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 |
|---|---|---|---|---|
'''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 Feature... | 41 |
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 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
lowercase : List[str] = logging.get_logger(__name__)
class __UpperCAmelCase ( _lowerCamelCase ):
def __init__( self , *lowerCAm... | 42 |
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 | 0 |
import argparse
import os
from pathlib import Path
import torch
from bark.generation import _load_model as _bark_load_model
from huggingface_hub import hf_hub_download
from transformers import EncodecConfig, EncodecModel, set_seed
from transformers.models.bark.configuration_bark import (
BarkCoarseConfig,
Bar... | 43 |
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 | 0 |
"""simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : int ) -> int:
if divisor % 5 == 0 or divisor % 2 == 0:
return 0
_lowerCAmelCase : Any = 1
_lowerCAmelCase : Optional[Any] = 1
while repunit:
_lowerCAmelCase ... | 44 |
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 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class __lowerCAmelCase ( metaclass=__SCREAMING_SNAKE_CASE ):
'''simple docstring'''
__UpperCAmelCase : Optional[int] = ['sentencepiece']
def __init__( self , *_a , ... | 45 |
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 | 0 |
"""simple docstring"""
import random
class lowercase :
@staticmethod
def _snake_case ( lowercase ) -> tuple[list[int], list[int]]:
lowerCAmelCase = [ord(lowercase ) for i in text]
lowerCAmelCase = []
lowerC... | 46 |
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 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def _lowerCAmelCase ( _UpperCamelCase : int ) -> bool:
"""simple docstring"""
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or num... | 47 |
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 | 0 |
def A ( _SCREAMING_SNAKE_CASE ) -> Any:
lowerCamelCase : Optional[Any] = []
lowerCamelCase : str = set({"(", "[", "{"} )
lowerCamelCase : int = set({")", "]", "}"} )
lowerCamelCase : Union[str, Any] = ... | 48 |
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 | 0 |
def __snake_case ( _UpperCAmelCase = 1000 ):
__a = 2**power
__a = str(_UpperCAmelCase )
__a = list(_UpperCAmelCase )
__a = 0
for i in list_num:
sum_of_num += int(_UpperCAmelCase )
return sum_of_num
if ... | 49 |
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 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN, USER, get_test... | 50 |
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 | 0 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
snake_case_ : Union[str, Any] = logging.get_logger(__name__)
snake_case_ : Optional[int] = {name: getattr... | 51 |
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 | 0 |
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 52 |
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 | 0 |
'''simple docstring'''
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrateg... | 53 |
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 | 0 |
"""simple docstring"""
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
a__ : int = logging.get_logger(__name__)
a__ : str... | 54 |
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 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax... | 55 |
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 | 0 |
'''simple docstring'''
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def __magic_name__ ( __UpperCAmelCase ) -> List[Any]: # pickla... | 56 |
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 | 0 |
"""simple docstring"""
def _lowerCamelCase ( _UpperCamelCase , _UpperCamelCase ):
'''simple docstring'''
if not isinstance(_UpperCamelCase , _UpperCamelCase ):
raise ValueError("iterations must be defined as integers" )
if not isinstance(_UpperCamelCase , _UpperCamelCas... | 57 |
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 | 0 |
'''simple docstring'''
from __future__ import annotations
lowercase_ = 10
def lowerCamelCase ( __lowerCamelCase : list[int] ) ->list[int]:
_SCREAMING_SNAKE_CASE = 1
_SCREAMING_SNAKE_CASE = max(__lowerCamelCase )
while placement <= max_digit:
... | 58 |
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 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_torch_available,
)
__lowerCamelCase = {
"""configuration_speecht5""": [
"""SPEECHT5_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""S... | 59 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 0 |
"""simple docstring"""
from ...utils import is_note_seq_available, is_transformers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailab... | 60 |
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 | 0 |
"""simple docstring"""
import os
import numpy
import onnx
def __a ( __lowerCamelCase, __lowerCamelCase ):
UpperCAmelCase_ : Any = a.name
UpperCAmelCase_ : Optional[Any] = b.name
UpperCAmelCase_ : str = ""
UpperCAmelCase_ : ... | 61 |
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 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils import... | 62 |
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 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def _lowerCamelCase ( lowercase : Any , ... | 63 |
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 | 0 |
"""simple docstring"""
import itertools
import string
from collections.abc import Generator, Iterable
def UpperCAmelCase__ (snake_case__ : Iterable[str] , snake_case__ : int ):
"""simple docstring"""
_snake_case : Optional[Any] = iter(sna... | 64 |
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 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
from .prior_transfor... | 65 |
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 | 0 |
"""simple docstring"""
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we h... | 66 |
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 | 0 |
'''simple docstring'''
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
__UpperCAmelCase =list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
__UpperCAmelCase =[file for fi... | 67 |
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 | 0 |
import flax.linen as nn
import jax
import jax.numpy as jnp
class a__ ( nn.Module ):
"""simple docstring"""
__lowerCamelCase = 42
__lowerCamelCase = jnp.floataa
def UpperCamelCase ( self ) -> Any:
'''simple docstring'''
A__ ... | 68 |
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 | 0 |
"""simple docstring"""
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_comm... | 69 |
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 | 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... | 70 |
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 | 0 |
import random
from .binary_exp_mod import bin_exp_mod
def A ( a_ ,a_=1_000 ) -> Optional[Any]:
if n < 2:
return False
if n % 2 == 0:
return n == 2
# this means n is odd
__UpperCamelCase : List[An... | 71 |
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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase__ = {
'''configuration_rembert''': [''... | 72 |
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 | 0 |
from __future__ import annotations
import time
a =list[tuple[int, int]]
a =[
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, ... | 73 |
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 | 0 |
"""simple docstring"""
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
_lowercase = logging.get_logger(__name__)
_lowercase = {
... | 74 |
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 | 0 |
'''simple docstring'''
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
a_ : Dict = HfApi()
a_ : Tuple = {}
# fmt: off
a_ : Union[str, Any] = torch.tensor([
-0.75_15, -1.68_83, 0.24_20... | 75 |
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 | 0 |
from typing import List, Optional, Union
import numpy as np
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import PaddingStrategy, TensorType, logging
a_ = logging.get_logger(__name__)
class _UpperCamelCase ... | 76 |
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 | 0 |
"""simple docstring"""
import argparse
import logging
import pickle
import random
import time
import numpy as np
from transformers import BertTokenizer, GPTaTokenizer, RobertaTokenizer
logging.basicConfig(
format="%(asctime)s - %(levelname)s - %(name)s - %(message)s", datefmt="%m/%d/%Y %H:%M:%S", level=log... | 77 |
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 | 0 |
"""simple docstring"""
from pathlib import Path
import numpy as np
from PIL import Image
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase , UpperCAmelCase , UpperCAmelCase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2]
return 0.2_9_8_9 * r + 0.5_8... | 78 |
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 | 0 |
'''simple docstring'''
from __future__ import annotations
from functools import lru_cache
from math import ceil
lowerCamelCase_ = 1_00
lowerCamelCase_ = set(range(3, NUM_PRIMES, 2))
primes.add(2)
lowerCamelCase_ = 42
for prime in range(3, ceil(NUM_PRIMES**0.5)... | 79 |
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 | 0 |
'''simple docstring'''
from math import factorial
a__ : dict[str, int] = {str(digit): factorial(digit) for digit in range(1_0)}
def _UpperCamelCase ( __A ) -> int:
'''simple docstring'''
if not isinstance(__A , __A ):
raise T... | 80 |
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 | 0 |
"""simple docstring"""
import math
from typing import Callable, List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from transformers import CLIPTextModel, CLIPTokenizer
from diffusers.models import AutoencoderKL, UNetaDConditionModel
from diffusers.pi... | 81 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class __lowe... | 82 |
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 | 0 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel
from diffusers import DDIMScheduler, LDMPipeline, UNetaDModel, VQModel
from diffusers.utils.testing_utils import enable_full_determinism, require_torch, slow, torch_device
enable_full_de... | 83 |
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 | 0 |
"""simple docstring"""
from queue import Queue
from typing import TYPE_CHECKING, Optional
if TYPE_CHECKING:
from ..models.auto import AutoTokenizer
class _SCREAMING_SNAKE_CASE :
def __lowerCAmelCase ( self , __A ) -> int:
raise No... | 84 |
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 | 0 |
'''simple docstring'''
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_SCREAMING_SNAKE_CASE : Union[str, Any... | 85 |
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 | 0 |
"""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__ = WebClient(token=os.environ["""CI_SLACK_BOT_TOKEN"""])
def __lowerCAmelCase (_... | 86 |
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 | 0 |
# 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
UpperCamelCase = TypeVar('''T''')
class snake_case_ ( Generic[T] ):
... | 87 |
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 | 0 |
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
__lowerCAmelCase : List[Any] = {'configuration_gpt_neox': ['GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoXConfig']}
t... | 88 |
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 | 0 |
'''simple docstring'''
# 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
#
# ... | 89 |
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 | 0 |
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():
from ..... | 90 |
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 | 0 |
"""simple docstring"""
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_wei... | 91 |
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 | 0 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class a__ ( unittest.TestCase , snake_case__ ):
def __SCREAMING_SNAKE_CASE( self ):
"""simple docstring"""
__lowerCAmelCase = load_tool(... | 92 |
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 | 0 |
'''simple docstring'''
import math
def snake_case_ ( __SCREAMING_SNAKE_CASE : int ):
"""simple docstring"""
if not isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
lowercase_ : Union[str, Any] = ... | 93 |
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 | 0 |
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
snake_case : List[str] = logging.get_logger(__name__)
snake_case : Tuple ... | 94 |
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 | 0 |
from ...configuration_utils import PretrainedConfig
class __lowerCAmelCase ( UpperCamelCase__):
_lowercase : str = """bert-generation"""
def __init__( self , lowerCAmelCase__=5_0_3_5_8 , lowerCAmelCase__=1_0_2_4 , low... | 95 |
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 | 0 |
"""simple docstring"""
def _snake_case ( lowercase__ , lowercase__ ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_lowerCamelCase : List[Any] = (boundary[1] - boundary[0]) / steps
_lowerCamelCase : Tuple = b... | 96 |
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 | 0 |
'''simple docstring'''
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class lowercase ( tf.keras.optimizers.schedules.LearningRateSchedule ... | 97 |
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 | 0 |
"""simple docstring"""
def a_ ( lowerCamelCase ):
if len(lowerCamelCase ) <= 1:
return [tuple(lowerCamelCase )]
UpperCAmelCase__ = []
def generate(lowerCamelCase , lowerCamelCase ):
UpperCAmelCase__ = [0] *... | 98 |
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 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_torch_available,
)
lowercase : Any = {
"""configuration_gpt_bigcode""": ["""GPT_BIGCODE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GPTBigCodeConfig"""],
}
try:
if not is_to... | 99 |
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 | 0 |
"""simple docstring"""
def _lowerCAmelCase ( UpperCamelCase_ = 50 ):
__SCREAMING_SNAKE_CASE = [1] * (length + 1)
for row_length in range(3 , length + 1 ):
for block_length in range(3 , row_length + 1 ):
for block_start in range(row_length - block_length ):... | 100 |
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 | 0 |
import requests
lowercase__ :Any = "" # <-- Put your OpenWeatherMap appid here!
lowercase__ :Tuple = "https://api.openweathermap.org/data/2.5/"
def UpperCamelCase ( lowerCAmelCase__ = "Chicago" , lowerCAmelCase__ = APPID ):
'''simple docstring'''
return requests.get(URL_BA... | 101 |
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 | 0 |
"""simple docstring"""
import unittest
from transformers import LiltConfig, 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 impor... | 102 |
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 | 0 |
import argparse
import os
import re
import packaging.version
A__ : Dict = '''examples/'''
A__ : Any = {
'''examples''': (re.compile(R'''^check_min_version\("[^"]+"\)\s*$''', re.MULTILINE), '''check_min_version("VERSION")\n'''),
'''init''': (re.compile(R'''^__version__\s+=\s+"([^... | 103 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 0 |
'''simple docstring'''
import cva
import numpy as np
class lowercase_ :
"""simple docstring"""
def __init__( self : str ,lowercase__ : float ,lowercase__ : int ):
if k in (0.0_4, 0.0_6):
__lowercase = k
__lowercase = window_size
... | 104 |
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 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def _SCREAMING_SNAKE_CASE ( _lowercase : Namespace ) ->int:
'''simple docstring'''
return Conver... | 105 |
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 | 0 |
"""simple docstring"""
import numpy as np
import torch
from torch.utils.data import Dataset, IterableDataset
from ..utils.generic import ModelOutput
class SCREAMING_SNAKE_CASE ( a_ ):
"""simple docstring"""
def __init__( self : List[Any] ,lowercase_ : T... | 106 |
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 | 0 |
import argparse
import collections
import numpy as np
import torch
from flax import traverse_util
from tax import checkpoints
from transformers import MTaConfig, UMTaEncoderModel, UMTaForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
def __magic_name__ ( A ... | 107 |
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 | 0 |
"""simple docstring"""
import json
import os
import unittest
from transformers import DebertaTokenizer, DebertaTokenizerFast
from transformers.models.deberta.tokenization_deberta import VOCAB_FILES_NAMES
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin... | 108 |
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 | 0 |
"""simple docstring"""
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_u... | 109 |
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 | 0 |
"""simple docstring"""
def __a ( __lowerCamelCase = 10**12 ):
UpperCAmelCase_ : List[Any] = 1
UpperCAmelCase_ : Optional[int] = 0
UpperCAmelCase_ : Optional[int] = 1
UpperCAmelCase_ : Optional[Any] = 1
while numerator ... | 61 |
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 | 0 |
"""simple docstring"""
import math
_UpperCamelCase : Optional[int] = 10
_UpperCamelCase : Optional[int] = 7
_UpperCamelCase : int = BALLS_PER_COLOUR * NUM_COLOURS
def a_ ( _lowerCAmelCase : List[Any] = 20 ):
'''simple docstring'''
... | 77 |
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 | 0 |
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, 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... | 23 |
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 | 0 |
"""simple docstring"""
import os
__A : str = {"I": 1, "V": 5, "X": 10, "L": 50, "C": 100, "D": 500, "M": 1000}
def lowercase ( _SCREAMING_SNAKE_CASE : Optional[int] ):
'''simple docstring'''
_UpperCAmelCase = 0
... | 260 |
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 | 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_extrac... | 297 |
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 | 0 |
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 transformers.utils.import_utils... | 275 |
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 | 0 |
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
fr... | 95 |
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 | 0 |
def UpperCAmelCase__ ( lowerCamelCase = 10 ):
if not isinstance(_SCREAMING_SNAKE_CASE, _SCREAMING_SNAKE_CASE ) or n < 0:
raise ValueError("Invalid input" )
lowercase :Optional[Any] = 10**n
lowercase :Optional[Any] = 28433 * (pow(2, 7830457, _SCREAMING_SNAKE_C... | 236 |
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 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case : Union[str, Any] = logging.get_logger(__name__)
snake_case : Any = {
"unc-nlp/lxmert-base-uncased": "https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json",
}
class... | 281 |
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 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_SCREAMING_SNAKE_CASE : Optional[int] = logging.get_logger(__name_... | 183 |
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 | 0 |
import unittest
from transformers import load_tool
from transformers.utils import is_torch_available
if is_torch_available():
import torch
from transformers.testing_utils import require_torch
from .test_tools_common import ToolTesterMixin
@require_torch
class __lowerCAmelCase ( unittest.Tes... | 156 |
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 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a = {
'configuration_bigbird_pegasus': [
'BIGBIRD_PEGASUS_PRETRAINED_CONFIG_ARCHIVE_MAP',
'BigBirdPegasusConfig',
'BigBirdPegas... | 61 |
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 | 0 |
"""simple docstring"""
import string
def a_ ( _lowerCAmelCase : Union[str, Any] ):
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
lowercase__ : int = ''
for symbol in message:
if sy... | 77 |
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 | 0 |
'''simple docstring'''
import argparse
import os
# New Code #
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedul... | 23 |
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 | 0 |
"""simple docstring"""
from math import isclose, sqrt
def lowercase ( _SCREAMING_SNAKE_CASE : str , _SCREAMING_SNAKE_CASE : Union[str, Any] , _SCREAMING_SNAKE_CASE : List[Any] ):
'''simple docstring'''
_UpperCAmelCase ... | 260 |
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 | 0 |
'''simple docstring'''
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.util... | 297 |
import random
class UpperCamelCase__ :
'''simple docstring'''
@staticmethod
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ : str ) -> tuple[list[int], list[int]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE = ... | 296 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, load_numpy, slow, torc... | 275 |
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 | 0 |
def _A ( SCREAMING_SNAKE_CASE : Optional[Any] ):
"""simple docstring"""
a__ : Union[str, Any] =current_set.copy()
for row_index, row in enumerate(_SCREAMING_SNAKE_CASE ):
a__ : Any =row[0]
for column_index, column in en... | 95 |
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 | 0 |
import inspect
import logging
import os
import random
import shutil
import tempfile
import unittest
import pytest
import torch
from torch import nn
from torch.utils.data import DataLoader, TensorDataset
from accelerate import Accelerator
from accelerate.test_utils import execute_subprocess_async, require_cuda
fr... | 236 |
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 | 0 |
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTokenizer
if TYPE_CHECKING:
... | 281 |
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 | 0 |
"""simple docstring"""
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_tokeni... | 183 |
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 | 0 |
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 : List[Any] = l... | 156 |
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 | 0 |
"""simple docstring"""
def __a ( __lowerCamelCase ):
return 10 - x * x
def __a ( __lowerCamelCase, __lowerCamelCase ):
if equation(_SCREAMING_SNAKE_CASE ) * equation(_SCREAMING_SNAKE_CASE ) >= 0:
raise ValueError("Wrong space!" )
UpperCAmelCase_ : Union[str, Any]... | 61 |
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 | 0 |
"""simple docstring"""
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def a_ ( _lowerCAmelCase : int ):
'''sim... | 77 |
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 | 0 |
'''simple docstring'''
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, Timeste... | 23 |
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 | 0 |
"""simple docstring"""
def lowercase ( _SCREAMING_SNAKE_CASE : str ):
'''simple docstring'''
if not isinstance(_SCREAMING_SNAKE_CASE , _SCREAMING_SNAKE_CASE ):
raise ValueError('''Input must be an integer''' )
if input_num <= 0:
rais... | 260 |
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 | 0 |
'''simple docstring'''
from typing import Any, Dict, List, Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from ..image_utils import load_image
if is_torch_avail... | 297 |
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 | 0 |
def _lowercase ( lowercase__ , lowercase__ ):
__lowerCAmelCase : Dict = len(_SCREAMING_SNAKE_CASE )
print('''The following activities are selected:''' )
# The first activity is always selected
__lowerCAmelCase : Union[str, Any] = 0
... | 275 |
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 | 0 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def _A ( ):
"""simple docstring"""
with offline(OfflineSimulationMode.CONNECT... | 95 |
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 | 0 |
import warnings
from ..trainer import Trainer
from ..utils import logging
_UpperCAmelCase : List[Any] = logging.get_logger(__name__)
class __lowerCAmelCase ( lowerCAmelCase_):
def __init__( self: str , _lowerCAmelCase: Dict=None , **_lowerCAmelCase: ... | 236 |
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 | 0 |
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_utils import FrozenDict
fro... | 281 |
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 | 0 |
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