code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN mode... | 358 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_commo... | 297 | 0 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class __lowerCamelCase ( __A ):
"""simple docstring"""
def __init__( self , *UpperCAmelCase , **Up... | 359 |
# 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 applic... | 297 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''simple docstring'''
def is_in_circle(__lowerCamelCase: float , __lowerCamelCase: float ... | 360 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __lowerCamelCase ( snake_case_ , snake_case_ ):
"""s... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int = 1000 ):
'''simple docstring'''
return sum(e for e in range(3 , lowerCAmelCase__ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"""{solution() = }""")
| 361 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , ):
'''simple docstring'''
lowercase_ = [redshift, radiation_density, matt... | 297 | 0 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name... | 362 |
import sys
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] ):
'''simple docstring'''
lowercase_ = len(__lowerCamelCase )
lowercase_ = [[0 for x in range(__lowerCamelCase )] for x in range(__lowerCamelCase )]
lowercase_ = [[0 ... | 297 | 0 |
import argparse
import gdown
import numpy as np
import torch
from huggingface_hub import hf_hub_download
from transformers import (
CLIPTokenizer,
CLIPTokenizerFast,
VideoMAEImageProcessor,
XCLIPConfig,
XCLIPModel,
XCLIPProcessor,
XCLIPTextConfig,
XCLIPVisionConfig,
)
def SCREAM... | 363 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float ):
'''simple docstring'''
return 10 - x * x
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float ):
'''simple docstring'''
if equation(__lowerCamelCase ... | 297 | 0 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
SCREAMING_SNAKE_CASE__ = transfor... | 364 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"""vocab_file""": """vocab.txt"... | 297 | 0 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""asapp/sew-d-tiny-100k""": """https://huggingface.co/asapp/sew-d-tiny-100k/resolve/main/config... | 365 |
from scipy.stats import pearsonr
import datasets
SCREAMING_SNAKE_CASE__ = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that ea... | 297 | 0 |
from ..utils import DummyObject, requires_backends
class __lowerCamelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowerCAmelCase__ = ["note_seq"]
def __init__( self , *UpperCAmelCase , **UpperCAmelCase ) ... | 366 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self ) -> int:
'''simple docstring'''
... | 297 | 0 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress... | 367 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.tes... | 297 | 0 |
import random
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''simple docstring'''
lowercase_ = num - 1
lowercase_ = 0
while s % 2 == 0:
lowercase_ = s // 2
t += 1
for _ in range(5 ):
lowercase_ = random.randrange(2 , num -... | 368 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''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..... | 297 | 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_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenizer, ... | 369 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 297 | 0 |
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 transformers.utils impor... | 370 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Tuple ):
'''simple docstring'''
for i in range(0 , UpperCAmelCase__ ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(" " , end="" )
for _ in range(0 , i + 1 ... | 371 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ... | 297 | 0 |
"""simple docstring"""
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __lowerCamelCase ( __lowercase , __lowercase ):
"""simple docstring"""
@register_to_config
def __... | 350 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(__lowerCamelCase , __lowerCamelCase ):
raise TypeError("Input value must be a 'int' type" )... | 297 | 0 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__... | 351 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __lowerCamel... | 297 | 0 |
"""simple docstring"""
from bisect import bisect
from itertools import accumulate
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: str , __lowerCamelCase: str , __lowerCamelCase: List[str] , __lowerCamelCase: int ):
'''simple docstring'''
lower... | 352 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self , UpperCAmelCase ) -> float:... | 297 | 0 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,
... | 353 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
SCREAMING_... | 297 | 0 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE__ = logging.get_logger("""transformers.models.speecht5""")
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optiona... | 354 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUn... | 297 | 0 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS
loggi... | 355 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __lowerCamelCase ( snake_case_ ... | 297 | 0 |
from typing import Dict
from .base import GenericTensor, Pipeline
class __lowerCamelCase ( __UpperCamelCase ):
"""simple docstring"""
def A__ ( self , UpperCAmelCase=None , UpperCAmelCase=None , UpperCAmelCase=None , **UpperCAmelCase ) ... | 356 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 297 | 0 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class __lowerCamelCase ( __lowerCamelCase ):
"""simple docstring"""
@require_torch
def A__ ... | 357 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 297 | 0 |
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
import torch
import torch.... | 358 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_commo... | 297 | 0 |
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
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"hus... | 359 |
# 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 applic... | 297 | 0 |
from __future__ import annotations
SCREAMING_SNAKE_CASE__ = []
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: list[list[int]] , __lowerCamelCase: int , __lowerCamelCase: int ):
'''simple docstring'''
for i in range(len(lowerCAmelCase__ ) ... | 360 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __lowerCamelCase ( snake_case_ , snake_case_ ):
"""s... | 297 | 0 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(""">=""", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoin... | 361 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , ):
'''simple docstring'''
lowercase_ = [redshift, radiation_density, matt... | 297 | 0 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: str ):
... | 362 |
import sys
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] ):
'''simple docstring'''
lowercase_ = len(__lowerCamelCase )
lowercase_ = [[0 for x in range(__lowerCamelCase )] for x in range(__lowerCamelCase )]
lowercase_ = [[0 ... | 297 | 0 |
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_flax_available():
im... | 363 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float ):
'''simple docstring'''
return 10 - x * x
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float ):
'''simple docstring'''
if equation(__lowerCamelCase ... | 297 | 0 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from ... import... | 364 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"""vocab_file""": """vocab.txt"... | 297 | 0 |
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"voc... | 365 |
from scipy.stats import pearsonr
import datasets
SCREAMING_SNAKE_CASE__ = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that ea... | 297 | 0 |
import math
SCREAMING_SNAKE_CASE__ = 1_0
SCREAMING_SNAKE_CASE__ = 7
SCREAMING_SNAKE_CASE__ = BALLS_PER_COLOUR * NUM_COLOURS
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int = 20 ):
'''simple docstring'''
lowercase_ = math.comb(SCREAMING_SNA... | 366 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self ) -> int:
'''simple docstring'''
... | 297 | 0 |
from collections.abc import Generator
from math import sin
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: bytes ):
'''simple docstring'''
if len(UpperCamelCase__ ) != 32:
raise ValueError("Input must be of length 32" )
lowercase_ = ... | 367 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.tes... | 297 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_i... | 368 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''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..... | 297 | 0 |
import argparse
import dataclasses
import json
import logging
import os
import shutil
from typing import List, Optional
import datasets
from accelerate import Accelerator
from datasets import load_dataset
from finetuning import finetune
from tqdm.auto import tqdm
import transformers
from transformers import Auto... | 369 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 297 | 0 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: List[str] ):
'''simple docstring'''
if "img_encoder.pos_embed" in name:
lowercase_ = ... | 370 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:... | 297 | 0 |
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin... | 371 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ... | 297 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Union[str, Any] = 100 ):
'''simple docstring'''
lowercase_ = set()
lowercase_ = 0
lowercase_ = n + 1 # maximum limit
for a in range(2 , __lowerCAmelCase ):
for b in ra... | 350 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(__lowerCamelCase , __lowerCamelCase ):
raise TypeError("Input value must be a 'int' type" )... | 297 | 0 |
import argparse
import json
import os
import fairseq
import torch
from torch import nn
from transformers import (
SpeechaTextaConfig,
SpeechaTextaForCausalLM,
SpeechaTextaTokenizer,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
Wa... | 351 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __lowerCamel... | 297 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import NezhaConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...generation.test_utils import GenerationTe... | 352 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self , UpperCAmelCase ) -> float:... | 297 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
SCREAMING_SNAKE_CASE__ = pd.read_csv("""sample_data.csv""", header=None)
SCREAMING_SN... | 353 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
SCREAMING_... | 297 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"""configuration_sew""": ["""SEW_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SEWConfig"""]}
try:
if not is_torch_available():
raise OptionalDepend... | 354 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUn... | 297 | 0 |
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
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
'goo... | 355 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __lowerCamelCase ( snake_case_ ... | 297 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE__ = {"""configuration_swin""": ["""SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """SwinConfig""", """SwinOnnxConfig"""]}
try:
if not is_torch_avai... | 356 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 297 | 0 |
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
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .modeling_utils import... | 357 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 297 | 0 |
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
SCREAMING_SNAKE_CASE__ = logging.getLogger(__name__)
class __lowerCamelCase ( lowerCamelCase__ ):
"""simpl... | 358 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_commo... | 297 | 0 |
from functools import reduce
SCREAMING_SNAKE_CASE__ = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'668966489504452445... | 359 |
# 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 applic... | 297 | 0 |
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils import DUMMY_UNKNOWN_IDENT... | 360 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __lowerCamelCase ( snake_case_ , snake_case_ ):
"""s... | 297 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class __lowerCamelCase ( __lowercase ):
"""simple docstring"""
lowerCAmelCase__ = '''encoder-decode... | 361 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , ):
'''simple docstring'''
lowercase_ = [redshift, radiation_density, matt... | 297 | 0 |
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int , __lowerCamelCase: int=() , __lowerCamelCase: s... | 362 |
import sys
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] ):
'''simple docstring'''
lowercase_ = len(__lowerCamelCase )
lowercase_ = [[0 for x in range(__lowerCamelCase )] for x in range(__lowerCamelCase )]
lowercase_ = [[0 ... | 297 | 0 |
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.features import Ar... | 363 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float ):
'''simple docstring'''
return 10 - x * x
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float ):
'''simple docstring'''
if equation(__lowerCamelCase ... | 297 | 0 |
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:
SCREAMING_S... | 364 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"""vocab_file""": """vocab.txt"... | 297 | 0 |
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class __lowerCamelCase ( __snake_case , __snake_case ):
"""simple docstring"""
@register_to_conf... | 365 |
from scipy.stats import pearsonr
import datasets
SCREAMING_SNAKE_CASE__ = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that ea... | 297 | 0 |
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.generation import (
F... | 366 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self ) -> int:
'''simple docstring'''
... | 297 | 0 |
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
SCREAMING_SNAKE_CA... | 367 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.tes... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int , __lowerCamelCase: int ):
'''simple docstring'''
return int((input_a, input_a).count(0 ) == 0 )
def SCREAMING_SNAKE_CASE_ ( ):
'''simple docstring'''
assert and_gate(0 , 0 ... | 368 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''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..... | 297 | 0 |
from math import pi, sqrt
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[int] ):
'''simple docstring'''
if num <= 0:
raise ValueError("math domain error" )
if num > 171.5:
raise OverflowError("math range error" )
elif num - int(a__ ) not in (0,... | 369 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 297 | 0 |
from pathlib import Path
import json
import tempfile
from transformers import FSMTTokenizer, FSMTConfig, FSMTForConditionalGeneration
from transformers.models.fsmt.tokenization_fsmt import VOCAB_FILES_NAMES
SCREAMING_SNAKE_CASE__ = """tiny-wmt19-en-ru"""
# Build
# borrowed from a test
SCREAMING_SNAKE_CA... | 370 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:... | 297 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import KarrasVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __lowerCamelCase ( snake_case_ ):
... | 371 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ... | 297 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int = 100 ):
'''simple docstring'''
lowercase_ = (n * (n + 1) // 2) ** 2
lowercase_ = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(f""... | 350 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(__lowerCamelCase , __lowerCamelCase ):
raise TypeError("Input value must be a 'int' type" )... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: List[Any] ):
'''simple docstring'''
lowercase_ = []
lowercase_ = set({"(", "[", "{"} )
lowercase_ = set({")", "]", "}"} )
lowercase_ = {"{": "}", "[": "]", "(": ")"}
for i in range(len(_SCR... | 351 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __lowerCamel... | 297 | 0 |
"""simple docstring"""
import argparse
import json
import torch
from diffusers import DDPMScheduler, LDMPipeline, UNetaDModel, VQModel
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Dict , __lowerCamelCase: Any=1 ):
'''simple docstring'''
if n_shave_prefix_segme... | 352 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self , UpperCAmelCase ) -> float:... | 297 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependencyNotAv... | 353 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
SCREAMING_... | 297 | 0 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enabl... | 354 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUn... | 297 | 0 |
SCREAMING_SNAKE_CASE__ = "0.21.0"
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
fr... | 355 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __lowerCamelCase ( snake_case_ ... | 297 | 0 |
import collections
import importlib.util
import os
import re
from pathlib import Path
SCREAMING_SNAKE_CASE__ = 'src/transformers'
# Matches is_xxx_available()
SCREAMING_SNAKE_CASE__ = re.compile(R"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
SCREAMING_SNAKE_CASE__... | 356 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 297 | 0 |
from __future__ import annotations
import math
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: list , __lowerCamelCase: list ):
'''simple docstring'''
if len(lowercase_ ) != 2 or len(a[0] ) != 2 or len(lowercase_ ) != 2 or len(b[0] ) != 2:
ra... | 357 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 297 | 0 |
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("repo_id" , ["canonical_dataset_name", "org-name/dataset-name"] )
@pytest.mark.parametrize("path" , ["filename.csv", "filename with blanks.csv"] )
@pytest.mark.parametrize... | 358 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_commo... | 297 | 0 |
import fire
from utils import calculate_rouge, save_json
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] , __lowerCamelCase: Dict , __lowerCamelCase: Optional[int]=None , **__lowerCamelCase: str ):
'''simple docstring'''
lowercase_ ... | 359 |
# 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 applic... | 297 | 0 |
SCREAMING_SNAKE_CASE__ = 8.3144598
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float ):
'''simple docstring'''
if temperature < 0:
raise Exception("Temperature cannot be less than 0 K" )
if molar_mass <= 0:
raise Except... | 360 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __lowerCamelCase ( snake_case_ , snake_case_ ):
"""s... | 297 | 0 |
SCREAMING_SNAKE_CASE__ = 2_5_6
# Modulus to hash a string
SCREAMING_SNAKE_CASE__ = 1_0_0_0_0_0_3
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: str , __lowerCamelCase: str ):
'''simple docstring'''
lowercase_ = len(_a )
lowercase_ =... | 361 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , ):
'''simple docstring'''
lowercase_ = [redshift, radiation_density, matt... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int , __lowerCamelCase: str = " " ):
'''simple docstring'''
lowercase_ = []
lowercase_ = 0
for index, char in enumerate(__lowerCAmelCase ):
if char == separator:
split_words.append(string[last_inde... | 362 |
import sys
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] ):
'''simple docstring'''
lowercase_ = len(__lowerCamelCase )
lowercase_ = [[0 for x in range(__lowerCamelCase )] for x in range(__lowerCamelCase )]
lowercase_ = [[0 ... | 297 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
SCREAMING_SNAKE_CASE__ = get_logger(__name__)
class __lowerCamelCase ( enum.Enum):
"""simple docstring"""
lowerCAmelCase__ = ... | 363 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float ):
'''simple docstring'''
return 10 - x * x
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float ):
'''simple docstring'''
if equation(__lowerCamelCase ... | 297 | 0 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_S... | 364 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"""vocab_file""": """vocab.txt"... | 297 | 0 |
# This code is adapted from OpenAI's release
# https://github.com/openai/human-eval/blob/master/human_eval/execution.py
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Di... | 365 |
from scipy.stats import pearsonr
import datasets
SCREAMING_SNAKE_CASE__ = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that ea... | 297 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFlip,
... | 366 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self ) -> int:
'''simple docstring'''
... | 297 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.hugg... | 367 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.tes... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Tuple ):
'''simple docstring'''
if bit_count < 0:
raise ValueError("The given input must be positive" )
# get the generated string sequence
lowercase_ = gray_code_sequence_string(lowerCamelCase_ )
#
# convert them... | 368 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''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..... | 297 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMIN... | 369 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 297 | 0 |
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCamelCase ( _lowerCAmelCase ):
"""simple docstring"""
lowerCAmelCase__ = (UnCLIPScheduler,)
def A__ ( self , **U... | 370 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:... | 297 | 0 |
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
SCREAMING_SNAKE_CASE__ = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def SCREAMING_SNAKE_CASE_ ( ... | 371 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ... | 297 | 0 |
"""simple docstring"""
import json
import logging
import os
import sys
from time import time
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, require_torch_tpu
logging.basicConfig(level=logging.DEBUG)
SCREAMING_SNAKE_CASE__ = logging.getLogger()
def SCREAMING_... | 350 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''simple docstring'''
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(__lowerCamelCase , __lowerCamelCase ):
raise TypeError("Input value must be a 'int' type" )... | 297 | 0 |
import numpy as np
from matplotlib import pyplot as plt
from sklearn.datasets import load_iris
from sklearn.metrics import ConfusionMatrixDisplay
from sklearn.model_selection import train_test_split
from xgboost import XGBClassifier
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: dict ):
... | 351 |
from dataclasses import dataclass
from typing import Optional
import torch
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .modeling_utils import ModelMixin
@dataclass
class __lowerCamel... | 297 | 0 |
"""simple docstring"""
from math import ceil
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int = 1001 ):
'''simple docstring'''
lowercase_ = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
lowercase_ = 2 * i + 1
lowercase_ = 2... | 352 |
from __future__ import annotations
from math import pi
from typing import Protocol
import matplotlib.pyplot as plt
import numpy as np
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self , UpperCAmelCase ) -> float:... | 297 | 0 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: List[str] , __lowerCamelCase: Union[str, Any] ):
'''simple docstring'''
lowercase_ = [1]
for i in range(2 , __lowerCamelCase ):
factorials.append(factorials[-1] * i )
assert 0 <= k < factorials[-1... | 353 |
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_mvp import MvpTokenizer
SCREAMING_... | 297 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __lowerCamelCase ( lowercase_ ):
"""simple docstring"""
def __init__( self , UpperCAmelCase , UpperCAmelCase ) -> int:
'''simple docstring'''
... | 354 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableUn... | 297 | 0 |
import argparse
from transformers import BigBirdConfig, BigBirdForPreTraining, BigBirdForQuestionAnswering, load_tf_weights_in_big_bird
from transformers.utils import logging
logging.set_verbosity_info()
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Dict , __lowerCamelCase: Union[s... | 355 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __lowerCamelCase ( snake_case_ ... | 297 | 0 |
import baseaa
def SCREAMING_SNAKE_CASE_ ( _SCREAMING_SNAKE_CASE: str ):
'''simple docstring'''
return baseaa.baaencode(string.encode("utf-8" ) )
def SCREAMING_SNAKE_CASE_ ( _SCREAMING_SNAKE_CASE: bytes ):
'''simple docstring'''
... | 356 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 297 | 0 |
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_table,
query_table,
)
from .np_formatter import NumpyFormatt... | 357 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pipe... | 297 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __lowerCamelCase ( lowerCamelCase__ ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmel... | 358 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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_commo... | 297 | 0 |
from pathlib import Path
import fire
from tqdm import tqdm
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any]="ro" , __lowerCamelCase: Optional[Any]="en" , __lowerCamelCase: List[str]="wmt16" , __lowerCamelCase: Tuple=None ):
'''simple doc... | 359 |
# 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 applic... | 297 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""bert-base-uncased""": """https:/... | 360 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class __lowerCamelCase ( snake_case_ , snake_case_ ):
"""s... | 297 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import torch
if is_vision_ava... | 361 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , __lowerCamelCase: float , ):
'''simple docstring'''
lowercase_ = [redshift, radiation_density, matt... | 297 | 0 |
from typing import Tuple, Union
from ...modeling_outputs import BackboneOutput
from ...modeling_utils import PreTrainedModel
from ...utils import is_timm_available, is_torch_available, requires_backends
from ...utils.backbone_utils import BackboneMixin
from .configuration_timm_backbone import TimmBackboneConfig
i... | 362 |
import sys
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Optional[Any] ):
'''simple docstring'''
lowercase_ = len(__lowerCamelCase )
lowercase_ = [[0 for x in range(__lowerCamelCase )] for x in range(__lowerCamelCase )]
lowercase_ = [[0 ... | 297 | 0 |
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline # noqa: F401
deprecate(
"""stable diffusion controlnet""",
"""0.22.0""",
"""Importing `StableDiffusionControlNetPipe... | 363 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float ):
'''simple docstring'''
return 10 - x * x
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: float , __lowerCamelCase: float ):
'''simple docstring'''
if equation(__lowerCamelCase ... | 297 | 0 |
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
... | 364 |
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {"""vocab_file""": """vocab.txt"... | 297 | 0 |
from typing import TYPE_CHECKING
from ...utils import _LazyModule
SCREAMING_SNAKE_CASE__ = {"""tokenization_byt5""": ["""ByT5Tokenizer"""]}
if TYPE_CHECKING:
from .tokenization_byta import ByTaTokenizer
else:
import sys
SCREAMING_SNAKE_CASE__ = _LazyModule(__name__, globa... | 365 |
from scipy.stats import pearsonr
import datasets
SCREAMING_SNAKE_CASE__ = """
Pearson correlation coefficient and p-value for testing non-correlation.
The Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assumption that ea... | 297 | 0 |
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class __lowerCamelCase ( nn.Module ):
"""simple docstring"""
lowerCAmelCase__ = 4... | 366 |
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __lowerCamelCase ( snake_case_ ):
"""simple docstring"""
def A__ ( self ) -> int:
'''simple docstring'''
... | 297 | 0 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
SCREAMING_SNAKE_CASE__ = """
import os
"""
SCREAMING_SNAKE_CASE__ = """
def foo():
import os
return False
"""
SCREAMING_SNAKE_CASE__ = """
def foo():
def bar():
if True... | 367 |
import gc
import unittest
import numpy as np
import torch
from diffusers import (
AudioDiffusionPipeline,
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
DiffusionPipeline,
Mel,
UNetaDConditionModel,
UNetaDModel,
)
from diffusers.utils import slow, torch_device
from diffusers.utils.tes... | 297 | 0 |
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: Union[str, Any] , __lowerCamelCase: Optional[int] , __lowerCamelCase: Tuple , __lowerCamelCase: ... | 368 |
def SCREAMING_SNAKE_CASE_ ( __lowerCamelCase: int ):
'''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..... | 297 | 0 |
class __lowerCamelCase :
"""simple docstring"""
def __init__( self , UpperCAmelCase ) -> List[str]:
'''simple docstring'''
lowercase_ = arr.split("," )
def A__ ( self ) -> int:
... | 369 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTest... | 297 | 0 |
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