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 |
|---|---|---|---|---|
from __future__ import annotations
from itertools import permutations
from random import randint
from timeit import repeat
def snake_case ( ):
'''simple docstring'''
__lowercase = [randint(-1_000 , 1_000 ) for i in range(10 )]
__lowercase = randint(-5_0... | 80 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : Optional[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""... | 675 | 0 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version(">=", FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed.checkpoint.default_pl... | 81 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ : Any = get_tests_dir("""fixture... | 675 | 0 |
"""simple docstring"""
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import ViTConfig, ViTForImageClassification, ViTImageProcessor, ViTModel
from transformers.utils imp... | 82 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class snake_case ( l... | 675 | 0 |
"""simple docstring"""
import qiskit
def snake_case_ ( A_ : int = 2 ):
'''simple docstring'''
_lowerCamelCase : List[Any] = qubits
# Using Aer's simulator
_lowerCamelCase : List[str] = qiskit.Aer.get_backend(''... | 83 |
'''simple docstring'''
import os
import sys
import unittest
a_ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import c... | 675 | 0 |
UpperCAmelCase = 0 # The first color of the flag.
UpperCAmelCase = 1 # The second color of the flag.
UpperCAmelCase = 2 # The third color of the flag.
UpperCAmelCase = (red, white, blue)
def UpperCAmelCase_ ( __SCREAMING_SNAKE_CASE ):
if not sequence:
... | 84 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=lowercase ):
"""simple docstring"""
_lowerCamelCase = ["onnx"]
def __init__( self , *UpperCamelCase , **Up... | 675 | 0 |
import os
def _a ( lowercase__ : str = "input.txt" ):
'''simple docstring'''
with open(os.path.join(os.path.dirname(lowercase__ ) , lowercase__ ) ) as input_file:
SCREAMING_SNAKE_CASE__ : List[str] = [
[int(lowercase__ ) for elem... | 85 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 675 | 0 |
from __future__ import annotations
from statistics import mean
def __snake_case ( __UpperCamelCase : list[int] ,__UpperCamelCase : list[int] ,__UpperCamelCase : int ):
"""simple docstring"""
A_ = [0] * no_of_processes
A_ = [0] * no_of_proces... | 86 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
a_ : int = """docs/source/en/_toctree.yml"""
def __snake_case ( UpperCAmelCase_ : Optional[int] ):
lowerCamelCase_ = defaultdict(UpperCAmelCase_ )
lowerCamel... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase : Tuple = {
"""configuration_whisper""": ["""WHISPER_PRETRAINED_CON... | 87 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __snake_case ( UpperCAmelCase_ : List[Any] , UpperCAmelCase_ : Dict , UpperCAmelCase_ ... | 675 | 0 |
"""simple docstring"""
import numpy as np
from sklearn.datasets import fetch_california_housing
from sklearn.metrics import mean_absolute_error, mean_squared_error
from sklearn.model_selection import train_test_split
from xgboost import XGBRegressor
def _snake_case ( __snake_case : d... | 88 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ ... | 675 | 0 |
import math
import os
import re
import sys
import unittest
from pathlib import Path
from typing import Tuple
from unittest.mock import patch
from parameterized import parameterized
from transformers.testing_utils import (
CaptureStderr,
ExtendSysPath,
TestCasePlus,
execute_subprocess_async,
get... | 89 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...... | 675 | 0 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
... | 90 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer i... | 675 | 0 |
"""simple docstring"""
def _snake_case ( snake_case__ : int , snake_case__ : int ):
while b:
A , A = b, a % b
return a
def _snake_case ( snake_case__ : int , snake_case__ : int ):
return a if b == 0 else euclidean_gcd_recursive(snake_case__ , a % b )
... | 91 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_t... | 675 | 0 |
'''simple docstring'''
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def _lowerCAmelCase ( __magic_name__ : List[str] ) -> Union[str, Any]:
# This defines a "chinese character" as anything in the CJK Unicode ... | 92 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
a_ : Optional[int] = HfArgumentParser(InitializationArguments)
a_ : str = parser.pa... | 675 | 0 |
"""simple docstring"""
import gc
import unittest
import numpy as np
import torch
from diffusers import StableDiffusionKDiffusionPipeline
from diffusers.utils import slow, torch_device
from diffusers.utils.testing_utils import enable_full_determinism, require_torch_gpu
enable_full_determinism()
@slo... | 93 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 675 | 0 |
'''simple docstring'''
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
SCREAMING_SNAKE_CASE = argparse.ArgumentParser('Stable Diffusion script with intel optimization', add_help=False)
parser.add_... | 94 |
'''simple docstring'''
import os
def __snake_case ( UpperCAmelCase_ : str = "matrix.txt" ):
with open(os.path.join(os.path.dirname(UpperCAmelCase_ ) , UpperCAmelCase_ ) ) as in_file:
lowerCamelCase_ = in_file.read()
lowerCamelCase_ = [[int(Upp... | 675 | 0 |
"""simple docstring"""
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
f... | 95 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)... | 675 | 0 |
"""simple docstring"""
def a ( __UpperCAmelCase : list[int] , __UpperCAmelCase : int ) -> bool:
__magic_name__: Optional[int] = len(__UpperCAmelCase )
__magic_name__: str = [[False] * (required_sum + 1) for _ in ra... | 96 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
a_ : Any = [
"""Prosecutor: \"No videos were used in the crash investigation\" German paper... | 675 | 0 |
from tempfile import TemporaryDirectory
from unittest import TestCase
from unittest.mock import MagicMock, patch
from transformers import AutoModel, TFAutoModel
from transformers.onnx import FeaturesManager
from transformers.testing_utils import SMALL_MODEL_IDENTIFIER, require_tf, require_torch
@require_torch... | 97 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceboo... | 675 | 0 |
'''simple docstring'''
from manim import *
class __lowerCAmelCase ( __magic_name__ ):
"""simple docstring"""
def snake_case__ ( self : Optional[Any] ) -> List[str]:
'''simple docstring'''
_UpperCamelCase = Recta... | 98 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class snake_case ( lowercase ):
"""... | 675 | 0 |
def a (lowerCAmelCase__ ):
__a = len(lowerCAmelCase__ )
while cur > 1:
# Find the maximum number in arr
__a = arr.index(max(arr[0:cur] ) )
# Reverse from 0 to mi
__a = arr[mi::-1] + arr[mi + 1 : len(lowerCAmelCase__ )]
# Reverse whole list
... | 99 |
'''simple docstring'''
def __snake_case ( ):
lowerCamelCase_ = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCamelCase_ = 6
lowerCamelCase_ = 1
lowerCamelCase_ = 1901
lowerCamelCase_ = 0
while year < 2001:
day += 7
if (year % 4 == 0 an... | 675 | 0 |
import argparse
import os
from pathlib import Path
import fairseq
import torch
from packaging import version
from torch import nn
from transformers import (
BartConfig,
BartForConditionalGeneration,
BartForSequenceClassification,
BartModel,
BartTokenizer,
)
from transformers.utils import log... | 100 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ : Optional[int] = logging.get_logger(__name__)
a_ : Dict = {
"""SenseTime/deformable-detr""": """h... | 675 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def a__ ( A__, A__ ):
SCREAMING_SNAKE_CASE_ : Optional[int] = F'''{sampling_rate}'''
SCREAMING_SNAKE_CASE_ : str = '1'
SCREAMIN... | 101 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class snake_case ( pl.LightningModule ):
"""simple docstring"""
def __init... | 675 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__magic_name__ : int = logging.get_logger(__name__)
__magic_name__ :... | 102 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : Optional[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""... | 675 | 0 |
"""simple docstring"""
def snake_case ( lowerCAmelCase_ , lowerCAmelCase_ ) -> int:
return 1 if input_a == input_a else 0
def snake_case ( ) -> None:
assert xnor_gate(0 , 0 ) == 1
assert xnor_gate(0 , 1 ) == 0
assert xnor_gate(1 , ... | 103 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ : Any = get_tests_dir("""fixture... | 675 | 0 |
"""simple docstring"""
def _lowerCamelCase ( UpperCAmelCase_ : int ) -> int:
"""simple docstring"""
if not isinstance(UpperCAmelCase_, UpperCAmelCase_ ):
raise ValueError("Input must be an integer" )
if input_num <= 0:
raise Value... | 104 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class snake_case ( l... | 675 | 0 |
def __UpperCAmelCase ( lowerCamelCase_ : int , lowerCamelCase_ : int , lowerCamelCase_ : int ) -> float:
"""simple docstring"""
SCREAMING_SNAKE_CASE_ : List[Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1) * common_d... | 105 |
'''simple docstring'''
import os
import sys
import unittest
a_ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import c... | 675 | 0 |
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
fro... | 106 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=lowercase ):
"""simple docstring"""
_lowerCamelCase = ["onnx"]
def __init__( self , *UpperCamelCase , **Up... | 675 | 0 |
'''simple docstring'''
def _SCREAMING_SNAKE_CASE ( __snake_case : list[list] ):
_A = current_set.copy()
for row_index, row in enumerate(__snake_case ):
_A = row[0]
for column_index, column in enumerate(__snake_case ):
if magnitude ==... | 107 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 675 | 0 |
import json
import os
import unittest
from transformers import BatchEncoding, MvpTokenizer, MvpTokenizerFast
from transformers.models.roberta.tokenization_roberta import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
fro... | 108 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
a_ : int = """docs/source/en/_toctree.yml"""
def __snake_case ( UpperCAmelCase_ : Optional[int] ):
lowerCamelCase_ = defaultdict(UpperCAmelCase_ )
lowerCamel... | 675 | 0 |
'''simple docstring'''
from collections.abc import Callable
import numpy as np
def __magic_name__ ( __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase , __UpperCAmelCase ) -> np.ndarray:
'''simple docstring'''
__SCREAM... | 109 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __snake_case ( UpperCAmelCase_ : List[Any] , UpperCAmelCase_ : Dict , UpperCAmelCase_ ... | 675 | 0 |
'''simple docstring'''
import time
import warnings
from abc import ABC
from copy import deepcopy
from typing import Optional
import torch
from ..utils import add_start_docstrings, logging
a__ : List[str] = logging.get_logger(__name__)
a__ : Tuple ... | 368 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ ... | 675 | 0 |
import unittest
from transformers import DonutProcessor
__UpperCamelCase = """naver-clova-ix/donut-base"""
class lowerCamelCase__ ( unittest.TestCase ):
"""simple docstring"""
def snake_case__ ( self ):
'''simple docstring'''
UpperC... | 551 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...... | 675 | 0 |
'''simple docstring'''
import heapq as hq
import math
from collections.abc import Iterator
class lowerCAmelCase__ :
def __init__( self : Tuple , UpperCamelCase_ : int ) -> Union[str, Any]:
"""simple docstring"""
lowerCamelCase_ : int = str(id_ )... | 501 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer i... | 675 | 0 |
import math
from collections.abc import Callable
def snake_case_ (__A : Callable[[float], float] , __A : float , __A : float ) -> Optional[Any]:
__lowerCAmelCase : Optional[int] = xa
__lowerCAmelCase : List[str] = xa
while True:
... | 651 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_t... | 675 | 0 |
'''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_t... | 143 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
a_ : Optional[int] = HfArgumentParser(InitializationArguments)
a_ : str = parser.pa... | 675 | 0 |
'''simple docstring'''
def _lowerCAmelCase ( lowercase ) -> List[str]:
__lowerCAmelCase = int(UpperCAmelCase_ )
if n_element < 1:
__lowerCAmelCase = ValueError("""a should be a positive number""" )
raise my_error
__lowerCAmelCase = ... | 689 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 675 | 0 |
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
BERT_START_DOCSTRIN... | 47 |
'''simple docstring'''
import os
def __snake_case ( UpperCAmelCase_ : str = "matrix.txt" ):
with open(os.path.join(os.path.dirname(UpperCAmelCase_ ) , UpperCAmelCase_ ) ) as in_file:
lowerCamelCase_ = in_file.read()
lowerCamelCase_ = [[int(Upp... | 675 | 0 |
def _lowercase ( lowercase__ , lowercase__ , lowercase__ ):
if principal <= 0:
raise Exception('''Principal borrowed must be > 0''' )
if rate_per_annum < 0:
raise Exception('''Rate of interest must be >= 0''' )
if years_to_repay <= 0 or not isinstance... | 492 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)... | 675 | 0 |
from __future__ import annotations
from collections.abc import Iterator
from typing import Any
class __lowerCAmelCase :
def __init__( self , lowerCAmelCase ) -> Union[str, Any]:
'''simple docstring'''
_lowercase =data
_... | 291 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
a_ : Any = [
"""Prosecutor: \"No videos were used in the crash investigation\" German paper... | 675 | 0 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if... | 328 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceboo... | 675 | 0 |
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class snake_case ( SCREAMING_SNAKE_CASE_ ):... | 477 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class snake_case ( lowercase ):
"""... | 675 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
a__ : int = """2020.9.26"""
a__ : Optional[Any] = """xcodz-dot, cclaus, dhruvmanila"""
def __lowerCamelCase ( UpperCAmelCase_ , UpperCAmelCase_ , UpperCA... | 368 |
'''simple docstring'''
def __snake_case ( ):
lowerCamelCase_ = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCamelCase_ = 6
lowerCamelCase_ = 1
lowerCamelCase_ = 1901
lowerCamelCase_ = 0
while year < 2001:
day += 7
if (year % 4 == 0 an... | 675 | 0 |
def UpperCamelCase_( _A :str )-> Optional[int]:
UpperCamelCase__ = 0
for ch in input_str:
UpperCamelCase__ = ord(UpperCAmelCase_ )
UpperCamelCase__ = pow(2 , UpperCAmelCase_ )
# If we already turned on bit for current character's unicode
... | 551 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ : Optional[int] = logging.get_logger(__name__)
a_ : Dict = {
"""SenseTime/deformable-detr""": """h... | 675 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput, apply_forward_hook
from .modeling_utils import ModelMixin
from .vae import... | 501 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class snake_case ( pl.LightningModule ):
"""simple docstring"""
def __init... | 675 | 0 |
import qiskit
def snake_case_ (__A : int , __A : int ) -> Any:
__lowerCAmelCase : Tuple = qiskit.Aer.get_backend("""aer_simulator""" )
# Create a Quantum Circuit acting on the q register
__lowerCAmelCase : Tuple = qiskit.QuantumCircuit(U... | 651 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : Optional[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""... | 675 | 0 |
'''simple docstring'''
from random import shuffle
import tensorflow as tf
from numpy import array
def A_ ( snake_case , snake_case ):
SCREAMING_SNAKE_CASE:Optional[int] = int(UpperCAmelCase_ )
assert noofclusters < len(UpperCAmelCase_ )
# Find out the dimens... | 143 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ : Any = get_tests_dir("""fixture... | 675 | 0 |
'''simple docstring'''
import os
from tempfile import TemporaryDirectory
from unittest import TestCase
import pytest
from absl.testing import parameterized
from datasets import config
from datasets.arrow_reader import HF_GCP_BASE_URL
from datasets.builder import DatasetBuilder
from datasets.dataset_dict ... | 689 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class snake_case ( l... | 675 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer import RoFormerToke... | 47 |
'''simple docstring'''
import os
import sys
import unittest
a_ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import c... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_UpperCamelCase = {"""configuration_unispeech""": ["""UNISPEECH_PRETRAINED_CONFIG_ARCHIVE_MAP""", """UniSpeechConfig"""]}
... | 492 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=lowercase ):
"""simple docstring"""
_lowerCamelCase = ["onnx"]
def __init__( self , *UpperCamelCase , **Up... | 675 | 0 |
lowercase_ = """
# Transformers 설치 방법
! pip install transformers datasets
# 마지막 릴리스 대신 소스에서 설치하려면, 위 명령을 주석으로 바꾸고 아래 명령을 해제하세요.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowercase_ = [{"""type""": """code""", """content""": INSTALL_CONTENT}]
lowercase_ ... | 291 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 675 | 0 |
from ..utils import is_flax_available, is_torch_available
if is_torch_available():
from .autoencoder_kl import AutoencoderKL
from .controlnet import ControlNetModel
from .dual_transformer_ad import DualTransformeraDModel
from .modeling_utils import ModelMixin
f... | 328 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
a_ : int = """docs/source/en/_toctree.yml"""
def __snake_case ( UpperCAmelCase_ : Optional[int] ):
lowerCamelCase_ = defaultdict(UpperCAmelCase_ )
lowerCamel... | 675 | 0 |
import os
from bleurt import score # From: git+https://github.com/google-research/bleurt.git
import datasets
a__ = datasets.logging.get_logger(__name__)
a__ = """\
@inproceedings{bleurt,
title={BLEURT: Learning Robust Metrics for Text Generation},
author={Thibault Sellam a... | 477 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __snake_case ( UpperCAmelCase_ : List[Any] , UpperCAmelCase_ : Dict , UpperCAmelCase_ ... | 675 | 0 |
'''simple docstring'''
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
a__ : Tuple = logging.get_logger(__name__)
... | 368 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ ... | 675 | 0 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.utils import logging... | 551 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...... | 675 | 0 |
'''simple docstring'''
import os
import pickle
import unittest
from transformers import AutoTokenizer
from transformers.models.bert.tokenization_bert import BertTokenizer
from transformers.models.bert_japanese.tokenization_bert_japanese import (
VOCAB_FILES_NAMES,
BertJapaneseTokenizer,
Charact... | 501 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer i... | 675 | 0 |
import unittest
import torch
from diffusers import DDIMScheduler, DDPMScheduler, UNetaDModel
from diffusers.training_utils import set_seed
from diffusers.utils.testing_utils import slow
__UpperCAmelCase = False
class SCREAMING_SNAKE_CASE ( unittest.TestCase ):
"""simple d... | 651 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_t... | 675 | 0 |
'''simple docstring'''
A_ = 2_56
# Modulus to hash a string
A_ = 1_00_00_03
def A_ ( snake_case , snake_case ):
SCREAMING_SNAKE_CASE:Any = len(UpperCAmelCase_ )
SCREAMING_SNAKE_CASE:List[Any] = len(UpperCAmelCase_ )
if p_len... | 143 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
a_ : Optional[int] = HfArgumentParser(InitializationArguments)
a_ : str = parser.pa... | 675 | 0 |
'''simple docstring'''
import inspect
import unittest
import warnings
from transformers import DeiTConfig
from transformers.models.auto import get_values
from transformers.testing_utils import (
require_accelerate,
require_torch,
require_torch_gpu,
require_vision,
slow,
torch_devic... | 689 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 675 | 0 |
import argparse
import json
from pathlib import Path
import requests
import timm
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DeiTConfig, DeiTForImageClassificationWithTeacher, DeiTImageProcessor
from transformers.utils import logging... | 47 |
'''simple docstring'''
import os
def __snake_case ( UpperCAmelCase_ : str = "matrix.txt" ):
with open(os.path.join(os.path.dirname(UpperCAmelCase_ ) , UpperCAmelCase_ ) ) as in_file:
lowerCamelCase_ = in_file.read()
lowerCamelCase_ = [[int(Upp... | 675 | 0 |
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 M... | 492 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)... | 675 | 0 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class __lowerCAmelCase ( SCREAM... | 291 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
a_ : Any = [
"""Prosecutor: \"No videos were used in the crash investigation\" German paper... | 675 | 0 |
import argparse
import os
import re
__UpperCamelCase : Optional[Any] = """src/transformers/models/auto"""
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
__UpperCamelCase : Dict = ... | 328 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceboo... | 675 | 0 |
import math
class snake_case :
'''simple docstring'''
def __init__( self : Any , lowerCAmelCase : Any=0) -> Optional[Any]: # a graph with Node 0,1,...,N-1
"""simple docstring"""
_snake_case : Tuple ... | 477 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class snake_case ( lowercase ):
"""... | 675 | 0 |
'''simple docstring'''
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.version impo... | 368 |
'''simple docstring'''
def __snake_case ( ):
lowerCamelCase_ = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCamelCase_ = 6
lowerCamelCase_ = 1
lowerCamelCase_ = 1901
lowerCamelCase_ = 0
while year < 2001:
day += 7
if (year % 4 == 0 an... | 675 | 0 |
def UpperCamelCase_( _A :int )-> List[Any]:
if length <= 0 or not isinstance(UpperCAmelCase_ , UpperCAmelCase_ ):
raise ValueError("Length must be a positive integer." )
return [n * (2 * n - 1) for n in range(UpperCAmelCase_ )]
if __name__ == "__main__":
print(hexagonal_numbers(... | 551 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ : Optional[int] = logging.get_logger(__name__)
a_ : Dict = {
"""SenseTime/deformable-detr""": """h... | 675 | 0 |
'''simple docstring'''
import os
import shutil
import sys
import tempfile
import unittest
from pathlib import Path
import pytest
import transformers
from transformers import (
BERT_PRETRAINED_CONFIG_ARCHIVE_MAP,
GPT2_PRETRAINED_CONFIG_ARCHIVE_MAP,
AutoTokenizer,
BertConfig,
BertTokeniz... | 501 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class snake_case ( pl.LightningModule ):
"""simple docstring"""
def __init... | 675 | 0 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
lowerCamelCase : Any =42
lowerCamelCase : Optional[Any] =None
lowerCamelCase :... | 651 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : Optional[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""... | 675 | 0 |
'''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,
convert_to_rgb,
get_resize_output_image_size,
normalize,
re... | 143 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ : Any = get_tests_dir("""fixture... | 675 | 0 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
_a : Optional[int] = HfArgumentParser(InitializationArguments)
_a : str = parser.par... | 689 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class snake_case ( l... | 675 | 0 |
from __future__ import annotations
import math
from collections import Counter
from string import ascii_lowercase
def UpperCAmelCase__ ( lowerCamelCase_ : str ):
__a , __a : Optional[int] = analyze_text(UpperCAmelCase_ )
__a : ... | 47 |
'''simple docstring'''
import os
import sys
import unittest
a_ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import c... | 675 | 0 |
from __future__ import annotations
from typing import Generic, TypeVar
_UpperCamelCase = TypeVar("T")
class __lowercase (Generic[T] ):
def __init__( self , A_ ) ->str:
'''simple docstring'''
__lowerCAmelCase : Optional[Any] = data
__lowerCA... | 492 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=lowercase ):
"""simple docstring"""
_lowerCamelCase = ["onnx"]
def __init__( self , *UpperCamelCase , **Up... | 675 | 0 |
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/confi... | 291 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 675 | 0 |
import os
from collections.abc import Iterator
def a_ ( _A = "." ) -> Any:
"""simple docstring"""
for dir_path, dir_names, filenames in os.walk(UpperCAmelCase_ ):
snake_case__ = [d for d in dir_names if d != 'scripts' and d[0] not in '._']
... | 328 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
a_ : int = """docs/source/en/_toctree.yml"""
def __snake_case ( UpperCAmelCase_ : Optional[int] ):
lowerCamelCase_ = defaultdict(UpperCAmelCase_ )
lowerCamel... | 675 | 0 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def lowercase ( SCREAMING_SNAKE_CASE__ : List[Any] ) -> Union[str, Any]:
_snake_case... | 477 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __snake_case ( UpperCAmelCase_ : List[Any] , UpperCAmelCase_ : Dict , UpperCAmelCase_ ... | 675 | 0 |
'''simple docstring'''
import argparse
import json
import re
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
MobileNetVaConfig,
MobileNetVaForImageClassification,
MobileNetV... | 368 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ ... | 675 | 0 |
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class lowerCamelCase__ ( pl.LightningModule ):
"""simple docstring"""
def __init__( self , snake_case ):
... | 551 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...... | 675 | 0 |
'''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... | 501 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer i... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__UpperCAmelCase = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""tokenization_ctrl""": ["""CTRLTokenizer"""... | 651 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_t... | 675 | 0 |
'''simple docstring'''
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
A_ = """src/transformers"""
A_ ... | 143 |
'''simple docstring'''
from arguments import InitializationArguments
from transformers import AutoConfig, AutoModelForCausalLM, AutoTokenizer, HfArgumentParser
# Configuration
a_ : Optional[int] = HfArgumentParser(InitializationArguments)
a_ : str = parser.pa... | 675 | 0 |
'''simple docstring'''
from typing import Optional, Union
import torch
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithPoolingAndNoAttention, ImageClassifierOutputWithNoAttention
fr... | 689 |
'''simple docstring'''
# Lint as: python3
import os
import re
import urllib.parse
from pathlib import Path
from typing import Callable, List, Optional, Union
from zipfile import ZipFile
from ..utils.file_utils import cached_path, hf_github_url
from ..utils.logging import get_logger
from ..utils.vers... | 675 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE__ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE__ = {
"""unc-nlp/lxmert-base-uncased""": """https://huggingface.co/unc-nlp/lxmert-base-uncased/resolve/main/config.j... | 47 |
'''simple docstring'''
import os
def __snake_case ( UpperCAmelCase_ : str = "matrix.txt" ):
with open(os.path.join(os.path.dirname(UpperCAmelCase_ ) , UpperCAmelCase_ ) ) as in_file:
lowerCamelCase_ = in_file.read()
lowerCamelCase_ = [[int(Upp... | 675 | 0 |
import numpy as np
from cva import COLOR_BGR2GRAY, cvtColor, imread
from numpy import array, uinta
from PIL import Image
from digital_image_processing import change_contrast as cc
from digital_image_processing import convert_to_negative as cn
from digital_image_processing import sepia as sp
from digital_image_proces... | 492 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)... | 675 | 0 |
import argparse
import torch
from transformers import (
UniSpeechSatConfig,
UniSpeechSatForAudioFrameClassification,
UniSpeechSatForSequenceClassification,
UniSpeechSatForXVector,
WavaVecaFeatureExtractor,
logging,
)
logging.set_verbosity_info()
lowercase_ = logg... | 291 |
'''simple docstring'''
from collections import defaultdict
from pathlib import Path
import pandas as pd
from rouge_cli import calculate_rouge_path
from utils import calculate_rouge
a_ : Any = [
"""Prosecutor: \"No videos were used in the crash investigation\" German paper... | 675 | 0 |
from __future__ import annotations
import random
# Maximum size of the population. Bigger could be faster but is more memory expensive.
__UpperCamelCase : Optional[int] = 200
# Number of elements selected in every generation of evolution. The selection takes
# place from best to ... | 328 |
'''simple docstring'''
import argparse
import torch
from transformers import (
EncodecConfig,
EncodecFeatureExtractor,
EncodecModel,
logging,
)
# checkpoints downloaded from:
# https://dl.fbaipublicfiles.com/encodec/v0/encodec_24khz-d7cc33bc.th
# https://huggingface.co/faceboo... | 675 | 0 |
import inspect
import unittest
from typing import List
import numpy as np
from transformers import EfficientFormerConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configur... | 477 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class snake_case ( lowercase ):
"""... | 675 | 0 |
'''simple docstring'''
def __lowerCamelCase ( ) ->List[str]:
return [list(range(10_00 - i , -10_00 - i , -1 ) ) for i in range(10_00 )]
a__ : Any = generate_large_matrix()
a__ : Optional[Any] = (
[[4, 3, 2,... | 368 |
'''simple docstring'''
def __snake_case ( ):
lowerCamelCase_ = [31, 28, 31, 30, 31, 30, 31, 31, 30, 31, 30, 31]
lowerCamelCase_ = 6
lowerCamelCase_ = 1
lowerCamelCase_ = 1901
lowerCamelCase_ = 0
while year < 2001:
day += 7
if (year % 4 == 0 an... | 675 | 0 |
from statistics import mean, stdev
def UpperCamelCase_( _A :list , _A :int = 3 )-> int:
UpperCamelCase__ = min(UpperCAmelCase_ )
UpperCamelCase__ = max(UpperCAmelCase_ )
# normalize data
return [round((x - x_min) / (x_max - x_min) , UpperCAmelCase_ ) for x in... | 551 |
'''simple docstring'''
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
a_ : Optional[int] = logging.get_logger(__name__)
a_ : Dict = {
"""SenseTime/deformable-detr""": """h... | 675 | 0 |
'''simple docstring'''
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.... | 501 |
'''simple docstring'''
import argparse
import pytorch_lightning as pl
import torch
from torch import nn
from transformers import LongformerForQuestionAnswering, LongformerModel
class snake_case ( pl.LightningModule ):
"""simple docstring"""
def __init... | 675 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
__UpperCAmelCase = {
"""configuration_layoutlmv2""": ["""LAYOUTLMV2_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 651 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
a_ : Optional[Any] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"""... | 675 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
A_ = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": (
"""https:... | 143 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
a_ : Any = get_tests_dir("""fixture... | 675 | 0 |
'''simple docstring'''
import argparse
from transformers import CLIPImageProcessor, CLIPVisionModelWithProjection
from diffusers import UnCLIPImageVariationPipeline, UnCLIPPipeline
if __name__ == "__main__":
_a : int = argparse.ArgumentParser()
parser.add_argument("""--dump_pat... | 689 |
'''simple docstring'''
import warnings
from typing import List
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import is_flax_available, is_tf_available, is_torch_available
class snake_case ( l... | 675 | 0 |
import importlib
import json
import os
from collections import OrderedDict
from typing import Dict, Optional, Union
# Build the list of all image processors
from ...configuration_utils import PretrainedConfig
from ...dynamic_module_utils import get_class_from_dynamic_module, resolve_trust_remote_... | 47 |
'''simple docstring'''
import os
import sys
import unittest
a_ : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, """utils"""))
import check_dummies # noqa: E402
from check_dummies import c... | 675 | 0 |
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class __lowercase (_UpperCAmelCase ):
def __init__( self , A_ , A_ = None , A_ = None... | 492 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class snake_case ( metaclass=lowercase ):
"""simple docstring"""
_lowerCamelCase = ["onnx"]
def __init__( self , *UpperCamelCase , **Up... | 675 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class __lowerCAmelCase ( SCREAMING_SNAKE_CASE ):
_... | 291 |
'''simple docstring'''
from __future__ import annotations
import unittest
import numpy as np
from transformers import LayoutLMConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common impor... | 675 | 0 |
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import flax
import jax
import jax.numpy as jnp
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils_flax import (
CommonSchedulerState,
FlaxKarrasDiffusionSchedulers,
Fl... | 328 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
a_ : int = """docs/source/en/_toctree.yml"""
def __snake_case ( UpperCAmelCase_ : Optional[int] ):
lowerCamelCase_ = defaultdict(UpperCAmelCase_ )
lowerCamel... | 675 | 0 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common ... | 477 |
'''simple docstring'''
import fire
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoTokenizer
from utils import SeqaSeqDataset, pickle_save
def __snake_case ( UpperCAmelCase_ : List[Any] , UpperCAmelCase_ : Dict , UpperCAmelCase_ ... | 675 | 0 |
'''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_modeli... | 368 |
'''simple docstring'''
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ = ""
for ch in key:
if ch == " " or ch not in key_no_dups and ch.isalpha():
key_no_dups += ch
return key_no_dups
def __snake_case ( UpperCAmelCase_ : str ):
lowerCamelCase_ ... | 675 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
__UpperCamelCase = datasets.utils.logging.get_logge... | 551 |
'''simple docstring'''
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...... | 675 | 0 |
'''simple docstring'''
import json
import os
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing... | 501 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from tokenizers.pre_tokenizers import BertPreTokenizer, PreTokenizer
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_roformer i... | 675 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def snake_case_ (__A : str , __A : str , **__A : Optional[Any] ) -> int:
__lowerCAmelCase : Optional[int] = AutoConfig.from_pretrained(UpperCAmelCase_ , **UpperCAmelCas... | 651 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ConvNextConfig, UperNetConfig
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_device
from transformers.utils import is_t... | 675 | 0 |
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