code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __snake... | 100 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 0 |
def a__ ( A__, A__ ):
return number | (1 << position)
def a__ ( A__, A__ ):
return number & ~(1 << position)
def a__ ( A__, A__ ):
return number ^ (1 << position)
def a__ ( A__, A__ ):
... | 101 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( ... | 627 | 0 |
"""simple docstring"""
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
__magic_name__ : Lis... | 102 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 0 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testin... | 103 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 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:
i... | 104 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCamelCase__ : Dict = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCHIVE_MAP''... | 105 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 0 |
import argparse
import torch
from transformers import (
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaForAudioFrameClassification,
WavaVecaForSequenceClassification,
WavaVecaForXVector,
logging,
)
logging.set_verbosity_info()
__snake_case :Optional[Any] =logging.get_logg... | 106 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 0 |
'''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration... | 107 |
'''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__ = "CLIPImageProcesso... | 627 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
__a: Dict = {
'''configuration_mobilevit''': ['''MOBILEVIT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''MobileViTConfi... | 108 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 0 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class __a ( metaclass=_snake_case ):
__UpperCamelCase : Optional[Any] = ['onnx']
def __init__( self : List[str] ,*lowerCamelCase : str ,**lowerCamelCase : Dic... | 109 |
'''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
#
# ... | 627 | 0 |
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" , [
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""": 10, """max_num_jobs""":... | 386 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'unc-nlp/lxmert-base-uncased': 'https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json',
}
class lowerCAmelCase_ ( _... | 10 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 0 |
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
from .d... | 144 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 0 |
'''simple docstring'''
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
a__ : Optional[Any] = parse(importlib.metadata.version('torch'))
def _lowercase ( __A ,__... | 601 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 0 |
def snake_case ( snake_case__ :Any) -> List[Any]:
if length <= 0 or not isinstance(a__ , a__):
raise ValueError("""Length must be a positive integer.""")
return [n * (2 * n - 1) for n in range(a__)]
if __name__ == "__main__":
print(hexagonal_numbers(len... | 401 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCamelCase__ : Tuple, lowerCamelCase__ : Dict ) -> List[Any]:
_SCREAMING_SNAKE_CASE : Any = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
_SCREAMING_SNAKE_CASE : Dict ... | 572 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 0 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase ( metaclass=__a ):
a__ :Tuple = ['''torch''', '''scipy''']
def __init__(self , *__UpperCamelCase , **__UpperCamelCase ) -> List[str]:
requires_backends(self ... | 635 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 0 |
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase__ ( snake_case ):
"""simple docstring"""
lowerCAmelCase__ : Dict = ['image_processor', 'tokenizer']
lowerCAmelCase__ : Optional[int] = 'A... | 221 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 0 |
from math import isqrt, loga
def lowerCAmelCase_ ( __A ) -> Optional[Any]:
'''simple docstring'''
UpperCAmelCase__ = [True] * max_number
for i in range(2, isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
for j... | 486 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 0 |
import math
import sys
import cva
import numpy as np
def __lowerCamelCase ( A__ : Optional[int] , A__ : Union[str, Any] ) -> str:
lowerCamelCase_ : Any = math.sqrt(a__ )
lowerCamelCase_ : Dict = 1 / (sigma * math.sqrt(2 * math.pi ))
return ... | 278 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 0 |
def lowerCamelCase__ ( _A = 2000000 ):
'''simple docstring'''
snake_case_ = [0 for i in range(n + 1 )]
snake_case_ = 1
snake_case_ = 1
for i in range(2 , int(n**0.5 ) + 1 ):
if primality_list[i] == 0:
... | 376 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 0 |
import enum
import os
from hashlib import shaaaa
from typing import Optional
from .. import config
from .logging import get_logger
__snake_case = get_logger(__name__)
class UpperCAmelCase ( enum.Enum ):
lowercase = """all_checks"""
lowercase ... | 386 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 0 |
def _snake_case ( __snake_case , __snake_case , __snake_case ):
if n == 0:
return 1
elif n % 2 == 1:
return (binary_exponentiation(a__ , n - 1 , a__ ) * a) % mod
else:
_UpperCamelCase = binary_exponentiation(a__ , n / 2... | 10 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
f... | 144 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( ... | 627 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
a__ : List[Any] = {'tokenization_herbert': ['HerbertTokenizer']}
try:
if not is_tokenizers_available():
raise OptionalDep... | 601 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 0 |
def snake_case ( snake_case__ :Tuple , snake_case__ :Optional[int] , snake_case__ :Tuple) -> Union[str, Any]:
if principal <= 0:
raise Exception("""Principal borrowed must be > 0""")
if rate_per_annum < 0:
raise Exception("""Rate of i... | 401 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def _lowerCAmelCase ( lowerCamelCase__ : str, lowerCamelCase__ : List[str] ) -> Union[str, Any]:
return math.sqrt(sum(pow(a - b, 2 ) for a, b... | 572 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 0 |
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : int ):
UpperCamelCase_ : Dict = n ** (1 / 3)
return (val * val * val) == n
if __name__ == "__main__":
print(perfect_cube(27))
print(perfect_cube(4))
| 635 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
a_ = {
'configuration_mctct': ['MCTCT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MCTCTConfig'],
'feature_extraction_mctct': ['MCTCTFeatureExtractor'],
'processing_mctct': ['MCTCTProcesso... | 221 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 0 |
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict import IterableDatasetDict... | 486 |
'''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__ = "CLIPImageProcesso... | 627 | 0 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def __lowerCamelCase ( A__ : Optional[int] , A__ : Any ) -> Optional[Any]:
lowerCamelCase_ : List[str] = list(a__ )
lowerCamelCase_ : Tuple = list(a... | 278 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 0 |
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, require_pyazr... | 376 |
'''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
#
# ... | 627 | 0 |
import math
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import SchedulerMixin, SchedulerOutput
class UpperCAmelCase ( __snake_case , __snake_case ):
... | 386 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
'facebook/nllb-moe-54B': 'https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json',
}
class lowerCAmelCase_ ( __lowercase )... | 10 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 0 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)
... | 144 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from tr... | 601 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 0 |
def snake_case ( snake_case__ :Optional[int] , snake_case__ :Optional[Any] = " ") -> Optional[int]:
_A = []
_A = 0
for index, char in enumerate(a__):
if char == separator:
split_words.append(string[last_index:index])
... | 401 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 0 |
"""simple docstring"""
import comet # From: unbabel-comet
import torch
import datasets
lowercase_ : Dict = datasets.logging.get_logger(__name__)
lowercase_ : List[str] = '\\n@inproceedings{rei-EtAl:2020:WMT,\n author = {Rei, Ricardo and Stewart, Craig ... | 572 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 0 |
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils... | 635 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 0 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configuratio... | 221 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 0 |
import importlib
import torch
import yaml
from omegaconf import OmegaConf
from taming.models.vqgan import VQModel
def lowerCAmelCase_ ( __A, __A=False ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase__ = OmegaConf.load(a__ )
... | 486 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import... | 278 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 0 |
def lowerCamelCase__ ( _A = 1000 ):
'''simple docstring'''
snake_case_ = 2**power
snake_case_ = 0
while n:
snake_case_ , snake_case_ = r + n % 10, n // 10
return r
if __name__ == "__main__":
print(solution(i... | 376 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 0 |
import argparse
import os
from pathlib import Path
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import PegasusConfig, PegasusForConditionalGeneration, PegasusTokenizer
from transformers.models.pegasus.configuration_pegasus import DEFAULTS, task_s... | 386 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 0 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_lowerCAmelCase = '\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={Wang, Alex and Pruksac... | 10 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 0 |
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 (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_channel_dimen... | 144 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( ... | 627 | 0 |
'''simple docstring'''
import os
a__ : Dict = {'I': 1, 'V': 5, 'X': 1_0, 'L': 5_0, 'C': 1_0_0, 'D': 5_0_0, 'M': 1_0_0_0}
def _lowercase ( __A ):
'''simple docstring'''
__UpperCamelCase = 0
__UpperCamelCase = 0
while index <... | 601 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onn... | 401 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCamelCase__ : Tuple, lowerCamelCase__ : Tuple, lowerCamelCase__ : Union[str, Any] ) -> Dict:
if exponent == 1:
return base
if exponent % 2 == 0:
_SCREAMING_SNAKE_CASE : Dict = _modexpt(a__, ex... | 572 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 0 |
import unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase ( unittest.TestCase ):
a__ :List[Any] = JukeboxTokenizer
a__ :Tuple = {
'''artist''': '''Zac Brown Band''',
'''... | 635 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 0 |
def __lowerCAmelCase ( A_ : Dict , A_ : Dict ) -> Optional[int]:
return int((input_a, input_a).count(0 ) == 0 )
def __lowerCAmelCase ( ) -> Optional[int]:
assert and_gate(0 , 0 ) == 0
assert and_gate(0 , 1 ) == 0
assert and_ga... | 221 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCAmelCase_ ( __A ) -> str:
'''simple docstring'''
def is_in_circle(__A, __A ) -> bool:
UpperCAmelCase__ = ... | 486 |
'''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__ = "CLIPImageProcesso... | 627 | 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__ : Union[str, Any] = logging.get_logger(__name__)
snake_case__ : List[str] ... | 278 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : Union[str, Any] = logging.get_logger(__name__)
lowercase_... | 376 |
'''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
#
# ... | 627 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class UpperCAmelCase ( __snake_case ):
lowercase ... | 386 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 0 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get_gp... | 10 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 0 |
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowerCamelCase = TypeVar('T')
class a ( Generic[T] ):
'''simple docstring'''
def __init__( self : Optional[int] , __snake_case : b... | 144 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 0 |
'''simple docstring'''
import random
from .binary_exp_mod import bin_exp_mod
def _lowercase ( __A ,__A=1_000 ):
'''simple docstring'''
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
__UpperCamelCase = n - 1
__U... | 601 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 0 |
from __future__ import annotations
def snake_case ( snake_case__ :Dict , snake_case__ :List[str]) -> Tuple:
if nth_term == "":
return [""]
_A = int(a__)
_A = int(a__)
_A = []
for temp in range(int(a__)):
... | 401 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase ( ... | 572 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 0 |
from __future__ import annotations
SCREAMING_SNAKE_CASE : Tuple = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : List[Any] , _SCREAMING_... | 635 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 0 |
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if version.parse(fairseq.__versi... | 221 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 0 |
def lowerCAmelCase_ ( __A, __A ) -> Dict:
'''simple docstring'''
return number | (1 << position)
def lowerCAmelCase_ ( __A, __A ) -> Optional[int]:
'''simple docstring'''
return number & ~(1 << position)
... | 486 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case__ : Optional[int] = logging.get_logger(__name__)
snake_case__ : Any = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/resolve/main/config.json',
}
class ... | 278 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 0 |
def lowerCamelCase__ ( _A , _A ):
'''simple docstring'''
if a < 0 or b < 0:
raise ValueError("the value of both inputs must be positive" )
snake_case_ = str(bin(a__ ) )[2:] # remove the leading "0b"
snake_case_ = str(b... | 376 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 0 |
import sys
__snake_case = (
'73167176531330624919225119674426574742355349194934'
'96983520312774506326239578318016984801869478851843'
'85861560789112949495459501737958331952853208805511'
'12540698747158523863050715693290963295227443043557'
'6689664895044524452316173185640309871112... | 386 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 0 |
import argparse
from .config import config_command_parser
from .config_args import default_config_file, load_config_from_file # noqa: F401
from .default import default_command_parser
from .update import update_command_parser
def _snake_case ( __snake_case=None ):
_UpperCamelCase = argparse.... | 10 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 0 |
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : List[Any] ) -> Union[str, Any]:
if not head:
return True
# split the list to two parts
UpperCAmelCase_ , UpperCAmelCase_ = head.next, head
while fast and fast.next:
UpperCAmelCase_ ... | 144 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( ... | 627 | 0 |
'''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 UpperCAmelCase__ ( UpperCAmelCa... | 601 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 0 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import GradientStat... | 401 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 0 |
"""simple docstring"""
import random
def _lowerCAmelCase ( lowerCamelCase__ : int, lowerCamelCase__ : Any, lowerCamelCase__ : str ) -> List[str]:
_SCREAMING_SNAKE_CASE : int = a[left_index]
_SCREAMING_SNAKE_CASE : int = left_index + 1... | 572 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 0 |
from __future__ import annotations
import math
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Optional[int] , _SCREAMING_SNAKE_CASE : Optional[Any] ):
UpperCamelCase_ : Dict = u
for i in range(1 , a__ ):
UpperCamelCase_ : Any = temp... | 635 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 0 |
import numpy
class UpperCAmelCase__ :
"""simple docstring"""
def __init__( self: Union[str, Any] , __lowerCAmelCase: numpy.ndarray , __lowerCAmelCase: numpy.ndarray ) -> None:
'''simple docstring'''
__UpperCAmelCase = input_ar... | 221 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 0 |
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 (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_ch... | 486 |
'''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__ = "CLIPImageProcesso... | 627 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
snake_case__ : int = {'configuration_dpt': ['DPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'DPTConfig']}
try:
... | 278 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Any = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
... | 376 |
'''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
#
# ... | 627 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase ( __snake_case ):
lowercase = ["""image_processor""", """tokenizer"""]
lowercase = """CLIPImageProcessor"""
... | 386 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 0 |
from typing import List, Optional, Union
import torch
from transformers import (
XLMRobertaTokenizer,
)
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDIMScheduler, DDPMScheduler
... | 10 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 0 |
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
_lowerCamelCase = {
... | 144 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models.modeling_utils import ModelMixin
class lowerCAmelCase__ ( a , a ):
"""simple docstring"""
@register_to_config
de... | 627 | 0 |
'''simple docstring'''
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.s... | 601 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
)... | 627 | 0 |
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
_SCREAMING_SNAKE_CASE = '.'
# Internal TensorFlow ops tha... | 401 |
'''simple docstring'''
import math
def a__ ( a__ ):
"""simple docstring"""
return math.sqrt(a__ ) * math.sqrt(a__ ) == num
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
__SCREAMING_SNAKE_CASE = n
while left <= ... | 627 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( lowerCamelCase__ : Dict ) -> str:
_SCREAMING_SNAKE_CASE : List[str] = [0] * len(a__ )
_SCREAMING_SNAKE_CASE : Optional[int] = []
_SCREAMING_SNAKE_CASE : List[str] = []
_SCREAMING_SNAKE_CASE : ... | 572 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
UpperCAmelCase : Any = 'src/transformers'
# This is to make sure the transfo... | 627 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( _SCREAMING_SNAKE_CASE : Dict ):
return len(set(a__ ) ) == len(a__ )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 635 |
'''simple docstring'''
import multiprocessing
import time
from arguments import PretokenizationArguments
from datasets import load_dataset
from transformers import AutoTokenizer, HfArgumentParser
def a__ ( a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = {}
__SCREAM... | 627 | 0 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
DataCo... | 221 |
'''simple docstring'''
import unittest
from transformers.models.xlm_prophetnet.tokenization_xlm_prophetnet import SPIECE_UNDERLINE, XLMProphetNetTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, slow
from transformers.utils import cached_property
from ...test_tokenization_com... | 627 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
UpperCamelCase__ = pd.read_csv('sample_data.csv', header=None)
UpperCamelCase__... | 486 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def a__ ( a__ , a__ ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = math.sqrt(a__ )
__SCREAMING_SNAKE_CASE = 1 / (sigma * math.sqrt(2 * math.pi ))
return cons * np.exp(-((img /... | 627 | 0 |
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class SCREAMING_SNAKE_CASE_ (unittest.TestCase ):
'''simple docstring'''
def _lowerCAmelCase ... | 278 |
'''simple docstring'''
import argparse
from pathlib import Path
import fairseq
import torch
from fairseq.models.xmod import XMODModel as FairseqXmodModel
from packaging import version
from transformers import XmodConfig, XmodForMaskedLM, XmodForSequenceClassification
from transformers.utils import logging
if v... | 627 | 0 |
import requests
lowercase__ : Dict = 'YOUR API KEY'
def lowerCamelCase__ ( _A , _A = giphy_api_key ):
'''simple docstring'''
snake_case_ = "+".join(query.split() )
snake_case_ = f"https://api.giphy.com/v1/gi... | 376 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfi... | 627 | 0 |
def _lowercase ( SCREAMING_SNAKE_CASE_ : Tuple ):
"""simple docstring"""
UpperCamelCase = current_set.copy()
for row_index, row in enumerate(a__ ):
UpperCamelCase = row[0]
for column_index, column in enumerate(a__ ):
... | 386 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Union[str, Any] = logging.get_logger(__name__)
UpperCAmelCase : Any = {
'uw-madison/mra-base-512-4': 'https://huggingface.co/uw-madison/mra-base-512-4/resolve/main... | 627 | 0 |
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_ ( unittest.TestCase ):
@prop... | 10 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class lowerCAmelCase__ ( unittes... | 627 | 0 |
def SCREAMING_SNAKE_CASE ( __UpperCamelCase : List[str] ) -> Union[str, Any]:
if not nums: # Makes sure that the list is not empty
raise ValueError('''List is empty''' )
UpperCAmelCase_ = sum(a__ ) / len(a__ ) # Calculate the average
return sum(abs(... | 144 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCAmelCase__ ( ... | 627 | 0 |
'''simple docstring'''
import warnings
from typing import List
from unittest.mock import Mock
import torch
from torch.utils.data import DataLoader, IterableDataset, TensorDataset
from accelerate.accelerator import Accelerator
from accelerate.utils.dataclasses import DistributedType
class ... | 601 |
'''simple docstring'''
UpperCAmelCase : Tuple = range(2, 2_0 + 1)
UpperCAmelCase : int = [1_0**k for k in range(ks[-1] + 1)]
UpperCAmelCase : dict[int, dict[int, list[list[int]]]] = {}
def a__ ( a__ , a__ , a__ , a__ ):
"""simple docstri... | 627 | 0 |
def snake_case ( snake_case__ :Dict = 50) -> Optional[int]:
_A = [1] * (length + 1)
for row_length in range(length + 1):
for tile_length in range(2 , 5):
for tile_start in range(row_length - tile_length + 1):
... | 401 |
'''simple docstring'''
import random
import unittest
import torch
from diffusers import IFInpaintingPipeline
from diffusers.utils import floats_tensor
from diffusers.utils.import_utils import is_xformers_available
from diffusers.utils.testing_utils import skip_mps, torch_device
from ..pipeline_params import (
... | 627 | 0 |
"""simple docstring"""
from pickle import UnpicklingError
import jax
import jax.numpy as jnp
import numpy as np
from flax.serialization import from_bytes
from flax.traverse_util import flatten_dict
from ..utils import logging
lowercase_ : List[Any] = logging.get_logger(__name__)
... | 572 |
'''simple docstring'''
from math import isqrt
def a__ ( a__ ):
"""simple docstring"""
return all(number % divisor != 0 for divisor in range(2 , isqrt(a__ ) + 1 ) )
def a__ ( a__ = 10**6 ):
"""simple docstring"""
__SCREAMING_SNAKE_CASE = 0
... | 627 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class UpperCamelCase ( __a ):
def __init__(self , __UpperCamelCas... | 635 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Tuple = logging.get_logger(__name__)
UpperCAmelCase : Any = {'ctrl': 'https://huggingface.co/ctrl/resolve/main/config.json'}
class lowerCAmelCase__ ( a ):
... | 627 | 0 |
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def __lowerCAmelCase ( A_ : Dict ) -> Union[str, Any]:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remote_code )
class UpperCAmelCase__ ( ... | 221 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common impor... | 627 | 0 |
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def lowerCAmelCase_ ( __A, __A ) ->... | 486 |
'''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__ = "CLIPImageProcesso... | 627 | 0 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
snake_case__ : int = Mapping[str, np.ndarray]
snake_case__ : int = Mapping[str, Any] # Is a nested di... | 278 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
fr... | 627 | 0 |
from math import cos, sin, sqrt, tau
from audio_filters.iir_filter import IIRFilter
def lowerCamelCase__ ( _A , _A , _A = 1 / sqrt(2 ) ):
'''simple docstring'''
snake_case_ = tau * frequency / samplerate
snake_case_ = s... | 376 |
'''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
#
# ... | 627 | 0 |
import inspect
import unittest
class UpperCAmelCase ( unittest.TestCase ):
def lowerCamelCase_ ( self : Dict ):
"""simple docstring"""
try:
import diffusers # noqa: F401
except ImportError:
... | 386 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fro... | 627 | 0 |
import math
def _snake_case ( __snake_case , __snake_case ):
_UpperCamelCase = len(a__ )
_UpperCamelCase = int(math.floor(math.sqrt(a__ ) ) )
_UpperCamelCase = 0
while arr[min(a__ , a__ ) - 1] < x:
_UpperCamelCa... | 10 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common imp... | 627 | 0 |
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