code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
"""simple docstring"""
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... | 88 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 88 | 1 |
"""simple docstring"""
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ ( A_ ):
__UpperCAmelCase = (DDPMScheduler,)
def UpperCamelCase_ ( self , **SCREAMING_SNAKE_CASE) ... | 88 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision,... | 88 | 1 |
"""simple docstring"""
import math
def _snake_case ( __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : Optional[Any] = 0
_lowerCamelCase : int = 0
while num > 0:
_lowerCamelCase : Any = num % 8
_lower... | 88 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 88 | 1 |
"""simple docstring"""
import math
def _snake_case ( __snake_case : float , __snake_case : float ):
"""simple docstring"""
if (
not isinstance(__snake_case , (int, float) )
or power_factor < -1
or power_factor... | 88 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from ... | 88 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase = {
"""configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConfi... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : list[list[int]] , __snake_case : int , __snake_case : int , __snake_case : list[int] ):
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
import random
import unittest
from transformers import TransfoXLConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMode... | 88 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE=None , SCREAMING_SNAKE_CASE=None) -> Tuple:
# Input as list
_lowerCamelCase : Any = list(poly_a or [0]... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : int = 1000000 ):
"""simple docstring"""
_lowerCamelCase : str = set(range(3 , __snake_case , 2 ) )
primes.add(2 )
for p in range(3 , __snake_case , 2 ):
... | 88 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDeco... | 88 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Chin... | 88 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
for param in module.parameters():
_lowerCamelCase : Optional[Any] = Fal... | 88 | 1 |
"""simple docstring"""
import unittest
from transformers import SPIECE_UNDERLINE, XLNetTokenizer, XLNetTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAmelCase = ... | 88 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvisio... | 88 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""facebook/dat... | 88 |
"""simple docstring"""
import numpy as np
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""... | 88 | 1 |
"""simple docstring"""
import numpy as np
import datasets
UpperCAmelCase = """
Compute the Mahalanobis Distance
Mahalonobis distance is the distance between a point and a distribution.
And not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distance.
It ... | 88 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Any = HfArgumentParser(__snake_case )
_lowerCamelCase : int = parser.pa... | 88 | 1 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, Truncation... | 88 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""kssteven/ibe... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE = 0) -> Optional[int]:
_lowerCamelCase : Dict = key
def UpperCamelCase_ ( self , SCREAMING_SNAKE_CASE ... | 88 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE) -> int:
_lowerCamelCase : int = data
_lowerCamelCase : List[str] = None
_lowerCamelCase : Any ... | 88 | 1 |
"""simple docstring"""
from transformers import BertTokenizerFast
from .custom_tokenization import CustomTokenizer
class lowercase__ ( A_ ):
__UpperCAmelCase = CustomTokenizer
pass
| 88 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 88 | 1 |
"""simple docstring"""
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase__ ( A_ ):
__UpperCAmelCase = (CMStochasticIterativeScheduler,)
__UpperCAmelCase = 10
... | 88 |
"""simple docstring"""
from collections import defaultdict
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : Tuple = first_str.lower().strip()
_lowerCamelCase : int = sec... | 88 | 1 |
"""simple docstring"""
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def _snake_case ( __snake_case : Tuple ):
"""simple docstring"""
_lowerCamelCase : Tuple ... | 88 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : bool = False ):
... | 88 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ ( A_ ):
def __init__( self , *SCREAMING_SNAKE_CASE ... | 88 |
"""simple docstring"""
import random
def _snake_case ( __snake_case : List[Any] , __snake_case : List[Any] , __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = a[left_index]
_lowerCamelCase... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : bool = False ):
... | 88 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase = """\
@misc{chen2021evaluating,
t... | 88 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffuser... | 88 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation... | 88 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : str = len(__snake_case )
_lowerCamelCase : Union[str, Any] = len(__snake_case )
_lowerCamelC... | 88 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
... | 88 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ ( A_ ):
def __init__( self , *SCREAMING_SNAKE_CASE ... | 88 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""facebook/s2t-wav2vec2-large-en-de""": (
"""https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/re... | 88 |
"""simple docstring"""
from math import isqrt, loga
def _snake_case ( __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:... | 88 | 1 |
"""simple docstring"""
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ :
... | 88 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 88 | 1 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvisio... | 88 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision,... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_co... | 88 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 88 | 1 |
"""simple docstring"""
from math import sqrt
def _snake_case ( __snake_case : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, ... | 88 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from ... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def _snake_case ( __snake_case : float , __snake_case : float ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("""Inductance cannot ... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : list[list[int]] , __snake_case : int , __snake_case : int , __snake_case : list[int] ):
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:... | 88 | 1 |
"""simple docstring"""
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowercase__ ( A_ ,unittest.TestCase ):
__UpperCAmelCase ... | 88 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE=None , SCREAMING_SNAKE_CASE=None) -> Tuple:
# Input as list
_lowerCamelCase : Any = list(poly_a or [0]... | 88 | 1 |
"""simple docstring"""
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 YolosConfig, YolosForObjectDetection, YolosImageProcessor
from transformers.utils import logging
log... | 88 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDeco... | 88 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LDMTextToImagePipeline, UNetaDConditionModel
from diffusers.utils.testing_utils import (
enable... | 88 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
for param in module.parameters():
_lowerCamelCase : Optional[Any] = Fal... | 88 | 1 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
... | 88 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvisio... | 88 | 1 |
"""simple docstring"""
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class lowercase__ ( unittest.TestCase ):
__Up... | 88 |
"""simple docstring"""
import numpy as np
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""... | 88 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""tanreinama/GPTSAN-2.8B-spout_is_uniform""": (
"""https://huggingface.co/tanreinama/GPTSAN-2.8B-spout_i... | 88 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Any = HfArgumentParser(__snake_case )
_lowerCamelCase : int = parser.pa... | 88 | 1 |
"""simple docstring"""
from math import factorial
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE) -> Optional[int]:
_lowerCamelCase : List[Any] = real
if isinstance(SCREAMING_SNAKE_CASE , SCREAMING_... | 88 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""kssteven/ibe... | 88 | 1 |
"""simple docstring"""
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
... | 88 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE) -> int:
_lowerCamelCase : int = data
_lowerCamelCase : List[str] = None
_lowerCamelCase : Any ... | 88 | 1 |
"""simple docstring"""
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-... | 88 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 88 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""google/switch-base-8""": """https://huggingface.co/google/switch-base-8/blob/main/config.json""",
}
c... | 88 |
"""simple docstring"""
from collections import defaultdict
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : Tuple = first_str.lower().strip()
_lowerCamelCase : int = sec... | 88 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
UpperCAmelCase = {
"""configuration_gpt_neo""": ["""GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTNeoConfig""", """GPTNeoOnnxConfi... | 88 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : bool = False ):
... | 88 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperC... | 88 |
"""simple docstring"""
import random
def _snake_case ( __snake_case : List[Any] , __snake_case : List[Any] , __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = a[left_index]
_lowerCamelCase... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : Dict = int(__snake_case )
if n_element < 1:
_lowerCamelCase : List[Any] = ValueError("""a should be a positive number""" )
... | 88 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase = """\
@misc{chen2021evaluating,
t... | 88 | 1 |
"""simple docstring"""
from ....configuration_utils import PretrainedConfig
from ....utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""speechbrain/m-ctc-t-large""": """https://huggingface.co/speechbrain/m-ctc-t-large/resolve/main/config.json"""... | 88 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation... | 88 | 1 |
"""simple docstring"""
from math import factorial
def _snake_case ( __snake_case : int , __snake_case : int ):
"""simple docstring"""
if n < k or k < 0:
raise ValueError("""Please enter positive integers for n and k where n >= k""" ... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : str = len(__snake_case )
_lowerCamelCase : Union[str, Any] = len(__snake_case )
_lowerCamelC... | 88 | 1 |
"""simple docstring"""
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnal... | 88 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ ( A_ ):
def __init__( self , *SCREAMING_SNAKE_CASE ... | 88 | 1 |
"""simple docstring"""
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_com... | 88 |
"""simple docstring"""
from math import isqrt, loga
def _snake_case ( __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
from math import ceil, floor, sqrt
def _snake_case ( __snake_case : int = 2000000 ):
"""simple docstring"""
_lowerCamelCase : list[int] = [0]
_lowerCamelCase : int
for idx in... | 88 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : int ):
"""simple docstring"""
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""" )
if rate_... | 88 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision,... | 88 | 1 |
"""simple docstring"""
import math
from typing import Any, Callable, List, Optional, Tuple, Union
import numpy as np
import torch
from ...models import TaFilmDecoder
from ...schedulers import DDPMScheduler
from ...utils import is_onnx_available, logging, randn_tensor
if is_onnx_available():
from... | 88 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : List[Any] , __snake_case : Tuple ):
"""simple docstring"""
_lowerCamelCase : Any = [0 for i in range(r + 1 )]
# nc0 = 1
_lowerCamelCase : List[Any] = 1
for i i... | 88 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from ... | 88 | 1 |
"""simple docstring"""
from argparse import ArgumentParser
from .env import EnvironmentCommand
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Optional[Any] = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : list[list[int]] , __snake_case : int , __snake_case : int , __snake_case : list[int] ):
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:... | 88 | 1 |
"""simple docstring"""
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class lowercase__ ( A_ ,unitt... | 88 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE=None , SCREAMING_SNAKE_CASE=None) -> Tuple:
# Input as list
_lowerCamelCase : Any = list(poly_a or [0]... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Callable
def _snake_case ( __snake_case : Callable[[int | float], int | float] , __snake_case : int | float , __snake_case : int | float , __snake_case : ... | 88 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDeco... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : int = 200 ):
"""simple docstring"""
_lowerCamelCase : Dict = [1, 2, 5, 10, 20, 50, 100, 200]
_lowerCamelCase : Union[str, Any] = [0] * (pence + 1)
_lowerCamelCase : List[Any] ... | 88 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
for param in module.parameters():
_lowerCamelCase : Optional[Any] = Fal... | 88 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""facebook/xlm... | 88 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvisio... | 88 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 88 |
"""simple docstring"""
import numpy as np
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""... | 88 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrai... | 88 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Any = HfArgumentParser(__snake_case )
_lowerCamelCase : int = parser.pa... | 88 | 1 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
from functools import partial
from pathlib import Path
import timm
import torch
from huggingface_hub import hf_hub_download
from transformers import LevitConfig, LevitForImageClassificationWithTeacher, LevitImagePr... | 88 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""kssteven/ibe... | 88 | 1 |
"""simple docstring"""
from math import ceil
def _snake_case ( __snake_case : int = 1001 ):
"""simple docstring"""
_lowerCamelCase : Dict = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
_lowerCamelCase : List[str] = 2 *... | 88 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE) -> int:
_lowerCamelCase : int = data
_lowerCamelCase : List[str] = None
_lowerCamelCase : Any ... | 88 | 1 |
"""simple docstring"""
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 lowercase__ ( A_ ,uni... | 88 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 88 | 1 |
"""simple docstring"""
UpperCAmelCase = {
"""A""": ["""B""", """C""", """E"""],
"""B""": ["""A""", """D""", """E"""],
"""C""": ["""A""", """F""", """G"""],
"""D""": ["""B"""],
"""E""": ["""A""", """B""", """D"""],
"""F""": ["""C"""],
"""G""": ["""C"""],
}
def _s... | 88 |
"""simple docstring"""
from collections import defaultdict
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : Tuple = first_str.lower().strip()
_lowerCamelCase : int = sec... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_visio... | 88 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : bool = False ):
... | 88 | 1 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
UpperCAmelCase = version.parse(version.parse(torch.__version__).base_version) < version.parse("""1.11""")
def _... | 88 |
"""simple docstring"""
import random
def _snake_case ( __snake_case : List[Any] , __snake_case : List[Any] , __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = a[left_index]
_lowerCamelCase... | 88 | 1 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
UpperCAmelCase = argparse.ArgumentParser(
description=(
"""Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for ... | 88 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase = """\
@misc{chen2021evaluating,
t... | 88 | 1 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion... | 88 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation... | 88 | 1 |
"""simple docstring"""
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : str = len(__snake_case )
_lowerCamelCase : Union[str, Any] = len(__snake_case )
_lowerCamelC... | 88 | 1 |
"""simple docstring"""
import argparse
import os
from io import BytesIO
from pathlib import Path
import requests
from clip_retrieval.clip_client import ClipClient
from PIL import Image
from tqdm import tqdm
def _snake_case ( __snake_case : Optional[Any] , __snake_case ... | 88 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ ( A_ ):
def __init__( self , *SCREAMING_SNAKE_CASE ... | 88 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_a... | 88 |
"""simple docstring"""
from math import isqrt, loga
def _snake_case ( __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:... | 88 | 1 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Any = HfArgumentParser(__snake_case )
_lowerCamelCase : int = parser.pa... | 88 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 88 | 1 |
"""simple docstring"""
# Copyright 2022 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-... | 88 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision,... | 88 | 1 |
"""simple docstring"""
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
return getitem, k
def _snake_case ... | 88 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 88 | 1 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
for param in module.parameters():
_lowerCamelCase : Optional[Any] = Fal... | 88 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from ... | 88 | 1 |
"""simple docstring"""
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplif... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : list[list[int]] , __snake_case : int , __snake_case : int , __snake_case : list[int] ):
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:... | 88 | 1 |
"""simple docstring"""
from jiwer import compute_measures
import datasets
UpperCAmelCase = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: impro... | 88 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE=None , SCREAMING_SNAKE_CASE=None) -> Tuple:
# Input as list
_lowerCamelCase : Any = list(poly_a or [0]... | 88 | 1 |
"""simple docstring"""
import argparse
import json
import os
import torch
from transformers import LukeConfig, LukeModel, LukeTokenizer, RobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def _snake_case ( __snake_case : Dict , __... | 88 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDeco... | 88 | 1 |
"""simple docstring"""
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class lowercase__ ( A_ ):
def __init__( self , SCREAMING_SNAKE_CASE , SCREAM... | 88 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
for param in module.parameters():
_lowerCamelCase : Optional[Any] = Fal... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
def _snake_case ( __snake_case : str , __snake_case : list[str] | None = None ):
"""simple docstring"""
_lowerCamelCase : List[str] = word_bank or []
# create a table
... | 88 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvisio... | 88 | 1 |
"""simple docstring"""
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 lowercase__ ( A_ ):... | 88 |
"""simple docstring"""
import numpy as np
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""... | 88 | 1 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transform... | 88 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Any = HfArgumentParser(__snake_case )
_lowerCamelCase : int = parser.pa... | 88 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase = {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNetConfig"""]}
... | 88 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""kssteven/ibe... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : int = 10**9 ):
"""simple docstring"""
_lowerCamelCase : Any = 1
_lowerCamelCase : int = 2
_lowerCamelCase : Tuple = 0
_lowerCamelCase : Any = 0
_lowerCamelCa... | 88 |
"""simple docstring"""
from __future__ import annotations
import queue
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE) -> int:
_lowerCamelCase : int = data
_lowerCamelCase : List[str] = None
_lowerCamelCase : Any ... | 88 | 1 |
"""simple docstring"""
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_... | 88 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 88 | 1 |
"""simple docstring"""
from collections import defaultdict
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : Tuple = first_str.lower().strip()
_lowerCamelCase : int = sec... | 88 |
"""simple docstring"""
from collections import defaultdict
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : Tuple = first_str.lower().strip()
_lowerCamelCase : int = sec... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : Any = 0
# if input_string is "aba" than new_input_string become "a|b|a"
_lowerCamelCase : List[Any] = """"""
_lowerCamelCase : ... | 88 |
"""simple docstring"""
from __future__ import annotations
from numpy import array, cos, cross, floataa, radians, sin
from numpy.typing import NDArray
def _snake_case ( __snake_case : float , __snake_case : float , __snake_case : bool = False ):
... | 88 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
UpperCAmelCase = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""Sq... | 88 |
"""simple docstring"""
import random
def _snake_case ( __snake_case : List[Any] , __snake_case : List[Any] , __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = a[left_index]
_lowerCamelCase... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : str , __snake_case : list[str] ):
"""simple docstring"""
_lowerCamelCase : int = """"""
for word_or_phrase in separated:
if not isinstance(__snake_case , __snake_ca... | 88 |
"""simple docstring"""
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCAmelCase = """\
@misc{chen2021evaluating,
t... | 88 | 1 |
"""simple docstring"""
def _snake_case ( __snake_case : int ):
"""simple docstring"""
if num <= 0:
raise ValueError("""Input must be a positive integer""" )
_lowerCamelCase : Optional[Any] = [True] * (num + 1)
_lowerCamelCase : ... | 88 |
"""simple docstring"""
from typing import Dict, List
from nltk.translate import gleu_score
import datasets
from datasets import MetricInfo
UpperCAmelCase = """\
@misc{wu2016googles,
title={Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation... | 88 | 1 |
"""simple docstring"""
class lowercase__ : # Public class to implement a graph
def __init__( self , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE) -> None:
_lowerCamelCase : str = row
_lowerCamelCase : Dict = col
... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : str , __snake_case : str ):
"""simple docstring"""
_lowerCamelCase : str = len(__snake_case )
_lowerCamelCase : Union[str, Any] = len(__snake_case )
_lowerCamelC... | 88 | 1 |
"""simple docstring"""
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 _snake_case ( __snake_case : d... | 88 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_imagegpt import ImageGPTImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class lowercase__ ( A_ ):
def __init__( self , *SCREAMING_SNAKE_CASE ... | 88 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class lowercase__ ( metaclass=A_ ):
__UpperCAmelCase = ['''torch''', '''scipy''']
def __init__( self , *SCREAMING_SNAKE_CASE , **SCREAMING_SNAKE_CASE) -> str:
... | 88 |
"""simple docstring"""
from math import isqrt, loga
def _snake_case ( __snake_case : int ):
"""simple docstring"""
_lowerCamelCase : List[str] = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:... | 88 | 1 |
"""simple docstring"""
import json
import os
from typing import Dict, List, Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""vocab_file"... | 88 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 88 | 1 |
"""simple docstring"""
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils impo... | 88 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision,... | 88 | 1 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 88 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = ... | 88 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import XGLMConfig, XGLMTokenizer, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTest... | 88 |
"""simple docstring"""
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from ... | 88 | 1 |
"""simple docstring"""
import unittest
from transformers import GPTNeoXJapaneseConfig, is_torch_available
from transformers.models.gpt_neox_japanese.tokenization_gpt_neox_japanese import GPTNeoXJapaneseTokenizer
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configu... | 88 |
"""simple docstring"""
def _snake_case ( __snake_case : list[list[int]] , __snake_case : int , __snake_case : int , __snake_case : list[int] ):
"""simple docstring"""
if graph[path[curr_ind - 1]][next_ver] == 0:... | 88 | 1 |
"""simple docstring"""
import logging
import os
import quant_trainer
import torch
from torch.utils.data import DataLoader
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput
UpperCAmelCase = logging.getLogger(__name__)
if is_t... | 88 |
"""simple docstring"""
import mpmath # for roots of unity
import numpy as np
class lowercase__ :
def __init__( self , SCREAMING_SNAKE_CASE=None , SCREAMING_SNAKE_CASE=None) -> Tuple:
# Input as list
_lowerCamelCase : Any = list(poly_a or [0]... | 88 | 1 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if ... | 88 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCAmelCase = {
"""configuration_vision_encoder_decoder""": ["""VisionEncoderDeco... | 88 | 1 |
"""simple docstring"""
import copy
import os
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Dict, Mapping, Optional, Union
if TYPE_CHECKING:
from ...processing_utils import ProcessorMixin
from ...utils import TensorType
from ...configuration_utils import PretrainedConfi... | 88 |
"""simple docstring"""
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def _snake_case ( __snake_case : List[str] ):
"""simple docstring"""
for param in module.parameters():
_lowerCamelCase : Optional[Any] = Fal... | 88 | 1 |
"""simple docstring"""
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git... | 88 |
"""simple docstring"""
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvisio... | 88 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {"""ctrl""": """https://huggingface.co/ctrl/resolve/main/config.json"""}
class lowercase__ ( A_ ):
... | 88 |
"""simple docstring"""
import numpy as np
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""
return 1 / (1 + np.exp(-vector ))
def _snake_case ( __snake_case : np.ndarray ):
"""simple docstring"""... | 88 | 1 |
"""simple docstring"""
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from... | 88 |
"""simple docstring"""
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _snake_case ( ):
"""simple docstring"""
_lowerCamelCase : Any = HfArgumentParser(__snake_case )
_lowerCamelCase : int = parser.pa... | 88 | 1 |
"""simple docstring"""
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_av... | 88 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCAmelCase = logging.get_logger(__name__)
UpperCAmelCase = {
"""kssteven/ibe... | 88 | 1 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.