code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from math import isclose, sqrt
def lowerCamelCase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> tuple[float, float, float]:
'''simple docstring'''
A = point_y / 4 / point_x
A = 2 * normal_... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Dict =logging.get_logger(__name__)
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : List[str] = 'timm_backbone'
def __init__( self : Optional[Any]... | 106 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, XLMRobertaTokenizer
from diffusers import AltDiffusionPipeline, AutoencoderKL, DDIMScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelines.alt_diffusion.modeling_roberta_series import ... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 1 |
import unicodedata
from dataclasses import dataclass
from typing import Optional, Union
import numpy as np
from transformers.data.data_collator import DataCollatorMixin
from transformers.file_utils import PaddingStrategy
from transformers.tokenization_utils_base import PreTrainedTokenizerBase
def lowerCame... | 106 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 1 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__snake_case :Optional[int] =200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to worst of that generation a... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] ) -> Tuple:
'''simple docstring'''
if "img_encoder.pos_embed" in name:
... | 106 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appli... | 106 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 1 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 1 |
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowerCamelCase_ ( lowerCAmelCase__ : List[Any] ) -> int:
'''simple docstring'''
return x + 2
class lowerCAmelCase__ ( un... | 106 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 1 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : List[str] = 'encoder-decoder'
A_ : Dict =... | 106 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 1 |
def lowerCamelCase_ ( lowerCAmelCase__ : int ) -> bool:
'''simple docstring'''
if not isinstance(lowerCAmelCase__ , lowerCAmelCase__ ):
A = F'''Input value of [number={number}] must be an integer'''
raise TypeError(lowerCAmelCa... | 106 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 1 |
from typing import TYPE_CHECKING
from ..utils import _LazyModule
__snake_case :int ={
'config': [
'EXTERNAL_DATA_FORMAT_SIZE_LIMIT',
'OnnxConfig',
'OnnxConfigWithPast',
'OnnxSeq2SeqConfigWithPast',
'PatchingSpec',
],
'convert': ['export', 'validate... | 106 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 1 |
from __future__ import annotations
from cmath import sqrt
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : int , lowerCAmelCase__ : int ) -> tuple[complex, complex]:
'''simple docstring'''
if a == 0:
raise ValueError('Coefficient \'... | 106 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_availabl... | 106 | 1 |
import os
import tempfile
import unittest
import numpy as np
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
from flax.jax_utils import replicate
from flax.training.common_utils ... | 106 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 1 |
import os
from datetime import datetime as dt
from github import Github
__snake_case :int =[
'good first issue',
'feature request',
'wip',
]
def lowerCamelCase_ ( ) -> Any:
'''simple docstring'''
A = Github(os.environ['GITHUB_TOK... | 106 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 1 |
import fire
from utils import calculate_rouge, save_json
def lowerCamelCase_ ( lowerCAmelCase__ : Any , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[str]=None , **lowerCAmelCase__ : Union[str, Any] ) -> Tuple:
'''simple docstring'''
A = [x.s... | 106 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor
fro... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 1 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__snake_case :Any ={
'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapaneseConfig'],
'tokenization_g... | 106 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 1 |
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
__snake_case :List[str] ='src/diffusers'
# Matches is_xxx_available()
__snake_case :Union[str, Any] =re.compile(r... | 106 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_t... | 106 | 1 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 1 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = re.compile(r'^(\+91[\-\s]?)?[0]?(91)?[789]\d{9}$' )
if match := re.search(lowerCAmelCase__ , lowerCAmelCase__ ):
return match.string... | 106 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 1 |
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,
)
from .test_pipelines_common import ANY
if is... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def lowerCamelCase_ ( lowerCAmelCase__ : Namespace ) -> Dict:
'''simple docstring'''
return ConvertCommand(
args.model_type , args.tf_chec... | 106 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 1 |
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_available, is_tf_available, logging
from .benchm... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 1 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_t... | 106 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 1 |
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, slow
fr... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 1 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 1 |
from math import factorial, radians
def lowerCamelCase_ ( lowerCAmelCase__ : float , lowerCAmelCase__ : int = 18 , lowerCAmelCase__ : int = 10 ) -> float:
'''simple docstring'''
A = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
# C... | 106 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :str =logging.get_logger(__name__)
__snake_case :int ={
'google/pegasus-large': 'https://huggingface.co/google/pegasus-large/resolve/main/config.json',
# See all PEGASUS models at https... | 106 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 1 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class lowerCAmelCase__ ( _lowerCamelCase ):
A_ : Optio... | 106 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 1 |
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWatermarker
from diffusers.utils.tes... | 106 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :Optional[Any] ={
'google/switch-base-8': 'https://huggingface.co/google/switch-base-8/blob/main/config.json',
}
class lowerC... | 106 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 1 |
from binascii import hexlify
from hashlib import shaaaa
from os import urandom
# RFC 3526 - More Modular Exponential (MODP) Diffie-Hellman groups for
# Internet Key Exchange (IKE) https://tools.ietf.org/html/rfc3526
__snake_case :Any ={
# 1536-bit
5: {
'prime': int(
'FFFFF... | 106 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 1 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
__snake_case :List[str] =argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Learned... | 106 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_availabl... | 106 | 1 |
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Dict =logging.get_logger(__name__)
__snake_case :Union[str, Any] ={
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
'funnel-tran... | 106 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 1 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 1 |
import random
from typing import Any
def lowerCamelCase_ ( lowerCAmelCase__ : list ) -> list[Any]:
'''simple docstring'''
for _ in range(len(lowerCAmelCase__ ) ):
A = random.randint(0 , len(lowerCAmelCase__ ) - 1 )
... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 1 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
__snake_case :Union[str, Any] ={
... | 106 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 1 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attenti... | 106 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_t... | 106 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
__snake_case :List[str] ={
'configuration_llama': ['LLAMA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LlamaConf... | 106 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 1 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_electra import ElectraTokenizer
__snake_case :int ={'vocab_file': 'vocab.txt', 'tokenizer_file': 'tokenizer.json'}
__snake_case ... | 106 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :str =logging.get_logger(__name__)
__snake_case :Dict ={
'google/realm-cc-news-pretrained-embedder': (
'https://huggingface.co/google/realm-cc-news-pretrained-embedder/resolve/main/... | 106 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 1 |
import re
import string
from collections import Counter
import sacrebleu
import sacremoses
from packaging import version
import datasets
__snake_case :Optional[Any] ='\n@inproceedings{xu-etal-2016-optimizing,\n title = {Optimizing Statistical Machine Translation for Text Simplification},\n au... | 106 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 1 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import requ... | 106 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 1 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from ... | 106 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 1 |
import logging
from transformers import PretrainedConfig
__snake_case :int =logging.getLogger(__name__)
__snake_case :Tuple ={
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/config.json',
}
class... | 106 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 1 |
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTeste... | 106 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 1 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
__snake_case :Optional[int] ={
'n_samples': 64,
'horizon': 32,
'num_inference_steps': 20,
'n_guide_steps': 2, # can set to 0 for faster sampling, does not use value network
'scale_... | 106 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 1 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 1 |
__snake_case :int =[sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(100000)]
def lowerCamelCase_ ( lowerCAmelCase__ : int ) -> int:
'''simple docstring'''
A = 0
while number:
# Increased Speed Slightly by checki... | 106 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 1 |
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
fro... | 106 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 1 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowerCamelCase_ ( lowerCAmelCase__ : Optional[int] ) -> ... | 106 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 1 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCAmelCase__ ( nn.Module ):
A_ : int
A_ : jnp.dtype = jnp.floataa
def __UpperCamelCase ( self : str ) -> Any:
A = nn.Conv(
... | 106 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 1 |
from collections import deque
from math import floor
from random import random
from time import time
class lowerCAmelCase__ :
def __init__( self : List[str] ) -> List[str]:
A = {}
def __UpperCamelCase ( self : Dict , __U... | 106 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_availabl... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[int] =logging.get_logger(__name__)
__snake_case :Tuple ={
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/reso... | 106 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 1 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
__snake_case :List[str] =version.parse(version.parse(tor... | 106 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ : Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ : List[str] = {
"""facebook/timesformer""": """https://huggingface.co/facebook/timesformer/resolve/main/config.json""",
... | 0 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 0 |
import re
from filelock import FileLock
try:
import nltk
__snake_case = True
except (ImportError, ModuleNotFoundError):
__snake_case = False
if NLTK_AVAILABLE:
with FileLock('''.lock''') as lock:
nltk.download('''punkt''', quiet=True)
... | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 0 |
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()
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = ... | 2 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
lowerCAmelCase : str = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( snake_case_):
def __init__( self ... | 3 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_t... | 106 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, Tens... | 4 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 0 |
'''simple docstring'''
from __future__ import annotations
def A (__lowerCamelCase :str ):
return [ord(__lowerCamelCase ) - 96 for elem in plain]
def A (__lowerCamelCase :list[int] ):
return "".join(chr(elem + 96 ) for elem in encoded )
def A ():
_lowerCAmelCase ... | 5 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 0 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCamelCase_ ( yaml.SafeLoader ):
def _snake_case ( self :List[str] , __A :List[Any] ) -> Optional[int]:
"""simple docstring"""
SC... | 6 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 0 |
"""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_index,
)
import transfo... | 7 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 0 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class SCREAMING_SNAKE_CASE (yaml.SafeLoader ):
def SCREAMING_SNAKE_CASE ( self , _UpperCAmelCase):
'''simple do... | 8 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 0 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 9 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 0 |
def _snake_case ( __snake_case = 10**12 ):
_UpperCamelCase = 1
_UpperCamelCase = 0
_UpperCamelCase = 1
_UpperCamelCase = 1
while numerator <= 2 * min_total - 1:
prev_numerator += 2 * numerator
numerator += 2 * prev_num... | 10 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .token... | 11 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 0 |
from datetime import datetime as dt
import os
from github import Github
lowerCamelCase__ : Dict = [
"""good first issue""",
"""good second issue""",
"""good difficult issue""",
"""feature request""",
"""new model""",
"""wip""",
]
def UpperCamelCase ( ) ... | 12 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 0 |
'''simple docstring'''
from __future__ import annotations
def UpperCAmelCase__ ( UpperCAmelCase_ : list[int] , UpperCAmelCase_ : list[int] , UpperCAmelCase_ : list[int] , UpperCAmelCase_ : list[list[str]] , UpperCAmelCase_ ... | 13 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 0 |
import collections
import os
import re
from pathlib import Path
a__ = '''src/transformers'''
# Matches is_xxx_available()
a__ = re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
a__ = re.compile(R'''^_import_struc... | 14 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 0 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
A : str = logging.get_logger(__name__)
A : str = {
'post_extract_proj': 'feature_projecti... | 15 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 0 |
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
__A : str = logging.get_logger(__name__)
_... | 16 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 0 |
from __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class lowerCamelCase_ ( _lowercase ):
def __lt__( self : str , __A : Tuple ):
return self[-1] < other[-1]
def... | 17 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
import numpy as np
import PIL
from PIL import Image
from ...utils import BaseOutput, is_torch_available, is_transformers_available
@dataclass
class lowerCAmelCase_ ( __magic_name__ ):
... | 18 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCAmelCase__ ( _lowerCamelCase ):
def __init__( self : int , __UpperCamelCase : Callable... | 106 | 0 |
"""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,
res... | 19 |
import unittest
from queue import Empty
from threading import Thread
from transformers import AutoTokenizer, TextIteratorStreamer, TextStreamer, is_torch_available
from transformers.testing_utils import CaptureStdout, require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_availabl... | 106 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_code
from ...image_... | 20 |
import math
import sys
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
A = ''
try:
with open(lowerCAmelCase__ , 'rb' ) as binary_file:
A = binary_file.read()
... | 106 | 0 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class __A ( UpperCamelCase__ ... | 21 |
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTokenizer,
AutoTokenize... | 106 | 0 |
'''simple docstring'''
from argparse import ArgumentParser
from .env import EnvironmentCommand
def snake_case_ ():
'''simple docstring'''
_a = ArgumentParser('''Diffusers CLI tool''' , usage='''diffusers-cli <command> [<args>]''' )
_a... | 22 |
import os
import time
import numpy as np
import onnxruntime as ort
__snake_case :Any ='1'
__snake_case :List[str] ='0'
__snake_case :Union[str, Any] ='1'
__snake_case :Optional[Any] =ort.SessionOptions()
__snake_case :List[str] =ort.GraphOptimizat... | 106 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
snake_case__ : Optional[Any] = {"""tokenization_herbert""": ["""HerbertTokenizer"""]}
try:
if not is_tokenizers_available():
raise OptionalDepende... | 23 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Optional[Any] =logging.get_logger(__name__)
__snake_case :Tuple ={
'transfo-xl-wt103': 'https://huggingface.co/transfo-xl-wt103/resolve/main/config.json',
}
class lowerCAmelCase_... | 106 | 0 |
'''simple docstring'''
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class lowerCAmelCase ( __lowerCAmelCase):
@staticmethod
@abstractmethod
def lowerCAmelCase ( __SCREAMING_SNAKE_CASE ) -> Dict:
'''simple docstring'''
... | 24 |
import re
def lowerCamelCase_ ( lowerCAmelCase__ : str ) -> str:
'''simple docstring'''
if len(re.findall('[ATCG]' , lowerCAmelCase__ ) ) != len(lowerCAmelCase__ ):
raise ValueError('Invalid Strand' )
return dna.translate(dna.maketr... | 106 | 0 |
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 BasicTransformerBlock
from .attention_processor import ... | 25 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_t... | 106 | 0 |
'''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order... | 26 |
from collections.abc import Sequence
def lowerCamelCase_ ( lowerCAmelCase__ : Sequence[int] | None = None ) -> int:
'''simple docstring'''
if nums is None or not nums:
raise ValueError('Input sequence should not be empty' )
A = n... | 106 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__A : List[str] = {
"configuration_tapas": ["TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP", "TapasConfig"],
"tokenization_tapas": ["TapasTokenizer... | 27 |
from typing import List
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : dict ) -> int:
'''simple docstring'''
A = {key: len(lowerCAmelCase__ ) for key, value in gen_kwargs.items() if isinstance(lowerCAmelCase__ , lowerCAmelCase__ )}
... | 106 | 0 |
'''simple docstring'''
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
UpperCamelCase_ = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understand... | 28 |
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCAmelCase__ ( unittest.TestCase ):
def __UpperCamelCase ( self : List[str] ) -> Any:
A = [
'safety_checker/pytorch_model... | 106 | 0 |
"""simple docstring"""
import inspect
import os
import unittest
from dataclasses import dataclass
import torch
from accelerate import Accelerator, DistributedDataParallelKwargs, GradScalerKwargs
from accelerate.state import AcceleratorState
from accelerate.test_utils import execute_subprocess_async, require_cuda, ... | 29 |
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
__snake_case :Any =None
try:
import msvcrt
except ImportError:
__snake_case :Union[str, Any] =None
try:
import fcntl
except ImportError:
__snake_case :str ... | 106 | 0 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
__a = 'scheduler_config.json'
class __a( _a ):
"""simple docstring"""
lowerCAmelCase = 1
... | 30 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :List[str] =logging.get_logger(__name__)
__snake_case :int ={'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class lowerCAmelCase__ ( _lowerCamelCase ... | 106 | 0 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCAmelCase__ ( _lowerCamelCase , unittest.TestCase ):
A_ : int = CTRLTok... | 106 | 0 |
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=A__ )
class __UpperCamelCase ( A__ ):
__A : str = field(default="""automatic-speech-recogniti... | 32 |
from collections.abc import Callable
import numpy as np
def lowerCamelCase_ ( lowerCAmelCase__ : Callable , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float , lowerCAmelCase__ : float ) -> np.array:
'''simple docstring'''
A ... | 106 | 0 |
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
lowerCamelCase__ : List[str] = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any mem... | 33 |
__snake_case :Any =256
# Modulus to hash a string
__snake_case :Optional[int] =1000003
def lowerCamelCase_ ( lowerCAmelCase__ : str , lowerCAmelCase__ : str ) -> bool:
'''simple docstring'''
A = len(lowerCAmelCase__ )
... | 106 | 0 |
"""simple docstring"""
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
SCREAMING_SNAKE_CASE_ = np.linspace(start=0, stop=75, num=75, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any member... | 34 |
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
UNetaDConditionModel,
VideoToVideoSDPipeline,
)
from diffusers.utils import floats_tensor, is_xformers_available... | 106 | 0 |
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
a_ :Any = '<<<<<<< This should probably be modified because it mentions: '
a_ :int = '=======\n>>>>>>>\n'
a_ :Di... | 35 |
from bisect import bisect
from itertools import accumulate
def lowerCamelCase_ ( lowerCAmelCase__ : int , lowerCAmelCase__ : str , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[Any] ) -> Union[str, Any]:
'''simple docstring'''
A = sorted(z... | 106 | 0 |
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
... | 36 |
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
__snake_case :str =False
class lowerCAmelCase__ ( unittest.TestCas... | 106 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transformers import BitConfig, B... | 37 |
import os
import time
from dataclasses import dataclass, field
from enum import Enum
from typing import Dict, List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...models.auto.modeling_auto import MODEL_FOR_QUESTION_ANSWERING_MAPPING
from ...tokenization_uti... | 106 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
A_ : Union[str, Any] = {"configur... | 38 |
import argparse
from collections import defaultdict
def lowerCamelCase_ ( lowerCAmelCase__ : List[str] , lowerCAmelCase__ : List[str] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : List[str] ) -> Union[str, Any]:
'''simple docstring'''
... | 106 | 0 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
lowerCAmelCase_ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow('''''', '''|''', ... | 39 |
import json
import os
import unittest
from transformers.models.gptsan_japanese.tokenization_gptsan_japanese import (
VOCAB_FILES_NAMES,
GPTSanJapaneseTokenizer,
)
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokeni... | 106 | 0 |
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