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 |
|---|---|---|---|---|
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class lowerCamelCase_ ( unittest.TestCase ):
'''simple docstring'''
def lowerCAmelCase_ ( self : Optional[int] ):
SCREAMING_SNAKE_CASE_ = [
'safety_checker/... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 1 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self : Union[str, Any] ... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
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__ : Dict = 'src/transformers'
lowerCamelCase__ ... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
import baseaa
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> bytes:
return baseaa.aaaencode(string.encode('utf-8' ) )
def UpperCAmelCase_ ( __UpperCAmelCase : bytes ) -> str:
return baseaa.aaadecode(__UpperCAmelCase ).decode('utf-8' )
if __na... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
import evaluate
import numpy as np
import torch
from datasets import load_dataset
from PIL import Image
from torchvision.transforms import (
CenterCrop,
Compose,
Normalize,
RandomHorizontalFlip... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
class lowerCamelCase_ ( _SC... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accel... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 1 |
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
if is_sentencepiec... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
import qiskit
def UpperCAmelCase_ ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> qiskit.result.counts.Counts:
SCREAMING_SNAKE_CASE_ = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
SCREAMING_S... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class lowerCamelCase_ ( nn.Module ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = jnp.floataa
def lowerCAmelCase_ ( self : List[str] ):
SCREAMING_SNAKE_CASE_ ... | 31 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import F... | 31 | 1 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[Any] = {
'configuration_autoformer': [
'AUTOFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP',
'Autof... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
CharacterTokenizer,
JumanppTokeni... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, 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
from... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
import argparse
import glob
import logging
import os
import sys
import time
from collections import defaultdict
from pathlib import Path
from typing import Dict, List, Tuple
import numpy as np
import pytorch_lightning as pl
import torch
from callbacks import SeqaSeqLoggingCallback, get_checkpoint_callback, get_ea... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
lowerCamelCase__ : Dict = version.parse(importlib_metadata.version('nltk'))
if NLTK_VERSION >= version.Version('3.6.4'):
from nltk import word_tokenize
lowe... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
import io
import os
import unicodedata
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ : int = logging.get_logger(__name__)
lowerCamelCase__ : Optional[i... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
from math import isqrt
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 , isqrt(__UpperCAmelCase ) + 1 ) )
def UpperCAmelCase_ ( __UpperCAmelCase : int = 10**6 ) -> int:
SCREAMING... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : int = 2_00 ) -> int:
SCREAMING_SNAKE_CASE_ = [1, 2, 5, 10, 20, 50, 1_00, 2_00]
SCREAMING_SNAKE_CASE_ = [0] * (pence + 1)
SCREAMING_SNAKE_CASE_ = 1 # base case: 1 way to make 0 pence
for coin in ... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
lowerCamelCase__ : str = [
'Audio',
'Array2D',
'Array3D',
'Array4D',
'Array5D',
'ClassLabel',
'Features',
'Sequence',
'Value',
'Image',
'Translation',
'TranslationVariableLanguages',
]
from .audio import Audio
from .features import ArrayaD, Arraya... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
import fire
from utils import calculate_rouge, save_json
def UpperCAmelCase_ ( __UpperCAmelCase : Dict , __UpperCAmelCase : List[Any] , __UpperCAmelCase : Tuple=None , **__UpperCAmelCase : List[str] ) -> Any:
SCREAMING_SNAKE_CASE_ = ... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 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 Pre... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class lowerCamelCase_ ( unittest.TestCase ... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
from collections.abc import Sequence
from queue import Queue
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : List[Any] , _lowerCAmelCase : Dict , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
lowerCamelCase__ : Optional[Any] = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for T... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : str , __UpperCAmelCase : int ) -> list:
SCREAMING_SNAKE_CASE_ = word.split()
def justify(__UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int ) -> str:
... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
from __future__ import annotations
def UpperCAmelCase_ ( __UpperCAmelCase : list[int] ) -> int:
SCREAMING_SNAKE_CASE_ = len(__UpperCAmelCase ) // 2
# choose the middle 3 elements
SCREAMING_SNAKE_CASE_ = lst[m - 1 : m + 2]
# if middle element ... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 1 |
import unittest
import numpy as np
from transformers import AlbertConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax.numpy as jnp
from tra... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
import warnings
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Tuple = logging.get_logger(__name__)
lowerCamelCase__ : int = {
'xlnet-base-cased': 'https://huggingface.co/xlnet-base-cased/resolve/main/config.json',... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class lowerCamelCase_ ( _... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
lowerCamelCase__ : int = logging.get_logger(__name__)
def UpperCAmelCase_ ( __UpperCAmelCase : int=None , __U... | 31 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import F... | 31 | 1 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFMod... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
import string
from math import logaa
def UpperCAmelCase_ ( __UpperCAmelCase : str , __UpperCAmelCase : str ) -> int:
SCREAMING_SNAKE_CASE_ = document.translate(
str.maketrans('' , '' , string.punctuation ) ).replace('\n' , ... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : int = 50 ) -> int:
SCREAMING_SNAKE_CASE_ = [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 + ... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
lowerCamelCase__ : Tuple = {
'Pillow': 'Pillow',
'accelerate': 'accelerate>=0.11.0',
'compel': 'compel==0.1.8',
'black': 'black~=23.1',
'datasets': 'datasets',
'filelock': 'filelock',
'flax': 'flax>=0.4.1',
'hf-doc-builder': 'hf-doc-builder>=0.3.0',
'huggingf... | 31 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 1 |
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCamelCase__ : List[Any] = logging.get_logger(__name__)
lowerCamelCase__ ... | 31 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
lowerCamelCase__ : Optional[int] = {'openai-gpt': 'https://huggingface.co/openai-gpt/resolve/main/config.json'}
class ... | 31 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : list[int] ) -> float:
if not nums: # Makes sure that the list is not empty
raise ValueError('List is empty' )
SCREAMING_SNAKE_CASE_ = sum(__UpperCAmelCase ) / len(__UpperCAmelCase ) # Calculate the average
... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 1 |
from __future__ import annotations
def UpperCAmelCase_ ( __UpperCAmelCase : list[int] , __UpperCAmelCase : int , __UpperCAmelCase : int , __UpperCAmelCase : int ) -> None:
if (direction == 1 and array[indexa] > array[indexa]) or (
dire... | 31 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 1 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def UpperCAmelCase_ ( __UpperCAmelCase : int , __UpperCAmelCase : int ) -> Union[str, Any]:
# ===== initialization =====
SCREA... | 31 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 1 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class lowerCamelCase_ ( _SCREAMING_SNAKE... | 31 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 1 |
from __future__ import annotations
from typing import Any
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : List[str] , _lowerCAmelCase : int = 6 ):
SCREAMING_SNAKE_CASE_ = None
SCREAMING_SNAKE_CASE_ = None... | 31 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 1 |
import sys
from typing import Tuple
import numpy as np
import torch
from PIL import Image
from torch import nn
from transformers.image_utils import PILImageResampling
from utils import img_tensorize
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Dict , ... | 31 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 1 |
import argparse
import os
import re
lowerCamelCase__ : List[Any] = 'src/transformers/models/auto'
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
lowerCamelCase__ : str = re.compile(r'[A-Z... | 31 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 1 |
from scipy.stats import pearsonr
import datasets
lowerCamelCase__ : Any = '\nPearson correlation coefficient and p-value for testing non-correlation.\nThe Pearson correlation coefficient measures the linear relationship between two datasets. The calculation of the p-value relies on the assum... | 31 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 1 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 1 |
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, requir... | 31 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 1 |
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import MaskaFormerConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transfo... | 31 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 1 |
def UpperCAmelCase_ ( __UpperCAmelCase : list[list[int | float]] ) -> int:
SCREAMING_SNAKE_CASE_ = len(__UpperCAmelCase )
SCREAMING_SNAKE_CASE_ = len(matrix[0] )
SCREAMING_SNAKE_CASE_ = min(__UpperCAmelCase , __UpperCAmelCase ... | 31 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 1 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 1 |
from typing import Dict
from transformers import EvalPrediction, HfArgumentParser, TrainingArguments, is_torch_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
get_torch_dist_unique_port,
require_torch_multi_gpu,
require_torch_neuroncore,
)
from transf... | 31 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import F... | 31 | 1 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Tuple , _lowerCAmelCase : Any , _lowerCAmelCase : Union[str, Any] , _lowerCAmelCase : Any ):
SCREAMING_SNAKE_CASE_ = name
SCREAMING_S... | 31 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 1 |
from __future__ import annotations
import math
from collections.abc import Callable
def UpperCAmelCase_ ( __UpperCAmelCase : Callable[[int | float], int | float] , __UpperCAmelCase : int | float , __UpperCAmelCase : int | float , __UpperCAmelCase : int = 1_00... | 31 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 1 |
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, PLBartTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
)
from ...test_tokenization_common i... | 31 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 1 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 1 |
def __lowercase ( snake_case ):
"""simple docstring"""
if num <= 0:
raise ValueError('''Input must be a positive integer''' )
__magic_name__ :List[Any] = [True] * (num + 1)
__magic_name__ :Tuple = 2
while p * p <= num:
if primes[p]:
... | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 0 |
from pathlib import PurePosixPath
from typing import Optional
import fsspec
from fsspec import AbstractFileSystem
from huggingface_hub.hf_api import DatasetInfo
from ..utils.file_utils import get_authentication_headers_for_url
from ..utils.hub import hf_hub_url
class __lowerCamelCase (_a ... | 1 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 0 |
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeat... | 2 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 0 |
'''simple docstring'''
def A_( A : bytes):
return "".join([hex(A)[2:].zfill(2).upper() for byte in list(A)])
def A_( A : str):
# Check data validity, following RFC3548
# https://www.ietf.org/rfc/rfc3548.txt
if (len(A) % 2) != 0:
ra... | 3 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 0 |
"""simple docstring"""
import os
import pytest
from datasets import (
get_dataset_config_info,
get_dataset_config_names,
get_dataset_infos,
get_dataset_split_names,
inspect_dataset,
inspect_metric,
)
__UpperCamelCase : int = pytest.mark.integration
@pytest.mark.p... | 4 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 0 |
'''simple docstring'''
_lowercase = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
_lowercase = [{"""type""": """code""", """content""": INSTALL_CO... | 5 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_url
from PIL import Image
from transformers import DPTConfig, DPTForDepthEstimation, DPTForSemanticSegmentation, DPTImageProcessor
from transformers.utils import logging
loggin... | 6 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 0 |
"""simple docstring"""
class lowercase_ :
'''simple docstring'''
def __init__( self : List[Any] , _UpperCAmelCase : Optional[Any] , _UpperCAmelCase : int , _UpperCAmelCase : int ):
_A = None
_A = None
_A = graph... | 7 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase__ : Union[str, Any] = {
'''configuration_blip_2''': [
'''BLIP_2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 8 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 0 |
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision.transforms.functional i... | 9 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 0 |
import json
import os
from typing import Optional, Tuple
import regex as re
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCAmelCase = logging.get_logger(__name__)
_lowerCAmelCase = {
"vocab_file": "vocab.json",
"merges_file": "merges.txt",
}
_lowerC... | 10 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 0 |
'''simple docstring'''
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTPException
from fas... | 11 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 0 |
def UpperCamelCase ( lowercase_ ) -> List[Any]:
'''simple docstring'''
lowercase__ : Any = len(lowercase_ )
for i in range(length - 1 ):
lowercase__ : List[str] = i
for k in range(i + 1 , lowercase_ ):
if collection[k] < collection[least]:
... | 12 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 0 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixi... | 13 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 0 |
def __UpperCAmelCase ( __a : str ) -> bool:
"""simple docstring"""
_a : Optional[int] = [int(__a ) for i in ip_va_address.split('''.''' ) if i.isdigit()]
return len(__a ) == 4 and all(0 <= int(__a ) <= 254 for octet in octets )... | 14 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 0 |
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel
from ...schedulers import ScoreSdeVeScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class A ( UpperCAmelCase__ ):
'''s... | 15 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 0 |
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __a ( A__ : Tuple ):
for param in module.parameters():
SCREAMING_SNAKE_CASE = False
def __a ( ):
SCREAMING_SNAKE_CASE = "cuda" if torch.cuda.... | 16 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 0 |
import pytest
from datasets import Dataset, DatasetDict, Features, NamedSplit, Value
from datasets.io.text import TextDatasetReader
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases
def __SCREAMING_SNAKE_CASE ( a__ : Optional[int] ,a__ : Any ) ... | 17 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import F... | 31 | 0 |
'''simple docstring'''
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
_SCREAMING_SNAKE_CASE = log... | 18 |
from __future__ import annotations
from collections.abc import Generator
def UpperCAmelCase_ ( ) -> Generator[int, None, None]:
SCREAMING_SNAKE_CASE_ = {}
SCREAMING_SNAKE_CASE_ = 2
while True:
SCREAMING_SNAKE_CASE_ = factor_map.pop(__Uppe... | 31 | 0 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_a = logging.get_l... | 19 |
import numpy as np
import torch
from torch.utils.data import DataLoader
from accelerate.utils.dataclasses import DistributedType
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Any , _lowerCAmelCase : Optional[int]=2 , _lowerCAme... | 31 | 0 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils ... | 20 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
lowerCamelCase__ : Union[str, Any] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( se... | 31 | 0 |
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowerCAmelCase_ ( lowerCamelCase ):
__magic_name__ : ... | 21 |
def UpperCAmelCase_ ( ) -> list[list[int]]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
lowerCamelCase__ : List[Any] = generate_large_matrix()
lowerCamelCase__ : List[Any] = (
[[4, 3, 2, -1], [3,... | 31 | 0 |
'''simple docstring'''
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import Gene... | 22 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 | 0 |
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModule
def ... | 23 |
import unittest
from typing import Tuple
import torch
from diffusers.utils import floats_tensor, randn_tensor, torch_all_close, torch_device
from diffusers.utils.testing_utils import require_torch
@require_torch
class lowerCamelCase_ :
'''simple docstring'''
@property
def lowerCAmelCase_ ... | 31 | 0 |
'''simple docstring'''
UpperCAmelCase_ : Dict = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax... | 24 |
import operator as op
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> Any:
SCREAMING_SNAKE_CASE_ = []
SCREAMING_SNAKE_CASE_ = lambda __UpperCAmelCase , __UpperCAmelCase : int(x / y ) # noqa: E731 integer division operation
SCREAMING_SNA... | 31 | 0 |
from .imports import is_tqdm_available
if is_tqdm_available():
from tqdm.auto import tqdm as _tqdm
from ..state import PartialState
def lowerCamelCase__ ( _a = True , *_a , **_a):
if not is_tqdm_available():
raise ImportError("Accelerate's `tqdm` module requires `tqdm` to be insta... | 25 |
def UpperCAmelCase_ ( __UpperCAmelCase : int ) -> int:
assert isinstance(__UpperCAmelCase , __UpperCAmelCase ), f"The input value of [n={number}] is not an integer"
if number == 1:
return 2
elif number < 1:
SCREAMING_SNAKE_CASE_ = ... | 31 | 0 |
'''simple docstring'''
from __future__ import annotations
def _a ( _lowerCamelCase , _lowerCamelCase = None , _lowerCamelCase = None ) -> None:
"""simple docstring"""
if start is None:
__snake_case : Optional[Any] ... | 26 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
if is_sentencepiece_available():
from ..ta.tokenization_ta import TaT... | 31 | 0 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase( __snake_case ):
'''simple docstring'''
__magic_name__ = 'M-CLIP'
def __init__( self , snake_case_=1024 , snake_case_=768... | 27 |
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
@require_torch
def lowerCAmelCase_ ( self ... | 31 | 0 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoMo... | 28 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = "M-CLIP"
def __init__( self : Tuple , _lowerCAmelCase : List[st... | 31 | 0 |
"""simple docstring"""
import enum
import warnings
from .. import MODEL_FOR_CAUSAL_LM_MAPPING, TF_MODEL_FOR_CAUSAL_LM_MAPPING
from ..utils import add_end_docstrings, is_tf_available
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
class __lowerCamelCase ( en... | 29 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProcessor
from diffusers.pi... | 31 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
# See all MEGATRON_BERT models at https://huggingface.co/models?filter=bert
}
class __a( _a ):
"""simple docstring"""
lowerCAmelC... | 30 |
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, List, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import TensorType, logging
if TYPE_CHECKING:
from ...onnx.config import PatchingSpec
from ...tokenizati... | 31 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"funnel-transformer/small": "https://huggingface.co/funnel-transformer/small/resolve/main/config.json",
"funnel-transformer/small-base"... | 32 |
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( self ... | 31 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
import diffusers
from diffusers import (
AutoencoderKL,
EulerDiscreteScheduler,
StableDiffusionLatentUpscalePipeline,
StableDiffusionPipeline... | 33 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingface.co/microsoft/swinv2... | 31 | 0 |
"""simple docstring"""
from functools import lru_cache
@lru_cache
def __snake_case ( _lowercase ):
"""simple docstring"""
if num < 0:
raise ValueError('''Number should not be negative.''' )
return 1 if num in (0, 1) else num * factorial(num - 1 )
if __na... | 34 |
import itertools
import random
import unittest
import numpy as np
from transformers import BatchFeature, SpeechTaFeatureExtractor
from transformers.testing_utils import require_torch
from transformers.utils.import_utils import is_torch_available
from ...test_sequence_feature_extraction_common import SequenceFea... | 31 | 0 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_camembert impo... | 35 |
from __future__ import annotations
from typing import TypedDict
class lowerCamelCase_ ( _SCREAMING_SNAKE_CASE ):
'''simple docstring'''
lowercase_ = 42
lowercase_ = 42
def UpperCAmelCase_ ( __UpperCAmelCase : str ) -> list[str]:... | 31 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def lowercase ( __A : dict , __A : str , __A : set , __A : set , __A : dict , __A : dict , __A : PriorityQueue , __A : dict , __A : float | int , ) -> float |... | 36 |
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : str ):
SCREAMING_SNAKE_CASE_ = {}
def lowerCAmelCase_ ( self : List[str] ):
print(self.vertex )
for i in self.vertex:
print(_lowerCAmelCase , ... | 31 | 0 |
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 37 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase__ : str = logging.get_logger(__name__)
lowerCamelCase__ : Tuple = {
'funnel-transformer/small': 'https://huggingface.co/funnel-transformer/small/resolve/main/config.json',
... | 31 | 0 |
'''simple docstring'''
def UpperCamelCase__ ( __magic_name__ : str = "The quick brown fox jumps over the lazy dog" , ) -> bool:
'''simple docstring'''
snake_case__ : Tuple = set()
# Replace all the whitespace in our sentence
snake_case__ : List[Any]... | 38 |
from __future__ import annotations
from collections.abc import Iterator
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : Union[str, Any] , _lowerCAmelCase : int ):
SCREAMING_SNAKE_CASE_ = value
SCREAMING_SNAKE_CASE_ ... | 31 | 0 |
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
while a != 0:
snake_case_, snake_case_ = b % a, a
return b
def __SCREAMING_SNAKE_CASE (SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ ):
if gcd(SCREAMING... | 39 |
def UpperCAmelCase_ ( __UpperCAmelCase : list , __UpperCAmelCase : int , __UpperCAmelCase : int = 0 , __UpperCAmelCase : int = 0 ) -> int:
SCREAMING_SNAKE_CASE_ = right or len(__UpperCAmelCase ) - 1
if left > right:
... | 31 | 0 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCamelCase ( snake_case__ : str ) -> None:
UpperCamelCase , UpperCamelCase : Tuple = analyze_text(snake_case__ )
UpperCamelCas... | 40 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_fnet import F... | 31 | 0 |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.