __init__( self : int ):
# test for the above condition
... | 289 | 1 |
"""simple docstring"""
import math
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Dict = []
lowerCAmelCase_ : Union[str, Any] = 2
lowerCAmelCase_ ... | 289 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowercase__ : Tuple = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] = """\
@inproceedings{bleurt,
titl... | 289 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str ) -> List[Any]:
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase_ ... | 289 | 1 |
"""simple docstring"""
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin,... | 289 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = 2
lowerCAmelCase_ : List[Any] = []
while... | 289 | 1 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transfor... | 289 |
"""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_sched... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[int] ) -> str:
"""simple docstring"""
return [
{
0: [1, 2],
1: [0, 2],
2: [0, 1, 3, 5],
3: [2, 4],
4: [3],
... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = len(lowerCAmelCase__ )
print('The followin... | 289 | 1 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 289 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 289 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_log... | 289 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ : int = HUGGINGFACE_HUB_CACHE
lowercase__ : Tuple = """config.json"""
lowercase__ : Union[str, Any] = """diffusion_pytorc... | 289 | 1 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ... | 289 |
"""simple docstring"""
import re
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : str = re.compile(
R'^(?:0|94|\+94|0{2}94)' R'7(0|1|2|4|5|6|7|8)' R'(-| |)' R'\d{7}$' )
... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> str:
"""simple docstring"""
if isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
"""simple docstring"""
if len(lowerCAmelCase__ ) != len(lowerCAmelCase__ ):
raise ValueError('String lengths must match... | 289 | 1 |
"""simple docstring"""
import os
# Precomputes a list of the 100 first triangular numbers
lowercase__ : Union[str, Any] = [int(0.5 * n * (n + 1)) for n in range(1, 1_0_1)]
def UpperCamelCase_ ( ) -> Tuple:
"""simple docstring"""
lowerCAmelCa... | 289 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : int = int(num... | 289 | 1 |
"""simple docstring"""
lowercase__ : Union[str, Any] = {
"""meter""": """m""",
"""kilometer""": """km""",
"""megametre""": """Mm""",
"""gigametre""": """Gm""",
"""terametre""": """Tm""",
"""petametre""": """Pm""",
"""exametre""": """Em""",
"""... | 289 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Dict = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconCon... | 289 | 1 |
"""simple docstring"""
import math
import sys
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> str:
"""simple docstring"""
lowerCAmelCase_ : Optional[int] = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as bin... | 289 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
lowercase__ : Any = TypeVar("""_T""")
class UpperCamelCase__ ( Generic[_T] ):
"""simple docstring"""
def __init__( self ... | 289 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
lowercase__ : int = {"""configuration_dpt""": ["""DPT_PRETRAIN... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowercase__ : Optional[int] = {
"""configuration_... | 289 | 1 |
"""simple docstring"""
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_... | 289 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[Any] = logging.getLogger(__name__)
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
... | 289 | 1 |
"""simple docstring"""
import math
lowercase__ : List[str] = 1_0
lowercase__ : Union[str, Any] = 7
lowercase__ : List[Any] = BALLS_PER_COLOUR * NUM_COLOURS
def UpperCamelCase_ ( lowerCAmelCase__ : int = 20 ) -> str:
... | 289 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str ) -> List[Any]:
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase_ ... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llam... | 289 | 1 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def UpperCamelCase_ ( lowerCAmelCase__ : List[Any] ) -> List[str]:
"""simple docstring"""
if (
(cp ... | 289 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 289 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
class UpperCamelCase__ ( lowercase_ ):
... | 289 |
"""simple docstring"""
import baseaa
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bytes:
"""simple docstring"""
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase_ ( lowerCAmelCase__ : bytes ) ... | 289 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase_ ( lowerCAmelCase__ : List[str... | 289 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
import argparse
from torch import nn
# transformers_old should correspond to branch `save_old_prophetnet_model_structure` here
# original prophetnet_checkpoints are saved under `patrickvonplaten/..._old` respectively
from transformers_old.modeling_prophetnet import ... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Optional[int] = logging.get_logger(__name__)
... | 289 | 1 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_we... | 289 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
def __init__( self : int ):
# test for the above condition
... | 289 | 1 |
"""simple docstring"""
from datetime import datetime as dt
import os
from github import Github
lowercase__ : Dict = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""feature request""",
"""new model""",
"""wip"""... | 289 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowercase__ : Tuple = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] = """\
@inproceedings{bleurt,
titl... | 289 | 1 |
"""simple docstring"""
import warnings
warnings.warn(
"""memory_utils has been reorganized to utils.memory. Import `find_executable_batchsize` from the main `__init__`: """
"""`from accelerate import find_executable_batch_size` to avoid this warning.""",
FutureWarning,
)
... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str ) -> List[Any]:
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase_ ... | 289 | 1 |
"""simple docstring"""
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python uti... | 289 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = 2
lowerCAmelCase_ : List[Any] = []
while... | 289 | 1 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
lowercase__ : Dict = logging.get_logger(__name__)
lowercase__ : Tuple = {
"""Intel/dpt-large""": """https:/... | 289 |
"""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_sched... | 289 | 1 |
"""simple docstring"""
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
lowercase__ : Union[str, Any] = log... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = len(lowerCAmelCase__ )
print('The followin... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : list[list[int]] ) -> int:
"""simple docstring"""
def update_area_of_max_square(lowerCAmelCase__ : int ... | 289 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 289 | 1 |
"""simple docstring"""
from typing import Any
def UpperCamelCase_ ( lowerCAmelCase__ : list , lowerCAmelCase__ : list , lowerCAmelCase__ : dict , lowerCAmelCase__ : dict , lowerCAmelCase__ : dict , ) -> li... | 289 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ : int = HUGGINGFACE_HUB_CACHE
lowercase__ : Tuple = """config.json"""
lowercase__ : Union[str, Any] = """diffusion_pytorc... | 289 | 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_sched... | 289 |
"""simple docstring"""
import re
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : str = re.compile(
R'^(?:0|94|\+94|0{2}94)' R'7(0|1|2|4|5|6|7|8)' R'(-| |)' R'\d{7}$' )
... | 289 | 1 |
"""simple docstring"""
import pytest
lowercase__ : Optional[Any] = """__dummy_dataset1__"""
lowercase__ : Any = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"t... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
"""simple docstring"""
if len(lowerCAmelCase__ ) != len(lowerCAmelCase__ ):
raise ValueError('String lengths must match... | 289 | 1 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[Any] = logging.getLogger(__name__)
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
... | 289 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : int = int(num... | 289 | 1 |
"""simple docstring"""
import doctest
import logging
import os
import unittest
from pathlib import Path
from typing import List, Union
import transformers
from transformers.testing_utils import require_tf, require_torch, slow
lowercase__ : Dict = logging.getLogger()
... | 289 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi
def UpperCamelCase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> dict[str, float]:
"""simple docstring"""
... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Dict = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconCon... | 289 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers.file_utils import has_file
from diffusers import UNetaDConditionModel, UNetaDModel
lowercase__ : Optional[Any] = False
lowercase__ : Dict = True
lowercase__ : ... | 289 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
lowercase__ : Any = TypeVar("""_T""")
class UpperCamelCase__ ( Generic[_T] ):
"""simple docstring"""
def __init__( self ... | 289 | 1 |
"""simple docstring"""
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
requi... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowercase__ : Optional[int] = {
"""configuration_... | 289 | 1 |
"""simple docstring"""
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
... | 289 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[Any] = logging.getLogger(__name__)
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
... | 289 | 1 |
"""simple docstring"""
import argparse
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_dummies.py
lowercase__ : Optional[Any] = """src/diffusers"""
# Matches is_xxx_availab... | 289 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml... | 289 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llam... | 289 | 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 AddedToken, PreTrainedTokenizer
from ...utils import logging
lowercase__ : List[Any] = logging... | 289 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 289 | 1 |
"""simple docstring"""
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
l... | 289 |
"""simple docstring"""
import baseaa
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bytes:
"""simple docstring"""
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase_ ( lowerCAmelCase__ : bytes ) ... | 289 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
fr... | 289 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Optional[int] = logging.get_logger(__name__)
... | 289 | 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/l... | 289 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
def __init__( self : int ):
# test for the above condition
... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = len(lowerCAmelCase__ )
print('The followin... | 289 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowercase__ : Tuple = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] = """\
@inproceedings{bleurt,
titl... | 289 | 1 |
"""simple docstring"""
import unittest
from parameterized import parameterized
from transformers import OpenLlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...te... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str ) -> List[Any]:
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase_ ... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
raise ValueError('check_bouncy() accepts only integer arguments' )
... | 289 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = 2
lowerCAmelCase_ : List[Any] = []
while... | 289 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowercase__ : Optional[int] = {
"""configuration_... | 289 |
"""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_sched... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = [0 for i in range(len(lowerCAmelCase__ ) )]
# initialize interval's left pointer and ri... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = len(lowerCAmelCase__ )
print('The followin... | 289 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import RoFormerConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMode... | 289 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 289 | 1 |
"""simple docstring"""
import argparse
import os
import torch
from transformers import FlavaImageCodebook, FlavaImageCodebookConfig
def UpperCamelCase_ ( lowerCAmelCase__ : Any , lowerCAmelCase__ : int , lowerCAmelCase__ : Dict , lowerCA... | 289 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ : int = HUGGINGFACE_HUB_CACHE
lowercase__ : Tuple = """config.json"""
lowercase__ : Union[str, Any] = """diffusion_pytorc... | 289 | 1 |
"""simple docstring"""
# Lint as: python3
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING, Dict, Optional
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.logging import get_logger
from ..utils.py_utils import map_nested
from ... | 289 |
"""simple docstring"""
import re
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : str = re.compile(
R'^(?:0|94|\+94|0{2}94)' R'7(0|1|2|4|5|6|7|8)' R'(-| |)' R'\d{7}$' )
... | 289 | 1 |
"""simple docstring"""
import argparse
import os
import re
import packaging.version
lowercase__ : List[str] = """examples/"""
lowercase__ : Tuple = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_ve... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
"""simple docstring"""
if len(lowerCAmelCase__ ) != len(lowerCAmelCase__ ):
raise ValueError('String lengths must match... | 289 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require... | 289 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : int = int(num... | 289 | 1 |
"""simple docstring"""
import requests
lowercase__ : str = """""" # <-- Put your OpenWeatherMap appid here!
lowercase__ : Optional[Any] = """https://api.openweathermap.org/data/2.5/"""
def UpperCamelCase_ ( lowerCAmelCase__ : str = "Chicago" , ... | 289 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
import baseaa
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bytes:
"""simple docstring"""
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase_ ( lowerCAmelCase__ : bytes ) ... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Dict = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconCon... | 289 | 1 |
"""simple docstring"""
import os
def UpperCamelCase_ ( ) -> Optional[Any]:
"""simple docstring"""
with open(os.path.dirname(lowerCAmelCase__ ) + '/p022_names.txt' ) as file:
lowerCAmelCase_ : int = str(file.readlines()[0] ... | 289 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
lowercase__ : Any = TypeVar("""_T""")
class UpperCamelCase__ ( Generic[_T] ):
"""simple docstring"""
def __init__( self ... | 289 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : List[Any] = {"""configuration_ibert""": ["""IBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """IBertConfig""", """IBertOnnxConfi... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowercase__ : Optional[int] = {
"""configuration_... | 289 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowercase__ : Optional[Any] = argparse.ArgumentParser(
description=(
"""Extraction some layers of the ... | 289 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[Any] = logging.getLogger(__name__)
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
... | 289 | 1 |
"""simple docstring"""
import heapq
import sys
import numpy as np
lowercase__ : Optional[int] = tuple[int, int]
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self : Any ):
lowerCAmelCase_... | 289 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml... | 289 | 1 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def UpperCamelCase_ ( lowerCAmelCase__ : Union[str, Any] ) -> Optional[Any]:
"""simple ... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llam... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : Dict = len(lowerCAmelCase__ ) + 1
lowerCAmelCase_ : Optio... | 289 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 289 | 1 |
"""simple docstring"""
import math
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> str:
"""simple docstring"""
lowerCAmelCase_ : str = 0
lowerCAmelCase_ : Union[str, Any] = 0
while num > 0:
lowerCAme... | 289 |
"""simple docstring"""
import baseaa
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bytes:
"""simple docstring"""
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase_ ( lowerCAmelCase__ : bytes ) ... | 289 | 1 |
"""simple docstring"""
class UpperCamelCase__ :
"""simple docstring"""
def __init__( self : Dict , SCREAMING_SNAKE_CASE_ : int ):
lowerCAmelCase_ : int = val
lowerCAmelCase_ : List[Any] ... | 289 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import LEDConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Optional[int] = logging.get_logger(__name__)
... | 289 | 1 |
"""simple docstring"""
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def UpperCamelCase_ ( ) -> Optional[Any]:
"""simple... | 289 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
def __init__( self : int ):
# test for the above condition
... | 289 | 1 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
return credit_card_number.startswith(('34', '35', '37', '4', '5', '6') )
def UpperCamelCase_ ( lowerCAmelCase__ : str ) ... | 289 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowercase__ : Tuple = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] = """\
@inproceedings{bleurt,
titl... | 289 | 1 |
"""simple docstring"""
import os
import tempfile
from functools import partial
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pytest
from datasets.arrow_dataset import Dataset
from datasets.search import ElasticSearchIndex, FaissIndex, MissingI... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str ) -> List[Any]:
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase_ ... | 289 | 1 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] , lowerCAmelCase__ : int ) -> tuple[float, list[float]]:
"""simple docstring"""
... | 289 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = 2
lowerCAmelCase_ : List[Any] = []
while... | 289 | 1 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
from numpy import floataa
from numpy.typing import NDArray
def UpperCamelCase_ ( lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ : NDArray[floataa] , lowerCAmelCase__ ... | 289 |
"""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_sched... | 289 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Optional[int] = logging.get_logger(__name__)
... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = len(lowerCAmelCase__ )
print('The followin... | 289 | 1 |
"""simple docstring"""
import argparse
from copy import deepcopy
import numpy as np
from datasets import ClassLabel, DatasetDict, load_dataset
from evaluate import load
from transformers import (
AutoModelForSequenceClassification,
AutoTokenizer,
DataCollatorWithPadding,
... | 289 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 289 | 1 |
"""simple docstring"""
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ... | 289 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ : int = HUGGINGFACE_HUB_CACHE
lowercase__ : Tuple = """config.json"""
lowercase__ : Union[str, Any] = """diffusion_pytorc... | 289 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJo... | 289 |
"""simple docstring"""
import re
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : str = re.compile(
R'^(?:0|94|\+94|0{2}94)' R'7(0|1|2|4|5|6|7|8)' R'(-| |)' R'\d{7}$' )
... | 289 | 1 |
"""simple docstring"""
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> int:
"""simple docstring"""
if len(lowerCAmelCase__ ) != len(lowerCAmelCase__ ):
raise ValueError('String lengths must match... | 289 | 1 |
"""simple docstring"""
from string import ascii_uppercase
lowercase__ : Dict = {char: i for i, char in enumerate(ascii_uppercase)}
lowercase__ : int = dict(enumerate(ascii_uppercase))
def UpperCamelCase_ ( lowerCAmelCase__ : str , lowerCAme... | 289 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
from math import gcd, sqrt
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : int = int(num... | 289 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Dict = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconCon... | 289 |
"""simple docstring"""
import unittest
from transformers import AlbertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffus... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase__ : Dict = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconCon... | 289 | 1 |
"""simple docstring"""
import math
def UpperCamelCase_ ( ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = input('Enter message: ' )
lowerCAmelCase_ : Any = int(input(f"Enter key [2-{len(lowerCAmelCase... | 289 |
"""simple docstring"""
from collections.abc import Iterable
from typing import Generic, TypeVar
lowercase__ : Any = TypeVar("""_T""")
class UpperCamelCase__ ( Generic[_T] ):
"""simple docstring"""
def __init__( self ... | 289 | 1 |
"""simple docstring"""
import math
def UpperCamelCase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> float:
"""simple docstring"""
if initial_intensity < 0:
raise ValueError('The value of intensity cannot be negative... | 289 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowercase__ : Optional[int] = {
"""configuration_... | 289 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=lowercase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ["""transformers""", """torch""", """note_seq"""]
... | 289 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[Any] = logging.getLogger(__name__)
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
... | 289 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
f... | 289 |
"""simple docstring"""
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml... | 289 | 1 |
"""simple docstring"""
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase__ : List[Any] = logging.get_logger(__name__)
lowercase__ : List[str] = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llam... | 289 | 1 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTImageProcessor, ViTMSNConfig, ViTMSNModel
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGENET_D... | 289 |
"""simple docstring"""
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale... | 289 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
def __init__( self : int ):
# test for the above condition
... | 289 |
"""simple docstring"""
import baseaa
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bytes:
"""simple docstring"""
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCamelCase_ ( lowerCAmelCase__ : bytes ) ... | 289 | 1 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowercase__ : Tuple = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] = """\
@inproceedings{bleurt,
titl... | 289 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_mod... | 289 | 1 |
"""simple docstring"""
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Cal... | 289 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Optional[int] = logging.get_logger(__name__)
... | 289 | 1 |
"""simple docstring"""
import os
import re
import sys
import traceback
import warnings
from pathlib import Path
from typing import Dict, Optional, Union
from uuid import uuida
from huggingface_hub import HfFolder, ModelCard, ModelCardData, hf_hub_download, whoami
from huggingface_hub.f... | 289 |
"""simple docstring"""
from abc import ABC, abstractmethod
from typing import List, Optional
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
def __init__( self : int ):
# test for the above condition
... | 289 | 1 |
"""simple docstring"""
import re
def UpperCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
"""simple docstring"""
lowerCAmelCase_ : str = re.compile(
R'^(?:0|94|\+94|0{2}94)' R'7(0|1|2|4|5|6|7|8)' R'(-| |)' R'\d{7}$' )
... | 289 |
"""simple docstring"""
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
lowercase__ : Tuple = datasets.logging.get_logger(__name__)
lowercase__ : List[Any] = """\
@inproceedings{bleurt,
titl... | 289 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowercase__ : Dict = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", ... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : Optional[Any] , lowerCAmelCase__ : str ) -> List[Any]:
"""simple docstring"""
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def UpperCamelCase_ ... | 289 | 1 |
"""simple docstring"""
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List,... | 289 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase_ ( lowerCAmelCase__ : int ) -> list[int]:
"""simple docstring"""
lowerCAmelCase_ : Any = 2
lowerCAmelCase_ : List[Any] = []
while... | 289 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : str = {
"""configuration_upernet""": ["""UperNetConfig"""],
}
try:
if not is_torch_available():
... | 289 |
"""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_sched... | 289 | 1 |
"""simple docstring"""
import argparse
import csv
import logging
import os
import random
import numpy as np
import torch
from torch.utils.data import DataLoader, RandomSampler, SequentialSampler, TensorDataset
from tqdm import tqdm, trange
from transformers import (
CONFIG_NAME,... | 289 |
"""simple docstring"""
def UpperCamelCase_ ( lowerCAmelCase__ : list[int] , lowerCAmelCase__ : list[int] ) -> None:
"""simple docstring"""
lowerCAmelCase_ : List[Any] = len(lowerCAmelCase__ )
print('The followin... | 289 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_tor... | 289 |
"""simple docstring"""
from diffusers.utils.testing_utils import require_onnxruntime
@require_onnxruntime
class UpperCamelCase__ :
"""simple docstring"""
pass
| 289 | 1 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow... | 289 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowercase__ : int = HUGGINGFACE_HUB_CACHE
lowercase__ : Tuple = """config.json"""
lowercase__ : Union[str, Any] = """diffusion_pytorc... | 289 | 1 |
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