code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import numpy as np
import pandas as pd
from sklearn.preprocessing import Normalizer
from sklearn.svm import SVR
from statsmodels.tsa.statespace.sarimax import SARIMAX
def a__ ( a__ , a__ , a__ , a__ , a__ ):
"""simple docstring""... | 267 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 267 | 1 |
'''simple docstring'''
from manim import *
class lowerCAmelCase__ ( a ):
"""simple docstring"""
def UpperCAmelCase__ ( self : Tuple ) -> Tuple:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = Rectangle(height=0.5 , width=0.5 ... | 267 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class l... | 267 | 1 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if not isinstance(a__ , a__ ):
__SCREAMING_SNAKE_CASE = F'Input value of [number={number}] must be an integer'
raise TypeError(a__ )
if number < 1:
__SCREAMIN... | 267 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 | 1 |
'''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Tuple = {
'facebook/data2vec-base-960h': 'https://huggingface.co/facebook/data2vec... | 267 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 | 1 |
'''simple docstring'''
import os
import re
import warnings
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_ta import ... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = int(a__ )
# Initialize Result
__SCREAMING_SNAKE_CASE = []
# Traverse through all denomination
for denomination in reversed(a__ ):
... | 267 | 1 |
'''simple docstring'''
def a__ ( a__ = 10_00 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = 1, 1
__SCREAMING_SNAKE_CASE = []
for i in range(1 , n + 1 ):
__SCREAMING_SNAKE_CASE = prev_numerato... | 267 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 267 | 1 |
'''simple docstring'''
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import vers... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
_enforce_args(a__ , a__ )
if n == 0:
return 0
__SCREAMING_SNAKE_CASE = float("""-inf""" )
for i in range(1 , n + 1 ):
__SCREAMING_SN... | 267 | 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 import BatchFe... | 267 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise ... | 267 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
UpperCAmelCase : Tuple = logging.get_logger(__name__)
class lowerCAmelCase__ ( a ):
"""simple docstring"""
def __init__( self ... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : Any ) -> Tuple:
... | 267 | 1 |
'''simple docstring'''
import os
import string
import sys
UpperCAmelCase : Union[str, Any] = 1 << 8
UpperCAmelCase : Any = {
'tab': ord('\t'),
'newline': ord('\r'),
'esc': 2_7,
'up': 6_5 + ARROW_KEY_FLAG,
'down': 6_6 + ARROW_KEY_FLAG,
'right': 6_7 + ARROW_KE... | 267 |
'''simple docstring'''
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... | 267 | 1 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import torch
from transformers import LukeConfig, LukeForMaskedLM, MLukeTokenizer, XLMRobertaTokenizer
from transformers.tokenization_utils_base import AddedToken
@torch.no_grad()
def a__ ( a__ ... | 267 |
'''simple docstring'''
import numpy as np
def a__ ( a__ , a__ , a__ = 1E-1_2 , a__ = 1_00 , ):
"""simple docstring"""
assert np.shape(a__ )[0] == np.shape(a__ )[1]
# Ensure proper dimensionality.
assert np.shape(a__ )[0] == n... | 267 | 1 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerC... | 267 |
'''simple docstring'''
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 ... | 267 | 1 |
'''simple docstring'''
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
UpperCAmelCase : Dict = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import check_copies # noqa:... | 267 |
'''simple docstring'''
from itertools import count
def a__ ( a__ = 50 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [1] * min_block_length
for n in count(a__ ):
fill_count_functions.append(1 )
for block_length in range(a__ ... | 267 | 1 |
'''simple docstring'''
import os
from math import logaa
def a__ ( a__ = "base_exp.txt" ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(a__ ) , a_... | 267 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Optional[Any] = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : List[Any] = None
try:
import fcntl
except ImportError:
Up... | 267 | 1 |
'''simple docstring'''
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester... | 267 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 267 | 1 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
class lowerCAmelCase__ ( ... | 267 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
class lowerCAmelCase__ ( ... | 267 | 1 |
'''simple docstring'''
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import M... | 267 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 267 | 1 |
'''simple docstring'''
from manim import *
class lowerCAmelCase__ ( a ):
"""simple docstring"""
def UpperCAmelCase__ ( self : Dict ) -> List[str]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = Rectangle(height=0.5 , width=0... | 267 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if isinstance(a__ , a__ ):
raise TypeError("""'float' object cannot be interpreted as an integer""" )
if isinstance(a__ , a__ ):
raise TypeError("""'str' object cann... | 267 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import SpeechaTextConfig, SpeechaTextForConditionalGeneration
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [
"""encoder.version""",
"""de... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : str ... | 267 | 1 |
'''simple docstring'''
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... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase__ ... | 267 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Optional[Any] = {
'microsoft/wavlm-base': 'https://huggingfac... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int ) -> List[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = n
__SCREAMING_SNAKE_CASE = ... | 267 | 1 |
'''simple docstring'''
# 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 ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # n... | 267 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unitt... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 267 | 1 |
'''simple docstring'''
import json
import os
import re
import unicodedata
from json.encoder import INFINITY
from typing import Any, Dict, List, Optional, Tuple, Union
import numpy as np
import regex
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEnco... | 267 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class l... | 267 | 1 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 267 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 | 1 |
'''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 .utils i... | 267 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 | 1 |
'''simple docstring'''
import itertools
import random
import unittest
import numpy as np
from transformers import is_speech_available
from transformers.testing_utils import require_torch, require_torchaudio
from ...test_sequence_feature_extraction_common import SequenceFeatureExtractionTestMixin
if is_speech_... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = int(a__ )
# Initialize Result
__SCREAMING_SNAKE_CASE = []
# Traverse through all denomination
for denomination in reversed(a__ ):
... | 267 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_vit_msn': ['VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ViTMSNConfig']}
try:
if not is_torch_available():... | 267 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 267 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
Diffusio... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
_enforce_args(a__ , a__ )
if n == 0:
return 0
__SCREAMING_SNAKE_CASE = float("""-inf""" )
for i in range(1 , n + 1 ):
__SCREAMING_SN... | 267 | 1 |
'''simple docstring'''
from math import ceil
def a__ ( a__ = 10_01 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
__SCREAMING_SNAKE_CASE = 2 * i + 1
__SCREAMING_... | 267 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise ... | 267 | 1 |
'''simple docstring'''
import numpy as np
import skfuzzy as fuzz
if __name__ == "__main__":
# Create universe of discourse in Python using linspace ()
UpperCAmelCase : Dict = np.linspace(start=0, stop=7_5, num=7_5, endpoint=True, retstep=False)
# Create two fuzzy sets by defining any members... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : Any ) -> Tuple:
... | 267 | 1 |
'''simple docstring'''
import random
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = num - 1
__SCREAMING_SNAKE_CASE = 0
while s % 2 == 0:
__SCREAMING_SNAKE_CASE = s // 2
t += 1
for _ in range(5 ... | 267 |
'''simple docstring'''
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... | 267 | 1 |
'''simple docstring'''
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 (
AutoencoderKL,
DDIMInverseScheduler,
DDIMScheduler,
DPMSolverMultistep... | 267 |
'''simple docstring'''
import numpy as np
def a__ ( a__ , a__ , a__ = 1E-1_2 , a__ = 1_00 , ):
"""simple docstring"""
assert np.shape(a__ )[0] == np.shape(a__ )[1]
# Ensure proper dimensionality.
assert np.shape(a__ )[0] == n... | 267 | 1 |
'''simple docstring'''
from heapq import heappop, heappush
import numpy as np
def a__ ( a__ , a__ , a__ , a__ , ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE = grid.shape
__SCREAMING_SNAKE_CASE = ... | 267 |
'''simple docstring'''
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 ... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
UpperCAmelCase : Tuple = TypeVar('T')
def a__ ( a__ ):
"""simple docstring"""
return (position - 1) // 2
def a__ ( a__ )... | 267 |
'''simple docstring'''
from itertools import count
def a__ ( a__ = 50 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [1] * min_block_length
for n in count(a__ ):
fill_count_functions.append(1 )
for block_length in range(a__ ... | 267 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase : List[str] = {
'configuration_mobilenet_v2': [
'MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Mobil... | 267 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Optional[Any] = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : List[Any] = None
try:
import fcntl
except ImportError:
Up... | 267 | 1 |
'''simple docstring'''
import itertools
import string
from collections.abc import Generator, Iterable
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = iter(a__ )
while True:
__SCREAMING_SNAKE_CASE = tuple(iter... | 267 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 267 | 1 |
'''simple docstring'''
import doctest
from collections import deque
import numpy as np
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[str] ) -> None:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [2, 1, 2, -1]
__SCR... | 267 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
class lowerCAmelCase__ ( ... | 267 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionTextToImagePipeline
from diffusers.utils.testing_utils import nightly, require_torch_gpu, torch_device
UpperCAmelCase : str = False
class lowerCAm... | 267 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 267 | 1 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
UpperCAmelCase : Tuple = logging.g... | 267 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if isinstance(a__ , a__ ):
raise TypeError("""'float' object cannot be interpreted as an integer""" )
if isinstance(a__ , a__ ):
raise TypeError("""'str' object cann... | 267 | 1 |
'''simple docstring'''
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
't5-sma... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : str ... | 267 | 1 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase__ ... | 267 | 1 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int ) -> List[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = n
__SCREAMING_SNAKE_CASE = ... | 267 | 1 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
UpperCAmelCase : str = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:])
UpperCAmelCase : L... | 267 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unitt... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ , ):
"""simple docstring"""
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError("""You cannot supply more or less than 2 values""" ... | 267 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 267 | 1 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tok... | 267 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class l... | 267 | 1 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Optional
from transformers import AutoConfig, AutoImageProcessor, AutoTokenizer, FlaxVisionEncoderDecoderModel, HfArgumentParser
@dataclass
class lowerCAmelCase__ :
"""simple docstring"""
lowerCAmelCase__ ... | 267 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__ = ["image_processor", "tokenizer"]
lowerCAmelCase__ = ... | 267 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 | 1 |
'''simple docstring'''
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pipelines.stable_diffusion.p... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = int(a__ )
# Initialize Result
__SCREAMING_SNAKE_CASE = []
# Traverse through all denomination
for denomination in reversed(a__ ):
... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
from collections.abc import Callable
def a__ ( a__ , a__ , a__ , a__ = 1_00 , ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = x_start
__SCREAMING_SNAKE_CASE =... | 267 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : Optional[Any] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : str ) -> Tuple:
"""simple docst... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
_enforce_args(a__ , a__ )
if n == 0:
return 0
__SCREAMING_SNAKE_CASE = float("""-inf""" )
for i in range(1 , n + 1 ):
__SCREAMING_SN... | 267 | 1 |
'''simple docstring'''
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers... | 267 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise ... | 267 | 1 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
UpperCAmelCase : int = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Mu... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : Any ) -> Tuple:
... | 267 | 1 |
'''simple docstring'''
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRING,
Bert... | 267 |
'''simple docstring'''
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... | 267 | 1 |
'''simple docstring'''
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Optional[Any] = logging.get_logger(__name__)
UpperCAmelCase : Dict = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/con... | 267 |
'''simple docstring'''
import numpy as np
def a__ ( a__ , a__ , a__ = 1E-1_2 , a__ = 1_00 , ):
"""simple docstring"""
assert np.shape(a__ )[0] == np.shape(a__ )[1]
# Ensure proper dimensionality.
assert np.shape(a__ )[0] == n... | 267 | 1 |
'''simple docstring'''
import fire
from utils import calculate_rouge, save_json
def a__ ( a__ , a__ , a__=None , **a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [x.strip() for x in open(a__ ).readlines()]
__SCREAMING_SNAKE_C... | 267 |
'''simple docstring'''
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 ... | 267 | 1 |
'''simple docstring'''
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class lowerCAmelCase__ ( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase__ ( self : Dict ... | 267 |
'''simple docstring'''
from itertools import count
def a__ ( a__ = 50 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [1] * min_block_length
for n in count(a__ ):
fill_count_functions.append(1 )
for block_length in range(a__ ... | 267 | 1 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Optional[Any] = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : List[Any] = None
try:
import fcntl
except ImportError:
Up... | 267 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Optional[Any] = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : List[Any] = None
try:
import fcntl
except ImportError:
Up... | 267 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
UpperCAmelCase : Optional[int] = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': [... | 267 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 267 | 1 |
'''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 GenerationTest... | 267 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
class lowerCAmelCase__ ( ... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
UpperCAmelCase : Dict = 'Muhammad Umer Farooq'
UpperCAmelCase : Any = 'MIT'
UpperCAmelCase : Tuple = '1.0.0'
UpperCAmelCase : Optional[Any] = 'Muhammad Umer Farooq'
UpperCAmelCase : Union[st... | 267 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 267 | 1 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : Any ) -> Tuple:
... | 267 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if isinstance(a__ , a__ ):
raise TypeError("""'float' object cannot be interpreted as an integer""" )
if isinstance(a__ , a__ ):
raise TypeError("""'str' object cann... | 267 | 1 |
'''simple docstring'''
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : str ... | 267 | 1 |
'''simple docstring'''
import unittest
from diffusers.models.unet_ad_blocks import * # noqa F403
from diffusers.utils import torch_device
from .test_unet_blocks_common import UNetBlockTesterMixin
class lowerCAmelCase__ ( a , unittest.TestCase ):
"""simple docstring"""
lowerCA... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase__ ... | 267 | 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 : Dict = logging.get_logger(__name__)
class lowerCAmelCase__ ... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int ) -> List[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = n
__SCREAMING_SNAKE_CASE = ... | 267 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 267 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unitt... | 267 | 1 |
'''simple docstring'''
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.huggin... | 267 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 267 | 1 |
'''simple docstring'''
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def a__ ( a__ ):
"""simple docstring"""
return sum(param.flo... | 267 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class l... | 267 | 1 |
'''simple docstring'''
import math
import tensorflow as tf
from packaging import version
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = tf.convert_to_tensor(a__ )
__SCREAMING_SNAKE_CASE = 0.5 * (1.0 + tf.math.erf(x / tf.cast(tf.sq... | 267 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Any = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'TrajectoryT... | 267 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 | 1 |
'''simple docstring'''
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCAmelCase__ ( nn.Module ):
"""simple docstring"""
lowerCAmelCase__ = 42
lowerCAmelCase__ = jnp.floataa
def UpperCAmelCase__ ( self : int ) -> Dic... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = int(a__ )
# Initialize Result
__SCREAMING_SNAKE_CASE = []
# Traverse through all denomination
for denomination in reversed(a__ ):
... | 267 | 1 |
'''simple docstring'''
import requests
from bsa import BeautifulSoup
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = BeautifulSoup(requests.get(a__ , params=a__ ).content , """html.parser""" )
__SCREAMING_S... | 267 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 267 | 1 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
_enforce_args(a__ , a__ )
if n == 0:
return 0
__SCREAMING_SNAKE_CASE = float("""-inf""" )
for i in range(1 , n + 1 ):
__SCREAMING_SN... | 267 | 1 |
'''simple docstring'''
import inspect
import math
import tempfile
import unittest
import numpy as np
from transformers import ViTMAEConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_availab... | 267 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise ... | 267 | 1 |
'''simple docstring'''
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql ... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : Any ) -> Tuple:
... | 267 | 1 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class l... | 267 |
'''simple docstring'''
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... | 267 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
... | 267 |
'''simple docstring'''
import numpy as np
def a__ ( a__ , a__ , a__ = 1E-1_2 , a__ = 1_00 , ):
"""simple docstring"""
assert np.shape(a__ )[0] == np.shape(a__ )[1]
# Ensure proper dimensionality.
assert np.shape(a__ )[0] == n... | 267 | 1 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def a__ ( a__ , a__ , a__ , a__ , a__ , a__ ):
"""simple docstring"""
if (ksize % 2) == 0:
__SCREAMI... | 267 |
'''simple docstring'''
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 ... | 267 | 1 |
'''simple docstring'''
import argparse
import logging
import os
from pathlib import Path
from typing import Any, Dict
import pytorch_lightning as pl
from pytorch_lightning.utilities import rank_zero_info
from transformers import (
AdamW,
AutoConfig,
AutoModel,
AutoModelForPreTraining,
AutoMod... | 267 |
'''simple docstring'''
from itertools import count
def a__ ( a__ = 50 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = [1] * min_block_length
for n in count(a__ ):
fill_count_functions.append(1 )
for block_length in range(a__ ... | 267 | 1 |
'''simple docstring'''
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
l... | 267 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Optional[Any] = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : List[Any] = None
try:
import fcntl
except ImportError:
Up... | 267 | 1 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch_availab... | 267 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_... | 267 | 1 |
'''simple docstring'''
from collections import deque
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[str] , __SCREAMING_SNAKE_CASE : str , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : ... | 267 |
'''simple docstring'''
import math
from enum import Enum
from typing import Optional, Union
from torch.optim import Optimizer
from torch.optim.lr_scheduler import LambdaLR
from .utils import logging
UpperCAmelCase : str = logging.get_logger(__name__)
class lowerCAmelCase__ ( ... | 267 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unitt... | 267 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_M... | 267 | 1 |
'''simple docstring'''
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCAmelCase : Optional[int] = logging.get_logger('transformers.models.speecht5')
def a__ ( a__ , ... | 267 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if isinstance(a__ , a__ ):
raise TypeError("""'float' object cannot be interpreted as an integer""" )
if isinstance(a__ , a__ ):
raise TypeError("""'str' object cann... | 267 | 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,
DDIMScheduler,... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
UpperCAmelCase : str ... | 267 | 1 |
'''simple docstring'''
import inspect
import unittest
import torch
import torch.nn as nn
from accelerate.hooks import (
AlignDevicesHook,
ModelHook,
SequentialHook,
add_hook_to_module,
attach_align_device_hook,
remove_hook_from_module,
remove_hook_from_submodules,
)
from accelerate.te... | 267 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCAmelCase : List[str] = logging.get_logger(__name__)
class lowerCAmelCase__ ... | 267 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
UpperCAmelCase : str = {
'configuration_gpt_neox_japanese': ['GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXJapanes... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int ) -> List[Any]:
"""simple docstring"""
__SCREAMING_SNAKE_CASE = n
__SCREAMING_SNAKE_CASE = ... | 267 | 1 |
'''simple docstring'''
from . import __version__
# Backward compatibility imports, to make sure all those objects can be found in file_utils
from .utils import (
CLOUDFRONT_DISTRIB_PREFIX,
CONFIG_NAME,
DISABLE_TELEMETRY,
DUMMY_INPUTS,
DUMMY_MASK,
ENV_VARS_TRUE_AND_AUTO_VALUES,
ENV_VARS... | 267 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import PNDMPipeline, PNDMScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unitt... | 267 | 1 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if not isinstance(a__ , a__ ):
raise TypeError("""only integers accepted as input""" )
else:
__SCREAMING_SNAKE_CASE = str(abs(a__ ) )
__SCREAMING_SNA... | 267 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simpl... | 267 | 1 |
'''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def a__ ( a__ ):
"""simple docstring"""
_... | 267 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class l... | 267 | 1 |
'''simple docstring'''
from ... import PretrainedConfig
UpperCAmelCase : Union[str, Any] = {
'sijunhe/nezha-cn-base': 'https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json',
}
class lowerCAmelCase__ ( a ):
"""simple docstring"""
lowerCAmelCase__... | 267 |
'''simple docstring'''
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from trans... | 267 | 1 |
'''simple docstring'''
def a__ ( a__ ):
"""simple docstring"""
if isinstance(a__ , a__ ):
raise TypeError("""'float' object cannot be interpreted as an integer""" )
if isinstance(a__ , a__ ):
raise TypeError("""'str' object cann... | 267 |
'''simple docstring'''
from __future__ import annotations
def a__ ( a__ , a__ , a__ ):
"""simple docstring"""
if len(a__ ) == 0:
raise ValueError("""find_max() arg is an empty sequence""" )
if (
left >= len(a__ )
... | 267 | 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
class ... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = int(a__ )
# Initialize Result
__SCREAMING_SNAKE_CASE = []
# Traverse through all denomination
for denomination in reversed(a__ ):
... | 267 | 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 is_torch_ava... | 267 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 267 | 1 |
'''simple docstring'''
import math
def a__ ( ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = input("""Enter message: """ )
__SCREAMING_SNAKE_CASE = int(input(F'Enter key [2-{len(a__ ) - 1}]: ' ) )
__SCREAMING_SNAKE_CASE = ... | 267 |
'''simple docstring'''
def a__ ( a__ , a__ ):
"""simple docstring"""
_enforce_args(a__ , a__ )
if n == 0:
return 0
__SCREAMING_SNAKE_CASE = float("""-inf""" )
for i in range(1 , n + 1 ):
__SCREAMING_SN... | 267 | 1 |
'''simple docstring'''
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, ca... | 267 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCAmelCase : Union[str, Any] = {'configuration_sew': ['SEW_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SEWConfig']}
try:
if not is_torch_available():
raise ... | 267 | 1 |
'''simple docstring'''
from __future__ import annotations
import time
UpperCAmelCase : Dict = list[tuple[int, int]]
UpperCAmelCase : List[str] = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0... | 267 |
'''simple docstring'''
class lowerCAmelCase__ :
"""simple docstring"""
def __init__( self : List[Any] , __SCREAMING_SNAKE_CASE : int , __SCREAMING_SNAKE_CASE : Union[str, Any] , __SCREAMING_SNAKE_CASE : Any ) -> Tuple:
... | 267 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
UpperCAmelCase : Optional[int] = logging.get_logger(__name__)
class lowerCAmelCase__ ( a ):
"""simpl... | 267 |
'''simple docstring'''
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... | 267 | 1 |
'''simple docstring'''
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class lowerCAmelCase__ ( a ):
"""simpl... | 267 |
'''simple docstring'''
import numpy as np
def a__ ( a__ , a__ , a__ = 1E-1_2 , a__ = 1_00 , ):
"""simple docstring"""
assert np.shape(a__ )[0] == np.shape(a__ )[1]
# Ensure proper dimensionality.
assert np.shape(a__ )[0] == n... | 267 | 1 |
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def _a ( a :Union[str, Any] ) -> List[str]:
a = os.path.join(args.tf_model_dir , '''parameters.json''' )
a = json.loads... | 0 |
'''simple docstring'''
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 ... | 267 | 0 |
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