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 |
|---|---|---|---|---|
import inspect
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
import torch.utils.checkpoint
from ...models import UNetaDModel, VQModel
from ...schedulers import (
DDIMScheduler,
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
... | 90 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def lowerCamelCase__ ( _A , _A=() , _A=None , _A="no" , _A="29500" ):
a : ... | 297 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
"""simple docstring"""
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Optional[Any] , SCREAMING_SNAKE_CASE : Tuple ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def UpperCAmelCase__ ( ):
'''simple docst... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: int = {
'''EleutherAI/gpt-neox-20b''': '''https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main... | 276 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
def lowerCAmelCase__ ( a__: str , a__: Optional[int] ) -> str:
'''simple docstring'''
return 1 if input_a == input_a else 0
def lowerCAmelCase__ ( ) -> int:
'''simple docstring'''
assert xnor_gate(0 , 0 ) == 1
assert xnor_gat... | 329 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 249 | 0 |
"""simple docstring"""
from math import log
from scipy.constants import Boltzmann, physical_constants
UpperCAmelCase = 300 # TEMPERATURE (unit = K)
def lowercase ( a__ : Union[str, Any] , a__ : str , a__ : List[str] , ) -> List[Any]:
if donor_conc <= 0:
raise Val... | 256 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
import inspect
import unittest
class A__ ( unittest.TestCase ):
"""simple docstring"""
def __lowercase ( self) -> int:
'''simple docstring'''
try:
import diffusers # noqa: F401
except ImportError:
... | 99 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
import os
import sys
import unittest
__a = 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_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_b... | 66 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class A__ ( __SCREAMING_SNAKE_CASE , unittest.TestCase):
_UpperCAmelCase : Dict = Tra... | 287 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class __A( __lowerCamelCase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE__ = (PNDMScheduler,)
SCREAMING_SNAKE_CASE__ = (("""num_inference_steps""", 50),)
def ... | 244 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = '''▁'''
__snake_case = {'''vocab_... | 348 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers imp... | 249 | 0 |
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
pass
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
pass
class __lowerCAmelCase :
"""simple docstring"""
... | 90 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
import requests
def lowerCamelCase__ ( _A , _A ):
a : List[Any] = {'''Content-Type''': '''application/json'''}
a : Optional[int] = requests.post(__UpperCamelCase , json={'text': message_body} , headers=__UpperCamelCas... | 297 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
"""simple docstring"""
import torch
from diffusers import UnCLIPScheduler
from .test_schedulers import SchedulerCommonTest
class lowercase ( _UpperCAmelCase ):
_SCREAMING_SNAKE_CASE = (UnCLIPScheduler,)
def _snake_case ( self , **lowercase ) -... | 46 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class A__ :
def __init__( self :int , SCREAMING_SNAKE_CASE :str = 6 ) -> None:
'''simple docstring'''
_a : Node |... | 276 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ :Any = logging.get_logger(__name__)
class __a ( UpperCAmelCase ):
_a : Optional[int] = 'encoder-decoder'
_a : Optional[int] = True
def __init__( self , **_SCR... | 329 |
"""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,
DDIMSchedu... | 249 | 0 |
"""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 transformers.utils impor... | 256 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
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_tokenization_common impor... | 99 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__a = {
"configuration_poolformer": [
"POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"PoolFormerConfig",
"PoolFormerOn... | 66 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Opt... | 249 | 0 |
import math
def _a ( lowerCamelCase, lowerCamelCase ):
if initial_intensity < 0:
raise ValueError("""The value of intensity cannot be negative""" )
# handling of negative values of initial intensity
if angle < 0 or angle > 360:
raise ValueError("""In Malus Law, the angle is in th... | 287 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
class __A:
"""simple docstring"""
def __init__(self , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase__ = n
UpperCamelCase__ = [None] * self.n
UpperCamelCase__ = 0 # index of the first element
UpperCamelCase__ = 0
UpperCamelCase__ = 0
... | 244 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
import os
import pytest
from transformers.dynamic_module_utils import get_imports
__snake_case = '''\nimport os\n'''
__snake_case = '''\ndef foo():\n import os\n return False\n'''
__snake_case = '''\ndef foo():\n def bar():\n if True:\n import os\n return Fal... | 348 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
__A = {
"susnato/ernie-m-base_pytorch": "https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json",
"susnato/ernie-m-large_pytorch": "https://huggingfa... | 90 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
... | 297 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
"""simple docstring"""
from ...utils import deprecate
from ..controlnet.pipeline_flax_controlnet import FlaxStableDiffusionControlNetPipeline # noqa: F401
deprecate(
"stable diffusion controlnet",
"0.22.0",
"Importing `FlaxStableDiffusionControlNetPipeline` from diffusers.pipelines.stable_diff... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''simple docstring'''
import collections
import gzip
import os
import urllib
import numpy
from tensorflow.python.framework import dtypes, random_seed
from tensorflow.python.platform import gfile
from tensorflow.python.util.deprecation import deprecated
A__: Optional[Any] = ... | 276 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
import copy
import tempfile
import unittest
from huggingface_hub import HfFolder, delete_repo
from parameterized import parameterized
from requests.exceptions import HTTPError
from transformers import AutoConfig, GenerationConfig
from transformers.testing_utils import TOKEN, USER, is_staging_test
class __a ... | 329 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 249 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDependenc... | 256 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
from __future__ import annotations
from math import ceil, floor, sqrt
def A_ ( A__ = 200_0000 ) -> Dict:
a__ : list[int] = [0]
a__ : int
for idx in range(1 , ceil(sqrt(target * 2 ) * 1.1 ) ):
triangle_numbers.append(triangle_numbers[-1] + i... | 99 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
Pipeline,
ZeroShotClassificationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, ... | 66 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
def _a ( lowerCamelCase = "The quick brown fox jumps over the lazy dog", ):
lowerCamelCase : Any = set()
# Replace all the whitespace in our sentence
lowerCamelCase : Any = input_str.replace(""" """, """""" )
for alpha in input_str:
if "a" <= alpha.lower() <= "z":
f... | 287 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ ... | 244 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __lowerCAmelCase )-> Optional[Any]:
'''simple docstring'''
if len(__UpperCamelCase ) == 0:
return array
UpperCAmelCase : Any =min(__UpperCamelCase ), max(__UpperCamelCase )
# ... | 348 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers imp... | 249 | 0 |
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print("Googling.....")
__A = "https://www.google.com/search?q=" + " ".join(sys.argv[1:])
__A = requests.get(url, headers={"U... | 90 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase: Optional[int] = logging.get_logger(__name__)
lowerCAmelCase: Any = {
'BridgeTower/bridgetower... | 297 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
"""simple docstring"""
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_u... | 46 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
'''simple docstring'''
import collections
import os
import re
from pathlib import Path
A__: str = '''src/transformers'''
# Matches is_xxx_available()
A__: int = re.compile(R'''is\_([a-z_]*)_available()''')
# Catches a one-line _import_struct = {xxx}
... | 276 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm impo... | 329 |
"""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,
DDIMSchedu... | 249 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
UpperCAmelCase = {"""processing_wav2vec2_with_lm""": ["""Wav2Vec2ProcessorWithLM"""]}
if TYPE_CHECKING:
from .processing_wavaveca_with_lm import WavaVecaProcessorWithLM
else:
import sys
UpperCAmelCase = _... | 256 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
import sys
from collections.abc import Mapping
from typing import TYPE_CHECKING
import numpy as np
import pyarrow as pa
from .. import config
from ..utils.py_utils import map_nested
from .formatting import TensorFormatter
if TYPE_CHECKING:
import torch
class A__ ( TensorFormatter[Mapping, '... | 99 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import torch
import torchaudio.compliance.kaldi as ta_kaldi
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, Tensor... | 66 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Opt... | 249 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase ={
"""configuration_distilbert""": [
"""DISTILBERT_PRETRAINED_CONFIG_ARCH... | 287 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
def __magic_name__ ( __a : str = 4_000_000 ):
'''simple docstring'''
UpperCamelCase__ = [0, 1]
UpperCamelCase__ = 0
while fib[i] <= n:
fib.append(fib[i] + fib[i + 1] )
if fib[i + 2] > n:
break
i += 1
Upp... | 244 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
__snake_case = {
'''n_samples''': 64,
'''horizon''': 32,
'''num_inference_steps''': 20,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not use value network
'''scale_grad_b... | 348 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(... | 90 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
from __future__ import annotations
from math import gcd
def lowerCamelCase__ ( _A , _A = 2 , _A = 1 , _A = 3 , ):
# A value less than 2 can cause an infinite loop in the algorithm.
if num < 2:
raise ValueError('The input value cannot be less than 2' ... | 297 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
"""simple docstring"""
import re
from filelock import FileLock
try:
import nltk
SCREAMING_SNAKE_CASE__ = True
except (ImportError, ModuleNotFoundError):
SCREAMING_SNAKE_CASE__ = False
if NLTK_AVAILABLE:
with FileLock(".lock") as lock:
nltk.download("... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''simple docstring'''
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('''9.1.0'''):
A__: Union[str, Any] = {
'''linear''': PIL.Image.Resampli... | 276 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
BertTokenizerFast,
... | 329 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 249 | 0 |
"""simple docstring"""
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def lowercase ( a__ : List[str] ) -> int:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class UpperCAmelCase_ ( ... | 256 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class A__ ( __UpperCAmelCase ):
"""simple docstring"""
def __init__( ... | 99 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require_... | 66 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
PreTrainedTokenizer,
TFAutoModelForSequenceCla... | 287 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTester... | 244 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
import json
import os
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from requests.exceptions import HTTPError
from transformers.utils import (
CONFIG_NAME,
FLAX_WEIGHTS_NAME,
TF2_WEIGHTS_NAME,
TRANSFORMERS_CACHE,
WEIGHTS_NAME,
cached_file,
get_file_f... | 348 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers imp... | 249 | 0 |
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionImageVariationPipeline
from diffusers.utils.testing_utils import load_image, require_torch_gpu, slow, torch_device
__A = False
class __lowerCAmelCase ( unittest.TestCase ):
... | 90 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''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_torc... | 297 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
"""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_distilbert import DistilBertTokenizer
SCREAMING_SNAKE_CASE__ = logging.get_lo... | 46 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: int = logging.get_logger(__name__)
... | 276 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
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 __a ( UpperCAmelCase ):
_a : Optional[int] = (DPMSolverSDESchedule... | 329 |
"""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,
DDIMSchedu... | 249 | 0 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def lowercase ( a__ : List[Any] ) ->... | 256 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWithNoAttention,
TFBaseModelOutpu... | 99 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
__a = {
"configuration_vision_encoder_decoder": ["VisionEncoderDecoderConfig", "VisionEncoderDecode... | 66 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Opt... | 249 | 0 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=__SCREAMING_SNAKE_CASE)
class A__ ( __SCREAMING_SNAKE_CASE):
# `task` is not a ClassVar since we want it to be part of the `asdict` outp... | 287 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
from ...utils.du... | 244 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
import heapq
def lowerCAmelCase_ ( __lowerCAmelCase )-> str:
'''simple docstring'''
UpperCAmelCase : list[list] =[]
# for each node and his adjacency list add them and the rank of the node to queue
# using heapq module the queue will be filled like... | 348 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
snake_case_ = (DDIMParallelScheduler,)
snake_case_ = (('''e... | 90 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTester... | 297 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
class lowercase ( _UpperCAmelCase ):
def __init__( self , *lowercase ... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
A__: Optional[int] = '''\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a ... | 276 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
def lowerCAmelCase__ ( a__: str , a__: Tuple ) -> Any:
'''simple docstring'''
return price * (1 + tax_rate)
if __name__ == "__main__":
print(f'''{price_plus_tax(1_0_0, 0.25) = }''')
print(f'''{price_plus_tax(125.50, 0.05) = }''')
| 329 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 249 | 0 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
UpperCAmelCase = [
# (stable-diffusion, HF Diffusers)
("""time_embed.0.weight""", """time_embedding.lin... | 256 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
import argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
lowercase : List[str] = version.parse(version.p... | 99 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import BertConfig, 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_available():
... | 66 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
_lowerCamelCase =re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")
@total_ordering
@dataclass
class A__ :
_UpperCAmelCase ... | 287 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_torch_available
from ...utils import OptionalDependencyNotAvailable
lowerCamelCase_ = {
'''configuration_gpt_neox_japanese''': ['''GPT_NEOX_JAPANESE_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoXJapaneseConfig'''],
'''tokeniz... | 244 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class __snake_case ( lowerCamelCase__ ):
def __init__( self , snake_case__ , snake_case__ ) -> List[Any]:
'''simple docstring'''
UpperCAmelCase : ... | 348 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers imp... | 249 | 0 |
from __future__ import annotations
from collections import Counter
from random import random
class __lowerCAmelCase :
"""simple docstring"""
def __init__( self ) -> Any:
'''simple docstring'''
__lowerCamelCase = ... | 90 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase: Any = logging.get_logger(__name__)
lowerCAmelCase: Any = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/a... | 297 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
"""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,
DPMSolverMul... | 46 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
A__: Optional[int] ... | 276 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
def lowerCAmelCase__ ( a__: Optional[Any] ) -> Dict:
'''simple docstring'''
_UpperCAmelCase = 1
for i in range(1 , num + 1 ):
fact *= i
return fact
def lowerCAmelCase__ ( a__: Union[str, Any] ) -> List[Any]:
'... | 329 |
"""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,
DDIMSchedu... | 249 | 0 |
"""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_of_images, t... | 256 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
def A_ ( A__ ) -> Dict:
return " ".join(input_str.split()[::-1] )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 99 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
def A_ ( _lowercase ):
'''simple docstring'''
if not nums:
raise ValueError("""List is empty""" )
return sum(__UpperCamelCase ) / len(__UpperCamelCase )
if __name__ == "__main__":
import doctest
doc... | 66 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except Opt... | 249 | 0 |
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 ( lowerCamelCase, lowerCamelCase, lowe... | 287 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
from a... | 244 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
from heapq import heappop, heappush
import numpy as np
def lowerCAmelCase_ ( __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , __lowerCAmelCase , )-> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase : List[str] =grid... | 348 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_toke... | 90 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@require... | 297 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
"""simple docstring"""
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowercase :
_SCREAMING_SNAKE_CASE = None
def _snake_case ( self ) -> Dict:
lowerCAmelCase = ... | 46 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''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_extract... | 276 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase__ :Tuple = {
'''configuration_blip''': [
'''BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''... | 329 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/... | 249 | 0 |
"""simple docstring"""
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
UpperCAmelCase = logging.get_logger("""transformers.models.speecht5""")
def lowercase ( a__ : List[str] , a__ : Any... | 256 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available():
imp... | 99 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
def A_ ( _lowercase ):
'''simple docstring'''
snake_case_ :Optional[Any] = [0] * len(__UpperCamelCase )
snake_case_ :int = []
snake_case_ :List[Any] = []
snake_case_ :int = 0
for values in graph.values():
... | 66 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
def _a ( lowerCamelCase ):
if p < 2:
raise ValueError("""p should not be less than 2!""" )
elif p == 2:
return True
lowerCamelCase : List[Any] = 4
lowerCamelCase : List[Any] = (1 << p) - 1
for _ in range(p - 2 ):
lowerCamelCase : List[str] = ... | 287 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
import heapq as hq
import math
from collections.abc import Iterator
class __A:
"""simple docstring"""
def __init__(self , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase__ = str(id_ )
UpperCamelCase__ = None
UpperCamelCase__ = None
UpperCamelCase... | 244 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
from typing import Any
def lowerCAmelCase_ ( __lowerCAmelCase )-> str:
'''simple docstring'''
if not input_list:
return []
UpperCAmelCase : Dict =[input_list.count(__UpperCamelCase ) for value in input_list]
UpperCAmelCase : Tup... | 348 |
"""simple docstring"""
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers imp... | 249 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | 250 |
'''simple docstring'''
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 250 | 1 |
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