code stringlengths 81 54k | code_codestyle int64 0 721 | style_context stringlengths 91 41.9k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
import os
import unittest
from transformers import MobileBertTokenizer, MobileBertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils i... | 714 |
import math
def A__( __lowerCAmelCase ):
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or number % 3 == 0:
# Negatives, 0, 1, all even numbers, all multiples of 3 are not primes
return False
# All prime... | 652 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowercase_ : Tuple = {
'''configuration_informer''': [
'''INFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'''InformerConfig''',
... | 715 |
import torch
from transformers import AutoModel
class lowercase ( torch.nn.Module ):
"""simple docstring"""
def __init__( self : Tuple , lowerCamelCase_ : Dict="sayef/fsner-bert-base-uncased" ):
'''simple docstring'''
... | 652 | 0 |
def A__( __lowerCAmelCase , __lowerCAmelCase ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_snake_case : Dict = (boundary[1] - boundary[0]) / steps
_snake_case : List[str] = boundary[0]
_snake_case : int = boundary... | 716 |
import torch
import torch.nn as nn
from transformers.modeling_utils import ModuleUtilsMixin
from transformers.models.ta.modeling_ta import TaBlock, TaConfig, TaLayerNorm
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class lowercase ( ... | 652 | 0 |
'''simple docstring'''
import asyncio
import os
import shutil
import subprocess
import sys
import tempfile
import unittest
from distutils.util import strtobool
from functools import partial
from pathlib import Path
from typing import List, Union
from unittest import mock
import torc... | 717 |
def A__( __lowerCAmelCase ):
assert column_title.isupper()
_snake_case : List[Any] = 0
_snake_case : List[str] = len(__lowerCAmelCase ) - 1
_snake_case : Dict = 0
while index >= 0:
_snake_case : List[str] = (ord(column_ti... | 652 | 0 |
import json
import os
import shutil
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoConfig, BertConfig, GPTaConfig
from transformers.configura... | 718 |
import sacrebleu as scb
from packaging import version
from sacrebleu import TER
import datasets
lowercase_ : List[str] = '''\
@inproceedings{snover-etal-2006-study,
title = "A Study of Translation Edit Rate with Targeted Human Annotation",
author = "Snover, Matthew and
D... | 652 | 0 |
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import AutoImageProcessor, ViTImageProcessor
from transformers.testing_utils import TOKEN... | 719 |
import re
from flax.core.frozen_dict import freeze
from flax.traverse_util import flatten_dict, unflatten_dict
from jax.experimental import PartitionSpec as P
# Sentinels
lowercase_ : Optional[int] = object()
# For specifying empty leaf dict `{}`
lowercase_ : List[Any] = ... | 652 | 0 |
from math import factorial
def A__( __lowerCAmelCase = 20 ):
_snake_case : List[Any] = 2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
_snake_case : int = n // 2
return int(factorial(__lowerCAmelCase ) / (factori... | 720 |
import argparse
import logging
import os
from datetime import datetime
import numpy as np
import torch
from torch import nn
from torch.utils.data import DataLoader, RandomSampler, TensorDataset
from tqdm import tqdm
from transformers import GPTaLMHeadModel
lowercase_ : Any = lo... | 652 | 0 |
def A__( __lowerCAmelCase , __lowerCAmelCase ):
return int((input_a, input_a).count(0 ) != 0 )
def A__( ):
assert nand_gate(0 , 0 ) == 1
assert nand_gate(0 , 1 ) == 1
assert nand_gate(1 , 0 ) == 1
assert nand_gate(1 , 1 ) == 0
if __name__ == "__main__... | 721 |
def A__( __lowerCAmelCase ):
if not isinstance(__lowerCAmelCase , __lowerCAmelCase ):
raise TypeError('only integers accepted as input' )
else:
_snake_case : Any = str(abs(__lowerCAmelCase ) )
_snake_case : List[str] = [list(__lowerCAmelC... | 652 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase_ : Tuple = {
'''configuration_perceiver''': ['''PERCEIVER_PRETRAINE... | 653 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 1 |
'''simple docstring'''
from .constants import (
MODEL_NAME,
OPTIMIZER_NAME,
RNG_STATE_NAME,
SAFE_WEIGHTS_INDEX_NAME,
SAFE_WEIGHTS_NAME,
SCALER_NAME,
SCHEDULER_NAME,
TORCH_LAUNCH_PARAMS,
WEIGHTS_INDEX_NAME,
WEIGHTS_NAME,
)
from .dataclasses import (
BnbQuantizationConfig... | 653 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : float , lowercase_ : float ):
if density <= 0:
raise ValueError("""Impossible fluid density""" )
if bulk_modulus <= 0:
raise ValueError("""Impossible bulk modulus""" )
... | 653 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. 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.... | 653 |
'''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,
)
lowercase_ : ... | 653 | 1 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CON... | 653 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 | 1 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 |
'''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
from transformers impor... | 653 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 1 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config... | 653 | 1 |
'''simple docstring'''
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import SPIECE_UNDERLINE, logging
lowercase_ : Optional[Any] ... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 653 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : str = logging.get_logger(__name__)
lowercase_ : Optional[int] = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/r... | 653 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 | 1 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, ... | 653 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
def get_matched_characters(lowercase_ : str , lowercase_ : str ) -> str:
lowercase = []
lowercase = min(len(_stra... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 | 1 |
'''simple docstring'''
import pytest
from datasets.parallel import ParallelBackendConfig, parallel_backend
from datasets.utils.py_utils import map_nested
from .utils import require_dill_gt_0_3_2, require_joblibspark, require_not_windows
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str]... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 | 1 |
'''simple docstring'''
import itertools
import string
from collections.abc import Generator, Iterable
def SCREAMING_SNAKE_CASE ( lowercase_ : Iterable[str] , lowercase_ : int ):
lowercase = iter(lowercase_ )
while True:
lowercase ... | 653 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowercase_ : Dict = {'''configuration_vit''': ['''VIT_PRETRAINED_C... | 653 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImage... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = len(lowercase_ ) + 1
lowercase = len(lowercase_ ) + 1
# dp is a 2d matrix where dp[i][j] denotes whether prefix string of
... | 653 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 1 |
'''simple docstring'''
import qiskit
def SCREAMING_SNAKE_CASE ( lowercase_ : int = 2 ):
lowercase = qubits
# Using Aer's simulator
lowercase = qiskit.Aer.get_backend("""aer_simulator""" )
# Creating a Quantum Circuit acting on... | 653 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowerca... | 653 | 1 |
'''simple docstring'''
import math
def SCREAMING_SNAKE_CASE ( lowercase_ : int ):
lowercase = math.loga(math.sqrt(4 * positive_integer + 1 ) / 2 + 1 / 2 )
return exponent == int(lowercase_ )
def SCREAMING_SNAKE_CASE ( lowerc... | 653 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 | 1 |
'''simple docstring'''
import unittest
from transformers import MODEL_FOR_DOCUMENT_QUESTION_ANSWERING_MAPPING, AutoTokenizer, is_vision_available
from transformers.pipelines import pipeline
from transformers.pipelines.document_question_answering import apply_tesseract
from transformers.testing_utils import (
... | 653 |
'''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
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 1 |
'''simple docstring'''
from transformers import DistilBertTokenizer, DistilBertTokenizerFast
from transformers.testing_utils import require_tokenizers, slow
from ..bert.test_tokenization_bert import BertTokenizationTest
@require_tokenizers
class __UpperCamelCase (_UpperCAmelCase ):
__A = ... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 1 |
'''simple docstring'''
import contextlib
from multiprocessing import Pool, RLock
from tqdm.auto import tqdm
from ..utils import experimental, logging
lowercase_ : List[str] = logging.get_logger(__name__)
class __UpperCamelCase :
__A = None
@experimental
def ... | 653 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 1 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 1 |
'''simple docstring'''
import importlib
import inspect
import os
import re
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
lowercase_ : Any = '''src/transformers'''
# This is to make sure the ... | 653 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 1 |
'''simple docstring'''
import numpy as np
def SCREAMING_SNAKE_CASE ( lowercase_ : np.ndarray ):
return 1 / (1 + np.exp(-vector ))
def SCREAMING_SNAKE_CASE ( lowercase_ : np.ndarray ):
return vector * sigmoid(lowercase_ )
if __na... | 653 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
WavaVecaConfig,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaForCTC,
WavaVecaForPreTraining,
WavaVecaProcessor,
logging,
... | 653 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_ : List[Any] = {'''configuration_opt''': ['''OPT_PRE... | 653 |
'''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,
)
lowercase_ : ... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int ):
if a < 0 or b < 0:
raise ValueError("""the value of both inputs must be positive""" )
lowercase = str(bin(lowercase_ ) )[2:] # remove the l... | 653 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase_ : Union[str, Any] = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 653 |
'''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
from transformers impor... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase_ : Union[str, Any] = {
'''configuration_transfo_xl''': ['''TRANSFO_XL_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''TransfoXLConfi... | 653 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 1 |
'''simple docstring'''
import torch
from diffusers import DiffusionPipeline
class __UpperCamelCase (_UpperCAmelCase ):
def __init__( self , _lowerCAmelCase , _lowerCAmelCase ) -> List[Any]:
'''simple docstring'''
super().__init__()
self.reg... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config... | 653 | 1 |
'''simple docstring'''
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRoberta... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 653 | 1 |
'''simple docstring'''
from urllib.parse import quote
import pytest
from datasets.utils.hub import hf_hub_url
@pytest.mark.parametrize("""repo_id""" , ["""canonical_dataset_name""", """org-name/dataset-name"""] )
@pytest.mark.parametrize("""path""" , ["""filename.csv""", """filename with blanks.cs... | 653 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int ):
if not isinstance(lowercase_ , lowercase_ ):
lowercase = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowercase_ )
if number < 0:
... | 653 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 | 1 |
'''simple docstring'''
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
lowercase_ : int = logging.... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 | 1 |
'''simple docstring'''
from PIL import Image
def SCREAMING_SNAKE_CASE ( lowercase_ : Image , lowercase_ : float ):
def brightness(lowercase_ : int ) -> float:
return 128 + level + (c - 128)
if not -255.0 <= level <= 255.0:
... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 | 1 |
'''simple docstring'''
# XXX: we want transformers master here - in the absense of conftest manipulating sys.path:
# hack it in for now:
import sys
from pathlib import Path
lowercase_ : Optional[Any] = Path(__file__).resolve().parents[3] / '''src'''
sys.path.insert(1, str(git_repo_path))
impo... | 653 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImage... | 653 | 1 |
'''simple docstring'''
import numpy as np
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : Optional[Any] , lowercase_ : int , lowercase_ : List[Any] , lowercase_ : str ):
lowercase = int(np.ceil((x_end - xa) / h )... | 653 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 1 |
'''simple docstring'''
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert... | 653 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowerca... | 653 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_videomae import VideoMAEImageProcessor
lowercase_ : Optional[Any] = logging.get_logger(__name__)
class __UpperCamelCase (_UpperCAmelCase ):
def __init__( self , *_lowerCAm... | 653 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 | 1 |
'''simple docstring'''
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import ... | 653 |
'''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
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
lowercase_ : str = {
'''configuration_layoutlmv3''': [
... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RoFormerConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import ... | 653 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 1 |
'''simple docstring'''
from __future__ import annotations
import os
import tempfile
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
from transformers import is_tensorflow_text_available, is_tf_available
from transformers.testing_utils import require_tensorflow_text, require_tf, s... | 653 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 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
lowercase_ : Dict = logging.get_logger(__name__)
lowercas... | 653 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 1 |
'''simple docstring'''
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
lowercase_ : Optional[int] = TypeVar('''KEY''')
lowercase_ : List[Any] = TypeVar('''VAL''')
@dataclass(frozen=_UpperCAmelCase ... | 653 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 1 |
'''simple docstring'''
import argparse
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_warmup, set_seed
from acceler... | 653 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 1 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
f... | 653 |
'''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,
)
lowercase_ : ... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowercase_ : Tuple = {
'''configuration_longformer''': [
'''LONGFORMER_PR... | 653 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 | 1 |
'''simple docstring'''
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class __UpperCamelCase (unittest.TestCase ):
def _a ( self ) -> List[str]:
'''simple docstr... | 653 |
'''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
from transformers impor... | 653 | 1 |
'''simple docstring'''
# coding=utf-8
# Copyright 2020 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int ):
if not isinstance(lowercase_ , lowercase_ ):
raise ValueError("""iterations must be defined as integers""" )
if not isinstance(lowercase_ , lowercase_ ... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
lowercase_ : Any = {
'''configuration_rag''': ['''RagConfig'''],
'''retrieval_rag''': ['''RagRetriever'''],
'''tokenization... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 653 | 1 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 | 1 |
'''simple docstring'''
import math
lowercase_ : Any = 10
lowercase_ : Any = 7
lowercase_ : str = BALLS_PER_COLOUR * NUM_COLOURS
def SCREAMING_SNAKE_CASE ( lowercase_ : int = 20 ):
lowercase = math.comb(lowerca... | 653 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 | 1 |
'''simple docstring'''
from collections import defaultdict
from math import ceil, sqrt
def SCREAMING_SNAKE_CASE ( lowercase_ : int = 100_0000 , lowercase_ : int = 10 ):
lowercase = defaultdict(lowercase_ )
for outer_width in range(3 , (t_limi... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 | 1 |
'''simple docstring'''
import gzip
import hashlib
import json
import multiprocessing
import os
import re
import shutil
import time
from pathlib import Path
import numpy as np
from arguments import PreprocessingArguments
from datasets import load_dataset
from minhash_deduplication import deduplicate_dataset
from... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 | 1 |
'''simple docstring'''
from jiwer import compute_measures
import datasets
lowercase_ : List[str] = '''\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER an... | 653 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 | 1 |
'''simple docstring'''
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availa... | 653 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImage... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int = 1000 ):
lowercase , lowercase = 1, 1
lowercase = []
for i in range(1 , n + 1 ):
lowercase = prev_numerator + 2 * prev_denominator
... | 653 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 1 |
'''simple docstring'''
import tensorflow as tf
from ...tf_utils import shape_list
class __UpperCamelCase (tf.keras.layers.Layer ):
def __init__( self , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase , _lowerCAmelCase=1 , _lowerCAmelCase=False ,... | 653 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowerca... | 653 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 | 1 |
'''simple docstring'''
# this script reports modified .py files under the desired list of top-level sub-dirs passed as a list of arguments, e.g.:
# python ./utils/get_modified_files.py utils src tests examples
#
# it uses git to find the forking point and which files were modified - i.e. files not under git won... | 653 |
'''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
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 1 |
'''simple docstring'''
import argparse
from typing import List
import evaluate
import numpy as np
import torch
from datasets import DatasetDict, load_dataset
# New Code #
# We'll be using StratifiedKFold for this example
from sklearn.model_selection import StratifiedKFold
from torch.optim import AdamW
from torc... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class __UpperCamelCase (_UpperCAmelCase ):
__A = ['''image_processor''', '''tokenizer''']
__A = '''ChineseCLIPImageProcessor'''
__A = ... | 653 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : list[list[float]] ):
lowercase = []
for data in source_data:
for i, el in enumerate(lowercase_ ):
if len(lowercase_ ) < i + 1:
data_lists.... | 653 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 653 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 1 |
'''simple docstring'''
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
#... | 653 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():... | 653 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_poolformer import PoolFormerImageProcessor
lowercase_ : Any = logging.get_logger(__name__)
class __UpperCamelCase (_UpperCAmelCase ):
def __init__( self , *_lowerCAmelCase... | 653 |
'''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,
)
lowercase_ : ... | 653 | 1 |
'''simple docstring'''
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 __UpperCamelCase (_UpperCAmel... | 653 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 | 1 |
'''simple docstring'''
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 653 |
'''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
from transformers impor... | 653 | 1 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..bit import BitConfig
lowercase_ : Tuple = logging.get_logger(__name__)
lowercase_ : List[Any] = {
'''Intel/dpt-large''': '''https://huggingface.co/... | 653 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_tf_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_tf_available():
import tensorflow as tf
lowercase_ : Union[str, An... | 653 | 1 |
'''simple docstring'''
from abc import ABC, abstractmethod
from typing import Optional, Union
from .. import Dataset, DatasetDict, Features, IterableDataset, IterableDatasetDict, NamedSplit
from ..utils.typing import NestedDataStructureLike, PathLike
class __UpperCamelCase (_UpperCAmelCase ):
... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''sayakpaul/vit-msn-base''': '''https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config... | 653 | 1 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : Union[str, Any] , lowercase_ : str ):
lowercase = """"""
for i in table:
res += inp[i - 1]
return res
def SCREAMING_SNAKE_CASE ( lowercase_ : List[An... | 653 | 1 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : list[int] , lowercase_ : list[int] ):
# Check if the input is valid
if not len(lowercase_ ) == len(lowercase_ ) == 3:
raise ValueError("""Please enter a valid equation.""" )
... | 653 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chann... | 653 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] ):
lowercase = int(lowercase_ )
assert noofclusters < len(lowercas... | 653 | 1 |
'''simple docstring'''
import sys
lowercase_ : int = (
'''73167176531330624919225119674426574742355349194934'''
'''96983520312774506326239578318016984801869478851843'''
'''85861560789112949495459501737958331952853208805511'''
'''12540698747158523863050715693290963295227443043557... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( lowercase_ : int , lowercase_ : int , lowercase_ : list[list[int]] ):
def update_area_of_max_square(lowercase_ : int , lowercase_ : int ) -> int:
# BASE CASE
if row >= r... | 653 | 1 |
'''simple docstring'''
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 TFMod... | 653 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase_ : int = {
'''bigcode/gpt_bigcode-santacoder''': '''https://huggingface.co/bigcode/gpt_bigcode-sant... | 653 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowercase_ : Any = logging.get_logger(__name__)
lowercase_ : str = {
'''unc-nlp/lxmert-base-uncased''': '''https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/m... | 653 |
'''simple docstring'''
import requests
def SCREAMING_SNAKE_CASE ( lowercase_ : str , lowercase_ : str ):
lowercase = {"""Content-Type""": """application/json"""}
lowercase = requests.post(lowercase_ , json={"""text""": message_body} , ... | 653 | 1 |
'''simple docstring'''
import collections
import importlib.util
import os
import re
from pathlib import Path
lowercase_ : Union[str, Any] = '''src/transformers'''
# Matches is_xxx_available()
lowercase_ : Tuple = re.compile(r'''is\_([a-z_]*)_available()''')
# Catches a one-... | 653 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileViTConfig,
MobileViTForImageClassification,
MobileViTForSemanticSegmentation,
MobileViTImage... | 653 | 1 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
lowercase_ : List[str] ... | 653 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visio... | 653 | 1 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttenti... | 653 |
'''simple docstring'''
from transformers import HfArgumentParser, TensorFlowBenchmark, TensorFlowBenchmarkArguments
def SCREAMING_SNAKE_CASE ( ):
lowercase = HfArgumentParser(lowercase_ )
lowercase = parser.parse_args_into_dataclasses()[0]
lowerca... | 653 | 1 |
'''simple docstring'''
import argparse
import collections
import os
import re
import tempfile
import pandas as pd
from datasets import Dataset
from huggingface_hub import hf_hub_download, upload_folder
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run... | 653 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 | 1 |
'''simple docstring'''
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class __UpperCamelCase (unittest.Tes... | 653 |
'''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
lowercase_ : Optional[Any] = logging.get_logger(__name__)
lowercase... | 653 | 1 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def SCREAMING_SNAKE_CASE ( lowercase_ : List[str] , lowercase_ : Optional[int] , lowercase_ : Tuple ):
lowercase = 0
if start < end:
... | 653 |
'''simple docstring'''
def SCREAMING_SNAKE_CASE ( ):
lowercase = []
lowercase = 1
while len(lowercase_ ) < 1E6:
constant.append(str(lowercase_ ) )
i += 1
lowercase = """""".join(lowercase_ )
... | 653 | 1 |
'''simple docstring'''
from importlib import import_module
from .logging import get_logger
lowercase_ : Any = get_logger(__name__)
class __UpperCamelCase :
def __init__( self , _lowerCAmelCase , _lowerCAmelCase=None ) -> Union[str, Any]:
'''si... | 653 |
'''simple docstring'''
import os
def SCREAMING_SNAKE_CASE ( ):
lowercase = os.path.join(os.path.dirname(lowercase_ ) , """num.txt""" )
with open(lowercase_ ) as file_hand:
return str(sum(int(lowercase_ ) for line in file_hand ) ... | 653 | 1 |
'''simple docstring'''
# coding=utf-8
# Copyright 2023 The HuggingFace Inc. team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# ... | 653 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
EulerAncestralDiscreteScheduler,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusi... | 653 | 1 |
'''simple docstring'''
from __future__ import annotations
import os
from typing import Any
import requests
lowercase_ : List[str] = '''https://api.github.com'''
# https://docs.github.com/en/free-pro-team@latest/rest/reference/users#get-the-authenticated-user
lowercase_ : Any =... | 653 |
'''simple docstring'''
import logging
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from seqaseq_trainer import SeqaSeqTrainer
from seqaseq_training_args import SeqaSeqTrainingArguments
import transformers
from transformers import (
AutoConfig,
AutoModelForSeq... | 653 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase_ : Any = {
'''configuration_conditional_detr''': [
'''CONDITIONAL_DETR_PRETRAINED_CONFIG_ARCHIVE_MAP''',
... | 653 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 653 | 1 |
'''simple docstring'''
import json
import os
import tempfile
import transformers
import datasets
from utils import generate_example_dataset, get_duration
lowercase_ : int = 50_0000
lowercase_ , lowercase_ : Union[str, Any] = os.path.split(__file__)
lowercase_ ... | 653 |
'''simple docstring'''
from ... import PretrainedConfig
lowercase_ : int = {
'''sijunhe/nezha-cn-base''': '''https://huggingface.co/sijunhe/nezha-cn-base/resolve/main/config.json''',
}
class __UpperCamelCase (_UpperCAmelCase ):
__A = NEZHA_PRETRAINED_CONFIG_ARCHIV... | 653 | 1 |
'''simple docstring'''
import argparse
import os
from . import (
ALBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
BART_PRETRAINED_MODEL_ARCHIVE_LIST,
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CAMEMBERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP,
DISTILBERT_PRETRAINED_CONFIG_ARCHIVE_... | 653 |
'''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,
)
lowercase_ : ... | 653 | 1 |
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