code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json"... | 16 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 1 |
"""simple docstring"""
_lowerCAmelCase = range(2, 2_0 + 1)
_lowerCAmelCase = [1_0**k for k in range(ks[-1] + 1)]
_lowerCAmelCase = {}
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
... | 16 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 1 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import TYPE_CHECKING, List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pip... | 16 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from transformers import OPTConfig, OPTModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name__)
def lowerCamelCase__ ( _lowerCamelCa... | 16 |
"""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 .forma... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : list[list[float]] = []
for data in source_data:
for i, el in enumerate(_lowerCamelCase ):
if len(_lowerCamelCase ) < i + 1:
... | 16 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audi... | 16 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if len(_lowerCamelCase ) == 0:
return array
_lowerCAmelCase, _lowerCAmelCase : Optional[Any] = min(_lowerCamelCase ... | 16 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
def update_area_of_max_square(_lowerCamelCase , _lowerCamelCase ) -> int:
# BASE CASE
if row >= rows or col >= cols:
... | 16 |
"""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_visio... | 16 | 1 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoenco... | 16 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
_lowerCAmelCase = 1.6_021E-19 # units = C
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , ):
'''simple docstring'''
if (conductivity, electron_conc, mobility).count(0 ) !... | 16 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 1 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 1 |
"""simple docstring"""
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
fro... | 16 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 1 |
"""simple docstring"""
from typing import Any
import numpy as np
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return np.array_equal(_lowerCamelCase , matrix.conjugate().T )
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):... | 16 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 1 |
"""simple docstring"""
import os
from itertools import chain
from random import randrange, shuffle
import pytest
from .sola import PokerHand
_lowerCAmelCase = (
"""4S 3H 2C 7S 5H""",
"""9D 8H 2C 6S 7H""",
"""2D 6D 9D TH 7D""",
"""TC 8C 2S JH 6C""",
"""JH 8S TH ... | 16 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 1 |
"""simple docstring"""
from numpy import exp, pi, sqrt
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase = 0.0 , _lowerCamelCase = 1.0 ):
'''simple docstring'''
return 1 / sqrt(2 * pi * sigma**2 ) * exp(-((x - mu) ** 2) / (2 * sigma**2) )
if __name__ ==... | 16 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 1 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
fro... | 16 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 1 |
"""simple docstring"""
_lowerCAmelCase = {str(digit): digit**5 for digit in range(1_0)}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return sum(DIGITS_FIFTH_POWER[digit] for digit in str(_lowerCamelCase ) )
def lowerCamelCase__ ( ):
... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 1 |
"""simple docstring"""
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_util... | 16 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( ):
'''simple docstring'''
return [
a * b * (1000 - a - b)
for a in range(1 , 999 )
for b in range(_lowerCamelCase , 999 )
if (a * a + b * b == (1000 - a - b) ** 2)
][0]
if __name... | 16 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if mass < 0:
raise ValueError('The mass of a body cannot be negative' )
return 0.5 * mass * abs(_lowerCamelCase ) * abs(_lowerCamelCase )
if __... | 16 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 1 |
"""simple docstring"""
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class __UpperCamelCase ( unittest.TestCase ):
def __lowerCamelCase ( self ):
'''simple docstring'''
_lowerCAmelC... | 16 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return sum(i for i in range(1 , number // 2 + 1 ) if number % i == 0 ) == number
if __name__ == "__main__":
print("""Program to check whether a number is a Perfect number or n... | 16 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 1 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 1 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
_lowerCAmelCase = pd.read_csv("""sample_data.csv""", head... | 16 |
"""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 .forma... | 16 | 1 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentT... | 16 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = [
["""a... | 16 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase = {
... | 16 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = []
_lowerCAmelCase, _lowerCAmelCase... | 16 |
"""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_visio... | 16 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import DistilBertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 16 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 1 |
"""simple docstring"""
import inspect
import tempfile
import unittest
from huggingface_hub import hf_hub_download
from transformers import is_torch_available
from transformers.testing_utils import is_flaky, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTes... | 16 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 1 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""voc... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 1 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
_lowerCAmelCase = logging.get_logger(__name__)
class __UpperCam... | 16 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 1 |
"""simple docstring"""
from collections.abc import Callable
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : float = a
_lowerCAmelCase : float = b
if function(_lower... | 16 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 1 |
"""simple docstring"""
import os
import re
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_... | 16 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from diffusers import OnnxStableDiffusionInpaintPipelineLegacy
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
load_numpy,
nightly,
require_onnxruntime,
require_torch_gpu,
)
i... | 16 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 1 |
"""simple docstring"""
import tempfile
import unittest
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from transformers.testing_utils import (
is_torch_available,
require_optimum,
require_torch,
slow,
)
if is_torch_available():
import torch
... | 16 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __UpperCamelCase ( a__ , unittest.TestCase )... | 16 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers impor... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 1 |
"""simple docstring"""
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common ... | 16 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""go... | 16 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 1 |
"""simple docstring"""
import warnings
from transformers import AutoTokenizer
from transformers.utils import is_torch_available
from transformers.utils.generic import ExplicitEnum
from ...processing_utils import ProcessorMixin
if is_torch_available():
import torch
class _... | 16 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 1 |
"""simple docstring"""
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def l... | 16 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 1 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
_lowerCAmelCase = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and W... | 16 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 1 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import Optional
import pandas as pd
import pyarrow as pa
import datasets
from datasets.table import table_cast
@dataclass
class __UpperCamelCase ( datasets.BuilderConfig ):
_Up... | 16 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 1 |
"""simple docstring"""
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
... | 16 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Any = Decimal
# Check if the provided matrix has 2 rows... | 16 |
"""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 .forma... | 16 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from torch import nn
from transformers import (
Adafactor,
AdamW,
... | 16 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 1 |
"""simple docstring"""
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_in... | 16 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 1 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 1 |
"""simple docstring"""
import qiskit
def lowerCamelCase__ ( _lowerCamelCase = 2 ):
'''simple docstring'''
_lowerCAmelCase : List[str] = qubits
# Using Aer's simulator
_lowerCAmelCase : List[str] = qiskit.Aer.get_backend('aer_simulator' ... | 16 |
"""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_visio... | 16 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTeste... | 16 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 1 |
"""simple docstring"""
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-ti... | 16 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 1 |
"""simple docstring"""
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
_lowerCAmelCase =... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 1 |
"""simple docstring"""
from .glue import glue_convert_examples_to_features, glue_output_modes, glue_processors, glue_tasks_num_labels
from .squad import SquadExample, SquadFeatures, SquadVaProcessor, SquadVaProcessor, squad_convert_examples_to_features
from .utils import DataProcessor, InputExample, ... | 16 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
import numpy as np
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase, _lowerCAmelCase : Union[str, Any] = np.shape(_lowerCamelCase )
if rows != columns:
... | 16 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 1 |
"""simple docstring"""
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class __UpperCamelCase ( unittest.TestCase ):
def __lowerCamelCase ( self ):
'''simple docstr... | 16 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 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, Train... | 16 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCAmelCase = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnnxConfig"""],
... | 16 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
_lowerCAmelCase = 1.054_571_817E-34 # unit of ℏ : J * s
_lowerCAmelCase = 3E8 # unit of c : m * s^-1
... | 16 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 1 |
"""simple docstring"""
import pytest
_lowerCAmelCase = """__dummy_dataset1__"""
_lowerCAmelCase = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"train\": REPO_URL + \"wikiann-bn-trai... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase = {
"""configuration_blenderbo... | 16 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
_lowerCAmelCase = logging.get_logger(__name__)
class __UpperCamelCase ( a__ ):
def __init__( self ,*_A ,**_A ):
'... | 16 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
_lowerCAmelCase = 2_0_0
# Number of elements selected in every generation of evolution. The selection takes
# place from best to... | 16 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __UpperC... | 16 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuratio... | 16 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def lowerCamelCase__ ( _lowerCamelCase , _lowerCam... | 16 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 1 |
"""simple docstring"""
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, loggi... | 16 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 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, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils... | 16 |
"""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 .forma... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase = 1000 ):
'''simple docstring'''
_lowerCAmelCase : Dict = 3
_lowerCAmelCase : Optional[Any] = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
... | 16 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
_lowerCAmelCase = {
"""configuration_convnext""": ["""CONVNEXT_PRETRAINED_... | 16 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 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_visio... | 16 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 1 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_tor... | 16 |
"""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_visio... | 16 | 1 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Optio... | 16 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 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/license... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 1 |
"""simple docstring"""
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_co... | 16 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
_lowerCAmelCase = logging.get_logge... | 16 | 1 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import Token... | 16 |
"""simple docstring"""
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class __UpperCamelCas... | 16 | 1 |
"""simple docstring"""
import inspect
import unittest
from transformers import ConvNextConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_c... | 16 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
create_state_space_tree(_lowerCamelCase , [] , 0 , [0 for i in range(len(_lowerCamelCase ) )] )
def lowerCamelCase__ ( _lowerCam... | 16 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase = {
"""configuration_git""": ["""GIT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GitConfig""", """GitVisionConfig"""],
"""process... | 16 |
"""simple docstring"""
import logging
import os
from .state import PartialState
class __UpperCamelCase ( logging.LoggerAdapter ):
@staticmethod
def __lowerCamelCase ( _A ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = ... | 16 | 1 |
"""simple docstring"""
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# 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/license... | 16 |
"""simple docstring"""
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
_lowerCAmelCase =... | 16 | 1 |
"""simple docstring"""
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
_lowerCAmelCase = logging.getLogger(__name__)
class __UpperCamelCase ( a__ ... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu, skip_... | 16 | 1 |
"""simple docstring"""
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learn... | 16 |
"""simple docstring"""
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __UpperCamelCase... | 16 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 | 1 |
"""simple docstring"""
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...u... | 16 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
_lowerCAmelCase = {"""UserAgent""": UserAgent().random}
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstr... | 16 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_lowerCAmelCase = logging.get_logger(__name__)
class __UpperCamelCase ( a__ ):
def __init__( self ,*_A ,**_A ):
'''si... | 16 |
"""simple docstring"""
import os
import unicodedata
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 SPIECE_UNDERLINE, logging
_lowerCAmelCase... | 16 | 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_input... | 16 |
"""simple docstring"""
import argparse
import struct
import unittest
class __UpperCamelCase :
def __init__( self ,_A ):
'''simple docstring'''
_lowerCAmelCase : Optional[int] = data
# Initialize hash values
_lowerCAmelCase ... | 16 | 1 |
"""simple docstring"""
import baseaa
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaaencode(string.encode('utf-8' ) )
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return baseaa.aaadecod... | 16 |
"""simple docstring"""
from collections.abc import Callable
class __UpperCamelCase :
def __init__( self ,_A = None ):
'''simple docstring'''
_lowerCAmelCase : list = []
# Stores indexes of each item for supporting updates and deletion.... | 16 | 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 TFModelTesterMixi... | 16 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTra... | 16 | 1 |
"""simple docstring"""
import argparse
import json
import os
from pathlib import Path
import requests
import torch
from transformers import JukeboxConfig, JukeboxModel
from transformers.utils import logging
logging.set_verbosity_info()
_lowerCAmelCase = logging.get_logger(__name_... | 16 |
"""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 .forma... | 16 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowerCAmelCase = {
"""configuration_roc_bert""": ["""ROC_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """RoCBertConfig"""],... | 16 |
"""simple docstring"""
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
fr... | 16 | 1 |
"""simple docstring"""
import unittest
from transformers import AutoTokenizer, FalconConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTest... | 16 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"""vocab_file""": """vocab.j... | 16 | 1 |
"""simple docstring"""
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils... | 16 |
"""simple docstring"""
import math
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from .attention_processor import Attention
from .embeddings import get_timestep_embedding
from .modeling_utils import ModelMixin
class __Upper... | 16 | 1 |
"""simple docstring"""
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError('the value of both inputs must be positive' )
_lowerCAmelCase : List[str] = str(bin(_lowerCamelCase ) ... | 16 |
"""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_visio... | 16 | 1 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
return [ord(_lowerCamelCase ) - 96 for elem in plain]
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
... | 16 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
_lowerCAmelCase = list[list[float | int]]
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : int = len... | 16 | 1 |
"""simple docstring"""
from collections.abc import Callable
import numpy as np
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : List[str] = int(... | 16 |
"""simple docstring"""
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase__ ( _lowerCamelCase ):
'''simple docstring'''
if (
(cp >= 0X4E00 and cp <= 0X9FFF)
or (cp >= 0... | 16 | 1 |
"""simple docstring"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ):
'''simple docstring'''
_lowerCAmelCase : Optional[Any] = 0
if star... | 16 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
... | 16 | 1 |
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