code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import 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 BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from trans... | 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 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 : Dict = get_logger(__name__)
_lowerCamelCase : Dict = r"""\n Args:\n input_ids (`jnp.ndarray` of... | 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 |
import functools
from typing import Any
def _lowercase( __a : str , __a : List[Any] ):
# Validation
if not isinstance(__a , __a ) or len(__a ) == 0:
raise ValueError('the string should be not empty string' )
if not isinsta... | 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'''
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers ... | 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'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_multi_gpu
from accelerate.utils import patch_environment
class _snake_case ( unit... | 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"""
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.ut... | 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"""
from random import randint
from tempfile import TemporaryFile
import numpy as np
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ , UpperCamelCase_ ):
__SCREAMING_SNAKE_CASE = 0
if start < end:
__SCREAMING_SNAKE_CASE = r... | 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'''
snake_case_ : Optional[int] = '\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\... | 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 collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, PreTrai... | 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"""
def UpperCAmelCase ( A : Any , A : Union[str, Any] ):
'''simple docstring'''
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 573 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__A = logging.get_logger(__name__)
__A = {
'''facebook/vit-mae-base''': '''https://huggingface.co/facebook/vit-mae-base/resolve/main/config.json''',
# See all ViT MAE models at https://hugging... | 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 __future__ import annotations
import requests
lowerCAmelCase_ : List[str] = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium c... | 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 |
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_ ) -> Optional[Any]:
"""simple docstring"""
ret... | 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 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def _lowercase( ):
a__ ={
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
'path': ['test_1.py', 'test_2.py', 'unit_test.py'... | 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'''
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
a_ = importlib.util.find_spec('s3fs') is not None
if _has_safs:
... | 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 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, DDIMScheduler, DDPMScheduler, StableDiffusionUpscalePipeline, UNetaDConditionM... | 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"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase : List[Any] = logging.get_logger(__name__)
UpperCAmelCase : List[Any] = {
'caidas/swin2sr-classicalsr-x2-64': (
'https://huggingface.co/caidas/swin2s... | 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 functools import lru_cache
def _lowerCAmelCase ( UpperCamelCase_ ):
__SCREAMING_SNAKE_CASE = 2
__SCREAMING_SNAKE_CASE = set()
while i * i <= n:
if n % i:
i += 1
else:
n //= i
factors.add(UpperCamelCase_ )
if n... | 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 gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
... | 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 unittest
from transformers import is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
if is_torch_available():
import torch
from transformers import XLMRobertaModel
@require_sentencepiece
@requir... | 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 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
f... | 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 random
def lowercase_ ( _lowerCamelCase: Any , _lowerCamelCase: List[Any] , _lowerCamelCase: Optional[int] ) -> Union[str, Any]:
'''simple docstring'''
__lowerCamelCase : str = a[left_index]
__lowerCamelCase : Lis... | 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'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ : Optional[int] = {
'configuration_trajectory_transformer': [
'TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG... | 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 random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 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 |
def _lowercase( __a : Optional[int] , __a : Tuple ):
while a != 0:
a__ =b % a, a
return b
def _lowercase( __a : Tuple , __a : Union[str, Any] ):
if gcd(__a , __a ) != 1:
a__ ... | 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'''
def _a( UpperCamelCase__ : Any, UpperCamelCase__ : List[str] ):
'''simple docstring'''
if discount_rate < 0:
raise ValueError('''Discount rate cannot be negative''' )
if not cash_flows:
r... | 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'''
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 ... | 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"""
UpperCAmelCase : Optional[Any] = '0.21.0'
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from... | 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 json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processors imp... | 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'''
import json
import os
from functools import lru_cache
from typing import List, Optional, Tuple
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case_ : str = logging.get_logger(__name__)
sna... | 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'''
def __A ( a_ : Any ,a_ : str ):
return abs(a_ ) if a == 0 else greatest_common_divisor(b % a ,a_ )
def __A ( a_ : Any ,a_ : Optional[Any] ):
while y: # --> when y=0 then loop will terminate and return x as final GCD.
... | 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 TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
lowercase = {'''configuration_fnet''': ['''FNET_PRETRAINED... | 573 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
__A = logging.get_logger(__name__)
class _snake_case ( __UpperCAmelCase ):
def __init__( self : List[Any] , *UpperCAmelCase : List[str... | 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'''
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class lowerCamelCase_ ( __UpperCAmelCase , unittest.TestCase ... | 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 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class UpperCamelCase_ ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 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 |
def _lowercase( __a : Optional[Any] ):
return 10 - x * x
def _lowercase( __a : str , __a : Any ):
# Bolzano theory in order to find if there is a root between a and b
if equation(__a ) * equation(__a ) >= 0:
raise Val... | 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'''
import math
def _a( UpperCamelCase__ : Tuple ):
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
... | 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'''
class _snake_case :
def __init__( self : Any ,SCREAMING_SNAKE_CASE__ : Any ,SCREAMING_SNAKE_CASE__ : Any ):
SCREAMING_SNAKE_CASE:List[Any] = name
SCREAMING_SNAKE_CASE:Tuple = val
def __str__( self : Unio... | 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 argparse
import os
import shutil
from pathlib import Path
import onnx
import torch
from packaging import version
from torch.onnx import export
from diffusers import OnnxRuntimeModel, OnnxStableDiffusionPipeline, StableDiffusionPipeline
UpperCAmelCase : Tuple = ve... | 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 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 ...te... | 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 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 lower... | 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 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 Syst... | 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
def UpperCAmelCase ( A : List[str] , A : Dict ):
'''simple docstring'''
if len(A ) == 0:
return False
_UpperCAmelCase = len(A ) // 2
if a_list[midpoint] == i... | 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 typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_speech_available, is_torch_available
__A = {
'''configuration_audio_spectrogram_transformer''': [
'''AUDIO_SPECTROGRAM_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 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'''
class lowerCamelCase_ :
def __init__( self : Dict , lowerCAmelCase__ : Optional[int] , lowerCAmelCase__ : Tuple , lowerCAmelCase__ : List[str] ):
"""simple docstring"""
SCREAMING_SNAKE_C... | 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 unittest
from transformers import JukeboxTokenizer
from transformers.testing_utils import require_torch
class UpperCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
UpperCAmelCase__ = JukeboxTokenizer
UpperCAmelCase__ = {
'artist': 'Zac Bro... | 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 __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
_lowerCAmelCase: Dict = TypeVar('T')
class lowercase_ (Generic[T] ):
def __init__( self , lowercase_ = True) -> None:
a__ ={} # dictionary of lists... | 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'''
def _a( UpperCamelCase__ : Any, UpperCamelCase__ : Optional[Any], UpperCamelCase__ : Tuple, UpperCamelCase__ : str, UpperCamelCase__ : List[Any], UpperCamelCase__ : Optional[int] ):
'''simple do... | 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 ...processing_utils import ProcessorMixin
class _snake_case ( __UpperCAmelCase ):
_A : Optional[int] = 'WhisperFeatureExtractor'
_A : Optional[Any] = 'WhisperTokenizer'
def __init__( self : str ,SCREAM... | 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"""
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils im... | 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 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 ... | 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'''
import numpy as np
import datasets
snake_case_ : Any = '\nCompute the Mahalanobis Distance\n\nMahalonobis distance is the distance between a point and a distribution.\nAnd not between two distinct points. It is effectively a multivariate equivalent of the Euclidean distanc... | 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 ...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 OptionalD... | 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"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoen... | 573 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
"""simple docstring"""
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
__A = input('''Enter image url: ''').strip()
print(F"""Downloading image from {url} ...""")
__A = BeautifulSoup(requests.get(url).content, '''html.parser''')
# The... | 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'''
def UpperCAmelCase ( A : Union[str, Any] , A : int ):
SCREAMING_SNAKE_CASE : Optional[Any] = word.split()
def justify(A : Any , A : List[str] , A : List[Any] ) -> str:
S... | 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 |
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def SCREAMING_SNAKE_CASE ( lowercase_ ) -> Any:
"""simple docstring"""
def wrapper(*lowercase_ , **lowercase_ ):
... | 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 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCAmelCase: Optional[int] = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Con... | 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'''
def _a( UpperCamelCase__ : Optional[int], UpperCamelCase__ : Union[str, Any] ):
'''simple docstring'''
if len(UpperCamelCase__ ) != len(UpperCamelCase__ ):
raise ValueError('''String lengths must match!''... | 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 gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from di... | 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"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
UpperCAmelCase : Optional[int] = {
'configuration_roberta':... | 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 math
def _lowerCAmelCase ( UpperCamelCase_ , UpperCamelCase_ ):
if initial_intensity < 0:
raise ValueError("""The value of intensity cannot be negative""" )
# handling of negative values of initial intensity
if angle < 0 or angle > 3... | 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'''
def __snake_case ( _UpperCAmelCase : Dict):
if any(not isinstance(_UpperCAmelCase, _UpperCAmelCase) or x < 0 for x in sequence):
raise TypeError('''Sequence must be list of non-negative integers''')
for _ in range(len(_UpperCAmelCase)):
for i, (r... | 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'''
def __A ( a_ : Optional[Any] ):
for i in range(0 ,a_ ):
for _ in range(0 ,n - i - 1 ): # printing spaces
print(" " ,end="" )
for _ in range(0 ,i + 1 ): # printing stars
print("* " ,end="" )
print()
de... | 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"""
def UpperCAmelCase ( A : List[Any] = 1000 ):
'''simple docstring'''
return sum(e for e in range(3 , A ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(F'''{solution() = }''')
| 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 = {
'''microsoft/cvt-13''': '''https://huggingface.co/microsoft/cvt-13/resolve/main/config.json''',
# See all Cvt models at https://huggingface.co/models... | 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'''
from __future__ import annotations
def UpperCAmelCase ( A : List[str] ):
SCREAMING_SNAKE_CASE : List[str] = 2
SCREAMING_SNAKE_CASE : int = []
while i * i <= n:
if n % i:
... | 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 |
_lowerCamelCase : Tuple = [
999,
800,
799,
600,
599,
500,
400,
399,
377,
355,
333,
311,
288,
266,
244,
222,
200,
199,
177,
155,
133,
111,
88,
66,
44,
22,
0,
]
_lowerCamelCase : Un... | 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 |
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 ..uti... | 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'''
import copy
import re
class __SCREAMING_SNAKE_CASE :
snake_case_ = 'hp'
snake_case_ = {}
snake_case_ = None
@classmethod
def __magic_name__ ( cls : Tuple , __lowercase : List[Any] , __... | 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 __future__ import annotations
from bisect import bisect_left
from functools import total_ordering
from heapq import merge
@total_ordering
class _snake_case ( __UpperCAmelCase ):
def __lt__( self : List[str] ,SCREAMING_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"""
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
UpperCAmelCase : Tuple = None
try:
import msvcrt
except ImportError:
UpperCAmelCase : Any = None
try:
import fcntl
except Impo... | 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 os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
__magic_name__ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE_ :
"""simple d... | 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'''
import json
from typing import List, Optional, Tuple
from tokenizers import pre_tokenizers, processors
from ...tokenization_utils_base import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_m... | 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'''
def __A ( a_ : Dict = 1_0_0 ):
lowerCAmelCase : Any = (n * (n + 1) // 2) ** 2
lowerCAmelCase : List[Any] = n * (n + 1) * (2 * n + 1) // 6
return sum_cubes - sum_squares
if __name__ == "__main__":
print(F'''{solution() = }'... | 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"""
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
ConditionalDetrConfig,
ConditionalDetrForObje... | 573 |
"""simple docstring"""
def lowercase__ ( lowerCamelCase, lowerCamelCase ):
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 621 | 0 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class _snake_case ( unittest.TestCase , __UpperCAmelCase ):
def lowerCamelCase__ ( self : Tuple ):
__lowerCamelCase : List... | 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 typing import Optional
from .. import Features, NamedSplit
from ..packaged_modules.text.text import Text
from ..utils.typing import NestedDataStructureLike, PathLike
from .abc import AbstractDatasetReader
class lowerCamelCase_ ( __UpperCAmelCase ):
... | 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 |
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_lowerCamelCase : Any = """src/transformers"""
_lowerCamelCase :... | 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 warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'The `image_to_image.py` script is outdated. Please use directly `from diffusers import'
' StableDiffusionImg2ImgPipeline` instead.'
)
| 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 |
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils import (
ChannelDimension,
ImageInput,... | 622 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 | 1 |
import os
import pytest
from attr import dataclass
a__ : Optional[int] = "us-east-1" # defaults region
@dataclass
class UpperCAmelCase__:
'''simple docstring'''
A : str
A : Optional[Any] = "arn:aws:iam::558105141721:role/sagemaker_execution_role"
A ... | 622 |
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/facebook/musicgen-small/resolve/main/compression_... | 622 | 1 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : str = logging.get_logger(__name__)
a__ : List[str] = {
"huggingface/informer-tourism-monthly": (
"https://huggingface.co/huggingface/infor... | 622 |
# 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
#
# Unless required by appli... | 622 | 1 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
A : int ... | 622 |
def _lowerCAmelCase ( A__ = 50_000_000 ):
lowercase__ = set()
lowercase__ = int((limit - 24) ** (1 / 2) )
lowercase__ = set(range(3 , prime_square_limit + 1 , 2 ) )
primes.add(2 )
for p in range(3 , prime_square_limit + 1 , 2 ):
... | 622 | 1 |
import sys
from collections import defaultdict
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : List[Any]) -> Optional[int]:
"""simple docstring"""
lowercase__ = []
def UpperCAmelCase ( self : Optional[Any] , l... | 622 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onnx.utils import compute_effective_axis_dimension
from ...util... | 622 | 1 |
def _lowerCAmelCase ( A__ , A__ = " " ):
lowercase__ = []
lowercase__ = 0
for index, char in enumerate(A__ ):
if char == separator:
split_words.append(string[last_index:index] )
lowercase__ = index + 1
elif index... | 622 |
from sklearn.metrics import matthews_corrcoef
import datasets
a__ : Any = "\nCompute the Matthews correlation coefficient (MCC)\n\nThe Matthews correlation coefficient is used in machine learning as a\nmeasure of the quality of binary and multiclass classifications. It takes\ninto account true a... | 622 | 1 |
from pathlib import Path
import fire
def _lowerCAmelCase ( A__ , A__ , A__ ):
lowercase__ = Path(A__ )
lowercase__ = Path(A__ )
dest_dir.mkdir(exist_ok=A__ )
for path in src_dir.iterdir():
lowercase__ = [x.rstrip() for x in list(path.open().read... | 622 |
import inspect
import unittest
from transformers import ViTHybridConfig
from transformers.testing_utils import require_accelerate, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Conf... | 622 | 1 |
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
from ...modeling_utils import PreT... | 622 |
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCAmelCase ( ):
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path import dirname as original_dirname
from... | 622 | 1 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.ba... | 622 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class UpperCAmelCase__( lowerCamelCase , un... | 622 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a__ : Optional[Any] = logging.get_logger(__name__)
a__ : Optional[Any] = {
"facebook/timesformer": "https://huggingface.co/facebook/timesformer/resolve/main/config.json",
}
class UpperCAme... | 622 |
import argparse
import requests
import torch
from PIL import Image
from transformers import SwinConfig, SwinForMaskedImageModeling, ViTImageProcessor
def _lowerCAmelCase ( A__ ):
lowercase__ = SwinConfig(image_size=192 )
if "base" in model_name:
lowercase__ = 6
... | 622 | 1 |
import math
def _lowerCAmelCase ( A__ , A__ ):
if 0 not in (x, y):
# We use the relation x^y = y*log10(x), where 10 is the base.
return y * math.logaa(A__ )
else:
if x == 0: # 0 raised to any number is 0
return 0
elif y... | 622 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : ... | 622 | 1 |
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_available():
import ... | 622 |
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
from transformers.utils import cached_property
fr... | 622 | 1 |
from math import sqrt
def _lowerCAmelCase ( A__ ):
assert isinstance(A__ , A__ ) and (
number >= 0
), "'number' must been an int and positive"
lowercase__ = True
# 0 and 1 are none primes.
if number <= 1:
lowercase__ = False
for diviso... | 622 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
a__ : Optional[Any] = logging.getLogger()
def _lowe... | 622 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModel,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import AutoencoderKL, DDIMScheduler, DDPMScheduler, StableU... | 622 |
import json
import os
import unittest
from transformers.models.ctrl.tokenization_ctrl import VOCAB_FILES_NAMES, CTRLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCAmelCase__( lowerCamelCase , unittest.TestCase ):
'''simple docstring'''
A : int ... | 622 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
a__ : Union[str, Any] = {"configuration_vit": ["VIT_PRETRAINED_CONFIG_ARCHIVE_MAP", "ViTConf... | 622 |
from argparse import ArgumentParser
from .add_new_model import AddNewModelCommand
from .add_new_model_like import AddNewModelLikeCommand
from .convert import ConvertCommand
from .download import DownloadCommand
from .env import EnvironmentCommand
from .lfs import LfsCommands
from .pt_to_tf import PTtoTFCommand
fro... | 622 | 1 |
import argparse
import os
import re
import packaging.version
a__ : List[str] = "examples/"
a__ : Any = {
"examples": (re.compile(R"^check_min_version\(\"[^\"]+\"\)\s*$", re.MULTILINE), "check_min_version(\"VERSION\")\n"),
"init": (re.compile(R"^__version__\s+=\s+\"([^\"]... | 622 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _lowerCAmelCase ( ):
with offline(OfflineSimulationMode.CONNECTION_TIMES_OUT ):
with pytest.ra... | 622 | 1 |
def _lowerCAmelCase ( A__ ):
if not grid or not grid[0]:
raise TypeError('The grid does not contain the appropriate information' )
for cell_n in range(1 , len(grid[0] ) ):
grid[0][cell_n] += grid[0][cell_n - 1]
lowercase__ = grid[0]
for ... | 622 |
def _lowerCAmelCase ( A__ = 600_851_475_143 ):
try:
lowercase__ = int(A__ )
except (TypeError, ValueError):
raise TypeError('Parameter n must be int or castable to int.' )
if n <= 0:
raise ValueError('Parameter n must be greater than or equa... | 622 | 1 |
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 UpperCAmelCase__( unittest.TestCase ):
'''simple docstring'''
def UpperCAmelCase ( self : ... | 622 |
from __future__ import annotations
def _lowerCAmelCase ( A__ , A__ = None ):
lowercase__ = word_bank or []
# create a table
lowercase__ = len(A__ ) + 1
lowercase__ = []
for _ in range(A__ ):
table.append([] )
# seed value
lowercas... | 622 | 1 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Tra... | 622 |
a__ : Tuple = "Tobias Carryer"
from time import time
class UpperCAmelCase__:
'''simple docstring'''
def __init__( self : str , lowerCAmelCase : List[str] , lowerCAmelCase : Any , lowerCAmelCase : str , lowerCAmelCase : ... | 622 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a__ : Optional[int] = logging.get_logger(__name__)
a__ : ... | 622 |
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
a__ : Optional[Any] = logging.get_logger(__name__)
class UpperCAmelCase__( lowerCamelCase ):
'''simple docstring'''
def __init__( self : Optional[Any] , *l... | 622 | 1 |
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