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 |
|---|---|---|---|---|
def UpperCamelCase ( snake_case__ : int ) -> str:
if isinstance(snake_case__ , snake_case__ ):
raise TypeError('\'float\' object cannot be interpreted as an integer' )
if isinstance(snake_case__ , snake_case__ ):
raise TypeError('\'str\' object can... | 40 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 621 | 0 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def _A ( A__ ):
"""simple docstring"""
__lowercase = FileLock(str(tmpdir / '''foo.lock''' ) )
__lowercase = FileLock(str(tmpdir / '''foo.lock''' ) )
... | 41 |
"""simple docstring"""
lowerCAmelCase__ = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lower... | 621 | 0 |
'''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilB... | 42 |
"""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 transformers.utils i... | 621 | 0 |
def _a ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
"""simple docstring"""
lowercase__ = ''''''
for word_or_phrase in separated:
if not isinstance(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
raise Exception('''join() accepts only strings to be join... | 43 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 621 | 0 |
'''simple docstring'''
def A_ ( _lowerCAmelCase : int ):
"""simple docstring"""
if not isinstance(_lowerCAmelCase , _lowerCAmelCase ):
raise ValueError("check_bouncy() accepts only integer arguments" )
_lowerCamelCase : Optional[int] ... | 44 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSeque... | 621 | 0 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
from ... im... | 45 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_=None , lowerCAmelCase_=None ) -> int:
_SCREAMING_SNAKE_CASE : Optional[int] = data
_SCREAMING_SNAKE_CASE : Tuple = ... | 621 | 0 |
"""simple docstring"""
import math
def lowerCamelCase_( _lowerCamelCase ) -> list:
'''simple docstring'''
_lowerCamelCase : List[str] = [True] * n
_lowerCamelCase : Optional[int] = False
_lowerCamelCase : List[str] = Fals... | 46 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import hugg... | 621 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
... | 47 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ ) -> None:
_SCREAMING_SNAKE_CASE : Dict = size
_SCREAMING_SNAKE_CASE : str = [0] * size
_SCREAMING_SNAKE_CASE : Any = ... | 621 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
UpperCAmelCase__ : int = {"configuration_van": ["VAN_PRETRAINED_CONFIG_ARCHIVE_MAP", "VanConfig"]}
try:
if not is_torch_available():
... | 48 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'huggingface/time-series-transformer-tourism-monthly': (
'htt... | 621 | 0 |
"""simple docstring"""
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class _UpperCAmelCase ( _lowerCAmelCase ):
# to overwrit... | 49 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input('Enter image url: ').strip()
print(F'Downloading image from {url} ...')
lowerCAmelCase__ = BeautifulSoup(requests.get(url).conten... | 621 | 0 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=a )
class UpperCamelCase__ (a ):
'''simple docstring'''
_UpperCamelCase ... | 50 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/... | 621 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a__ : List[Any] = {'configuration_xlnet': ['XL... | 51 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 621 | 0 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_sch... | 52 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 621 | 0 |
from __future__ import annotations
import math
from collections.abc import Callable
def a_ ( lowerCAmelCase_ : Callable[[int | float], int | float], lowerCAmelCase_ : int | float, lowerCAmelCase_ : int | float, lowerCAmelCase_ : int = 100, ):
__lowerCAmelCase... | 53 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowercase_... | 621 | 0 |
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import require_tokenizers, require_vision
fro... | 54 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return abs(lowerCamelCase ) if a == 0 else greatest_common_divisor(b % a, lowerCamelCase )
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
while y: # --> when y=0 ... | 621 | 0 |
from __future__ import annotations
import math
import random
from typing import Any
class UpperCAmelCase :
'''simple docstring'''
def __init__( self : Tuple ):
__A = []
__A = 0
__A = 0
def UpperCamelCase_ ( self : Li... | 55 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCAmelCase__ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for T... | 621 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a : Optional[int] = {
"configuration_nllb_moe": [
"NLLB_MOE_PRETRAINED_CONFIG_ARCHIVE_MAP",
"NllbMoeConfig",
]
}
try:
i... | 56 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
lowerCAmelCase__ = r'\n Args:\n input_ids (`jnp.ndarray` of ... | 621 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer... | 57 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
fro... | 621 | 0 |
"""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
__lowerCAmelCase : Any = '''src/transform... | 58 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase__ ( ):
_SCREAMING_SNAKE_CASE : dict[int, int] = {}
_SCREAMING_SNAKE_CASE : List[Any] = 2
while True:
_SCREAMING_SNAKE_CASE : List[Any] ... | 621 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {
"configuration_informer": [
"INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP",
"InformerConfig",
],
}
try:
if no... | 59 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 621 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( _UpperCamelCase ) -> list:
"""simple docstring"""
if len(_UpperCamelCase ) == 0:
return []
snake_case_ , snake_case_ : Dict = min(_UpperCamelCase ), max(_UpperCamelCase ... | 60 |
"""simple docstring"""
import operator as op
def lowercase__ ( lowerCamelCase ):
_SCREAMING_SNAKE_CASE : int = []
_SCREAMING_SNAKE_CASE : Dict = lambda lowerCamelCase, lowerCamelCase : int(x / y ) # noqa: E731 integer division operation
... | 621 | 0 |
from __future__ import annotations
import math
def _A ( lowerCAmelCase_ : int ):
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all e... | 61 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
import qiskit
def lowerCamelCase__ ( lowercase , lowercase ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Dict = qiskit.Aer.get_backend("aer_simulator" )
SCREAMING_SNAKE_CASE : Dict = qiskit.QuantumCircuit(4 , 2 )
# encode i... | 62 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 621 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 63 |
"""simple docstring"""
lowerCAmelCase__ = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lower... | 621 | 0 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : Optional[int] = {
'RUCAIBox/mvp': 'https://huggingface.co/RUCAIBox/mvp/resolve/main/config.json',
}
class _lowerCamelCase ... | 64 |
"""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 transformers.utils i... | 621 | 0 |
"""simple docstring"""
def lowerCAmelCase ( __UpperCamelCase ):
'''simple docstring'''
if not isinstance(__UpperCamelCase , __UpperCamelCase ):
raise ValueError("""Input must be an integer""" )
if input_num <= 0:
raise ValueError("""Input must be positive""" )... | 65 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 621 | 0 |
import copy
import unittest
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modelin... | 66 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSeque... | 621 | 0 |
import os
def SCREAMING_SNAKE_CASE__ ( ) -> List[Any]:
with open(os.path.dirname(snake_case__ ) + '/grid.txt' ) as f:
_lowercase = [] # noqa: E741
for _ in range(20 ):
l.append([int(snake_case__ ) for x in f.readline().split()] )
_lowercase ... | 67 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_=None , lowerCAmelCase_=None ) -> int:
_SCREAMING_SNAKE_CASE : Optional[int] = data
_SCREAMING_SNAKE_CASE : Tuple = ... | 621 | 0 |
def lowercase__ ( A_: int , A_: int ) -> int:
"""simple docstring"""
return int((input_a, input_a).count(1 ) != 0 )
def lowercase__ ( ) -> None:
"""simple docstring"""
assert or_gate(0 , 0 ) == 0
... | 68 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import hugg... | 621 | 0 |
'''simple docstring'''
def __UpperCAmelCase ( _UpperCAmelCase : int ) -> bool:
return number & 1 == 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 69 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ ) -> None:
_SCREAMING_SNAKE_CASE : Dict = size
_SCREAMING_SNAKE_CASE : str = [0] * size
_SCREAMING_SNAKE_CASE : Any = ... | 621 | 0 |
import argparse
import os
import torch
from transformers import FlavaConfig, FlavaForPreTraining
from transformers.models.flava.convert_dalle_to_flava_codebook import convert_dalle_checkpoint
def _SCREAMING_SNAKE_CASE ( lowercase : str ):
'''simple docstring'''
... | 70 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'huggingface/time-series-transformer-tourism-monthly': (
'htt... | 621 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def a__ ( _SCREAMING_SNAKE_CASE : Callable[[int | float], int | float] , _SCREAMING_SNAKE_CASE : int | float , _SCREAMING_SNAKE_CASE : int | float , _SCREAMING_SNAKE_CAS... | 71 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input('Enter image url: ').strip()
print(F'Downloading image from {url} ...')
lowerCAmelCase__ = BeautifulSoup(requests.get(url).conten... | 621 | 0 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import SwinvaConfig
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_c... | 72 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/... | 621 | 0 |
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tenso... | 73 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 621 | 0 |
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table import array_cast
from ..utils... | 74 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 621 | 0 |
'''simple docstring'''
def a__ ( lowerCAmelCase__ = 50 ) -> int:
UpperCAmelCase__ : int = [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... | 75 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowercase_... | 621 | 0 |
"""simple docstring"""
from sympy import diff, lambdify, symbols
from sympy.functions import * # noqa: F403
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase = "x" , __UpperCamelCase = 10**-10 , __UpperCamelCase = 1 , ):
__lower... | 76 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return abs(lowerCamelCase ) if a == 0 else greatest_common_divisor(b % a, lowerCamelCase )
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
while y: # --> when y=0 ... | 621 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
A = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""tokenizat... | 77 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCAmelCase__ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for T... | 621 | 0 |
'''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_... | 78 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
lowerCAmelCase__ = r'\n Args:\n input_ids (`jnp.ndarray` of ... | 621 | 0 |
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokenizer,
... | 79 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
fro... | 621 | 0 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformers.utils import lo... | 80 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase__ ( ):
_SCREAMING_SNAKE_CASE : dict[int, int] = {}
_SCREAMING_SNAKE_CASE : List[Any] = 2
while True:
_SCREAMING_SNAKE_CASE : List[Any] ... | 621 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_tf_cross_test,
require_tf,
require_torch,
require_torchvision,
require_vision,
)
from transformers.utils import is_tf_available, is_torch_available, is_vision_available
if is_vision... | 81 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 621 | 0 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
f... | 82 |
"""simple docstring"""
import operator as op
def lowercase__ ( lowerCamelCase ):
_SCREAMING_SNAKE_CASE : int = []
_SCREAMING_SNAKE_CASE : Dict = lambda lowerCamelCase, lowerCamelCase : int(x / y ) # noqa: E731 integer division operation
... | 621 | 0 |
"""simple docstring"""
import os
import re
import shutil
import sys
import tempfile
import unittest
import black
lowerCAmelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, '''utils'''))
import check_copies ... | 83 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_common im... | 84 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 621 | 0 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import ConfigTester... | 85 |
"""simple docstring"""
lowerCAmelCase__ = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lower... | 621 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def __snake_case ( __UpperCamelCase : str ,__UpperCamelCase : str ,**__UpperCamelCase : str ):
"""simple docstring"""
A_ = AutoConfig.from_pretrained(__UpperCamelCase ,*... | 86 |
"""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 transformers.utils i... | 621 | 0 |
import math
from collections.abc import Iterator
from itertools import takewhile
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or ... | 87 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 621 | 0 |
"""simple docstring"""
import argparse
import torch
from transformers import LxmertConfig, LxmertForPreTraining, load_tf_weights_in_lxmert
from transformers.utils import logging
logging.set_verbosity_info()
def _snake_case ( __snake_case : Tuple , __snake_case : ... | 88 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSeque... | 621 | 0 |
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from torchvision import transforms
from transformers import BitImageProcessor, FocalNetConfig, FocalNetForImageClassification
from transformers.image_utils import IMAGENET_DEFAULT_MEAN, IMAGEN... | 89 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_=None , lowerCAmelCase_=None ) -> int:
_SCREAMING_SNAKE_CASE : Optional[int] = data
_SCREAMING_SNAKE_CASE : Tuple = ... | 621 | 0 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def _snake_case ( A , A , A , A , A ) -> np.array:
lowerCAmelCase__ = int(np.ceil((x_end - xa) / step_size ) )
lowerCAmelCase__ ... | 90 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import hugg... | 621 | 0 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
f... | 91 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ ) -> None:
_SCREAMING_SNAKE_CASE : Dict = size
_SCREAMING_SNAKE_CASE : str = [0] * size
_SCREAMING_SNAKE_CASE : Any = ... | 621 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested... | 92 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'huggingface/time-series-transformer-tourism-monthly': (
'htt... | 621 | 0 |
"""simple docstring"""
from __future__ import annotations
def __A (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) ->tuple[int, int]:
"""simple docstring"""
if b == 0:
return (1, 0)
((lowerCAmelCase__) , (lowerCAmelCase__)) :Optional[Any] = extended_euc... | 93 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input('Enter image url: ').strip()
print(F'Downloading image from {url} ...')
lowerCAmelCase__ = BeautifulSoup(requests.get(url).conten... | 621 | 0 |
'''simple docstring'''
import collections
import os
from typing import List, Optional, Tuple
from transformers.utils import is_jieba_available, requires_backends
if is_jieba_available():
import jieba
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
SCREAMING_SNAKE... | 94 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/... | 621 | 0 |
"""simple docstring"""
from ... import PretrainedConfig
lowerCamelCase_ = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class UpperCamelCase_ (__A ):
__magic_name__ = NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP
... | 95 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 621 | 0 |
"""simple docstring"""
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowerCamelCase = logging.get_logger(__name__)
__lowerCamelCase = {
'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/c... | 96 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 621 | 0 |
from collections import defaultdict
from typing import Optional
from ..image_utils import load_image
from ..utils import (
add_end_docstrings,
is_torch_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, ChunkPipeline
if is_torch_available():
import to... | 97 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowercase_... | 621 | 0 |
'''simple docstring'''
from __future__ import annotations
lowercase__ : Dict = [-10, -5, 0, 5, 5.1, 11, 13, 21, 3, 4, -21, -10, -5, -1, 0]
lowercase__ : Optional[int] = [-5, 0, 5, 5.1, 11, 13, 21, -1, 4, -1, -10, -5, -1, 0, -1]
def a__ ( lowercase : list[float] ... | 98 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return abs(lowerCamelCase ) if a == 0 else greatest_common_divisor(b % a, lowerCamelCase )
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
while y: # --> when y=0 ... | 621 | 0 |
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available
from diffuse... | 99 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCAmelCase__ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for T... | 621 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import torch
from datasets import load_dataset
from torchvision.transforms import Compose, Lambda, Normalize, RandomHorizontalFlip, RandomResizedCrop, ToTensor
from torchvision.transforms.functional import In... | 100 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
lowerCAmelCase__ = r'\n Args:\n input_ids (`jnp.ndarray` of ... | 621 | 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,
TFAut... | 101 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
fro... | 621 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCamelCase (SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
if len(SCREAMING_SNAKE_CASE ) == 0:
raise ValueError("""find_max() arg is an empty sequence""... | 102 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase__ ( ):
_SCREAMING_SNAKE_CASE : dict[int, int] = {}
_SCREAMING_SNAKE_CASE : List[Any] = 2
while True:
_SCREAMING_SNAKE_CASE : List[Any] ... | 621 | 0 |
"""simple docstring"""
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, Ag... | 103 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 621 | 0 |
"""simple docstring"""
import inspect
import unittest
from transformers import ViTMSNConfig
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_config... | 104 |
"""simple docstring"""
import operator as op
def lowercase__ ( lowerCamelCase ):
_SCREAMING_SNAKE_CASE : int = []
_SCREAMING_SNAKE_CASE : Dict = lambda lowerCamelCase, lowerCamelCase : int(x / y ) # noqa: E731 integer division operation
... | 621 | 0 |
from PIL import Image
def __UpperCAmelCase ( lowerCamelCase_ : Image ) -> Image:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ : List[Any] = image.size
SCREAMING_SNAKE_CASE_ : str = 0
SCREAMING_SNAKE_CAS... | 105 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor, ids_tensor, random_attenti... | 106 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 621 | 0 |
'''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_co... | 107 |
"""simple docstring"""
lowerCAmelCase__ = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lower... | 621 | 0 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional
from packaging import version
if TYPE_CHECKING:
from ... import PreTrainedTokenizer, TensorType
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ..... | 108 |
"""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 transformers.utils i... | 621 | 0 |
'''simple docstring'''
import re
def __magic_name__ ( __UpperCAmelCase ) -> bool:
'''simple docstring'''
__SCREAMING_SNAKE_CASE = re.compile(
R"""^(?:0|94|\+94|0{2}94)""" R"""7(0|1|2|4|5|6|7|8)""" R"""(-| |)""" R"""\d{7}$""" )
return bool(re.search(... | 109 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 621 | 0 |
'''simple docstring'''
import inspect
import warnings
from typing import Any, Dict, Optional, Union
from packaging import version
def _a( *UpperCamelCase__ : Optional[int], UpperCamelCase__ : List[Any] = None, UpperCamelCase__ : List[str]=True, Upper... | 296 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSeque... | 621 | 0 |
'''simple docstring'''
def A_ ( snake_case , snake_case , snake_case ):
def count_of_possible_combinations(snake_case ) -> int:
if target < 0:
return 0
if target == 0:
return 1
return sum(count_of_possible_combinations(target - item ) for item in array ... | 143 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_=None , lowerCAmelCase_=None ) -> int:
_SCREAMING_SNAKE_CASE : Optional[int] = data
_SCREAMING_SNAKE_CASE : Tuple = ... | 621 | 0 |
"""simple docstring"""
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
f... | 139 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import hugg... | 621 | 0 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 155 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ ) -> None:
_SCREAMING_SNAKE_CASE : Dict = size
_SCREAMING_SNAKE_CASE : str = [0] * size
_SCREAMING_SNAKE_CASE : Any = ... | 621 | 0 |
'''simple docstring'''
from math import pi, sqrt, tan
def __snake_case ( _UpperCAmelCase : List[str]):
if side_length < 0:
raise ValueError('''surface_area_cube() only accepts non-negative values''')
return 6 * side_length**2
def __snake_case ( _UpperCAmel... | 212 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'huggingface/time-series-transformer-tourism-monthly': (
'htt... | 621 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase = {
"""configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """BloomOnnxConf... | 525 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input('Enter image url: ').strip()
print(F'Downloading image from {url} ...')
lowerCAmelCase__ = BeautifulSoup(requests.get(url).conten... | 621 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
import random
from typing import Any
class lowercase__ :
'''simple docstring'''
def __init__( self ) -> None:
_UpperCAmelCase = []
_UpperC... | 573 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/... | 621 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''naver-clova-ix/donut-base''': '''https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json''',
# See all Donut models at https://h... | 646 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 621 | 0 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import Bat... | 527 |
"""simple docstring"""
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...t... | 621 | 0 |
import os
import sys
import unittest
_lowerCamelCase : Optional[int] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_mode... | 87 |
"""simple docstring"""
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def lowercase_... | 621 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tensorflow_text_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase: str = {
'configuration_bert': ['BE... | 20 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return abs(lowerCamelCase ) if a == 0 else greatest_common_divisor(b % a, lowerCamelCase )
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
while y: # --> when y=0 ... | 621 | 0 |
'''simple docstring'''
class __SCREAMING_SNAKE_CASE :
def __init__( self : Any , __lowercase : str , __lowercase : Union[str, Any]=None , __lowercase : str=None ) -> int:
SCREAMING_SNAKE_CASE__ : Optional[int] ... | 296 |
"""simple docstring"""
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCAmelCase__ = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for T... | 621 | 0 |
'''simple docstring'''
from ...utils import logging
from ..ta.modeling_tf_ta import TFTaEncoderModel, TFTaForConditionalGeneration, TFTaModel
from .configuration_mta import MTaConfig
A_ = logging.get_logger(__name__)
A_ = "T5Config"
class _snake_case ( _... | 143 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
lowerCAmelCase__ = get_logger(__name__)
lowerCAmelCase__ = r'\n Args:\n input_ids (`jnp.ndarray` of ... | 621 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : Any = logging.get_logger(__name__)
UpperCAmelCase : str = {}
class lowerCamelCase__ ( __UpperCAmelCase ):
"""simple docstring"""
... | 139 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxDPMSolverMultistepScheduler, FlaxStableDiffusionPipeline
from diffusers.utils import is_flax_available, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
fro... | 621 | 0 |
"""simple docstring"""
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
__magic_name__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE_ ( __UpperCAmelCase ):
"""simple docstring"""
... | 155 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Generator
def lowercase__ ( ):
_SCREAMING_SNAKE_CASE : dict[int, int] = {}
_SCREAMING_SNAKE_CASE : List[Any] = 2
while True:
_SCREAMING_SNAKE_CASE : List[Any] ... | 621 | 0 |
'''simple docstring'''
def __snake_case ( _UpperCAmelCase : str, _UpperCAmelCase : Any, _UpperCAmelCase : Optional[int], _UpperCAmelCase : Union[str, Any]):
# Return True if there is node that has not iterated.
UpperCamelCase = [False] * len... | 212 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 621 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase = {
"""configuration_graphormer""": ["""GRAPHORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GraphormerConfig"""],
... | 525 |
"""simple docstring"""
import operator as op
def lowercase__ ( lowerCamelCase ):
_SCREAMING_SNAKE_CASE : int = []
_SCREAMING_SNAKE_CASE : Dict = lambda lowerCamelCase, lowerCamelCase : int(x / y ) # noqa: E731 integer division operation
... | 621 | 0 |
"""simple docstring"""
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowercase__ ... | 573 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 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_torch_ava... | 646 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, PNDMScheduler, StableDiffusionInpaintPipeline, UNetaDConditionModel
from diffusers.util... | 621 | 0 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Any = logging.get_logger(__name__)
# TODO Update this
lowerCAmelCase_ : ... | 527 |
"""simple docstring"""
lowerCAmelCase__ = '\n# Transformers installation\n! pip install transformers datasets\n# To install from source instead of the last release, comment the command above and uncomment the following one.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lower... | 621 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCamelCase : Union[str, Any] = {"""configuration_yolos""": ["""YOLOS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """YolosConfig""", """YolosOnnxConfig"""]}
try:... | 87 |
"""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 transformers.utils i... | 621 | 0 |
import operator as op
def _lowercase( __a : List[Any] ):
a__ =[]
a__ =lambda __a , __a : int(x / y ) # noqa: E731 integer division operation
a__ ={
'^': op.pow,
'*': op.mul,
'/': div,
'+': op.add,
... | 20 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 621 | 0 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
D... | 296 |
"""simple docstring"""
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSeque... | 621 | 0 |
'''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import skle... | 143 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ , lowerCAmelCase_=None , lowerCAmelCase_=None ) -> int:
_SCREAMING_SNAKE_CASE : Optional[int] = data
_SCREAMING_SNAKE_CASE : Tuple = ... | 621 | 0 |
"""simple docstring"""
class lowerCamelCase__ :
"""simple docstring"""
def __init__( self : List[str] ):
'''simple docstring'''
__UpperCAmelCase : Tuple = 0
__UpperCAmelCase : Optional[Any] = 0
__UpperCAme... | 139 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
import hugg... | 621 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import AutoTokenizer, GPTaTokenizer, GPTaTokenizerFast
from transformers.models.gpta.tokenization_gpta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import Tokeniz... | 155 |
"""simple docstring"""
class _lowerCAmelCase :
def __init__( self , lowerCAmelCase_ ) -> None:
_SCREAMING_SNAKE_CASE : Dict = size
_SCREAMING_SNAKE_CASE : str = [0] * size
_SCREAMING_SNAKE_CASE : Any = ... | 621 | 0 |
'''simple docstring'''
import argparse
import json
import os
from collections import OrderedDict
import numpy as np
import tensorflow as tf
import torch
def __snake_case ( _UpperCAmelCase : Tuple):
UpperCamelCase = os.path.join(args.tf_model_dir, '''parameters.json''')
... | 212 |
"""simple docstring"""
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'huggingface/time-series-transformer-tourism-monthly': (
'htt... | 621 | 0 |
'''simple docstring'''
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert import BertTokenizer
lowerCAmelCase = logging.... | 525 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
lowerCAmelCase__ = input('Enter image url: ').strip()
print(F'Downloading image from {url} ...')
lowerCAmelCase__ = BeautifulSoup(requests.get(url).conten... | 621 | 0 |
"""simple docstring"""
class lowercase__ :
'''simple docstring'''
def __init__( self , snake_case ) -> None:
_UpperCAmelCase = size
_UpperCAmelCase = [0] * size
_UpperCAmelCase = [0] * si... | 573 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2sr-classicalsr-x2-64/resolve/... | 621 | 0 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, DDIMScheduler, LMSDiscreteScheduler, PNDMScheduler, UNetaDConditionModel
from diffusers.pipelin... | 646 |
"""simple docstring"""
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed... | 621 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.