code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import unittest
from transformers import 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 import ModelTesterMixin,... | 296 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE_ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
... | 296 | 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 UpperCamelCase__ ( ... | 296 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase__ ( unittest.TestC... | 296 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""mi... | 296 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Un... | 296 | 1 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transforme... | 296 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE_ = logging.getLogger(__name__)
@dataclass
class UpperCamelCase__ ( lowerCAmel... | 296 | 1 |
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_uti... | 296 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 296 | 1 |
from collections import defaultdict
from math import gcd
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_50_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = defaultdict(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = 2
while 2 * euc... | 296 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10 ) -> str:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("""Invalid input""" )
SCREAMING_SNAKE_CASE = 10**n
SCREAMING_SNAK... | 296 | 1 |
import tempfile
import unittest
import numpy as np
import transformers
from transformers import GPTaTokenizer, GPTJConfig, is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax, tooslow
from ...generation.test_flax_utils import FlaxGener... | 296 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFI... | 296 | 1 |
import json
import re
from typing import TYPE_CHECKING, List, Optional, Tuple, Union
import numpy as np
from ...utils import is_tf_available, is_torch_available, logging
if TYPE_CHECKING:
if is_torch_available():
import torch
if is_tf_available():
import ... | 296 |
from pathlib import Path
import fire
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = Path(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
from argparse import ArgumentParser
from ..pipelines import Pipeline, PipelineDataFormat, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__) # pylint: disable=invalid-name
def... | 296 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert impor... | 296 | 1 |
import absl # noqa: F401 # Here to have a nice missing dependency error message early on
import nltk # 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 six # noqa: F401 # Here to... | 296 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/git-base""": """https://huggingface.co/mi... | 296 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""andr... | 296 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.im... | 296 | 1 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless r... | 296 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProc... | 296 | 1 |
from __future__ import annotations
from math import gcd
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 2 , _SCREAMING_SNAKE_CASE = 1 , _SCREAMING_SNAKE_CASE = 3 , ) -> int | None:
'''simple docstring'''
if num < 2:
... | 296 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ ... | 296 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_falcon""": ["""FALCON_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FalconConfig"""],
}
try:
if n... | 296 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_ = logging.get_logg... | 296 | 1 |
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 296 |
from collections import defaultdict
from math import gcd
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_50_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = defaultdict(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = 2
while 2 * euc... | 296 | 1 |
import argparse
import math
import traceback
import dateutil.parser as date_parser
import requests
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> Tuple:
'''simple docstring'''
SCREAMING_SNAKE_CASE = {}
SCREAMING_SNAKE_CASE = job["""started_at... | 296 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __lowercase ( ) -> Dict:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_... | 296 | 1 |
import operator as op
SCREAMING_SNAKE_CASE_ = """scaler.pt"""
SCREAMING_SNAKE_CASE_ = """pytorch_model"""
SCREAMING_SNAKE_CASE_ = """random_states"""
SCREAMING_SNAKE_CASE_ = """optimizer"""
SCREAMING_SNAKE_CASE_ = """scheduler"""... | 296 |
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 __lowercase ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any... | 296 | 1 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from... | 296 |
import os
from distutils.util import strtobool
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Tuple:
'''simple docstring'''
for e in env_keys:
SCREAMING_SNAKE_CASE = int(os.environ.get(_SCREAMING_SNAKE_CASE , -1 ) )... | 296 | 1 |
import math
SCREAMING_SNAKE_CASE_ = 1_0
SCREAMING_SNAKE_CASE_ = 7
SCREAMING_SNAKE_CASE_ = BALLS_PER_COLOUR * NUM_COLOURS
def __lowercase ( _SCREAMING_SNAKE_CASE = 20 ) -> str:
'''simple docstring'''
SCREAMING_SNAKE_CASE ... | 296 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
def __lowercase ( _SCREAMING_SNAKE_CASE=None , ... | 296 | 1 |
import warnings
from ...utils import logging
from .image_processing_layoutlmva import LayoutLMvaImageProcessor
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( se... | 296 |
import math
import unittest
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
assert isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
if 1... | 296 | 1 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase__ ( lowerCAmelCase_ , ... | 296 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
from argparse import ArgumentParser
from datasets.commands.convert import ConvertCommand
from datasets.commands.dummy_data import DummyDataCommand
from datasets.commands.env import EnvironmentCommand
from datasets.commands.run_beam import RunBeamCommand
from datasets.commands.test import TestCommand
... | 296 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""snap-research/efficientformer-l1-300""": (
"""https://huggingface.c... | 296 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""EleutherAI/gpt-neox-20b""": """https://huggingface.co/EleutherAI/gpt-neox-20b/resolve/main/config.json"... | 296 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE_ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
... | 296 | 1 |
import warnings
from ..trainer import Trainer
from ..utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : str ,lowerCamelCase... | 296 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase__ ( unittest.TestC... | 296 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_00_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = limit + 1
SCREAMING_SNAKE_CASE = [0] * limit
for first_term in range(1 , _SCREAMING_SNAKE_CASE ):
for n in range(_SCREAMI... | 296 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Un... | 296 | 1 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ ... | 296 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE_ = logging.getLogger(__name__)
@dataclass
class UpperCamelCase__ ( lowerCAmel... | 296 | 1 |
SCREAMING_SNAKE_CASE_ = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
SCREAMING_SNAK... | 296 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 296 | 1 |
import os
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> Any:
'''simple docstring'''
SCREAMING_SNAKE_CASE = len(grid[0] )
SCREAMING_SNAKE_CASE = len(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 0... | 296 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10 ) -> str:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("""Invalid input""" )
SCREAMING_SNAKE_CASE = 10**n
SCREAMING_SNAK... | 296 | 1 |
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils import depr... | 296 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFI... | 296 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmbedding, Timesteps
from .mod... | 296 |
from pathlib import Path
import fire
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = Path(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
import os
SCREAMING_SNAKE_CASE_ = {"""I""": 1, """V""": 5, """X""": 1_0, """L""": 5_0, """C""": 1_0_0, """D""": 5_0_0, """M""": 1_0_0_0}
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = 0
... | 296 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert impor... | 296 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_resnet""": ["""RESNET_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 296 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/git-base""": """https://huggingface.co/mi... | 296 | 1 |
from math import ceil, sqrt
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_00_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = 0
for outer_width in range(3 , (limit // 4) + 2 ):
if outer_width**2 > limit:
... | 296 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.im... | 296 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFI... | 296 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProc... | 296 | 1 |
def __lowercase ( ) -> str:
'''simple docstring'''
for n in range(1 , 1_00_00_00 ):
yield n * (n + 1) // 2
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> Any:
'''simple docstring'''
SCREAMING_SNAKE_CASE = 1
... | 296 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ ... | 296 | 1 |
import argparse
from transformers import TaConfig, TaForConditionalGeneration, load_tf_weights_in_ta
from transformers.utils import logging
logging.set_verbosity_info()
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str... | 296 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_ = logging.get_logg... | 296 | 1 |
def __lowercase ( ) -> int:
'''simple docstring'''
return [
a * b * (10_00 - a - b)
for a in range(1 , 9_99 )
for b in range(_SCREAMING_SNAKE_CASE , 9_99 )
if (a * a + b * b == (10_00 - a - b) ** 2)
][0]
if _... | 296 |
from collections import defaultdict
from math import gcd
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_50_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = defaultdict(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = 2
while 2 * euc... | 296 | 1 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from t... | 296 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __lowercase ( ) -> Dict:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_... | 296 | 1 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
SCREAMING_SNAKE_CASE_ = loggi... | 296 |
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 __lowercase ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any... | 296 | 1 |
from __future__ import annotations
import inspect
import unittest
from math import floor
import numpy as np
from transformers import CvtConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_avail... | 296 |
import os
from distutils.util import strtobool
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Tuple:
'''simple docstring'''
for e in env_keys:
SCREAMING_SNAKE_CASE = int(os.environ.get(_SCREAMING_SNAKE_CASE , -1 ) )... | 296 | 1 |
import json
import os
import shutil
import tempfile
import unittest
from transformers import BatchEncoding, CanineTokenizer
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.tokenization_utils import AddedToken
from transformers.utils import cached_property... | 296 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
def __lowercase ( _SCREAMING_SNAKE_CASE=None , ... | 296 | 1 |
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_available
f... | 296 |
import math
import unittest
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
assert isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
if 1... | 296 | 1 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""snap-research/efficientformer-l1-300""": (
"""https://huggingface.c... | 296 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_com... | 296 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""snap-research/efficientformer-l1-300""": (
"""https://huggingface.c... | 296 | 1 |
import copy
from typing import TYPE_CHECKING, Any, Mapping, Optional, OrderedDict
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto.configuration_auto import AutoConfig
if TYPE_CHECKING:
... | 296 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE_ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
... | 296 | 1 |
from PIL import Image
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Image:
'''simple docstring'''
def brightness(_SCREAMING_SNAKE_CASE ) -> float:
return 1_28 + level + (c - 1_28)
if not -255.0 <= level <= 255.0:
... | 296 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase__ ( unittest.TestC... | 296 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10**12 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = 1
SCREAMING_SNAKE_CASE = 0
SCREAMING_SNAKE_CASE = 1
SCREAMING_SNAKE_CASE = 1
while numerator <= 2 * min_total - 1... | 296 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Un... | 296 | 1 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE_ = logging.getLogger(__name__)
@dataclass
class UpperCamelCase__ ( lowerCAmel... | 296 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE_ = logging.getLogger(__name__)
@dataclass
class UpperCamelCase__ ( lowerCAmel... | 296 | 1 |
from collections.abc import Callable
class UpperCamelCase__ :
'''simple docstring'''
def __init__( self : List[str] ,lowerCamelCase__ : Callable | None = None ) -> None:
'''simple docstring'''
SCREAMING_SNAKE_... | 296 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 296 | 1 |
import math
from collections.abc import Callable
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> float:
'''simple docstring'''
SCREAMING_SNAKE_CASE = xa
SCREAMING_SNAKE_CASE = xa
while ... | 296 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10 ) -> str:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("""Invalid input""" )
SCREAMING_SNAKE_CASE = 10**n
SCREAMING_SNAK... | 296 | 1 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE_ = TypeVar("""T""")
class UpperCamelCase__ ( Generic[T] )... | 296 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFI... | 296 | 1 |
from math import factorial, radians
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE = 18 , _SCREAMING_SNAKE_CASE = 10 ) -> float:
'''simple docstring'''
SCREAMING_SNAKE_CASE = angle_in_degrees - ((angle_in_degrees // 360.0) * 360.0)
... | 296 |
from pathlib import Path
import fire
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = Path(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from transf... | 296 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert impor... | 296 | 1 |
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
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)... | 296 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/git-base""": """https://huggingface.co/mi... | 296 | 1 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
S... | 296 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.im... | 296 | 1 |
import cva
import numpy as np
class UpperCamelCase__ :
'''simple docstring'''
def __init__( self : List[str] ,lowerCamelCase__ : float ,lowerCamelCase__ : int ) -> List[Any]:
'''simple docstring'''
... | 296 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProc... | 296 | 1 |
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 __lowercase ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any... | 296 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ ... | 296 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/conf... | 296 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_ = logging.get_logg... | 296 | 1 |
import unittest
import numpy as np
from diffusers import LMSDiscreteScheduler, OnnxStableDiffusionInpaintPipeline
from diffusers.utils.testing_utils import (
is_onnx_available,
load_image,
nightly,
require_onnxruntime,
require_torch_gpu,
)
from ..test_pipelines_onnx_commo... | 296 |
from collections import defaultdict
from math import gcd
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_50_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = defaultdict(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = 2
while 2 * euc... | 296 | 1 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE_ = TypeVar("""KEY""")
SCREAMING_SNAKE_CASE_ = TypeVar("""VAL""")
@dataclass(frozen=lowerCAmelCase_ , slots=lowerCAme... | 296 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __lowercase ( ) -> Dict:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_... | 296 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> list[list]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = current_set.copy()
for row_index, row in enumerate(_SCREAMING_SNAKE_CASE ):
SCREAMING_SNAKE_CASE = row[0]
for column_index, co... | 296 |
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 __lowercase ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any... | 296 | 1 |
from __future__ import annotations
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> str: # noqa: E741
'''simple docstring'''
while r - l > 1:
SCREAMING_SNAKE_CASE = ... | 296 |
import os
from distutils.util import strtobool
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Tuple:
'''simple docstring'''
for e in env_keys:
SCREAMING_SNAKE_CASE = int(os.environ.get(_SCREAMING_SNAKE_CASE , -1 ) )... | 296 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_ = {
"""configuration_bigbird_pegasus""": [
"""BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""BigBirdPegasusConfig""",... | 296 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
def __lowercase ( _SCREAMING_SNAKE_CASE=None , ... | 296 | 1 |
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTokenizer, ... | 296 |
import math
import unittest
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
assert isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
if 1... | 296 | 1 |
from torch import nn
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> Optional[int]:
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
... | 296 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
# Lint as: python3
import itertools
import os
import re
SCREAMING_SNAKE_CASE_ = re.compile(r"""([A-Z]+)([A-Z][a-z])""")
SCREAMING_SNAKE_CASE_ = re.compile(r"""([a-z\d])([A-Z])""")
SCREAMING_SNAKE_CASE_ = re.compile(r"""(?<!_)_(?!_)""")
SCREAMING_SNAKE_C... | 296 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""snap-research/efficientformer-l1-300""": (
"""https://huggingface.c... | 296 | 1 |
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
SCREAMING_SNAKE_CASE_ = HfApi()
SCREAMING_SNAKE_CASE_ = {}
# fmt: off
SCREAMING_SNAKE_CASE_ = torch.tensor([
-0.7515, -1.6883, 0.2420, 0.0300, 0.6347... | 296 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE_ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
... | 296 | 1 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __lowercase ( ) -> Dict:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_... | 296 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase__ ( unittest.TestC... | 296 | 1 |
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize... | 296 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Un... | 296 | 1 |
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=lowerCAmelCase_ ):
'''simple docstring'''
__snake_case : List[str] = ["note_seq"]
def __init__( self : Dict ,*lowerCamelCase__ : Tuple ... | 296 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE_ = logging.getLogger(__name__)
@dataclass
class UpperCamelCase__ ( lowerCAmel... | 296 | 1 |
from __future__ import annotations
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
SCREAMING_SNAKE_CASE = get_failure_array(_SCREAMING_SNAKE_CASE )
# 2) Step through text searching for pattern
... | 296 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 296 | 1 |
SCREAMING_SNAKE_CASE_ = 6_5_5_2_1
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = 1
SCREAMING_SNAKE_CASE = 0
for plain_chr in plain_text:
SCREAMING_SNAKE_CASE = ... | 296 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10 ) -> str:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("""Invalid input""" )
SCREAMING_SNAKE_CASE = 10**n
SCREAMING_SNAK... | 296 | 1 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""xlm-... | 296 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFI... | 296 | 1 |
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, SquadDataTrainingArgument... | 296 |
from pathlib import Path
import fire
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = Path(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_co... | 296 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert impor... | 296 | 1 |
import os
import sys
SCREAMING_SNAKE_CASE_ = os.path.join(os.path.dirname(__file__), """src""")
sys.path.append(SRC_DIR)
from transformers import (
AutoConfig,
AutoModel,
AutoModelForCausalLM,
AutoModelForMaskedLM,
AutoModelForQuestionAnswering,
AutoMode... | 296 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/git-base""": """https://huggingface.co/mi... | 296 | 1 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __lowercase ( ) -> Optional[Any]:
'''simple docstring'''
with offli... | 296 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.im... | 296 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/cvt-13""": """https://huggingface.co/microsoft/cvt-13/resolve/main/config.json""",
# See... | 296 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProc... | 296 | 1 |
import unittest
from parameterized import parameterized
from transformers import AutoTokenizer, GPTNeoXConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuratio... | 296 |
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ ... | 296 | 1 |
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
SCREAMING_SNAKE_CASE_ = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2), ... | 296 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_ = logging.get_logg... | 296 | 1 |
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class UpperCamelCase__ ( lowerCAmelC... | 296 |
from collections import defaultdict
from math import gcd
def __lowercase ( _SCREAMING_SNAKE_CASE = 1_50_00_00 ) -> int:
'''simple docstring'''
SCREAMING_SNAKE_CASE = defaultdict(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = 2
while 2 * euc... | 296 | 1 |
import unittest
from transformers import DonutProcessor
SCREAMING_SNAKE_CASE_ = """naver-clova-ix/donut-base"""
class UpperCamelCase__ ( unittest.TestCase ):
'''simple docstring'''
def SCREAMING_SNAKE_CASE__ ( self : Optional[Any] ... | 296 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def __lowercase ( ) -> Dict:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ArgumentParser("""Diffusers CLI tool""" , usage="""diffusers-cli <command> [<args>]""" )
SCREAMING_... | 296 | 1 |
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
SCREAMING_SNAKE_CASE_ = datasets.utils.logging.get_logger(__name__)
@dataclass
class ... | 296 |
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 __lowercase ( _SCREAMING_SNAKE_CASE ) -> Union[str, Any... | 296 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_ = {"""configuration_vit""": ["""VIT_PRETRAINED_CONFIG... | 296 |
import os
from distutils.util import strtobool
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> Tuple:
'''simple docstring'''
for e in env_keys:
SCREAMING_SNAKE_CASE = int(os.environ.get(_SCREAMING_SNAKE_CASE , -1 ) )... | 296 | 1 |
import argparse
import random
import joblib
import numpy as np
import torch
from igf.igf import (
SecondaryLearner,
collect_objective_set,
compute_perplexity,
generate_datasets,
load_gpta,
recopy_gpta,
set_seed,
train_secondary_learner,
)
from torch.utils.dat... | 296 |
import dataclasses
import json
import warnings
from dataclasses import dataclass, field
from time import time
from typing import List
from ..utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
def __lowercase ( _SCREAMING_SNAKE_CASE=None , ... | 296 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10 ) -> str:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("""Invalid input""" )
SCREAMING_SNAKE_CASE = 10**n
SCREAMING_SNAK... | 296 |
import math
import unittest
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
assert isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) and (
number >= 0
), "'number' must been an int and positive"
if 1... | 296 | 1 |
import math
from datetime import datetime, timedelta
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> datetime:
'''simple docstring'''
SCREAMING_SNAKE_CASE = year % 19
SCREAMING_SNAKE_CASE = year % 4
SCREAMING_SNAKE_CASE = year % 7
... | 296 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
SCREAMING_SNAKE_CASE = F"""Input value of [number={number}] must be an integer"""
raise TypeErro... | 296 |
from typing import List
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""snap-research/efficientformer-l1-300""": (
"""https://huggingface.c... | 296 | 1 |
import argparse
import fairseq
import torch
from transformers import UniSpeechSatConfig, UniSpeechSatForCTC, UniSpeechSatForPreTraining, logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""pos... | 296 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
SCREAMING_SNAKE_CASE_ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
... | 296 | 1 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
SCREAMING_SNAKE_CASE_ = object()
# For specifying empty leaf dict `{}`
SCREAMING_SNAKE_CASE_ = ... | 296 |
import unittest
import numpy as np
import torch
from diffusers import KarrasVePipeline, KarrasVeScheduler, UNetaDModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_determinism()
class UpperCamelCase__ ( unittest.TestC... | 296 | 1 |
import contextlib
import copy
import random
from typing import Any, Dict, Iterable, Optional, Union
import numpy as np
import torch
from .utils import deprecate, is_transformers_available
if is_transformers_available():
import transformers
def __lowercase ( _SCREAMING_... | 296 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Un... | 296 | 1 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 296 |
import logging
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import arg_to_scheduler
from transformers import TrainingArguments
SCREAMING_SNAKE_CASE_ = logging.getLogger(__name__)
@dataclass
class UpperCamelCase__ ( lowerCAmel... | 296 | 1 |
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class UpperCamelCase... | 296 |
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DPMSolverMultistepScheduler,
TextToVideoSDPipeline,
UNetaDConditionModel,
)
from diffusers.utils impo... | 296 | 1 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class UpperCamelCase__ ( lowerCAmelCase_ ):
''... | 296 |
def __lowercase ( _SCREAMING_SNAKE_CASE = 10 ) -> str:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("""Invalid input""" )
SCREAMING_SNAKE_CASE = 10**n
SCREAMING_SNAK... | 296 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 296 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_ = {
"""configuration_llama""": ["""LLAMA_PRETRAINED_CONFI... | 296 | 1 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available... | 296 |
from pathlib import Path
import fire
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ) -> List[str]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = Path(_SCREAMING_SNAKE_CASE )
SCREAMING_SNAKE_CASE = ... | 296 | 1 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProc... | 296 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert impor... | 296 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
SCREAMING_SNAKE_CASE_ = logging.get_logg... | 296 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""microsoft/git-base""": """https://huggingface.co/mi... | 296 | 1 |
from math import asin, atan, cos, radians, sin, sqrt, tan
SCREAMING_SNAKE_CASE_ = 637_8137.0
SCREAMING_SNAKE_CASE_ = 635_6752.31_4245
SCREAMING_SNAKE_CASE_ = 6_3_7_8_1_3_7
def __lowercase ( _SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE , ... | 296 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from transformers import TvltFeatureExtractor, is_datasets_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.im... | 296 | 1 |
def __lowercase ( _SCREAMING_SNAKE_CASE ) -> bool:
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise ValueError("""Input series is not valid, valid series - [2, 4, 6]""" )
if len(_SCREAMING_SNAKE_CASE ) ... | 296 |
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 (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImageProc... | 296 | 1 |
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