code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
from __future__ import annotations
from typing import Generic, TypeVar
lowerCAmelCase_ : Optional[Any] = TypeVar('T')
class __SCREAMING_SNAKE_CASE (Generic[T] ):
"""simple docstring"""
def __init__( self : Optional[Any] , ... | 692 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(CMStochasticIterativeScheduler,)
__a =10
def... | 692 | 1 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerC... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
import inspect
import tempfile
from collections import OrderedDict, UserDict
from collections.abc import MutableMapping
from contextlib import ExitStack, contextmanager
from dataclasses import fields
from enum import Enum
from typing import Any, ContextManager, List, Tuple
import nu... | 692 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/re... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
from cmath import sqrt
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : int ) -> tuple[complex, complex]:
if a == 0:
raise ValueError("Coefficient 'a' must not b... | 692 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeI... | 692 | 1 |
'''simple docstring'''
from dataclasses import asdict, dataclass
from typing import Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : str = logging.get_logger(__name__)
# TODO Update this
lowerCAmelCase_ : str = ... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def __init__( self : Op... | 692 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerC... | 692 | 1 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int = 100 ) -> int:
_a = sum(i * i for i in range(1 , n + 1 ) )
_a = int(math.pow(sum(range(1 , n + 1 ) ) , 2 ) )
return square_of_sum... | 692 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tok... | 692 | 1 |
'''simple docstring'''
import colorsys
from PIL import Image # type: ignore
def _lowerCamelCase ( lowercase : float , lowercase : float , lowercase : int ) -> float:
_a = x
_a = y
for step in range(lowercase ): #... | 692 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : List[Any] ):
_a = psutil.Process()
_a = False
def ... | 692 | 1 |
'''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
from lavis.models import load_model_and_preprocess
from PIL import Image
from tran... | 692 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(DDIMParallelScheduler,)
__a =(('eta', 0.0), ('num_inference_s... | 692 | 1 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ , unittest.TestCase ):
"""s... | 692 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _lowerCamelCase ( lowercase : Any ) -> List[str]:
return getitem, k
def _lowerCamelCase ( lowercase : Opt... | 692 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
lowerCAmelCase_ : Optional[Any] = {
'configuration_gpt_neo': ['GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GPTNeoConfig', 'GP... | 692 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ , unittest.TestCase ):
"""s... | 692 | 1 |
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import BertTokenizer, BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES
from transformers.testing_utils import require_vis... | 692 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as ... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int , lowercase : int ) -> int:
_a = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
_a = n - k
# Calculate C(n,k)
for i in range... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docst... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str , lowercase : Any ) -> List[Any]:
_a = ""
for i in table:
res += inp[i - 1]
return res
def _lowerCamelCase ( lowercase : str ) -> int:
retu... | 692 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddin... | 692 | 1 |
'''simple docstring'''
import math
lowerCAmelCase_ : Tuple = 10
lowerCAmelCase_ : Tuple = 7
lowerCAmelCase_ : int = BALLS_PER_COLOUR * NUM_COLOURS
def _lowerCamelCase ( lowercase : int = 20 ) -> str:
_a = ... | 692 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =42
class __SCREAMING_SN... | 692 | 1 |
'''simple docstring'''
import re
def _lowerCamelCase ( lowercase : str ) -> bool:
_a = re.compile(
r"^(?:0|94|\+94|0{2}94)" r"7(0|1|2|4|5|6|7|8)" r"(-| |)" r"\d{7}$" )
return bool(re.search(lowercase , lowercase ) )
if __name__ ==... | 692 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class ... | 692 | 1 |
'''simple docstring'''
import argparse
import importlib
from pathlib import Path
# Test all the extensions added in the setup
lowerCAmelCase_ : int = [
'kernels/rwkv/wkv_cuda.cu',
'kernels/rwkv/wkv_op.cpp',
'kernels/deformable_detr/ms_deform_attn.h',
'kernels/deformable_... | 692 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ : List[Any] = [
# tf -> hf
('/', '.'),
('layer_',... | 692 | 1 |
'''simple docstring'''
import unittest
from datasets import load_dataset
from transformers import BloomTokenizerFast
from transformers.testing_utils import require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
class __SCREAMING_SNAKE_CASE (lowerCam... | 692 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str , lowercase : list[str] ) -> str:
_a = ""
for word_or_phrase in separated:
if not isinstance(lowercase , lowercase ):
raise Exception("join() accepts only str... | 692 | 1 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddin... | 692 |
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lowerCAmelCase_ : List[Any] =... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
def _lowerCamelCase ( lowercase : str , lowercase : list[str] | None = None ) -> list[list[str]]:
_a = word_bank or []
# create a table
_a = len(lowercase ) + 1
_... | 692 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
lowerCAmelCase_ : Optional[Any] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:]... | 692 | 1 |
'''simple docstring'''
from packaging import version
from .import_utils import is_accelerate_available
if is_accelerate_available():
import accelerate
def _lowerCamelCase ( lowercase : Union[str, Any] ) -> Any:
if not is_accelerate_available():
return me... | 692 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCAmelCase_ : Optional[Any] = datasets.logging.get_logger(__name__)
lowerCAmelCase_ : ... | 692 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase_ )
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple... | 692 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples... | 692 | 1 |
'''simple docstring'''
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_util... | 692 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(CMStochasticIterativeScheduler,)
__a =10
def... | 692 | 1 |
'''simple docstring'''
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
import tempfile
import numpy as np
import torch
from transformers import AutoTokenizer, TaEncoderModel
from diffusers import DDPMScheduler, UNetaDConditionModel
from diffusers.models.attention_processor import AttnAddedKVProcessor
from diffusers.pipelines.deepfloyd_if import IFWate... | 692 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/re... | 692 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attent... | 692 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeI... | 692 | 1 |
'''simple docstring'''
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTes... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import OPTConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_... | 692 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerC... | 692 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeI... | 692 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tok... | 692 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : List[str] = {
'configuration_m2m_100': ['M2M_100_PRETRAINED_CONFIG_ARCHIVE_MAP', 'M2M100Config', '... | 692 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : List[Any] ):
_a = psutil.Process()
_a = False
def ... | 692 | 1 |
'''simple docstring'''
import os
from argparse import ArgumentParser
from typing import List
import torch.utils.data
from datasets import Dataset, IterableDataset
from datasets.distributed import split_dataset_by_node
lowerCAmelCase_ : Dict = 4
lowerCAmelCase_ : List[Any] ... | 692 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(DDIMParallelScheduler,)
__a =(('eta', 0.0), ('num_inference_s... | 692 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
from transformers.gener... | 692 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _lowerCamelCase ( lowercase : Any ) -> List[str]:
return getitem, k
def _lowerCamelCase ( lowercase : Opt... | 692 | 1 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ : List[Any] = [
# tf -> hf
('/', '.'),
('layer_',... | 692 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ , unittest.TestCase ):
"""s... | 692 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
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_configuration_common im... | 692 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as ... | 692 | 1 |
'''simple docstring'''
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def _lowerCamelCase ( ) -> Optional[int]:
_a = {
"repo_name": ["test_repo1", "test_repo2"... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docst... | 692 | 1 |
'''simple docstring'''
from ....configuration_utils import PretrainedConfig
from ....utils import logging
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'speechbrain/m-ctc-t-large': 'https://huggingface.co/speechbrain/m-... | 692 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddin... | 692 | 1 |
'''simple docstring'''
import re
def _lowerCamelCase ( lowercase : str ) -> str:
if len(re.findall("[ATCG]" , lowercase ) ) != len(lowercase ):
raise ValueError("Invalid Strand" )
return dna.translate(dna.maketrans("ATCG" , "TAGC" ) ... | 692 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =42
class __SCREAMING_SN... | 692 | 1 |
'''simple docstring'''
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common impor... | 692 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class ... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import pi
def _lowerCamelCase ( lowercase : float , lowercase : float , lowercase : float ) -> dict[str, float]:
if (inductance, frequency, reactance).count(0 ) != 1:
rais... | 692 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ : List[Any] = [
# tf -> hf
('/', '.'),
('layer_',... | 692 | 1 |
'''simple docstring'''
import numpy as np
import torch
import tqdm
from ...models.unet_ad import UNetaDModel
from ...pipelines import DiffusionPipeline
from ...utils import randn_tensor
from ...utils.dummy_pt_objects import DDPMScheduler
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
... | 692 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str , lowercase : list[str] ) -> str:
_a = ""
for word_or_phrase in separated:
if not isinstance(lowercase , lowercase ):
raise Exception("join() accepts only str... | 692 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ : Dict = logging.get_logger(__name__)
lowerCAmelCase_ : List[st... | 692 |
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lowerCAmelCase_ : List[Any] =... | 692 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase_ : Union[str, Any] = {
'configu... | 692 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
lowerCAmelCase_ : Optional[Any] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:]... | 692 | 1 |
'''simple docstring'''
import tempfile
import torch
from diffusers import PNDMScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(PNDMScheduler,)
__a =(('num_inference_steps', 50),)
... | 692 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCAmelCase_ : Optional[Any] = datasets.logging.get_logger(__name__)
lowerCAmelCase_ : ... | 692 | 1 |
'''simple docstring'''
import itertools
import string
from collections.abc import Generator, Iterable
def _lowerCamelCase ( lowercase : Iterable[str] , lowercase : int ) -> Generator[tuple[str, ...], None, None]:
_a = iter(lowercase )
while T... | 692 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples... | 692 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
lowerCAmelCase_ : Union[str, Any] = {
'configuration_trocr': ['TROC... | 692 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(CMStochasticIterativeScheduler,)
__a =10
def... | 692 | 1 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : List[Any] ):
_a = psutil.Process()
_a = False
def ... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def _lowerCamelCase ( lowercase : str ) -> Dict:
# This defines a "chinese character" as anything in the CJK Unicode block:
# ht... | 692 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/re... | 692 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING, TF_MODEL_FOR_AUDIO_CLASSIFICATION_MAPPING
from transformers.pipelines import AudioClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 692 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeI... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 1000 ) -> int:
_a , _a = 1, 1
_a = 2
while True:
_a = 0
_a = fa + fa
_a , _a = fa, f
index += ... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
from math import factorial
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : float ) -> float:
if successes > trials:
raise ValueError("successes must be lower or equal to trials" )
if trials < ... | 692 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerC... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int ) -> int:
if n == 1 or not isinstance(lowercase , lowercase ):
return 0
elif n == 2:
return 1
else:
_a = [0, 1]
for i in range(2 , n + 1 ):
... | 692 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tok... | 692 | 1 |
'''simple docstring'''
import importlib
import os
import fsspec
import pytest
from fsspec import register_implementation
from fsspec.registry import _registry as _fsspec_registry
from datasets.filesystems import COMPRESSION_FILESYSTEMS, HfFileSystem, extract_path_from_uri, is_remote_filesystem
from .uti... | 692 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : List[Any] ):
_a = psutil.Process()
_a = False
def ... | 692 | 1 |
'''simple docstring'''
import numpy
# List of input, output pairs
lowerCAmelCase_ : Any = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
lowerCAmelCase_ : str = (((5_15, 22, 13), 5_55), ((61, 35, 49), 1_... | 692 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(DDIMParallelScheduler,)
__a =(('eta', 0.0), ('num_inference_s... | 692 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _lowerCamelCase ( lowercase : Any ) -> List[str]:
return getitem, k
def _lowerCamelCase ( lowercase : Opt... | 692 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =None
__a =False
__a =False
__a =False
__a =None
... | 692 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ , unittest.TestCase ):
"""s... | 692 | 1 |
'''simple docstring'''
lowerCAmelCase_ : Any = range(2, 20 + 1)
lowerCAmelCase_ : Tuple = [10**k for k in range(ks[-1] + 1)]
lowerCAmelCase_ : dict[int, dict[int, list[list[int]]]] = {}
def _lowerCamelCase ( lowercase : Tuple ... | 692 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as ... | 692 | 1 |
'''simple docstring'''
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docst... | 692 | 1 |
'''simple docstring'''
from argparse import ArgumentParser
from . import BaseTransformersCLICommand
def _lowerCamelCase ( lowercase : Optional[int] ) -> Tuple:
return DownloadCommand(args.model , args.cache_dir , args.force , args.trust_remot... | 692 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddin... | 692 | 1 |
'''simple docstring'''
from math import loga
def _lowerCamelCase ( lowercase : int ) -> int:
if a < 0:
raise ValueError("Input value must be a positive integer" )
elif isinstance(lowercase , lowercase ):
raise TypeError("Input value must b... | 692 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =42
class __SCREAMING_SN... | 692 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import center_crop, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils import (
... | 692 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class ... | 692 | 1 |
'''simple docstring'''
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, ByTaTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
from ...test_tokenization_com... | 692 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ : List[Any] = [
# tf -> hf
('/', '.'),
('layer_',... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int = 100 ) -> int:
_a = n * (n + 1) * (2 * n + 1) / 6
_a = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(f"""{solution() =... | 692 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str , lowercase : list[str] ) -> str:
_a = ""
for word_or_phrase in separated:
if not isinstance(lowercase , lowercase ):
raise Exception("join() accepts only str... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
from collections.abc import Callable
def _lowerCamelCase ( lowercase : Callable[[int | float], int | float] , lowercase : int | float , lowercase : int | float , lowercase : int = 100 ... | 692 |
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lowerCAmelCase_ : List[Any] =... | 692 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ : List[Any] = {'configuration_glpn': ['GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GLPNConfig']}
try:
if not... | 692 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
lowerCAmelCase_ : Optional[Any] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:]... | 692 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from typing import Dict, List, Tuple
from transformers import MaskFormerSwinConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, torch_device
from transformers.utils import is_torch_available
from ..... | 692 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCAmelCase_ : Optional[Any] = datasets.logging.get_logger(__name__)
lowerCAmelCase_ : ... | 692 | 1 |
'''simple docstring'''
import gc
import tempfile
import unittest
import numpy as np
import torch
from diffusers import VersatileDiffusionPipeline
from diffusers.utils.testing_utils import load_image, nightly, require_torch_gpu, torch_device
lowerCAmelCase_ : Union[str, Any] = False
cl... | 692 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples... | 692 | 1 |
'''simple docstring'''
import os
import zipfile
import pytest
from datasets.utils.extract import (
BzipaExtractor,
Extractor,
GzipExtractor,
LzaExtractor,
SevenZipExtractor,
TarExtractor,
XzExtractor,
ZipExtractor,
ZstdExtractor,
)
from .utils import require_lza, requ... | 692 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(CMStochasticIterativeScheduler,)
__a =10
def... | 692 | 1 |
'''simple docstring'''
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _lowerCamelCase ( lowercase : Optional[int] , lowercase : Tuple , lowerc... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
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
... | 692 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/re... | 692 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeI... | 692 | 1 |
'''simple docstring'''
import os
import time
import numpy as np
import onnxruntime as ort
lowerCAmelCase_ : Dict = '1'
lowerCAmelCase_ : int = '0'
lowerCAmelCase_ : Any = '1'
lowerCAmelCase_ : List[Any] = ort.SessionOptions()
lower... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __SCREAMING_SN... | 692 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerC... | 692 | 1 |
'''simple docstring'''
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import numpy as np
import pandas as pd
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
BartFor... | 692 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tok... | 692 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ : Dict = logging.get_logger(__name__)
lowerCAmelCase_ : List[st... | 692 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : List[Any] ):
_a = psutil.Process()
_a = False
def ... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str ) -> str:
return "".join(chr(ord(lowercase ) - 32 ) if "a" <= char <= "z" else char for char in word )
if __name__ == "__main__":
from doctest import testmod
testmod()
| 692 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(DDIMParallelScheduler,)
__a =(('eta', 0.0), ('num_inference_s... | 692 | 1 |
'''simple docstring'''
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPToken... | 692 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _lowerCamelCase ( lowercase : Any ) -> List[str]:
return getitem, k
def _lowerCamelCase ( lowercase : Opt... | 692 | 1 |
'''simple docstring'''
import os
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers.models.realm.configuration_realm import RealmConfig
from transformers.models.realm.retrieval_realm import _REALM_B... | 692 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ , unittest.TestCase ):
"""s... | 692 | 1 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(DDIMParallelScheduler,)
__a =(('eta', 0.0), ('num_inference_s... | 692 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as ... | 692 | 1 |
'''simple docstring'''
lowerCAmelCase_ : str = [0, 2, 4, 6, 8]
lowerCAmelCase_ : Dict = [1, 3, 5, 7, 9]
def _lowerCamelCase ( lowercase : int , lowercase : int , lowercase : list[int] , lowercase : int ) -> i... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
lowerCAmelCase_ : Union[str, Any] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docst... | 692 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowerCAmelCase_ : Dict = 50_00_00
lowerCAmelCase_ , lowerCAmelCase_ : int = os.path.split(__file__)
lowe... | 692 |
'''simple docstring'''
from typing import Any, Dict, Optional
import torch
import torch.nn.functional as F
from torch import nn
from ..utils import maybe_allow_in_graph
from .activations import get_activation
from .attention_processor import Attention
from .embeddings import CombinedTimestepLabelEmbeddin... | 692 | 1 |
'''simple docstring'''
import os
from distutils.util import strtobool
def _lowerCamelCase ( lowercase : Any , lowercase : int ) -> List[str]:
for e in env_keys:
_a = int(os.environ.get(lowercase , -1 ) )
if val >= 0:
... | 692 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =42
class __SCREAMING_SN... | 692 | 1 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
... | 692 |
'''simple docstring'''
import unittest
from diffusers import FlaxAutoencoderKL
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import require_flax
from .test_modeling_common_flax import FlaxModelTesterMixin
if is_flax_available():
import jax
@require_flax
class ... | 692 | 1 |
'''simple docstring'''
import io
import math
from typing import Dict, Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import convert_to_rgb, normalize, to_channel_dimension_forma... | 692 |
'''simple docstring'''
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
lowerCAmelCase_ : List[Any] = [
# tf -> hf
('/', '.'),
('layer_',... | 692 | 1 |
'''simple docstring'''
from typing import List, Optional
from tokenizers import ByteLevelBPETokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_blenderbot_small import BlenderbotSmallTokenizer
lowerCAmelCase_ : str = ... | 692 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : str , lowercase : list[str] ) -> str:
_a = ""
for word_or_phrase in separated:
if not isinstance(lowercase , lowercase ):
raise Exception("join() accepts only str... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : Optional[Any] , __a : int ):
_a = data
_a = None
_a = None
... | 692 |
'''simple docstring'''
lowerCAmelCase_ : Optional[Any] = '\n# Transformers 설치 방법\n! pip install transformers datasets\n# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.\n# ! pip install git+https://github.com/huggingface/transformers.git\n'
lowerCAmelCase_ : List[Any] =... | 692 | 1 |
'''simple docstring'''
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
lowerCAmelCase_ : List[str] = object()
# For specifying empty leaf dict `{}`
lowerCAmelCase... | 692 |
'''simple docstring'''
import sys
import webbrowser
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
print('Googling.....')
lowerCAmelCase_ : Optional[Any] = 'https://www.google.com/search?q=' + ' '.join(sys.argv[1:]... | 692 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
... | 692 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
lowerCAmelCase_ : Optional[Any] = datasets.logging.get_logger(__name__)
lowerCAmelCase_ : ... | 692 | 1 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as ... | 692 |
'''simple docstring'''
import math
def _lowerCamelCase ( lowercase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples... | 692 | 1 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class __SCREAMING_SNAKE_CASE (unittest.TestCase ):
"... | 692 |
'''simple docstring'''
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(CMStochasticIterativeScheduler,)
__a =10
def... | 692 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_upernet': ['UperNetConfig'],
}
try:
if not is_torch_available():
raise OptionalDepen... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_yolos import YolosImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowerCAmelCase_ : List[str] = Mapping[str, np.ndarray]
lowerCAmelCase_ : Any ... | 692 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCAmelCase_ : str = {
'facebook/timesformer': 'https://huggingface.co/facebook/timesformer/re... | 692 | 1 |
'''simple docstring'''
import sys
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - ... | 692 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeI... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import deque
from collections.abc import Iterator
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =42
class __SCREAMING_SN... | 692 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowerCAmelCase_ : Optional[int] = logging.get_logger(__name__)
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
... | 692 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
__a =42
__a =None
__a =None
lowerCAmelCase_ : int = ... | 692 |
'''simple docstring'''
import logging
from pathlib import Path
import numpy as np
import pytorch_lightning as pl
import torch
from pytorch_lightning.callbacks import EarlyStopping, ModelCheckpoint
from pytorch_lightning.utilities import rank_zero_only
from utils_rag import save_json
def _lowerC... | 692 | 1 |
'''simple docstring'''
import numpy as np
import torch
from imwatermark import WatermarkEncoder
# Copied from https://github.com/Stability-AI/generative-models/blob/613af104c6b85184091d42d374fef420eddb356d/scripts/demo/streamlit_helpers.py#L66
lowerCAmelCase_ : Tuple = 0B101100111110110... | 692 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase_ : Any = {
'configuration_biogpt': ['BIOGPT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'BioGptConfig'],
'tok... | 692 | 1 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : int ) -> int:
assert (
isinstance(lowercase , lowercase ) and number_of_steps > 0
), F'number_of_steps needs to be positive integer, your input {number_of_steps}'
if number_of_steps == 1:
... | 692 |
'''simple docstring'''
import gc
import threading
import time
import psutil
import torch
class __SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : List[Any] ):
_a = psutil.Process()
_a = False
def ... | 692 | 1 |
'''simple docstring'''
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common impor... | 692 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
__a =(DDIMParallelScheduler,)
__a =(('eta', 0.0), ('num_inference_s... | 692 | 1 |
'''simple docstring'''
from collections import deque
from .hash_table import HashTable
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ ):
"""simple docstring"""
def __init__( self : Any , *__a : Union[str, Any] , **__a : List[str] ):
super().... | 692 |
'''simple docstring'''
from operator import delitem, getitem, setitem
import pytest
from data_structures.hashing.hash_map import HashMap
def _lowerCamelCase ( lowercase : Any ) -> List[str]:
return getitem, k
def _lowerCamelCase ( lowercase : Opt... | 692 | 1 |
'''simple docstring'''
import itertools
import math
def _lowerCamelCase ( lowercase : int ) -> bool:
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbe... | 692 |
'''simple docstring'''
import os
import unittest
from transformers.models.phobert.tokenization_phobert import VOCAB_FILES_NAMES, PhobertTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class __SCREAMING_SNAKE_CASE (lowerCamelCase_ , unittest.TestCase ):
"""s... | 692 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ : Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase_ : Any = {
'microsoft/swinv2-tiny-patch4-window8-256': (
'https://huggingf... | 692 |
'''simple docstring'''
import math
import time
from transformers import Trainer, is_torch_tpu_available
from transformers.trainer_utils import PredictionOutput, speed_metrics
if is_torch_tpu_available(check_device=False):
import torch_xla.core.xla_model as xm
import torch_xla.debug.metrics as ... | 692 | 1 |
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