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 |
|---|---|---|---|---|
import os
import sys
import tempfile
import torch
from .state import AcceleratorState
from .utils import PrecisionType, PrepareForLaunch, is_mps_available, patch_environment
def UpperCamelCase ( snake_case__ , snake_case__=() , snake_case__=None , snake_case__="no" , snake_case__=... | 659 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 659 | 1 |
from collections import deque
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : Tuple = len(snake_case__)
lowerCAmelCase_ : Any = deque()
lowerCAmelCase_ : int = [False for _ in range(snake_case__)]
lowerCAmelCase_ : int = [-1 ... | 659 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_lowerc... | 659 | 1 |
import datasets
from .evaluate import evaluate
_lowercase = '''\
@article{hendrycks2021cuad,
title={CUAD: An Expert-Annotated NLP Dataset for Legal Contract Review},
author={Dan Hendrycks and Collin Burns and Anya Chen and Spencer Ball},
journal={arXiv preprint arXiv:2103.06268},
y... | 659 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 1 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import Decoder, DecoderOutput, Encoder... | 659 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCamelCase ( ):
lowerCAmelCase_ : Dict = HfArgumentParser(snake_case__)
lowerCAmelCase_ : Dict = parser.parse_args_into_dataclasses()[0]
lowerCAmelCase_ : Lis... | 659 | 1 |
import faiss # noqa: F401 # Here to have a nice missing dependency error message early on
import numpy # noqa: F401 # Here to have a nice missing dependency error message early on
import requests # noqa: F401 # Here to have a nice missing dependency error message early on
import sklearn # noqa: F401 # Here to ha... | 659 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
''' ... | 659 | 1 |
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
_lowercase = '''__DUMMY_TRANSFORMERS_USER__'''
_lowercase = '''Dummy User'''
_lowercase = '''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'''
... | 659 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 659 | 1 |
from numpy import exp, pi, sqrt
def UpperCamelCase ( snake_case__ , snake_case__ = 0.0 , snake_case__ = 1.0):
return 1 / sqrt(2 * pi * sigma**2) * exp(-((x - mu) ** 2) / (2 * sigma**2))
if __name__ == "__main__":
import doctest
doctest.testmod()
| 659 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
),
}
class __... | 659 | 1 |
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import Accelerator
from accelerate.te... | 659 |
from math import factorial
def UpperCamelCase ( snake_case__ , snake_case__):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter pos... | 659 | 1 |
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
_lowercase = {
'''E''': 12.70,
'''T''': 9.06,
'''A''': 8.17,
'''O''': 7.51,
'''I''': 6.97,
'''N''': 6.75,
'''S''': 6.33,
'''H''': 6.09,
'''R''': 5.99,
'''D''': 4.25,
'''L''': 4.03,... | 659 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ):
lowerCAmelCase_ : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=snake_case__ , default="biencoder-nq-dev.json" , help="Path... | 659 | 1 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
),
}
class __... | 659 |
from collections.abc import Sequence
def UpperCamelCase ( snake_case__ = None):
if nums is None or not nums:
raise ValueError("Input sequence should not be empty")
lowerCAmelCase_ : Dict = nums[0]
for i in range(1 , len(snake_case__)):
lowerCAme... | 659 | 1 |
import warnings
from pathlib import Path
from typing import List, Tuple, Union
import fire
from torch import nn
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer, PreTrainedModel
from transformers.utils import logging
_lowercase = logging.get_logger(__name__)
def UpperCamelCase ( sn... | 659 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_lowercase = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_lowercase = _LazyModule(__name__, globals()['''__file__'''... | 659 | 1 |
_lowercase = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
_lowercase = [{'''type''': '''code... | 659 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = '''src/diffuse... | 659 | 1 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = '''src/diffuse... | 659 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'''
... | 659 | 1 |
import numpy
# List of input, output pairs
_lowercase = (
((5, 2, 3), 15),
((6, 5, 9), 25),
((11, 12, 13), 41),
((1, 1, 1), 8),
((11, 12, 13), 41),
)
_lowercase = (((515, 22, 13), 555), ((61, 35, 49), 150))
_lowercase = [2, 4, 1, 5]
_lowercase = len(train_data)
_l... | 659 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Paddi... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
'''configuration_layoutlmv2''': ['''LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''LayoutLMv2Conf... | 659 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowercase = 10
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
... | 659 | 1 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import require_tok... | 659 |
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
_lowercase = logging.get_logger(__name__)
_lowercase = {
... | 659 | 1 |
from argparse import ArgumentParser
from .env import EnvironmentCommand
def UpperCamelCase ( ):
lowerCAmelCase_ : Dict = ArgumentParser("Diffusers CLI tool" , usage="diffusers-cli <command> [<args>]")
lowerCAmelCase_ : Union[str, Any] = parser.add_subparsers(hel... | 659 |
from collections.abc import Generator
from math import sin
def UpperCamelCase ( snake_case__):
if len(snake_case__) != 32:
raise ValueError("Input must be of length 32")
lowerCAmelCase_ : Tuple = b""
for i in [3, 2, 1, 0]:
little_endian += string_aa[8... | 659 | 1 |
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
global f # a global dp table for knapsack
if f[i][j] < 0:
if j < wt[i - 1]:
lowerCAmelCase_ : Dict = mf_knapsack(i - 1 , snake_case__ , snake... | 659 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Trai... | 659 | 1 |
import logging
import os
from logging import (
CRITICAL, # NOQA
DEBUG, # NOQA
ERROR, # NOQA
FATAL, # NOQA
INFO, # NOQA
NOTSET, # NOQA
WARN, # NOQA
WARNING, # NOQA
)
from typing import Optional
from tqdm import auto as tqdm_lib
_lowercase = {
'''debug''': logging... | 659 |
from __future__ import annotations
from collections.abc import Callable
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = 1_00 , ):
lowerCAmelCase_ : Any = x_start
lowerCAmelCase_ : Optional[Any] = fnc(snake_case_... | 659 | 1 |
from __future__ import annotations
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__):
lowerCAmelCase_ : Optional[int] = list(range(len(snake_case__)))
lowerCAmelCase_ : Dict = [v / w for v, w in zip(snake_case__ , snake_case__)]
i... | 659 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import nightly, slow, t... | 659 | 1 |
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = len(snake_case__)
while cur > 1:
# Find the maximum number in arr
lowerCAmelCase_ : List[str] = arr.index(max(arr[0:cur]))
# Reverse from 0 to mi
lowerCAmel... | 659 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
'''iou_prediction_head.lay... | 659 | 1 |
import warnings
from diffusers import StableDiffusionImgaImgPipeline # noqa F401
warnings.warn(
'''The `image_to_image.py` script is outdated. Please use directly `from diffusers import'''
''' StableDiffusionImg2ImgPipeline` instead.'''
)
| 659 |
class __snake_case :
"""simple docstring"""
def __init__( self : Union[str, Any] ,lowerCAmelCase__ : str = "" ,lowerCAmelCase__ : bool = False ) -> None:
'''simple docstring'''
lowerCAmelCase_ : dict[str, RadixNode] = {... | 659 | 1 |
import unittest
from transformers import PegasusConfig, PegasusTokenizer, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor
if is_flax_available():
impo... | 659 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 659 | 1 |
from functools import reduce
_lowercase = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557'''
'''6689664895044... | 659 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_lowerc... | 659 | 1 |
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__):
# Construct model
... | 659 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 1 |
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case__ )
class __snake_case ( snake_case__ ):
"""simple docstring"""
UpperCamelCase_ = field(default='language-modelin... | 659 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCamelCase ( ):
lowerCAmelCase_ : Dict = HfArgumentParser(snake_case__)
lowerCAmelCase_ : Dict = parser.parse_args_into_dataclasses()[0]
lowerCAmelCase_ : Lis... | 659 | 1 |
from string import ascii_lowercase, ascii_uppercase
def UpperCamelCase ( snake_case__):
if not sentence:
return ""
lowerCAmelCase_ : int = dict(zip(snake_case__ , snake_case__))
return lower_to_upper.get(sentence[0] , sentence[0]) + sentence[1:]
if _... | 659 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
''' ... | 659 | 1 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import Token... | 659 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 659 | 1 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
_lowercase = datasets.load_iris()
_lowercase = np.array(data['''data'''])
_lowercase = np.array(data['''target'''])
_lowercase = data['''target_names... | 659 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
),
}
class __... | 659 | 1 |
import warnings
from ...utils import logging
from .image_processing_chinese_clip import ChineseCLIPImageProcessor
_lowercase = logging.get_logger(__name__)
class __snake_case ( snake_case__ ):
"""simple docstring"""
def __init__( self : Optional[Any] ,*lowerCAmelCase__ ... | 659 |
from math import factorial
def UpperCamelCase ( snake_case__ , snake_case__):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter pos... | 659 | 1 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.bar... | 659 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ):
lowerCAmelCase_ : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=snake_case__ , default="biencoder-nq-dev.json" , help="Path... | 659 | 1 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 659 |
from collections.abc import Sequence
def UpperCamelCase ( snake_case__ = None):
if nums is None or not nums:
raise ValueError("Input sequence should not be empty")
lowerCAmelCase_ : Dict = nums[0]
for i in range(1 , len(snake_case__)):
lowerCAme... | 659 | 1 |
import json
import multiprocessing
import os
import re
from collections import defaultdict
import torch
from accelerate import Accelerator
from accelerate.utils import set_seed
from arguments import HumanEvalArguments
from datasets import load_dataset, load_metric
from torch.utils.data import IterableDataset
from t... | 659 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_lowercase = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_lowercase = _LazyModule(__name__, globals()['''__file__'''... | 659 | 1 |
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : Dict = int(snake_case__)
if n_element < 1:
lowerCAmelCase_ : Tuple = ValueError("a should be a positive number")
raise my_error
lowerCAmelCase_ : str = [1]
lowerCAmel... | 659 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = '''src/diffuse... | 659 | 1 |
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
import jax.numpy as jnp
from fla... | 659 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'''
... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_flax_available, is_torch_available
_lowercase = {
'''configuration_gpt_neo''': ['''GPT_NEO_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''GPTNeoConfig''', '''GPTNeoOnnxConfig'''],
}
try:
if not is_torch... | 659 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Paddi... | 659 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-santacoder/resolve/main/config.json''',
}
class __snake_case ( snake_c... | 659 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowercase = 10
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
... | 659 | 1 |
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class __snake_case ( snake_case__ ):... | 659 |
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
_lowercase = logging.get_logger(__name__)
_lowercase = {
... | 659 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''uclanlp/visualbert-vqa''': '''https://huggingface.co/uclanlp/visualbert-vqa/resolve/main/config.json''',
'''uclanlp/visualbert-vqa-pre''': '''https:/... | 659 |
from collections.abc import Generator
from math import sin
def UpperCamelCase ( snake_case__):
if len(snake_case__) != 32:
raise ValueError("Input must be of length 32")
lowerCAmelCase_ : Tuple = b""
for i in [3, 2, 1, 0]:
little_endian += string_aa[8... | 659 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder import ... | 659 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Trai... | 659 | 1 |
import numpy as np
import qiskit
def UpperCamelCase ( snake_case__ = 8 , snake_case__ = None):
lowerCAmelCase_ : List[Any] = np.random.default_rng(seed=snake_case__)
# Roughly 25% of the qubits will contribute to the key.
# So we take more than we need.
lowerCAme... | 659 |
from __future__ import annotations
from collections.abc import Callable
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = 1_00 , ):
lowerCAmelCase_ : Any = x_start
lowerCAmelCase_ : Optional[Any] = fnc(snake_case_... | 659 | 1 |
from typing import Dict, List, Optional, Tuple, Union
import torch
from ...models import AutoencoderKL, TransformeraDModel
from ...schedulers import KarrasDiffusionSchedulers
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __snake_case ( snake_case__ ):... | 659 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import nightly, slow, t... | 659 | 1 |
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=snake_case__ ):
"""simple docstring"""
UpperCamelCase_ = ['keras_nlp']
def __init__( self : List[Any] ,*lowerCAmelCase__ : List[Any] ,**lowerCAmelCase__ : Dict ) ... | 659 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
'''iou_prediction_head.lay... | 659 | 1 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_lowercase = '''scheduler_config.json'''
class __snake_case ( snake_case__ ):
"""simple docstring"""
UpperCamelCas... | 659 |
class __snake_case :
"""simple docstring"""
def __init__( self : Union[str, Any] ,lowerCAmelCase__ : str = "" ,lowerCAmelCase__ : bool = False ) -> None:
'''simple docstring'''
lowerCAmelCase_ : dict[str, RadixNode] = {... | 659 | 1 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__):
lowerCAmelCase_ : Union[str, Any] = OmegaConf.load(snake_case__)
lowerCAmelCase_ : ... | 659 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 659 | 1 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 659 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_lowerc... | 659 | 1 |
from collections.abc import Iterable
from typing import Generic, TypeVar
_lowercase = TypeVar('''_T''')
class __snake_case ( Generic[_T] ):
"""simple docstring"""
def __init__( self : str ,lowerCAmelCase__ : Iterable[_T] | None = None ) -> None:
... | 659 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 1 |
import json
import os
import re
import unittest
from transformers import CodeGenTokenizer, CodeGenTokenizerFast
from transformers.models.codegen.tokenization_codegen import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin... | 659 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCamelCase ( ):
lowerCAmelCase_ : Dict = HfArgumentParser(snake_case__)
lowerCAmelCase_ : Dict = parser.parse_args_into_dataclasses()[0]
lowerCAmelCase_ : Lis... | 659 | 1 |
import os
import warnings
from typing import List, Optional
from ...tokenization_utils_base import BatchEncoding
from ...utils import logging
from .configuration_rag import RagConfig
_lowercase = logging.get_logger(__name__)
class __snake_case :
"""simple docstring"""
def __init__( ... | 659 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
''' ... | 659 | 1 |
import argparse
import os
import re
_lowercase = '''src/diffusers'''
# Pattern that looks at the indentation in a line.
_lowercase = re.compile(r'''^(\s*)\S''')
# Pattern that matches `"key":" and puts `key` in group 0.
_lowercase = re.compile(r'''^\s*"([^"]+)":''')
# Pattern that matches ... | 659 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 659 | 1 |
from __future__ import annotations
import bisect
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ = 0 , snake_case__ = -1):
if hi < 0:
lowerCAmelCase_ : int = len(snake_case__)
while lo < hi:
lowerCAmelCase_ : Union[str... | 659 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
),
}
class __... | 659 | 1 |
from __future__ import annotations
_lowercase = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__ , ):
lowerCAmelCase_ : Tuple ... | 659 |
from math import factorial
def UpperCamelCase ( snake_case__ , snake_case__):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter pos... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {
'''configuration_convbert''': ['''CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''ConvBertConfig''', '''... | 659 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ):
lowerCAmelCase_ : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=snake_case__ , default="biencoder-nq-dev.json" , help="Path... | 659 | 1 |
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 659 |
from collections.abc import Sequence
def UpperCamelCase ( snake_case__ = None):
if nums is None or not nums:
raise ValueError("Input sequence should not be empty")
lowerCAmelCase_ : Dict = nums[0]
for i in range(1 , len(snake_case__)):
lowerCAme... | 659 | 1 |
from math import pow, sqrt
def UpperCamelCase ( *snake_case__):
lowerCAmelCase_ : Any = len(snake_case__) > 0 and all(value > 0.0 for value in values)
return result
def UpperCamelCase ( snake_case__ , snake_case__):
return (
round(sqrt(molar_mass_a /... | 659 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_lowercase = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_lowercase = _LazyModule(__name__, globals()['''__file__'''... | 659 | 1 |
from __future__ import annotations
_lowercase = tuple[int, int, int]
_lowercase = tuple[str, str, str]
# used alphabet --------------------------
# from string.ascii_uppercase
_lowercase = '''ABCDEFGHIJKLMNOPQRSTUVWXYZ'''
# -------------------------- default selection --------------------... | 659 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = '''src/diffuse... | 659 | 1 |
_lowercase = {
'''Pillow''': '''Pillow''',
'''accelerate''': '''accelerate>=0.11.0''',
'''compel''': '''compel==0.1.8''',
'''black''': '''black~=23.1''',
'''datasets''': '''datasets''',
'''filelock''': '''filelock''',
'''flax''': '''flax>=0.4.1''',
'''hf-doc-builder''': '''hf-... | 659 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'''
... | 659 | 1 |
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 BatchEncoding, PreTrainedTokenizer
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercas... | 659 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Paddi... | 659 | 1 |
from __future__ import annotations
def UpperCamelCase ( snake_case__ , snake_case__):
lowerCAmelCase_ : Optional[Any] = get_failure_array(snake_case__)
# 2) Step through text searching for pattern
lowerCAmelCase_ , lowerCAmelCase_ : Union[str, Any] ... | 659 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowercase = 10
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
... | 659 | 1 |
from unittest.mock import patch
import pyspark
from datasets.packaged_modules.spark.spark import (
Spark,
SparkExamplesIterable,
_generate_iterable_examples,
)
from ..utils import (
require_dill_gt_0_3_2,
require_not_windows,
)
def UpperCamelCase ( snake_case__ , snake_case__):... | 659 |
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
_lowercase = logging.get_logger(__name__)
_lowercase = {
... | 659 | 1 |
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, randn_tensor
from .scheduling_utils import SchedulerMixin
@dataclass
# Copied from diffusers.sch... | 659 |
from collections.abc import Generator
from math import sin
def UpperCamelCase ( snake_case__):
if len(snake_case__) != 32:
raise ValueError("Input must be of length 32")
lowerCAmelCase_ : Tuple = b""
for i in [3, 2, 1, 0]:
little_endian += string_aa[8... | 659 | 1 |
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import ThreadedIterator
from tqdm impo... | 659 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Trai... | 659 | 1 |
import html
from ...feature_extraction_utils import BatchFeature, FeatureExtractionMixin
from ...utils import is_bsa_available, logging, requires_backends
if is_bsa_available():
import bsa
from bsa import BeautifulSoup
_lowercase = logging.get_logger(__name__)
class __snake_case ( snake_... | 659 |
from __future__ import annotations
from collections.abc import Callable
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = 1_00 , ):
lowerCAmelCase_ : Any = x_start
lowerCAmelCase_ : Optional[Any] = fnc(snake_case_... | 659 | 1 |
from __future__ import annotations
import math
_lowercase = '''2020.9.26'''
_lowercase = '''xcodz-dot, cclaus, dhruvmanila'''
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ , snake_case__):
if not all(isinstance(snake_case__ ... | 659 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import nightly, slow, t... | 659 | 1 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
'''iou_prediction_head.lay... | 659 | 1 |
def UpperCamelCase ( snake_case__ , snake_case__):
def get_matched_characters(snake_case__ , snake_case__) -> str:
lowerCAmelCase_ : Optional[Any] = []
lowerCAmelCase_ : Union[str, Any] = min(len(_stra) , len(_stra)) // 2
... | 659 |
class __snake_case :
"""simple docstring"""
def __init__( self : Union[str, Any] ,lowerCAmelCase__ : str = "" ,lowerCAmelCase__ : bool = False ) -> None:
'''simple docstring'''
lowerCAmelCase_ : dict[str, RadixNode] = {... | 659 | 1 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import (
DiffusionPipeline,
UnCLIPImag... | 659 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 659 | 1 |
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ , lowerCAmelCase_ : str = [], []
while len(snake_case__) > 1:
lowerCAmelCase_ , lowerCAmelCase_ : Dict = min(snake_case__), max(snake_case__)
start.append(snake_case__)
... | 659 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_lowerc... | 659 | 1 |
from ..utils import DummyObject, requires_backends
class __snake_case ( metaclass=snake_case__ ):
"""simple docstring"""
UpperCamelCase_ = ['transformers', 'torch', 'note_seq']
def __init__( self : Any ,*lowerCAmelCase__ : List[str] ,**lowerCAmelCase__ :... | 659 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 1 |
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
# Return True if there is node that has not iterated.
lowerCAmelCase_ : Union[str, Any] = [False] * len(snake_case__)
lowerCAmelCase_ : Any = []
queue.append(s... | 659 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCamelCase ( ):
lowerCAmelCase_ : Dict = HfArgumentParser(snake_case__)
lowerCAmelCase_ : Dict = parser.parse_args_into_dataclasses()[0]
lowerCAmelCase_ : Lis... | 659 | 1 |
import os
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = len(grid[0])
lowerCAmelCase_ : int = len(snake_case__)
lowerCAmelCase_ : Union[str, Any] = 0
lowerCAmelCase_ : List[Any] = 0
lowerCAmelCase_ : D... | 659 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
''' ... | 659 | 1 |
_lowercase = '''0.21.0'''
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader import skip_first_batches
from .launc... | 659 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 659 | 1 |
_lowercase = '''
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
'''
_lowercase = [{'''type''': '''code... | 659 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
),
}
class __... | 659 | 1 |
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 met
class __snake_case ( sn... | 659 |
from math import factorial
def UpperCamelCase ( snake_case__ , snake_case__):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter pos... | 659 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applic... | 659 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ):
lowerCAmelCase_ : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=snake_case__ , default="biencoder-nq-dev.json" , help="Path... | 659 | 1 |
def UpperCamelCase ( snake_case__): # noqa: E741
lowerCAmelCase_ : Dict = len(snake_case__)
lowerCAmelCase_ : Union[str, Any] = 0
lowerCAmelCase_ : List[str] = [0] * n
lowerCAmelCase_ : str = [False] * n
lowerCAmelCase_ : ... | 659 |
from collections.abc import Sequence
def UpperCamelCase ( snake_case__ = None):
if nums is None or not nums:
raise ValueError("Input sequence should not be empty")
lowerCAmelCase_ : Dict = nums[0]
for i in range(1 , len(snake_case__)):
lowerCAme... | 659 | 1 |
from typing import Any, Dict, List, Optional, Tuple, Union
import torch
from torch import nn
from torch.utils.data import DistributedSampler, RandomSampler
from transformers import PreTrainedModel, Trainer, logging
from transformers.integrations import is_fairscale_available
from transformers.models.fsmt.configura... | 659 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_lowercase = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_lowercase = _LazyModule(__name__, globals()['''__file__'''... | 659 | 1 |
import math
def UpperCamelCase ( snake_case__ , snake_case__ = 0 , snake_case__ = 0):
lowerCAmelCase_ : Any = end or len(snake_case__)
for i in range(snake_case__ , snake_case__):
lowerCAmelCase_ : Optional[int] = i
lowerCAmelC... | 659 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = '''src/diffuse... | 659 | 1 |
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 UpperCamelCase ( snake_case__):
low... | 659 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''microsoft/swinv2-tiny-patch4-window8-256''': (
'''https://huggingface.co/microsoft/swinv2-tiny-patch4-window8-256/resolve/main/config.json'''
... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase = {
'''configuration_blenderbot''': [
'''BLENDERBOT_PRETRAINED_CONFIG_ARCHI... | 659 |
from typing import List, Optional, Union
import numpy as np
from ....audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ....feature_extraction_sequence_utils import SequenceFeatureExtractor
from ....feature_extraction_utils import BatchFeature
from ....file_utils import Paddi... | 659 | 1 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
_lowercase = '''
Hugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenagers.[2] Aft... | 659 |
from __future__ import annotations
# This is the precision for this function which can be altered.
# It is recommended for users to keep this number greater than or equal to 10.
_lowercase = 10
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__):
... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
_lowercase = {
'''configuration_layoutlmv3''': [
'''LAYOUTLMV3_PRETRAINED_CONFIG_ARC... | 659 |
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
_lowercase = logging.get_logger(__name__)
_lowercase = {
... | 659 | 1 |
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class __snake_case ( snake_case__ ):
"""simple docstring"""
def __init__( self : Any ,lowerCAmelCase__ : Optional[Any]="" ,lowerCAmelCase__ : Any="train" ) -> Li... | 659 |
from collections.abc import Generator
from math import sin
def UpperCamelCase ( snake_case__):
if len(snake_case__) != 32:
raise ValueError("Input must be of length 32")
lowerCAmelCase_ : Tuple = b""
for i in [3, 2, 1, 0]:
little_endian += string_aa[8... | 659 | 1 |
from __future__ import annotations
_lowercase = '''#'''
class __snake_case :
"""simple docstring"""
def __init__( self : Tuple ) -> None:
'''simple docstring'''
lowerCAmelCase_ : dict = {}
def UpperCAmelCase_ ( ... | 659 |
import logging
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import librosa
import torch
from datasets import DatasetDict, load_dataset
from packaging import version
from torch import nn
from transformers import (
HfArgumentParser,
Trainer,
Trai... | 659 | 1 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from transformers import CLIPImageProcessor, CLIPVisionModel
from ...models import PriorTransformer
from ...pipelines import DiffusionPipeline
from ...schedulers import HeunDiscreteScheduler
from .... | 659 |
from __future__ import annotations
from collections.abc import Callable
def UpperCamelCase ( snake_case__ , snake_case__ , snake_case__ , snake_case__ = 1_00 , ):
lowerCAmelCase_ : Any = x_start
lowerCAmelCase_ : Optional[Any] = fnc(snake_case_... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase = {
'''configuration_time_series_transformer''': [
'''TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''TimeSeriesTransformerConfig''',
],
}
... | 659 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
PNDMScheduler,
StableDiffusionLDMaDPipeline,
UNetaDConditionModel,
)
from diffusers.utils import nightly, slow, t... | 659 | 1 |
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : Optional[int] = int(snake_case__)
if decimal in (0, 1): # Exit cases for the recursion
return str(snake_case__)
lowerCAmelCase_ , lowerCAmelCase_ : Optional[int] = divmod(snake_case__ ,... | 659 |
import argparse
import re
import numpy as np
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SamConfig,
SamImageProcessor,
SamModel,
SamProcessor,
SamVisionConfig,
)
_lowercase = {
'''iou_prediction_head.lay... | 659 | 1 |
import unittest
from transformers import AutoTokenizer, NystromformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from... | 659 |
class __snake_case :
"""simple docstring"""
def __init__( self : Union[str, Any] ,lowerCAmelCase__ : str = "" ,lowerCAmelCase__ : bool = False ) -> None:
'''simple docstring'''
lowerCAmelCase_ : dict[str, RadixNode] = {... | 659 | 1 |
import unittest
import torch
from torch import nn
from diffusers.models.activations import get_activation
class __snake_case ( unittest.TestCase ):
"""simple docstring"""
def UpperCAmelCase_ ( self : List[Any] ) -> List[str]:
'''simple docstring'''
... | 659 |
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModel... | 659 | 1 |
from scipy.stats import spearmanr
import datasets
_lowercase = '''
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive correlations imply that ... | 659 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_lowerc... | 659 | 1 |
from __future__ import annotations
from math import gcd
def UpperCamelCase ( snake_case__ , snake_case__ = 2 , snake_case__ = 1 , snake_case__ = 3 , ):
# A value less than 2 can cause an infinite loop in the algorithm.
if num < 2:
raise ValueError("The input... | 659 |
import os
_lowercase = {'''I''': 1, '''V''': 5, '''X''': 10, '''L''': 50, '''C''': 100, '''D''': 500, '''M''': 1000}
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : List[str] = 0
lowerCAmelCase_ : Any = 0
while index < len(snake_case__) - 1:
... | 659 | 1 |
_lowercase = 0 # The first color of the flag.
_lowercase = 1 # The second color of the flag.
_lowercase = 2 # The third color of the flag.
_lowercase = (red, white, blue)
def UpperCamelCase ( snake_case__):
if not sequence:
return []
if len(snake_c... | 659 |
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def UpperCamelCase ( ):
lowerCAmelCase_ : Dict = HfArgumentParser(snake_case__)
lowerCAmelCase_ : Dict = parser.parse_args_into_dataclasses()[0]
lowerCAmelCase_ : Lis... | 659 | 1 |
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : Union[str, Any] = 1
for i in range(1 , num + 1):
fact *= i
return fact
def UpperCamelCase ( snake_case__):
lowerCAmelCase_ : Optional[int] = 0
while number > 0:
... | 659 |
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
_lowercase = [
'''Prosecutor: "No videos were used in the crash investigation" German papers say they saw a cell phone video of the'''
''' ... | 659 | 1 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''google/vit-base-patch16-224... | 659 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test_to... | 659 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase = {
'''configuration_mobilenet_v2''': [
'''MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''MobileNetV2Config''',
'''MobileNetV... | 659 |
from ....configuration_utils import PretrainedConfig
from ....utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''Visual-Attention-Network/van-base''': (
'''https://huggingface.co/Visual-Attention-Network/van-base/blob/main/config.json'''
),
}
class __... | 659 | 1 |
_lowercase = '''0.18.2'''
from .configuration_utils import ConfigMixin
from .utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_inflect_available,
is_invisible_watermark_available,
is_k_diffusion_available,
is_k_diffusion_version,
is_librosa_available,
is_no... | 659 |
from math import factorial
def UpperCamelCase ( snake_case__ , snake_case__):
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("Please enter pos... | 659 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase = logging.get_logger(__name__)
_lowercase = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.json''',
}
class __snake_case ( snake_case__ ... | 659 |
import argparse
import json
from tqdm import tqdm
def UpperCamelCase ( ):
lowerCAmelCase_ : Any = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
"--src_path" , type=snake_case__ , default="biencoder-nq-dev.json" , help="Path... | 659 | 1 |
import pytest
import datasets.config
from datasets.utils.info_utils import is_small_dataset
@pytest.mark.parametrize("dataset_size" , [None, 4_00 * 2**20, 6_00 * 2**20])
@pytest.mark.parametrize("input_in_memory_max_size" , ["default", 0, 1_00 * 2**20, 9_00 * 2**20])
def UpperCamelCase ( snake... | 659 |
from collections.abc import Sequence
def UpperCamelCase ( snake_case__ = None):
if nums is None or not nums:
raise ValueError("Input sequence should not be empty")
lowerCAmelCase_ : Dict = nums[0]
for i in range(1 , len(snake_case__)):
lowerCAme... | 659 | 1 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tensor,... | 659 |
from typing import TYPE_CHECKING
from ....utils import _LazyModule
_lowercase = {'''tokenization_tapex''': ['''TapexTokenizer''']}
if TYPE_CHECKING:
from .tokenization_tapex import TapexTokenizer
else:
import sys
_lowercase = _LazyModule(__name__, globals()['''__file__'''... | 659 | 1 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_lowerc... | 659 |
import argparse
import glob
import importlib.util
import os
import re
import black
from doc_builder.style_doc import style_docstrings_in_code
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
_lowercase = '''src/diffuse... | 659 | 1 |
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