code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
__a = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
import dataclasses # noqa
impor... | 145 |
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
class S... | 282 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_si... | 202 |
from __future__ import annotations
from typing import Any
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : Tuple , lowercase : int , lowercase : int , lowercase : float = 0 ):
'''simple docstring'''
_snake_case , _snake_case = row... | 282 | 0 |
'''simple docstring'''
def UpperCamelCase( UpperCAmelCase_ ):
UpperCAmelCase : int = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function' )
UpperCAmelCase : int = hex_num[0] == '-'
if is_negative:
UpperCAmelCase : U... | 151 |
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
_lowerCamelCase : Dict = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE__ ( UpperCAmelCase ):
'''simple docstring'''
def __init__( self : Tuple ,... | 282 | 0 |
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __a :
__lowercase : int
__lowercase : int
class __a :
def __init__( self , lowerCAmelCase__ ) -> ... | 196 |
def a_ ( __lowercase : str ) -> int:
_snake_case = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function' )
_snake_case = hex_num[0] == '-'
if is_negative:
_snake_case = hex_num[1:]
try:
_snake_case = int(__lowercase ... | 282 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
__SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
class lowerCamelCase_ (snake_case__ ):
'''simple docstring'''
def __init__( ... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenization_u... | 282 | 0 |
_lowerCAmelCase : Optional[Any] = [sum(int(c, 10) ** 2 for c in i.__str__()) for i in range(100_000)]
def __snake_case ( _lowerCAmelCase : int ) -> int:
A_ : Any = 0
while number:
# Increased Speed Slightly by checking every 5 digits together.
... | 300 |
import os
from typing import Any, Callable, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from ...models.controlnet import ControlNetModel, ControlNetOutput
from ...models.modeling_utils import ModelMixin
from ...utils import logging
_lowerCamelCase : List[str] = logging.get... | 282 | 0 |
"""simple docstring"""
from collections.abc import Sequence
def _snake_case ( lowercase__ , lowercase__ ):
return sum(c * (x**i) for i, c in enumerate(__lowercase ) )
def _snake_case ( lowercase__ , lowercase__ ):
_... | 96 |
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
def __init__( self : List[str] , lowercase : list[int] ):
'''simple docstring'''
_snake_case = len(lowercase )
_snake_case = [0] * len_array
if len_array > 0:
_snake_case = array[0]
for i in range... | 282 | 0 |
"""simple docstring"""
from typing import List
from .keymap import KEYMAP, get_character
def _snake_case ( snake_case__ : str ):
def decorator(snake_case__ : Optional[Any] ):
A = getattr(__lowercase , 'handle_key' , [] )
handle += [key]
setattr(__low... | 74 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class SCREAMING_SNAKE_CASE__ ( nn.Module ):
'''simple docstring'''
def __init__( self : Optional[int] , lowercase : int = 16 , lowercase : int = 88 , l... | 282 | 0 |
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=__lowerCamelCase ):
'''simple docstring'''
lowerCAmelCase__ = ["torch"]
def __init__( self : Dict , *A : Optional[Any] , **A : Tupl... | 111 |
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
@require_torch
@require_optimum
@slow
class SCREAMING_SNA... | 282 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_pr... | 109 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
_lowerCamelCase : List[Any] = HfApi()
_lowerCamelCase : Dict = {}
# fmt: off
_lowerCamelCase : List[Any] = torch.tensor([
-0.7_5_1_5, -1.6_8_8_3, 0.2_4_2_0, 0.0_3_0... | 282 | 0 |
"""simple docstring"""
def UpperCamelCase ( UpperCAmelCase ) ->int:
"""simple docstring"""
if not numbers:
return 0
if not isinstance(__lowercase , (list, tuple) ) or not all(
isinstance(__lowercase , __lowercase ) for number in numbers ):
raise V... | 243 |
import inspect
import unittest
from transformers import MobileNetVaConfig
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_configuration_common import ConfigTester
from ...test... | 282 | 0 |
'''simple docstring'''
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class A__ ... | 145 |
import argparse
import pickle
import numpy as np
import torch
from torch import nn
from transformers import ReformerConfig, ReformerModelWithLMHead
from transformers.utils import logging
logging.set_verbosity_info()
def a_ ( __lowercase : Dict , __lowercase : int , __low... | 282 | 0 |
"""simple docstring"""
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_A : int = False
class a__ ( unittest.TestCase ):... | 202 |
import argparse
import os
import shutil
import torch
from emmental.modules import MagnitudeBinarizer, ThresholdBinarizer, TopKBinarizer
def a_ ( __lowercase : Dict ) -> List[Any]:
_snake_case = args.pruning_method
_snake_case = args.threshold
_snake_case = args.model_name_or_... | 282 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowercase__ = {
'''configuration_gpt_neo''': ['''GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoConfig''', '''GPTNeoOnnxConfig''... | 151 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class SCREAMING_SNAKE_CASE__ :
'''simple docstring'''
@property
def A ( sel... | 282 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __a ( __UpperCamelCase ):
def __init__( self , lowerCAmelCase__ ... | 196 |
_lowerCamelCase : int = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase : str = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
_lowerCamelCase : List[str] = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''Thursday''',
... | 282 | 0 |
'''simple docstring'''
import logging
import math
import os
from dataclasses import dataclass, field
from glob import glob
from typing import Optional
from torch.utils.data import ConcatDataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_WITH_LM_HEAD_MAPPING,
AutoConfig,
A... | 31 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
_lowerCamelCase : int = False
class SCREAMING_SNAKE_CASE__ ( unittest.TestCase ):
'''simple... | 282 | 0 |
import comet # From: unbabel-comet
import torch
import datasets
_lowerCAmelCase : Union[str, Any] = datasets.logging.get_logger(__name__)
_lowerCAmelCase : List[Any] = '''\
@inproceedings{rei-EtAl:2020:WMT,
author = {Rei, Ricardo and Stewart, Craig and Farinha, Ana C... | 300 |
import numpy as np
def a_ ( __lowercase : np.array ) -> np.array:
return 1 / (1 + np.exp(-vector ))
if __name__ == "__main__":
import doctest
doctest.testmod() | 282 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self , lowercase=2 , lower... | 96 |
import unittest
from transformers import AutoTokenizer, is_flax_available
from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, slow
if is_flax_available():
import jax.numpy as jnp
from transformers import FlaxXLMRobertaModel
@require_sentencepiece
@require_token... | 282 | 0 |
"""simple docstring"""
from sklearn.metrics import mean_squared_error
import datasets
_lowercase = '''\
@article{scikit-learn,
title={Scikit-learn: Machine Learning in {P}ython},
author={Pedregosa, F. and Varoquaux, G. and Gramfort, A. and Michel, V.
and Thirion, B. and Grisel, O. and Blond... | 74 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokenizer
else:
_lowerCamelCase ... | 282 | 0 |
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {'''vocab_file''': '''vocab.json'''}
_snake_case = {... | 283 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',... | 283 | 1 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
fro... | 283 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''edbeeching/decision-transformer-gym-hopper-medium''': (
'''https://huggingface.co/edbeeching/decision-transformer-gy... | 283 | 1 |
def lowercase_( ):
'''simple docstring'''
lowerCamelCase : Optional[int] = []
lowerCamelCase : List[str] = 1
while len(SCREAMING_SNAKE_CASE_ ) < 1E6:
constant.append(str(SCREAMING_SNAKE_CASE_ ) )
i += 1
lowerCamelCase : Union[str, Any] = "".join(... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 4000000 ):
'''simple docstring'''
lowerCamelCase : Any = [0, 1]
lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
lowerCamelCase : Un... | 283 | 1 |
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_transformers.c... | 283 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''Vi... | 283 | 1 |
import math
import numpy as np
import qiskit
from qiskit import Aer, ClassicalRegister, QuantumCircuit, QuantumRegister, execute
def lowercase_( SCREAMING_SNAKE_CASE_ = 3 ):
'''simple docstring'''
if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
raise ... | 283 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_snake_case = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm'... | 283 | 1 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase : Dict = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 283 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 283 | 1 |
import requests
_snake_case = '''''' # <-- Put your OpenWeatherMap appid here!
_snake_case = '''https://api.openweathermap.org/data/2.5/'''
def lowercase_( SCREAMING_SNAKE_CASE_ = "Chicago" , SCREAMING_SNAKE_CASE_ = APPID ):
'''simple docstring... | 283 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stab... | 283 | 1 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILIm... | 283 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''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 not...''')
_snake_case = ... | 283 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_snake_case = 2_99_79_24_58
# Symbols
_snake_case , _snake_case , _snake_case , _snake_case = symbols('''ct x y z''')
d... | 283 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/resolve/main/config.json''',
}
class U... | 283 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
def __init__( self , *__A , **__A ):... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 3 , SCREAMING_SNAKE_CASE_ = 7 , SCREAMING_SNAKE_CASE_ = 1000000 ):
'''simple docstring'''
lowerCamelCase : str = 0
lowerCamelCase : str = 1
for current_denominator in range(1 , limit + 1 ):
lowerC... | 283 |
import argparse
_snake_case = '''docs/source/_static/js/custom.js'''
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
with open(SCREAMING_SNAKE_CASE_ , encoding="utf-8" , newline="\n" ) as f:
lowerCamelCase : List[str] ... | 283 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple
import torch
from torch import nn
from transformers import RobertaPreTrainedModel, XLMRobertaConfig, XLMRobertaModel
from transformers.utils import ModelOutput
@dataclass
class UpperCAmelCase_ ( UpperCamelCase ):
'''si... | 283 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : Any = ["flax"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 | 1 |
import math
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Any = []
lowerCamelCase : int = 2
lowerCamelCase : Dict = int(math.sqrt(SCREAMING_SNAKE_CASE_ ) ) # Size of every segment
lowerCamelCase : Dict = ... | 283 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 10 ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) or n < 0:
raise ValueError("Invalid input" )
lowerCamelCase : int = 10**n
lowerCamelCase : Optional[int] = 28433 * (pow(2 ... | 283 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase : Dict = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 283 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCAmelCase_ ( ... | 283 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Optional[int] = "M-CLIP"
def __init__( self , __A=1024 , __A=768 , **... | 283 | 1 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowercase_( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAM... | 283 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 283 | 1 |
from __future__ import annotations
import math
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if num <= 0:
lowerCamelCase : List[str] = f"""{num}: Invalid input, please enter a positive integer."""
raise ValueError(SCREAMING_SNAKE_CASE_ )
lo... | 283 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase_ ( UpperCamelCase , unittest.TestCas... | 283 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_cas... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowerCamelCase : List[Any] = 1
lowerCamelCase : Union[str, Any] = 1
while repunit:
lowerCamelCase : Union[str, Any] = (10 * repunit + 1)... | 283 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=UpperCamelCase )
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : str ... | 283 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILIm... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 10 , SCREAMING_SNAKE_CASE_ = 22 ):
'''simple docstring'''
lowerCamelCase : Dict = range(1 , SCREAMING_SNAKE_CASE_ )
lowerCamelCase : Dict = range(1 , SCREAMING_SNAKE_CASE_ )
return sum(
1 for powe... | 283 |
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 UpperCAmelCase_ ( UpperCamelCase ):
'''simpl... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Union[str, Any] = ""
for i in table:
res += inp[i - 1]
return res
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
retur... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
for i in range(len(SCREAMING_SNAKE_CASE_ ) - 1 , 0 , -1 ):
lowerCamelCase : Tuple = False
for j in range(SCREAMING_SNAKE_CASE_ , 0 , -1 ):
if unsorted[j] < unsorted[j... | 283 | 1 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case =... | 283 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
fro... | 283 | 1 |
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
_snake_case = WebClient(token=os.environ['''CI_SLACK_BOT_TOKEN'''])
def lowercase_( SCREAMI... | 283 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',... | 283 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 283 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''edbeeching/decision-transformer-gym-hopper-medium''': (
'''https://huggingface.co/edbeeching/decision-transformer-gy... | 283 | 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 lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 4000000 ):
'''simple docstring'''
lowerCamelCase : Any = [0, 1]
lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
lowerCamelCase : Un... | 283 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
_snake_case = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
pass
el... | 283 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''Vi... | 283 | 1 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : List[Any] = ["torch"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_snake_case = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm'... | 283 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOut... | 283 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 283 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/conf... | 283 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stab... | 283 | 1 |
import argparse
import copy
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : int = {}
with open(SCREAMING_SNAKE_CASE_ ) as f:
for line in f:
if line.split()[0] not in dict_of_neighbours:
lowerCamelCase : Optional[... | 283 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
... | 283 | 1 |
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class UpperCAmelCase_ ( unittest.TestCase ):
'''simple docstring'''
def _snake_case ( self ):
"""simple docstring"""... | 283 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_snake_case = 2_99_79_24_58
# Symbols
_snake_case , _snake_case , _snake_case , _snake_case = symbols('''ct x y z''')
d... | 283 | 1 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
def __init__( self , *__A , **__A ):... | 283 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
def __init__( self , *__A , **__A ):... | 283 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A... | 283 |
import argparse
_snake_case = '''docs/source/_static/js/custom.js'''
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
with open(SCREAMING_SNAKE_CASE_ , encoding="utf-8" , newline="\n" ) as f:
lowerCamelCase : List[str] ... | 283 | 1 |
from __future__ import annotations
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Dict = str(SCREAMING_SNAKE_CASE_ )
return n == n[::-1]
def lowercase_( SCREAMING_SNAKE_CASE_ = 1000000 ):
'''simple docstring'''
... | 283 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : Any = ["flax"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 | 1 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
_snake_case = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
'''>'... | 283 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 283 | 1 |
import re
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if len(re.findall("[ATCG]" , SCREAMING_SNAKE_CASE_ ) ) != len(SCREAMING_SNAKE_CASE_ ):
raise ValueError("Invalid Strand" )
return dna.translate(dna.maketrans("ATCG" , "TAGC" ) )
... | 283 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase : Dict = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 283 | 1 |
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Optional[int] = FileLock(str(tmpdir / "foo.lock" ) )
lowerCamelCase : Optional[int] = ... | 283 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Optional[int] = "M-CLIP"
def __init__( self , __A=1024 , __A=768 , **... | 283 | 1 |
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, PegasusConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common i... | 283 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 283 | 1 |
from typing import List
from .keymap import KEYMAP, get_character
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
def decorator(SCREAMING_SNAKE_CASE_ ):
lowerCamelCase : List[Any] = getattr(SCREAMING_SNAKE_CASE_ , "handle_key" , [] ... | 283 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase_ ( UpperCamelCase , unittest.TestCas... | 283 | 1 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fn... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowerCamelCase : List[Any] = 1
lowerCamelCase : Union[str, Any] = 1
while repunit:
lowerCamelCase : Union[str, Any] = (10 * repunit + 1)... | 283 | 1 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_snake_case = get_tests_dir('''fixtures/test_sen... | 283 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILIm... | 283 | 1 |
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
... | 283 |
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 UpperCAmelCase_ ( UpperCamelCase ):
'''simpl... | 283 | 1 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : int = (UnCLIPScheduler,)
def _snake_case ( self , **__A ):
... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
for i in range(len(SCREAMING_SNAKE_CASE_ ) - 1 , 0 , -1 ):
lowerCamelCase : Tuple = False
for j in range(SCREAMING_SNAKE_CASE_ , 0 , -1 ):
if unsorted[j] < unsorted[j... | 283 | 1 |
from __future__ import annotations
import queue
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , __A ):
"""simple docstring"""
lowerCamelCase : Dict = data
lowerCamelCase : int = None
lowerCame... | 283 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
fro... | 283 | 1 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Optional[int] = "M-CLIP"
def __init__( self , __A=1024 , __A=768 , **... | 283 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',... | 283 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_snake_case = {
'''configuration_ctrl''': ['''CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''CTRLConfig'''],
'''tokenization_ctrl''': ['''CTRLTokenize... | 283 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''edbeeching/decision-transformer-gym-hopper-medium''': (
'''https://huggingface.co/edbeeching/decision-transformer-gy... | 283 | 1 |
import requests
from bsa import BeautifulSoup
def lowercase_( SCREAMING_SNAKE_CASE_ = "AAPL" ):
'''simple docstring'''
lowerCamelCase : Union[str, Any] = f"""https://in.finance.yahoo.com/quote/{symbol}?s={symbol}"""
lowerCamelCase : List[Any] = BeautifulSoup(req... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 4000000 ):
'''simple docstring'''
lowerCamelCase : Any = [0, 1]
lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
lowerCamelCase : Un... | 283 | 1 |
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version import Version
_s... | 283 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''Vi... | 283 | 1 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : Any = ["flax"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_snake_case = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm'... | 283 | 1 |
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowercase_( SCREAMIN... | 283 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 283 | 1 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 283 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stab... | 283 | 1 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.fea... | 283 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
... | 283 | 1 |
from typing import List
import numpy as np
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Any = {key: len(SCREAMING_SNAKE_CASE_ ) for key, value in gen_kwargs.items() if isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ )}... | 283 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_snake_case = 2_99_79_24_58
# Symbols
_snake_case , _snake_case , _snake_case , _snake_case = symbols('''ct x y z''')
d... | 283 | 1 |
import numpy as np
from cva import destroyAllWindows, imread, imshow, waitKey
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , __A , __A , __A ):
"""simple docstring"""
if dst_width < 0 or dst_height < 0:
... | 283 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
def __init__( self , *__A , **__A ):... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
return "".join(chr(ord(SCREAMING_SNAKE_CASE_ ) - 32 ) if "a" <= char <= "z" else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 283 |
import argparse
_snake_case = '''docs/source/_static/js/custom.js'''
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
with open(SCREAMING_SNAKE_CASE_ , encoding="utf-8" , newline="\n" ) as f:
lowerCamelCase : List[str] ... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase , lowerCamelCase : Any = [], []
while len(SCREAMING_SNAKE_CASE_ ) > 1:
lowerCamelCase , lowerCamelCase : Optional[Any] = min(SCREAMING_SNAKE_CASE_ ), max(SCREAMING_SNAKE_CASE_ )
sta... | 283 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : Any = ["flax"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : Optional[Any] = len(SCREAMING_SNAKE_CASE_ )
lowerCamelCase : List[Any] = sum(SCREAMING_SNAKE_CASE_ )
lowerCamelCase : Tuple = [[False for x in range(s + 1 )] for y in range(n + 1 )... | 283 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 283 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''google/switch-base-8''': '''https://huggingface.co/google/switch-base-8/blob/main/config.json''',
}
class UpperCAmelCase_ ... | 283 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase : Dict = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 283 | 1 |
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring... | 283 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Optional[int] = "M-CLIP"
def __init__( self , __A=1024 , __A=768 , **... | 283 | 1 |
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , __A ):
"""simple docstring"""
lowerCamelCase : Optional[Any] = set_counts
lowerCamelCase : List[str] = max(__A )
lowerCamelCase : Optional[Any] ... | 283 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vision
from transform... | 283 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''Vi... | 283 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase_ ( UpperCamelCase , unittest.TestCas... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if not isinstance(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) or number < 0:
raise ValueError("Input must be a non-negative integer" )
lowerCamelCase : Dict = 0
while number:
# This way we arri... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
lowerCamelCase : List[Any] = 1
lowerCamelCase : Union[str, Any] = 1
while repunit:
lowerCamelCase : Union[str, Any] = (10 * repunit + 1)... | 283 | 1 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_snake_case = 2_99_79_24_58
# Symbols
_snake_case , _snake_case , _snake_case , _snake_case = symbols('''ct x y z''')
d... | 283 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils import PILIm... | 283 | 1 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import To... | 283 |
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 UpperCAmelCase_ ( UpperCamelCase ):
'''simpl... | 283 | 1 |
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e)
warnings.warn(
'''The co... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
for i in range(len(SCREAMING_SNAKE_CASE_ ) - 1 , 0 , -1 ):
lowerCamelCase : Tuple = False
for j in range(SCREAMING_SNAKE_CASE_ , 0 , -1 ):
if unsorted[j] < unsorted[j... | 283 | 1 |
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require_tokenizers
@require... | 283 |
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
UNetaDConditionModel,
)
fro... | 283 | 1 |
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_ten... | 283 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_snake_case = {
'''configuration_squeezebert''': [
'''SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''SqueezeBertConfig''',... | 283 | 1 |
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCAmelCase_ ( yaml.SafeLoader ):
'''simple docstring'''
def _snake_case ( self , __A ):
"""simple docstring"""
lowerCa... | 283 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
'''edbeeching/decision-transformer-gym-hopper-medium''': (
'''https://huggingface.co/edbeeching/decision-transformer-gy... | 283 | 1 |
import argparse
import json
import numpy
import torch
from transformers.models.xlm.tokenization_xlm import VOCAB_FILES_NAMES
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowercase_( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAK... | 283 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 4000000 ):
'''simple docstring'''
lowerCamelCase : Any = [0, 1]
lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
lowerCamelCase : Un... | 283 | 1 |
import os
from typing import Optional
import fsspec
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Optional[int] = ""
__A : str =... | 283 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_snake_case = {
'''configuration_vision_encoder_decoder''': ['''VisionEncoderDecoderConfig''', '''Vi... | 283 | 1 |
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 UpperCAmelCase_ ( UpperCamelCase , UpperCamelC... | 283 |
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_snake_case = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
parser.add_argument('''--dpm'... | 283 | 1 |
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 specific notes:
# - tqdm must be checked... | 283 |
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 283 | 1 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stab... | 283 |
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.pipeline_stab... | 283 | 1 |
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, InputFeatures, SingleSentenceClass... | 283 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_snake_case = logging.get_logger(__name__)
_snake_case = {
... | 283 | 1 |
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class Uppe... | 283 |
from math import sqrt
import numpy as np
from sympy import symbols
# Coefficient
# Speed of light (m/s)
_snake_case = 2_99_79_24_58
# Symbols
_snake_case , _snake_case , _snake_case , _snake_case = symbols('''ct x y z''')
d... | 283 | 1 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : str = SwinConfig(image_size=192 )
... | 283 |
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
_snake_case = logging.get_logger(__name__)
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
def __init__( self , *__A , **__A ):... | 283 | 1 |
import numpy
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self , __A , __A ):
"""simple docstring"""
lowerCamelCase : Dict = input_array
# Random initial weights are assigned where first argument is the
... | 283 |
import argparse
_snake_case = '''docs/source/_static/js/custom.js'''
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
with open(SCREAMING_SNAKE_CASE_ , encoding="utf-8" , newline="\n" ) as f:
lowerCamelCase : List[str] ... | 283 | 1 |
def lowercase_( SCREAMING_SNAKE_CASE_ = 4000000 ):
'''simple docstring'''
lowerCamelCase : Any = [0, 1]
lowerCamelCase : Union[str, Any] = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
lowerCamelCase : Un... | 283 |
from ..utils import DummyObject, requires_backends
class UpperCAmelCase_ ( metaclass=UpperCamelCase ):
'''simple docstring'''
__A : Any = ["flax"]
def __init__( self , *__A , **__A ):
"""simple docstring"""
... | 283 | 1 |
import warnings
from functools import wraps
from typing import Callable
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
@wraps(SCREAMING_SNAKE_CASE_ )
def _inner_fn(*SCREAMING_SNAKE_CASE_ , **SCREAMING_SNAKE_CASE_ ):
warnings.warn(
(f"""'{fn... | 283 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless re... | 283 | 1 |
import argparse
import os
import re
import packaging.version
_snake_case = '''examples/'''
_snake_case = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(R'''^_... | 283 |
import argparse
import torch
from transformers import YosoConfig, YosoForMaskedLM
def lowercase_( SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
if "model" in orig_key:
lowerCamelCase : Dict = orig_key.replace("model." , "" )
if "norm1" in orig_key:
... | 283 | 1 |
import colorsys
from PIL import Image # type: ignore
def lowercase_( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
'''simple docstring'''
lowerCamelCase : List[str] = x
lowerCamelCase : List[str] = y
for step ... | 283 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class UpperCAmelCase_ ( UpperCamelCase ):
'''simple docstring'''
__A : Optional[int] = "M-CLIP"
def __init__( self , __A=1024 , __A=768 , **... | 283 | 1 |
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