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, OnnxSeqaSeqConfigWithPast
from ...utils import logging
if TYPE_CHECKING:
from ...fea... | 78 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...sch... | 78 | 1 |
"""simple docstring"""
import logging
import os
import sys
import warnings
from dataclasses import dataclass, field
from random import randint
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import DatasetDict, load_dataset
import transformers
fr... | 78 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 | 1 |
"""simple docstring"""
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
snake_case_ = """\
"""
snake_case_ = """
Perplexity (PPL) is one... | 78 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 | 1 |
"""simple docstring"""
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class A_ :
"""simple docstring"""
__UpperCamelCase = 42 # [batch_size x 3]
__UpperCamelCase = 42 # [ba... | 78 |
"""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 ... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
import string
from itertools import cycle, product
from pathlib import Path
snake_case_ = (
string.ascii_letters + string.digits + string.punctuation + string.whitespace
)
snake_case_ = [ord(letter) for let... | 78 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Union[str, Any] ) -> str:
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
from math import factorial, pi
def _lowerCAmelCase ( lowercase_ , lowercase_ = 30 ):
if not isinstance(lowercase_ , (int, float) ):
raise ValueError('maclaurin_sin() requires either an int or float for theta' )
if not isinsta... | 78 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, S... | 78 | 1 |
"""simple docstring"""
from typing import Optional, Tuple
import jax
import jax.numpy as jnp
from flax import linen as nn
from flax.core.frozen_dict import FrozenDict
from transformers import CLIPConfig, FlaxPreTrainedModel
from transformers.models.clip.modeling_flax_clip import FlaxCLIPVisionModul... | 78 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ = " " ):
UpperCAmelCase = []
UpperCAmelCase = 0
for index, char in enumerate(lowercase_ ):
if char == separator:
split_words.append(string[l... | 78 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
snake_case_ = loggi... | 78 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
... | 78 | 1 |
"""simple docstring"""
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import a... | 78 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
snake_case_ = """1"""
snake_case_ = """0"""
snake_case_ = """1"""
snake_case_ = ort.SessionOptions()
snake_case_ = ort.GraphOptimiz... | 78 | 1 |
"""simple docstring"""
import argparse
import json
import os
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_schedule_with_wa... | 78 |
"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils ... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( ):
UpperCAmelCase = []
UpperCAmelCase = 1
while len(lowercase_ ) < 1e6:
constant.append(str(lowercase_ ) )
i += 1
UpperCAmelCase = ''.join(lowerc... | 78 |
"""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
snake_case_ = logging.get_logger(__name__)
snake... | 78 | 1 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[Any] , lowercase_ :int ) -> None:
UpperCAmelCase = size
UpperCAmelCase = [0] * size
UpperCAmelCase ... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5On... | 78 | 1 |
"""simple docstring"""
import unittest
from .lib import (
Matrix,
Vector,
axpy,
square_zero_matrix,
unit_basis_vector,
zero_vector,
)
class A_ ( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase__ ... | 78 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resi... | 78 | 1 |
"""simple docstring"""
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packag... | 78 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = list(range(len(lowercase_ ) ) )
UpperCAmelCase = [v / w for v, w in zip(lowercase_ , lowercase_ ... | 78 | 1 |
"""simple docstring"""
import importlib.metadata
from typing import Union
from packaging.version import Version, parse
from .constants import STR_OPERATION_TO_FUNC
snake_case_ = parse(importlib.metadata.version("""torch"""))
def _lowerCAmelCase ( lowercase_ , lowercase... | 78 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_av... | 78 | 1 |
"""simple docstring"""
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_x... | 78 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
... | 78 | 1 |
"""simple docstring"""
from typing import List
import jiwer
import jiwer.transforms as tr
from packaging import version
import datasets
from datasets.config import PY_VERSION
if PY_VERSION < version.parse("""3.8"""):
import importlib_metadata
else:
import importlib.metadata as impo... | 78 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCAmelCase ( lowercase_ = "isbn/0140328726" ):
UpperCAmelCase = olid.strip().strip('/' ) # Remove leading/trailing whitespace & ... | 78 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
snake_case_ = {"""configuration_reformer""": ["""REFORMER_PR... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowercase_ :int , lowercase_ :Optional[int]=None , lowercase_ :List[str]=None ) -> str:
UpperCAmelCase = data
UpperCAm... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
import json
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
snake_case_ = {"""UserAgent""": UserAgent().random}
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase ... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[Any] , lowercase_ :int ) -> None:
UpperCAmelCase = size
UpperCAmelCase = [0] * size
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
import unittest
from transformers import SqueezeBertConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_commo... | 78 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowercase_ :int , lowercase_ :MutableSequence[float] ) -> None... | 78 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def _lowerCAmelCase ( lowercase_ = 8 ):
UpperCAmelCase = ascii_letters + digits + punctuation
return "".join(s... | 78 | 1 |
"""simple docstring"""
from math import ceil
def _lowerCAmelCase ( lowercase_ = 1001 ):
UpperCAmelCase = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
UpperCAmelCase = 2 * i + 1
UpperCAmelCase = 2 *... | 78 |
"""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 impor... | 78 | 1 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class A_ ( metaclass=SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
__UpperCamelCase = ["""torch"""]
def __init__( self :Any , *lowercase_ :List[... | 78 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...sch... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
if number > 0:
raise ValueError('input must be a negative integer' )
UpperCAmelCase = len(bin(lowercase_ )[3:] )
UpperCAmelCase = bin(abs(lowercase_ ) - (1 <... | 78 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 | 1 |
"""simple docstring"""
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ... | 78 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 | 1 |
"""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 |
"""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 ... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
UpperCAmelCase = [0 for i in range(r + 1 )]
# nc0 = 1
UpperCAmelCase = 1
for i in range(1 , n + 1 ):
# to compute current row from previous row.
... | 78 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Union[str, Any] ) -> str:
UpperCAmelCase ... | 78 | 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
... | 78 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, S... | 78 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case_ = {
"""configuration_squeezebert""": [
"""SQUEEZEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 78 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ = " " ):
UpperCAmelCase = []
UpperCAmelCase = 0
for index, char in enumerate(lowercase_ ):
if char == separator:
split_words.append(string[l... | 78 | 1 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
snake_case_ = logging.get_logger(__name__)
class A_ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring... | 78 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
... | 78 | 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
... | 78 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
snake_case_ = """1"""
snake_case_ = """0"""
snake_case_ = """1"""
snake_case_ = ort.SessionOptions()
snake_case_ = ort.GraphOptimiz... | 78 | 1 |
"""simple docstring"""
from typing import Callable, List, Optional, Tuple, Union
import torch
from transformers import CLIPTextModel, CLIPTokenizer
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin, TransformeraDModel, VQModel
from ...schedulers im... | 78 |
"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils ... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ = 0 , lowercase_ = 0 ):
UpperCAmelCase = right or len(lowercase_ ) - 1
if left > right:
return -1
elif list_data[left] == key:
return left
... | 78 |
"""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
snake_case_ = logging.get_logger(__name__)
snake... | 78 | 1 |
"""simple docstring"""
from PIL import Image
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
UpperCAmelCase = (259 * (level + 255)) / (255 * (259 - level))
def contrast(lowercase_ ) -> int:
return int(128 + factor * (c - 128) )
r... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5On... | 78 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
snake_case_ = {
"""configuration_data2vec_audio""": ["""DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP""", """Data2VecAudioC... | 78 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resi... | 78 | 1 |
"""simple docstring"""
from collections import deque
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase = len(lowercase_ )
UpperCAmelCase = deque()
UpperCAmelCase = [False for _ in range(lowercase_ )]
UpperCAmelCase ... | 78 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = list(range(len(lowercase_ ) ) )
UpperCAmelCase = [v / w for v, w in zip(lowercase_ , lowercase_ ... | 78 | 1 |
"""simple docstring"""
import os
from typing import List, Optional, Union
from ...tokenization_utils import PreTrainedTokenizer
from ...tokenization_utils_base import AddedToken
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {... | 78 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_av... | 78 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
snake_case_ = {
"""configuration_bloom""": ["""BLOOM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """BloomConfig""", """Bloom... | 78 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
... | 78 | 1 |
"""simple docstring"""
# A Bipartite Graph is a graph whose vertices can be divided into two independent sets,
# U and V such that every edge (u, v) either connects a vertex from U to V or a vertex
# from V to U. In other words, for every edge (u, v), either u belongs to U and v to V,
# or u belongs to ... | 78 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCAmelCase ( lowercase_ = "isbn/0140328726" ):
UpperCAmelCase = olid.strip().strip('/' ) # Remove leading/trailing whitespace & ... | 78 | 1 |
"""simple docstring"""
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module,... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowercase_ :int , lowercase_ :Optional[int]=None , lowercase_ :List[str]=None ) -> str:
UpperCAmelCase = data
UpperCAm... | 78 | 1 |
"""simple docstring"""
import logging
import os
from typing import List, Tuple
import numpy as np
import psutil
import torch
import torch.distributed as dist
from transformers import RagRetriever
snake_case_ = logging.getLogger(__name__)
class A_ ( S... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[Any] , lowercase_ :int ) -> None:
UpperCAmelCase = size
UpperCAmelCase = [0] * size
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
snake_case_ = HUGGINGFACE_HUB_CACHE
snake_case_ = """config.json"""
snake_case_ = """diffusion_pytorch_model.bin"""
snake_case_ = ... | 78 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('You cannot supply more or less than 2 values' )
elif e... | 78 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def _lowerCAmelCase ( lowercase_ = 8 ):
UpperCAmelCase = ascii_letters + digits + punctuation
return "".join(s... | 78 | 1 |
"""simple docstring"""
import unittest
from transformers import RoFormerTokenizer, RoFormerTokenizerFast
from transformers.testing_utils import require_rjieba, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@require_rjieba
@require_tokenizers
class ... | 78 |
"""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 impor... | 78 | 1 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import tensorflow as tf
from .utils import logging
snake_case_ = logging.get_logger(__name__)
def _lowerCAmelCase ( lowercase_ ):
if isinstance(lowercase_ , np.ndarray )... | 78 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...sch... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase = []
UpperCAmelCase = []
UpperCAmelCase = {
'^': 3,
'*': 2,
'/': 2,
'%': 2,
'+': 1,
'-': 1,
... | 78 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 | 1 |
"""simple docstring"""
import unittest
from transformers import MODEL_FOR_VISUAL_QUESTION_ANSWERING_MAPPING, is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
r... | 78 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 | 1 |
"""simple docstring"""
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import ... | 78 |
"""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 ... | 78 | 1 |
"""simple docstring"""
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
snake_case_ = re.compile(R"""^(?P<major>\d+)""" R"""\.(?P<minor>\d+)""" R"""\.(?P<patch>\d+)$""")
... | 78 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Union[str, Any] ) -> str:
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
... | 78 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, S... | 78 | 1 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :Tuple , lowercase_ :int ) -> Optional[int]:
UpperCAmelCase = n
UpperCAmelCase = [None] * self.n
UpperCAmelCase ... | 78 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ = " " ):
UpperCAmelCase = []
UpperCAmelCase = 0
for index, char in enumerate(lowercase_ ):
if char == separator:
split_words.append(string[l... | 78 | 1 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def _lowerCAmelCase ( lowercase_ = 8 ):
UpperCAmelCase = ascii_letters + digits + punctuation
return "".join(s... | 78 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
... | 78 | 1 |
"""simple docstring"""
import math
class A_ :
"""simple docstring"""
def UpperCAmelCase__ ( self :str , lowercase_ :list[list[float]] , lowercase_ :list[int] ) -> int:
UpperCAmelCase = 0.0
U... | 78 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
snake_case_ = """1"""
snake_case_ = """0"""
snake_case_ = """1"""
snake_case_ = ort.SessionOptions()
snake_case_ = ort.GraphOptimiz... | 78 | 1 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
i... | 78 |
"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils ... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
return not any(
neighbour == 1 and colored_vertices[i] == color
for i, neighbour in enumerate(lowercase_ ) )
def _lowerCAmelCase ( lowercase_ , lowercase_ ... | 78 |
"""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
snake_case_ = logging.get_logger(__name__)
snake... | 78 | 1 |
"""simple docstring"""
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
snake_case_ = """"""
snake_case_ = """"""
snake_case_ = """"""
snake_case_ = 1 # (0 is vertical, 1 is horizontal)
def _lowe... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5On... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ = 1000 ):
UpperCAmelCase , UpperCAmelCase = 1, 1
UpperCAmelCase = 2
while True:
UpperCAmelCase = 0
UpperCAmelCase = fa + fa
... | 78 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resi... | 78 | 1 |
"""simple docstring"""
import argparse
import json
import subprocess
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
UpperCAmelCase = []
UpperCAmelCase = (
F"""curl -H \"Accept: application/vnd.github+json\" -H \"Authorization: Bearer {... | 78 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = list(range(len(lowercase_ ) ) )
UpperCAmelCase = [v / w for v, w in zip(lowercase_ , lowercase_ ... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
if len(lowercase_ ) <= 1:
return [tuple(lowercase_ )]
UpperCAmelCase = []
def generate(lowercase_ , lowercase_ ):
if k == 1:
res.append... | 78 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_av... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import BlenderbotConfig, BlenderbotTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_config... | 78 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
... | 78 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""RWKV/rwkv-4-169m-pile""": """https://huggingface.co/RWKV/rwkv-4-169m-pile/resolve/main/config.json"... | 78 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCAmelCase ( lowercase_ = "isbn/0140328726" ):
UpperCAmelCase = olid.strip().strip('/' ) # Remove leading/trailing whitespace & ... | 78 | 1 |
"""simple docstring"""
from decimal import Decimal, getcontext
from math import ceil, factorial
def _lowerCAmelCase ( lowercase_ ):
if not isinstance(lowercase_ , lowercase_ ):
raise TypeError('Undefined for non-integers' )
elif precision < 1:
... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowercase_ :int , lowercase_ :Optional[int]=None , lowercase_ :List[str]=None ) -> str:
UpperCAmelCase = data
UpperCAm... | 78 | 1 |
"""simple docstring"""
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[Any] , lowercase_ :int ) -> None:
UpperCAmelCase = size
UpperCAmelCase = [0] * size
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
... | 78 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 78 | 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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils ... | 78 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def _lowerCAmelCase ( lowercase_ = 8 ):
UpperCAmelCase = ascii_letters + digits + punctuation
return "".join(s... | 78 | 1 |
"""simple docstring"""
import gc
import unittest
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DDPMScheduler,
PriorTransformer,
StableUnCLIPPipeline,
... | 78 |
"""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 impor... | 78 | 1 |
"""simple docstring"""
import functools
import logging
import os
import sys
import threading
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import ... | 78 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...sch... | 78 | 1 |
"""simple docstring"""
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBe... | 78 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ , ):
if (stress, tangential_force, area).count(0 ) != 1:
raise ValueError('You cannot supply more or less than 2 values' )
elif stress < 0:... | 78 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
UpperCAmelCase = 0
UpperCAmelCase = len(lowercase_ ) - 1
while i < j:
if nums[i] + nums[j] == target:
... | 78 |
"""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 ... | 78 | 1 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import Callable, Dict, List, Tuple
import timm
import torch
import torch.nn as nn
from classy_vision.models.regnet import RegNet, RegNetP... | 78 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Union[str, Any] ) -> str:
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, S... | 78 | 1 |
"""simple docstring"""
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case_ = lo... | 78 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ = " " ):
UpperCAmelCase = []
UpperCAmelCase = 0
for index, char in enumerate(lowercase_ ):
if char == separator:
split_words.append(string[l... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
from fractions import Fraction
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
return (
num != den and num % 10 == den // 10 and (num // 10) / (den % 10) == num / den
)
def _lowerCAmelCase ( l... | 78 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
... | 78 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import... | 78 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
snake_case_ = """1"""
snake_case_ = """0"""
snake_case_ = """1"""
snake_case_ = ort.SessionOptions()
snake_case_ = ort.GraphOptimiz... | 78 | 1 |
"""simple docstring"""
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
snake_case_ = [
"""Prosecutor: \"No videos were used in the crash investigation\" German paper... | 78 |
"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils ... | 78 | 1 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
... | 78 |
"""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
snake_case_ = logging.get_logger(__name__)
snake... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import DistilBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterM... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5On... | 78 | 1 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 78 |
"""simple docstring"""
import argparse
import os
import re
import numpy as np
import PIL
import torch
from timm import create_model
from torch.optim.lr_scheduler import OneCycleLR
from torch.utils.data import DataLoader, Dataset
from torchvision.transforms import Compose, RandomResizedCrop, Resi... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ = " " ):
UpperCAmelCase = []
UpperCAmelCase = 0
for index, char in enumerate(lowercase_ ):
if char == separator:
split_words.append(string[l... | 78 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = list(range(len(lowercase_ ) ) )
UpperCAmelCase = [v / w for v, w in zip(lowercase_ , lowercase_ ... | 78 | 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 impor... | 78 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_av... | 78 | 1 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCAmelCase ( lowercase_ = "isbn/0140328726" ):
UpperCAmelCase = olid.strip().strip('/' ) # Remove leading/trailing whitespace & ... | 78 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
... | 78 | 1 |
"""simple docstring"""
snake_case_ = {
0: """0""",
1: """1""",
2: """2""",
3: """3""",
4: """4""",
5: """5""",
6: """6""",
7: """7""",
8: """8""",
9: """9""",
10: """a""",
11: """b""",
12: """c""",
13: """d""",
14: """... | 78 |
"""simple docstring"""
from json import JSONDecodeError # Workaround for requests.exceptions.JSONDecodeError
import requests
def _lowerCAmelCase ( lowercase_ = "isbn/0140328726" ):
UpperCAmelCase = olid.strip().strip('/' ) # Remove leading/trailing whitespace & ... | 78 | 1 |
"""simple docstring"""
from collections import OrderedDict
from typing import TYPE_CHECKING, Any, Mapping, Optional
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
if TYPE_CHECKING:
from ... import FeatureExtractionMixin, Tenso... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[str] , lowercase_ :int , lowercase_ :Optional[int]=None , lowercase_ :List[str]=None ) -> str:
UpperCAmelCase = data
UpperCAm... | 78 | 1 |
"""simple docstring"""
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers imp... | 78 |
"""simple docstring"""
class A_ :
"""simple docstring"""
def __init__( self :List[Any] , lowercase_ :int ) -> None:
UpperCAmelCase = size
UpperCAmelCase = [0] * size
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
from __future__ import annotations
def _lowerCAmelCase ( lowercase_ , lowercase_ ):
UpperCAmelCase = []
create_all_state(1 , lowercase_ , lowercase_ , [] , lowercase_ )
return result
def _lowerCAmelCase ( lowercase... | 78 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.p... | 78 | 1 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ ):
UpperCAmelCase = current_set.copy()
for row_index, row in enumerate(lowercase_ ):
UpperCAmelCase = row[0]
for column_index, column in enumerate(lowercase_ ):
... | 78 |
"""simple docstring"""
import secrets
from random import shuffle
from string import ascii_letters, ascii_lowercase, ascii_uppercase, digits, punctuation
def _lowerCAmelCase ( lowercase_ = 8 ):
UpperCAmelCase = ascii_letters + digits + punctuation
return "".join(s... | 78 | 1 |
"""simple docstring"""
import argparse
import struct
import unittest
class A_ :
"""simple docstring"""
def __init__( self :int , lowercase_ :bytes ) -> None:
UpperCAmelCase = data
# Initialize h... | 78 |
"""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 impor... | 78 | 1 |
"""simple docstring"""
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_squeezebert import SqueezeBertTokenizer
snake_case_ = log... | 78 |
"""simple docstring"""
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...sch... | 78 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
... | 78 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 | 1 |
"""simple docstring"""
import colorsys
from PIL import Image # type: ignore
def _lowerCAmelCase ( lowercase_ , lowercase_ , lowercase_ ):
UpperCAmelCase = x
UpperCAmelCase = y
for step in range(lowercase_ ): # noqa: B007
... | 78 |
"""simple docstring"""
import requests
snake_case_ = """""" # <-- Put your OpenWeatherMap appid here!
snake_case_ = """https://api.openweathermap.org/data/2.5/"""
def _lowerCAmelCase ( lowercase_ = "Chicago" , lowercase_ = APPID ):
return requests.ge... | 78 | 1 |
"""simple docstring"""
import inspect
import unittest
import numpy as np
from transformers import ViTConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTester... | 78 |
"""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 ... | 78 | 1 |
"""simple docstring"""
from . import (
albert,
align,
altclip,
audio_spectrogram_transformer,
auto,
autoformer,
bark,
bart,
barthez,
bartpho,
beit,
bert,
bert_generation,
bert_japanese,
bertweet,
big_bird,
bigbird_pegasus,... | 78 |
"""simple docstring"""
from collections import deque
from math import floor
from random import random
from time import time
class A_ :
"""simple docstring"""
def __init__( self :Union[str, Any] ) -> str:
UpperCAmelCase ... | 78 | 1 |
"""simple docstring"""
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
snake_case_ ... | 78 |
"""simple docstring"""
from .glue import GlueDataset, GlueDataTrainingArguments
from .language_modeling import (
LineByLineTextDataset,
LineByLineWithRefDataset,
LineByLineWithSOPTextDataset,
TextDataset,
TextDatasetForNextSentencePrediction,
)
from .squad import SquadDataset, S... | 78 | 1 |
"""simple docstring"""
import unittest
from transformers import DebertaConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common im... | 78 |
"""simple docstring"""
def _lowerCAmelCase ( lowercase_ , lowercase_ = " " ):
UpperCAmelCase = []
UpperCAmelCase = 0
for index, char in enumerate(lowercase_ ):
if char == separator:
split_words.append(string[l... | 78 | 1 |
"""simple docstring"""
import subprocess
import sys
from transformers import BertConfig, BertModel, BertTokenizer, pipeline
from transformers.testing_utils import TestCasePlus, require_torch
class A_ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
... | 78 |
"""simple docstring"""
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
... | 78 | 1 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class A_ ( SCREAMING_SNAKE_CASE_ ):
"""simple docstring"""
@staticmethod
@abstractmethod
def UpperCAmelCase__ ( lowercase_ :Ar... | 78 |
"""simple docstring"""
import os
import time
import numpy as np
import onnxruntime as ort
snake_case_ = """1"""
snake_case_ = """0"""
snake_case_ = """1"""
snake_case_ = ort.SessionOptions()
snake_case_ = ort.GraphOptimiz... | 78 | 1 |
"""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
snake_case_ = logging.get_logger(__name__)
snake... | 78 |
"""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 convert_to_rgb, normalize, rescale, resize, to_channel_dimension_format
from ...image_utils ... | 78 | 1 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
snake_case_ = logging.get_logger(__name__)
snake_case_ = {
"""transfo-xl-wt103""": """https://huggingface.co/transfo-xl-wt103/resolve/main/config.json""",
}
... | 78 |
"""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
snake_case_ = logging.get_logger(__name__)
snake... | 78 | 1 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
snake_case_ = """▁"""
snake_case_ = {"... | 78 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
snake_case_ = {
"""configuration_longt5""": ["""LONGT5_PRETRAINED_CONFIG_ARCHIVE_MAP""", """LongT5Config""", """LongT5On... | 78 | 1 |
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