code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod() | 363 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, r... | 364 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 0 |
'''simple docstring'''
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, prepa... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=a_ )
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : str ... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 0 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class UpperCamelCase ( pl.LightningModule ):
"""simple docstring"""
de... | 367 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 0 |
'''simple docstring'''
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import Paddi... | 368 | '''simple docstring'''
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ... | 345 | 0 |
'''simple docstring'''
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,
CharacterToken... | 369 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 0 |
'''simple docstring'''
UpperCamelCase : Any = """0.18.2"""
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_dif... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class UpperCamelCase ( unittest.TestCase , a_ ):
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( self : Tuple):
"""simp... | 371 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 0 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def SCREAMING_SNAKE_CASE__ ( ) -> Union[str, Any]:
"""simple docstring"""
a : Union[str, Any] = {
... | 350 | '''simple docstring'''
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn ... | 345 | 0 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeqa... | 351 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : list[int | float] , snake_case : int , snake_case : int ) -> int | float:
"""simple docstring"""
if len(snake_case ) =... | 345 | 0 |
'''simple docstring'''
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class UpperCamelCase ( nn.Module ):
"""simple docstring"""
def __init__( self : List[str] , UpperCAmelCase_ : in... | 352 | '''simple docstring'''
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accel... | 345 | 0 |
import torch
from transformers import PreTrainedModel, XLMRobertaConfig, XLMRobertaModel
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Dict = "M-CLIP"
def __init__( self : Dict , UpperCAmelCase_ : Any=1_0_2_4 , UpperCAmelCase_ ... | 353 | '''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils im... | 345 | 0 |
'''simple docstring'''
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemake... | 354 | '''simple docstring'''
import inspect
import unittest
from transformers import ViTConfig
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, ... | 345 | 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, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...feature_extraction... | 355 | '''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 345 | 0 |
'''simple docstring'''
import math
def SCREAMING_SNAKE_CASE__ ( snake_case : list , snake_case : int ) -> int:
"""simple docstring"""
a : Optional[int] = len(snake_case )
a : Optional[int] = int(math.floor(mat... | 356 | '''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 UpperCamelCase ( a_ , unittest.TestCase ):
"""simple docstring""... | 345 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
UpperCamelCase : Optional[Any] = logging.get_logger(__name__)
UpperCamelCase : int = {
"""shi-la... | 357 | '''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( snake_case : int , snake_case : int ) -> bool:
"""simple docstring"""
return numa ^ numa < 0
if __name__ == "__main__":
import doctest
doctest.testmod()
| 345 | 0 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SwiftFormerConfig,
SwiftFormerForImageClassification,
ViTImageProcessor,
)
from transformers.utils impo... | 358 | '''simple docstring'''
from typing import Dict, Iterable, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 345 | 0 |
'''simple docstring'''
import argparse
import math
import os
from copy import deepcopy
import torch
from audio_diffusion.models import DiffusionAttnUnetaD
from diffusion import sampling
from torch import nn
from diffusers import DanceDiffusionPipeline, IPNDMScheduler, UNetaDModel
UpperCamelCase : Option... | 359 | '''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def SCREAMING_SNAKE_CASE__ ( snake_case : str , snake_case : float | Decimal , snake_case : float = 10**-10 ... | 345 | 0 |
'''simple docstring'''
import numpy as np
from nltk.translate import meteor_score
import datasets
from datasets.config import importlib_metadata, version
UpperCamelCase : Any = version.parse(importlib_metadata.version("""nltk"""))
if NLTK_VERSION >= version.Version("""3.6.4"""):
fr... | 360 | '''simple docstring'''
import unittest
from transformers import XLMConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impo... | 345 | 0 |
'''simple docstring'''
import argparse
import datetime
def SCREAMING_SNAKE_CASE__ ( snake_case : str ) -> str:
"""simple docstring"""
a : Tuple = {
'0': 'Sunday',
'1': 'Monday',
'2': 'Tuesday',
'3': 'Wednesday',
... | 361 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase : List[str] = {"""processing_layout... | 345 | 0 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise O... | 362 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase : Tuple = {
"""configuration_pegasus_x""": ["""PEGASUS_X_PRETRAINED_CONFIG_ARCHIVE_MAP""", """PegasusXConfig"""],
}
try:
if not... | 345 | 0 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class UpperCamelCase ( unittest.TestCase ):
"""simple docstring"""
def SCREAMING_SNAKE_CASE_ ( self : Any):
"""simple docstring"""
... | 363 | '''simple docstring'''
import math
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
"""facebook/data2vec-base-960h""": """https://huggingface.co/facebook/da... | 345 | 0 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase ( nn.Module ):
"""simple docstring"""
A : int
A ... | 364 | '''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
UpperCamelCase : Optional[Any] = logging.getLogger(__name__)
class UpperCamelCase ( a_ ):
"""simple docstring"""
A : Tuple = "masked_bert"
... | 345 | 0 |
'''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 365 | '''simple docstring'''
import copy
import random
from transformers import CLIPTokenizer
class UpperCamelCase ( a_ ):
"""simple docstring"""
def __init__( self : Union[str, Any] , *UpperCAmelCase_ : Dict , **UpperCAmelCase_ : Any):
"""s... | 345 | 0 |
'''simple docstring'''
UpperCamelCase : Optional[int] = [
"""Audio""",
"""Array2D""",
"""Array3D""",
"""Array4D""",
"""Array5D""",
"""ClassLabel""",
"""Features""",
"""Sequence""",
"""Value""",
"""Image""",
"""Translation""",
"""TranslationVariableL... | 366 | '''simple docstring'''
import argparse
import json
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import AutoImageProcessor, SwinConfig, SwinForImageClassification
def SCREAMING_SNAKE_CASE__ ( snake_case : str... | 345 | 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 UpperCamelCase ( a_ , unittest.TestCase ):
... | 367 | '''simple docstring'''
import baseaa
import io
import json
import os
from copy import deepcopy
from ..optimizer import AcceleratedOptimizer
from ..scheduler import AcceleratedScheduler
class UpperCamelCase :
"""simple docstring"""
def __init__( self : List[str] , Uppe... | 345 | 0 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
UpperCamelCase : str = logging.get_logger(__name__)
UpperCamelCase : Dict = {"""vocab_file""": """vocab.json... | 368 | '''simple docstring'''
import os
import time
import warnings
from dataclasses import dataclass, field
from enum import Enum
from typing import List, Optional, Union
import torch
from filelock import FileLock
from torch.utils.data import Dataset
from ...tokenization_utils_base import PreTrainedTokenizerBase
from ... | 345 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTok... | 369 | '''simple docstring'''
from typing import Dict, List, Optional, Tuple, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to... | 345 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : Tuple = logging.get_logger(__name__)
UpperCamelCase : Any = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microso... | 370 | '''simple docstring'''
from __future__ import annotations
def SCREAMING_SNAKE_CASE__ ( snake_case : int | float | str , snake_case : int | float | str ) -> list[str]:
"""simple docstring"""
if nth_term == "":
return [""]
a : ... | 345 | 0 |
'''simple docstring'''
import argparse
import io
import requests
import torch
from omegaconf import OmegaConf
from diffusers import AutoencoderKL
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import (
assign_to_checkpoint,
conv_attn_to_linear,
create_vae_diffusers_config,
renew_v... | 371 | '''simple docstring'''
import torch
def SCREAMING_SNAKE_CASE__ ( ) -> str:
"""simple docstring"""
if torch.cuda.is_available():
a : int = torch.cuda.device_count()
else:
a : Any = 0
print(F"""Successfully ran on {num_gpus}... | 345 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42 # [batch_size x 3]
__a =42 # [batch_size x 3]
__a =42 # [batc... | 346 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def _lowerCamelCase... | 346 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _lowerCamelCase ( lowercase : Tuple , lowercase ... | 346 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE... | 346 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : List[str] = logging.get_logger(__name__)
lowerCAmelCase_ : List[str] = {
'microsoft/wavlm-base': 'https://huggingf... | 346 |
'''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
lowerCAmelCase_ : Dict = lo... | 346 | 1 |
'''simple docstring'''
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokeni... | 346 |
'''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def UpperCamelCase__ ( self : Dict ):
_a = Rectangle(height=0.5 , width=0.5 )
_a = Rectangle(height=0.46 ... | 346 | 1 |
'''simple docstring'''
from collections import defaultdict
from graphs.minimum_spanning_tree_prims import prisms_algorithm as mst
def _lowerCamelCase ( ) -> Union[str, Any]:
_a , _a = 9, 14 # noqa: F841
_a = [
[0, 1, 4],
[0, 7, 8... | 346 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowerCAmelCase_ : Tuple = WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def _l... | 346 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import Counter
from random import random
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : Optional[int] ):
_a = {}
def UpperCamelCase__ (... | 346 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCamelCase ( ) -> str:
_a = HfArgumentParser(lowercase )
_a = parser.parse_args_into_dataclasses()[0]
_a =... | 346 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ )... | 346 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCAmelCase_ : Union[str, Any] = None
try:
import msvcrt
except ImportError:
lowerCAmelCase_ : Tuple = None
try:
import fcntl
e... | 346 | 1 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Im... | 346 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42 # [batch_size x 3]
__a =42 # [batch_size x 3]
__a =42 # [batc... | 346 | 1 |
'''simple docstring'''
import os
import pytest
from transformers.dynamic_module_utils import get_imports
lowerCAmelCase_ : Optional[int] = '\nimport os\n'
lowerCAmelCase_ : Any = '\ndef foo():\n import os\n return False\n'
lowerCAmelCase_ : int = '\n... | 346 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCAmelCase_ : List[str] = TypeVar('T')
lowerCAmelCase_ : Dict = TypeVar('U')
class __SCREAMING_SNAKE_CASE (Generic[T, U] ):
... | 346 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int , lowercase : int ) -> int:
return int(input_a == input_a == 0 )
def _lowerCamelCase ( ) -> None:
print("Truth Table of NOR Gate:" )
print("| Input 1 | ... | 346 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
lowerCAmelCase_ : Optional[int] = True
except (ImportError, ModuleNotFoundError):
lowerCAmelCase_ : Tuple = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
... | 346 | 1 |
'''simple docstring'''
import json
import os
from typing import Optional, Tuple
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase_ : Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {'vocab_file': 'vocab.j... | 346 |
'''simple docstring'''
import requests
lowerCAmelCase_ : List[Any] = 'YOUR API KEY'
def _lowerCamelCase ( lowercase : str , lowercase : str = giphy_api_key ) -> list:
_a = "+".join(query.split() )
_a = ... | 346 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCAmelCase_ : Dict = False
class __SCRE... | 346 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmel... | 346 | 1 |
'''simple docstring'''
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():
... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int , lowercase : list ) -> Union[str, Any]:
_enforce_args(lowercase , lowercase )
if n == 0:
return 0
_a = float("-inf" )
for i in range(1 , ... | 346 | 1 |
'''simple docstring'''
import importlib.util
import os
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import (
is_accelerate_available,
is_flax_available,
is_safetensors_available,
is_tf_available,
is_torch... | 346 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available()... | 346 | 1 |
'''simple docstring'''
import argparse
import os
import re
import packaging.version
lowerCAmelCase_ : Dict = 'examples/'
lowerCAmelCase_ : str = {
'examples': (re.compile(R'^check_min_version\("[^"]+"\)\s*$', re.MULTILINE), 'check_min_version("VERSION")\n'),
'init':... | 346 |
'''simple docstring'''
from random import randint, random
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : int , lowercase : bool = False , lowercase : bool = False , lowercase : int =... | 346 | 1 |
'''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 diffuser... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 10 ) -> str:
if not isinstance(lowercase , lowercase ) or n < 0:
raise ValueError("Invalid input" )
_a = 10**n
_a = 2_8433 * (pow(2 , 783_0457 ... | 346 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Tuple, Union
import numpy as np
import PIL
import torch
from ...models import UNetaDModel
from ...schedulers import RePaintScheduler
from ...utils import PIL_INTERPOLATION, logging, randn_tensor
from ..pipeline_utils import Diffusi... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 6008_5147_5143 ) -> int:
try:
_a = int(lowercase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 346 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForCo... | 346 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForCo... | 346 | 1 |
'''simple docstring'''
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
from transformer... | 346 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 346 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
lowerCAmelCase_ : Tuple = 1.0_5_4_5_7_1_8_1_7e-3_4 # unit of ℏ : J * s
lowerCAmelCase_ : Union[str, Any] ... | 346 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __S... | 346 | 1 |
'''simple docstring'''
from typing import List
from .keymap import KEYMAP, get_character
def _lowerCamelCase ( lowercase : str ) -> List[Any]:
def decorator(lowercase : Union[str, Any] ):
_a = getattr(lowercase , "handle_key... | 346 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerCam... | 346 | 1 |
'''simple docstring'''
import numpy as np
lowerCAmelCase_ : str = [
['a', 'b', 'c', 'd', 'e'],
['f', 'g', 'h', 'i', 'k'],
['l', 'm', 'n', 'o', 'p'],
['q', 'r', 's', 't', 'u'],
['v', 'w', 'x', 'y', 'z'],
]
class __SCREAMING_SNAKE_CASE :
"""simple docstring"... | 346 |
'''simple docstring'''
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
lowerCAmelCase_ : str = {
'linear': PIL.Image.Resampling.BILINEAR,
... | 346 | 1 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...models.auto.modeling_auto import MODEL_FOR_CAUSAL_LM_MAPPING_NAMES
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase_ : Dict = logg... | 346 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def _lowerCamelCase... | 346 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowerCAmelCase_ : Optional[int] = {
'configuration_mega': ['MEGA_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegaConfig', 'MegaOnnxConfig'... | 346 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE... | 346 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCamelCase ( lowercase : list[int] , lowercase : list[int] , lowercase : int ) -> tuple[float, list[float]]:
_a = list(range(len(lowercase ) ) ... | 346 |
'''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
lowerCAmelCase_ : Dict = lo... | 346 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BertForMaskedLM
if __name__ == "__main__":
lowerCAmelCase_ : Optional[int] = argparse.ArgumentParser(
description=(
'Extraction some layers of the full BertForMaskedLM or RObertaForMas... | 346 |
'''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def UpperCamelCase__ ( self : Dict ):
_a = Rectangle(height=0.5 , width=0.5 )
_a = Rectangle(height=0.46 ... | 346 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
fro... | 346 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowerCAmelCase_ : Tuple = WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def _l... | 346 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int ) -> str:
_a = int(lowercase )
if decimal in (0, 1): # Exit cases for the recursion
return str(lowercase )
_a , _a = divmod(lowercase , 2 )
... | 346 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCamelCase ( ) -> str:
_a = HfArgumentParser(lowercase )
_a = parser.parse_args_into_dataclasses()[0]
_a =... | 346 | 1 |
'''simple docstring'''
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if... | 346 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCAmelCase_ : Union[str, Any] = None
try:
import msvcrt
except ImportError:
lowerCAmelCase_ : Tuple = None
try:
import fcntl
e... | 346 | 1 |
'''simple docstring'''
import string
from math import logaa
def _lowerCamelCase ( lowercase : str , lowercase : str ) -> int:
_a = document.translate(
str.maketrans("" , "" , string.punctuation ) ).replace... | 346 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42 # [batch_size x 3]
__a =42 # [batch_size x 3]
__a =42 # [batc... | 346 | 1 |
'''simple docstring'''
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence... | 346 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCAmelCase_ : List[str] = TypeVar('T')
lowerCAmelCase_ : Dict = TypeVar('U')
class __SCREAMING_SNAKE_CASE (Generic[T, U] ):
... | 346 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int ) -> int:
_a = [1]
_a , _a , _a = 0, 0, 0
_a = ugly_nums[ia] * 2
_a = ugly_nums[ia] * 3
_a = ugly_nums[ia] * 5
for _ i... | 346 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
lowerCAmelCase_ : Optional[int] = True
except (ImportError, ModuleNotFoundError):
lowerCAmelCase_ : Tuple = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
... | 346 | 1 |
'''simple docstring'''
import numpy as np
from transformers import BatchFeature
from transformers.testing_utils import require_tf, require_torch
from .test_feature_extraction_common import FeatureExtractionSavingTestMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstr... | 346 |
'''simple docstring'''
import requests
lowerCAmelCase_ : List[Any] = 'YOUR API KEY'
def _lowerCamelCase ( lowercase : str , lowercase : str = giphy_api_key ) -> list:
_a = "+".join(query.split() )
_a = ... | 346 | 1 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
lowerCAmelCase_ : Dict = Path(__file__).resolve().parents[3] / 'src'
sys.path.insert(1, str(git_repo_path))
import d... | 346 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmel... | 346 | 1 |
'''simple docstring'''
import math
import sys
import cva
import numpy as np
def _lowerCamelCase ( lowercase : np.ndarray , lowercase : float ) -> np.ndarray:
# For applying gaussian function for each element in matrix.
_a = math.sqrt(... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int , lowercase : list ) -> Union[str, Any]:
_enforce_args(lowercase , lowercase )
if n == 0:
return 0
_a = float("-inf" )
for i in range(1 , ... | 346 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 6008_5147_5143 ) -> int:
try:
_a = int(lowercase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 346 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available()... | 346 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import datasets
import tensorflow as tf
from transformers import AutoTokenizer
lowerCAmelCase_ : Dict = logging.getLogger(__name__)
def _lowerCamelCase ( ) -> int:
_a = argparse.Argumen... | 346 |
'''simple docstring'''
from random import randint, random
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : int , lowercase : bool = False , lowercase : bool = False , lowercase : int =... | 346 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, BatchEncoding, PreTrainedTokenizer
from ...utils import logging
lowerCAmelCase_ : Optional[Any] = log... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 10 ) -> str:
if not isinstance(lowercase , lowercase ) or n < 0:
raise ValueError("Invalid input" )
_a = 10**n
_a = 2_8433 * (pow(2 , 783_0457 ... | 346 | 1 |
'''simple docstring'''
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
lowerCAmelCase_ : List[Any] = '\\n\n'
lowerCAmelCase_ : Optional[Any] = '\... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 6008_5147_5143 ) -> int:
try:
_a = int(lowercase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 346 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : Optional[Any] , lowercase : List[Any] ) -> str:
_a = ""
for i in table:
res += inp[i - 1]
return res
def _lowerCamelCase ( lowercase : Union[str, Any]... | 346 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForCo... | 346 | 1 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
... | 346 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 346 | 1 |
'''simple docstring'''
import copy
from collections import OrderedDict
from typing import Dict, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase_ : Lis... | 346 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __S... | 346 | 1 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _lowerCamelCase ( ) -> int:
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.pa... | 346 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerCam... | 346 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : list[int] ) -> list[int]:
_a = len(lowercase )
for i in range(lowercase ):
for j in range(i + 1 , lowercase ):
if numbers[j] < numbers[i]:
_a... | 346 |
'''simple docstring'''
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
lowerCAmelCase_ : str = {
'linear': PIL.Image.Resampling.BILINEAR,
... | 346 | 1 |
'''simple docstring'''
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : Any , __a : List[str] , __a : List[Any] ):
_a = name
_a = val
def __str__( self : Optional[Any] ):
re... | 346 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def _lowerCamelCase... | 346 | 1 |
'''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 PoolFormerConfig, PoolFormerForImageClassification, PoolFormerImageProces... | 346 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE... | 346 | 1 |
'''simple docstring'''
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
lowerCAmelCase_ : List[str] = 2_00
# Number of elements selected in every generation of evolution. The selection takes
# place fro... | 346 |
'''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
lowerCAmelCase_ : Dict = lo... | 346 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_t... | 346 |
'''simple docstring'''
from manim import *
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def UpperCamelCase__ ( self : Dict ):
_a = Rectangle(height=0.5 , width=0.5 )
_a = Rectangle(height=0.46 ... | 346 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PI... | 346 |
'''simple docstring'''
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
lowerCAmelCase_ : Tuple = WebClient(token=os.environ['CI_SLACK_BOT_TOKEN'])
def _l... | 346 | 1 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase_ : Dict = logging.get_logger(__name__)
lowerCAmelCase_ : Union[str, Any] = ... | 346 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def _lowerCamelCase ( ) -> str:
_a = HfArgumentParser(lowercase )
_a = parser.parse_args_into_dataclasses()[0]
_a =... | 346 | 1 |
'''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, PreTra... | 346 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
lowerCAmelCase_ : Union[str, Any] = None
try:
import msvcrt
except ImportError:
lowerCAmelCase_ : Tuple = None
try:
import fcntl
e... | 346 | 1 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int ) -> bool:
assert isinstance(lowercase , lowercase ) and (
number >= 0
), "'number' must been an int and positive"
if 1 < number < 4:
# 2 and 3 are primes
... | 346 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42 # [batch_size x 3]
__a =42 # [batch_size x 3]
__a =42 # [batc... | 346 | 1 |
'''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 Optional... | 346 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCAmelCase_ : List[str] = TypeVar('T')
lowerCAmelCase_ : Dict = TypeVar('U')
class __SCREAMING_SNAKE_CASE (Generic[T, U] ):
... | 346 | 1 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def _lowerCamelCase ( lowercase : Callable , lowercase : float , lowercase : float , lowercase : float , lowercase : float ) -> ... | 346 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
lowerCAmelCase_ : Optional[int] = True
except (ImportError, ModuleNotFoundError):
lowerCAmelCase_ : Tuple = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
... | 346 | 1 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int ) -> str:
_a = 0
_a = 0
while num > 0:
_a = num % 8
_a = octal + (remainder * math.floor(math.pow(10 , lowercas... | 346 |
'''simple docstring'''
import requests
lowerCAmelCase_ : List[Any] = 'YOUR API KEY'
def _lowerCamelCase ( lowercase : str , lowercase : str = giphy_api_key ) -> list:
_a = "+".join(query.split() )
_a = ... | 346 | 1 |
'''simple docstring'''
lowerCAmelCase_ : dict[tuple[int, int, int], int] = {}
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : int ) -> int:
# if we are absent twice, or late 3 consecutive days,
... | 346 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
lowerCAmel... | 346 | 1 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def _lowerCamelCase ( lowercase : str , lowercase : str , **lowercase : List[str] ) -> Dict:
_a = AutoConfig.from... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int , lowercase : list ) -> Union[str, Any]:
_enforce_args(lowercase , lowercase )
if n == 0:
return 0
_a = float("-inf" )
for i in range(1 , ... | 346 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
t... | 346 |
'''simple docstring'''
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available()... | 346 | 1 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MaMaaaConfig, MaMaaaForConditionalGeneration
def _lowerCamelCase ( lowercase : int ) -> Any:
_a = [
"encoder.version",
"decoder.version",
... | 346 |
'''simple docstring'''
from random import randint, random
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : int , lowercase : bool = False , lowercase : bool = False , lowercase : int =... | 346 | 1 |
'''simple docstring'''
import argparse
import json
import os
import numpy as np
import PIL
import requests
import tensorflow.keras.applications.efficientnet as efficientnet
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from tensorflow.keras.preprocessing import image
from... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 10 ) -> str:
if not isinstance(lowercase , lowercase ) or n < 0:
raise ValueError("Invalid input" )
_a = 10**n
_a = 2_8433 * (pow(2 , 783_0457 ... | 346 | 1 |
'''simple docstring'''
import math
from typing import Optional
import numpy as np
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : str = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'facebook/encodec_24khz': ... | 346 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 6008_5147_5143 ) -> int:
try:
_a = int(lowercase )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
... | 346 | 1 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
lowerCAmelCase_ : List[str] = '\\n@misc{chen2021evalua... | 346 |
'''simple docstring'''
import argparse
import logging
import os
import sys
import numpy as np
import onnxruntime
import torch
from bart_onnx.generation_onnx import BARTBeamSearchGenerator
from bart_onnx.reduce_onnx_size import remove_dup_initializers
import transformers
from transformers import BartForCo... | 346 | 1 |
'''simple docstring'''
import importlib
import sys
from argparse import REMAINDER, ArgumentParser
from pathlib import Path
import torch_xla.distributed.xla_multiprocessing as xmp
def _lowerCamelCase ( ) -> str:
_a = ArgumentParser(
description=(
"... | 346 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev... | 346 | 1 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational ... | 346 |
'''simple docstring'''
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __S... | 346 | 1 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, loggin... | 346 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerCam... | 346 | 1 |
'''simple docstring'''
import random
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
@staticmethod
def UpperCamelCase__ ( __a : str ):
_a = [ord(__a ) for i in text]
_a = []
_a = []
for i... | 346 |
'''simple docstring'''
import PIL.Image
import PIL.ImageOps
from packaging import version
from PIL import Image
if version.parse(version.parse(PIL.__version__).base_version) >= version.parse('9.1.0'):
lowerCAmelCase_ : str = {
'linear': PIL.Image.Resampling.BILINEAR,
... | 346 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import time
import timeit
import datasets
import numpy as np
import pycuda.autoinit # noqa: F401
import pycuda.driver as cuda
import tensorrt as trt
import torch
from absl import logging as absl_logging
from accelerate import Accelerator
fro... | 346 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def _lowerCamelCase... | 346 | 1 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope="session" )
def _lowerCamelCase... | 346 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SNAKE... | 346 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_... | 346 |
'''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
lowerCAmelCase_ : Dict = lo... | 346 | 1 |
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