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 argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
UniSpeechConfig,
UniSpeechForCTC,
UniSpeechForPreTraining,
WavaVecaFeatureExtractor,
WavaVecaPhonemeCTCTokenizer,
WavaVecaProcessor,
logging,
)
logging.s... | 700 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Union[str, Any] =["""image_processor""", """tokenizer"""]
a_ : ... | 669 | 0 |
'''simple docstring'''
import os
import shutil
from pathlib import Path
from typing import Optional, Union
import numpy as np
from huggingface_hub import hf_hub_download
from ..utils import ONNX_EXTERNAL_WEIGHTS_NAME, ONNX_WEIGHTS_NAME, is_onnx_available, logging
if is_onnx_available():
import onnx... | 701 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase_ = """http://www.mocksite.com/file1.txt"... | 669 | 0 |
import dataclasses
import re
import string
from typing import Any, Dict, Iterator, List, Mapping, Optional, Sequence, Tuple
import numpy as np
from . import residue_constants
lowerCAmelCase_ = Mapping[str, np.ndarray]
lowerCAmelCase_ = Mapping[str, Any] # Is a nested dict.
lowerCAmelCas... | 702 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""roberta-base""": """https://huggingface... | 669 | 0 |
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch
if is_tf_availab... | 703 |
from random import randint, random
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: bool = False , lowerCAmelCase: bool = False , lowerCAmelCase: int = 5 , )-> list:
_snake_case : Dict ... | 669 | 0 |
from typing import Any, Callable, Dict, List, Optional, Union
import torch
from transformers import CLIPImageProcessor, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
LMSDiscreteScheduler,
PNDMScheduler,
StableDiffusionPipeline,
... | 704 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
lowerCAmelCas... | 669 | 0 |
import qiskit
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int )-> qiskit.result.counts.Counts:
_snake_case : Any = qiskit.Aer.get_backend('aer_simulator' )
# Create a Quantum Circuit acting on the q register
_snake_case : Union[str, Any] ... | 705 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {name: getattr(transformers, name + """Fast""") for name i... | 669 | 0 |
import argparse
from argparse import Namespace
import torch
from torch import nn
from transformers import XGLMConfig, XGLMForCausalLM
def lowerCamelCase_ ( lowerCAmelCase: Dict )-> List[str]:
_snake_case : str = [
'decoder.version',
'decoder.output_projection.wei... | 706 |
def lowerCamelCase_ ( lowerCAmelCase: bytes )-> str:
return "".join([hex(lowerCAmelCase )[2:].zfill(2 ).upper() for byte in list(lowerCAmelCase )] )
def lowerCamelCase_ ( lowerCAmelCase: str )-> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/rf... | 669 | 0 |
import copy
import json
import os
import tempfile
from transformers import is_torch_available
from .test_configuration_utils import config_common_kwargs
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
def __init__( self : Tuple , UpperCam... | 707 |
import csv
import tweepy
# Twitter API credentials
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
def lowerCamelCase_ ( lowerCAmelCase: str )-> None:
# authorize twitter, initialize tweepy
_snake_... | 669 | 0 |
import random
import unittest
from torch.utils.data import BatchSampler, DataLoader, IterableDataset
from accelerate import Accelerator
from accelerate.data_loader import (
BatchSamplerShard,
DataLoaderDispatcher,
DataLoaderShard,
IterableDatasetShard,
SkipBatchSampler,
SkipDataLoader,
... | 708 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _lowerCAmelCase :
'''simple docstring'''
a_ : Optional[Union[str, Path]] =None
a_ : bool =False
a_ : bool ... | 669 | 0 |
import json
import os
import unittest
from transformers import CLIPTokenizer, CLIPTokenizerFast
from transformers.models.clip.tokenization_clip import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_tokenizers
from ...test_tokenization_common import TokenizerTesterMixin
@requir... | 709 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 669 | 0 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class _lowerCAmelCase ( unittest.TestCase ):
'''simple docstring'''
def UpperCamelCase_ ( self : Any ):
'''sim... | 710 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> list:
_snake_case : List[Any] = int(lowerCAmelCase )
if n_element < 1:
_snake_case : int = ValueError('a should be a positive number' )
raise my_error
_snake_case : Union[str, Any] ... | 669 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Any ="""timm_backbone"""
def __init__( self ... | 711 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prep... | 669 | 0 |
import importlib
import shutil
import threading
import warnings
from typing import List
import fsspec
import fsspec.asyn
from . import compression
from .hffilesystem import HfFileSystem
lowerCAmelCase_ = importlib.util.find_spec("""s3fs""") is not None
if _has_safs:
from .safilesystem import Sa... | 712 |
# 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
#
# Unless required by app... | 669 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {"""configuration_mbart""": ["""MBART_PRET... | 713 |
# Function to print upper half of diamond (pyramid)
def lowerCamelCase_ ( lowerCAmelCase: Optional[Any] )-> List[str]:
for i in range(0 , lowerCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 669 | 0 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase_ = """http://www.mocksite.com/file1.txt"... | 714 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c... | 669 | 0 |
import math
from datetime import datetime, timedelta
def lowerCamelCase_ ( lowerCAmelCase: int )-> datetime:
_snake_case : Optional[Any] = year % 19
_snake_case : List[Any] = year % 4
_snake_case : Optional[Any] = year % 7
_snake_case : ... | 715 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: bool = True , lowerCAmelCase: float = math.inf , lowerCAmelCase: float = -math.inf , lowerCAmelCase: float = math.... | 669 | 0 |
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_torch_available, is_vision_available
fr... | 716 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor imp... | 669 | 0 |
'''simple docstring'''
import timeit
import numpy as np
import datasets
from datasets.arrow_writer import ArrowWriter
from datasets.features.features import _ArrayXD
def lowerCamelCase_ ( lowerCAmelCase: Optional[int] )-> List[Any]:
def wrapper(*lowerCAmelCase: Tuple , **lowerCAme... | 717 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> int:
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
_snake_case : Union[str, Any] = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCAmelCase )
if number < 1:
_snake_... | 669 | 0 |
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transformers
from transformers... | 718 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowerCAmelCase_ = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}
... | 669 | 0 |
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
from ...tokenization_ut... | 719 |
from __future__ import annotations
from random import random
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Dict , UpperCamelCase : int | None = None ):
'''simple docstring'''
_snake_case : str = ... | 669 | 0 |
import logging
import os
import sys
from dataclasses import dataclass, field
from importlib import import_module
from typing import Dict, List, Optional, Tuple
import numpy as np
from seqeval.metrics import accuracy_score, fa_score, precision_score, recall_score
from torch import nn
from utils_ner import Split, ... | 720 |
from functools import reduce
lowerCAmelCase_ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66... | 669 | 0 |
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Union[str, Any] ="""Speech2TextFeatureExtractor"""
a_ : Union[str, Any] ... | 721 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCamelCase_ ( )-> Any:
_snake_case : List[str] = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
'path': ['test_... | 669 | 0 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
lowerCAmelCase_ = TypeVar("""T""")
class _lowerCAmelCase ( Generic[T] ):
'''simple docstring'''
a_ : deque[T] # Cache store of keys
a_ : ... | 700 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Union[str, Any] =["""image_processor""", """tokenizer"""]
a_ : ... | 669 | 0 |
'''simple docstring'''
import csv
import tweepy
# Twitter API credentials
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
def lowerCamelCase_ ( lowerCAmelCase: str )-> None:
# authorize twitter,... | 701 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase_ = """http://www.mocksite.com/file1.txt"... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int )-> float:
return base * power(lowerCAmelCase , (exponent - 1) ) if exponent else 1
if __name__ == "__main__":
print("""Raise base to the power of exponent using recursion...""")
lowerCAmelCase_ ... | 702 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""roberta-base""": """https://huggingface... | 669 | 0 |
from torch import nn
class _lowerCAmelCase ( nn.Module ):
'''simple docstring'''
def __init__( self : Union[str, Any] , UpperCamelCase : Optional[Any] , UpperCamelCase : Dict ):
'''simple docstring'''
super().__init__... | 703 |
from random import randint, random
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: bool = False , lowerCAmelCase: bool = False , lowerCAmelCase: int = 5 , )-> list:
_snake_case : Dict ... | 669 | 0 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Dict =["""image_processor""", """tokenizer"""]
a_ : Dict =... | 704 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
lowerCAmelCas... | 669 | 0 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 705 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {name: getattr(transformers, name + """Fast""") for name i... | 669 | 0 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""SenseTime/deformable-detr""": """https://huggingface.co/sensetime/deformable-detr/resol... | 706 |
def lowerCamelCase_ ( lowerCAmelCase: bytes )-> str:
return "".join([hex(lowerCAmelCase )[2:].zfill(2 ).upper() for byte in list(lowerCAmelCase )] )
def lowerCamelCase_ ( lowerCAmelCase: str )-> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/rf... | 669 | 0 |
from __future__ import annotations
def lowerCamelCase_ ( lowerCAmelCase: list )-> float:
if not nums:
raise ValueError('List is empty' )
return sum(lowerCAmelCase ) / len(lowerCAmelCase )
if __name__ == "__main__":
import doctest
doctest.testmod()
| 707 |
import csv
import tweepy
# Twitter API credentials
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
def lowerCamelCase_ ( lowerCAmelCase: str )-> None:
# authorize twitter, initialize tweepy
_snake_... | 669 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaImgaImgPipeline,
KandinskyVaaPriorPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils import floats_tensor, load_image, load_numpy, slo... | 708 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _lowerCAmelCase :
'''simple docstring'''
a_ : Optional[Union[str, Path]] =None
a_ : bool =False
a_ : bool ... | 669 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""google/m... | 709 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 669 | 0 |
import copy
import fnmatch
import json
import os
import pickle as pkl
import shutil
import sys
import tarfile
import tempfile
from collections import OrderedDict
from contextlib import contextmanager
from functools import partial
from hashlib import shaaaa
from io import BytesIO
from pathlib import Path
from url... | 710 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> list:
_snake_case : List[Any] = int(lowerCAmelCase )
if n_element < 1:
_snake_case : int = ValueError('a should be a positive number' )
raise my_error
_snake_case : Union[str, Any] ... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: bytes )-> str:
return "".join([hex(lowerCAmelCase )[2:].zfill(2 ).upper() for byte in list(lowerCAmelCase )] )
def lowerCamelCase_ ( lowerCAmelCase: str )-> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/rfc/rfc3... | 711 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prep... | 669 | 0 |
import numpy as np
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Dict ):
'''simple docstring'''
_snake_case : Any = (0, 0)
_snake_case : Any = None
_snake_case : List[Any] ... | 712 |
# 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
#
# Unless required by app... | 669 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {
"""configuration_mobilebert""": [
"""MOBILEBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 713 |
# Function to print upper half of diamond (pyramid)
def lowerCamelCase_ ( lowerCAmelCase: Optional[Any] )-> List[str]:
for i in range(0 , lowerCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 669 | 0 |
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 transformers import Au... | 714 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c... | 669 | 0 |
from collections.abc import Generator
def lowerCamelCase_ ( )-> Generator[int, None, None]:
_snake_case : Optional[Any] = 0, 1
while True:
_snake_case : str = b, a + b
yield b
def lowerCamelCase_ ( lowerCAmelCase: int = 10_00 )-> int:
_snak... | 715 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: bool = True , lowerCAmelCase: float = math.inf , lowerCAmelCase: float = -math.inf , lowerCAmelCase: float = math.... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: float )-> float:
return 10 - x * x
def lowerCamelCase_ ( lowerCAmelCase: float , lowerCAmelCase: float )-> float:
# Bolzano theory in order to find if there is a root between a and b
if equation(lowerCAmelCase ) * equation(lowerCAmelCas... | 716 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor imp... | 669 | 0 |
'''simple docstring'''
from math import ceil
from typing import List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import BatchFeature, SequenceFeatureExtractor
from ...utils import TensorType, logging
... | 717 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> int:
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
_snake_case : Union[str, Any] = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCAmelCase )
if number < 1:
_snake_... | 669 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCAmelCase_ = {
"""configuration_electra""": ["""ELECTRA_PRETRAINED_CONFIG_ARCHIVE_M... | 718 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowerCAmelCase_ = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}
... | 669 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transformers.utils.import_u... | 719 |
from __future__ import annotations
from random import random
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Dict , UpperCamelCase : int | None = None ):
'''simple docstring'''
_snake_case : str = ... | 669 | 0 |
import tempfile
import unittest
from transformers import TaConfig, is_torch_available
from transformers.testing_utils import (
require_sentencepiece,
require_tokenizers,
require_torch,
slow,
torch_device,
)
from ...generation.test_utils import GenerationTesterMixin
from ...test_modeling_comm... | 720 |
from functools import reduce
lowerCAmelCase_ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66... | 669 | 0 |
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch
if is_torch_tpu_available(check_device=... | 721 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCamelCase_ ( )-> Any:
_snake_case : List[str] = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
'path': ['test_... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: int = 50 )-> int:
_snake_case : Any = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
... | 700 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Union[str, Any] =["""image_processor""", """tokenizer"""]
a_ : ... | 669 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _lowerCAmelCase :
'''simple docstring'''
a_ : Optional[Union[str, Path]] =None
a_ : bool =Fa... | 701 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase_ = """http://www.mocksite.com/file1.txt"... | 669 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""bert-base-uncased""": """https://huggin... | 702 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""roberta-base""": """https://huggingface... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int )-> int:
return int((input_a, input_a).count(1 ) != 0 )
def lowerCamelCase_ ( )-> None:
assert or_gate(0 , 0 ) == 0
assert or_gate(0 , 1 ) == 1
assert or_gate(1 , 0 )... | 703 |
from random import randint, random
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: bool = False , lowerCAmelCase: bool = False , lowerCAmelCase: int = 5 , )-> list:
_snake_case : Dict ... | 669 | 0 |
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint
lowerCAmelCase_ ... | 704 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
lowerCAmelCas... | 669 | 0 |
import inspect
import re
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_config_docstrings.py
lowerCAmelCase_ = """src/transformers"""
# This is to make sure the... | 705 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {name: getattr(transformers, name + """Fast""") for name i... | 669 | 0 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_bert import BertTokenizer
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = ... | 706 |
def lowerCamelCase_ ( lowerCAmelCase: bytes )-> str:
return "".join([hex(lowerCAmelCase )[2:].zfill(2 ).upper() for byte in list(lowerCAmelCase )] )
def lowerCamelCase_ ( lowerCAmelCase: str )-> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/rf... | 669 | 0 |
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch_model
from transformer... | 707 |
import csv
import tweepy
# Twitter API credentials
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
def lowerCamelCase_ ( lowerCAmelCase: str )-> None:
# authorize twitter, initialize tweepy
_snake_... | 669 | 0 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Optional[int] =(CMStochasticIterativeScheduler,)
a_ : Any ... | 708 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _lowerCAmelCase :
'''simple docstring'''
a_ : Optional[Union[str, Path]] =None
a_ : bool =False
a_ : bool ... | 669 | 0 |
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
lowerCAmelCase_ = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
lowerCAmelCase_ = [file for file in filepat... | 709 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 669 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers import BertTokenizer
def lowerCamelCase_ ( lowerCAmelCase: Dict )-> Tuple:
# This defines a "chinese character" as anything in the CJK Unicode block:
# https://en.wikipedia.org/wiki/CJK_Unified_Ideogr... | 710 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> list:
_snake_case : List[Any] = int(lowerCAmelCase )
if n_element < 1:
_snake_case : int = ValueError('a should be a positive number' )
raise my_error
_snake_case : Union[str, Any] ... | 669 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptomath
from . import rabin_miller
lowerCAmelCase_ = 3
def lowerCamelCase_ ( lowerCAmelCase: int )-> int:
print('Generating primitive root of p' )
while True:
_snake_case : int = random.rand... | 711 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prep... | 669 | 0 |
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase ( metaclass=UpperCAmelCase_ ):
'''simple docstring'''
a_ : List[str] =["""torch""", """transformers""", """onnx"""]
def __init__( self : str , *UpperCamelCase ... | 712 |
# 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
#
# Unless required by app... | 669 | 0 |
import unittest
import numpy as np
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_video_inputs
if is_torch_available():
import... | 713 |
# Function to print upper half of diamond (pyramid)
def lowerCamelCase_ ( lowerCAmelCase: Optional[Any] )-> List[str]:
for i in range(0 , lowerCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: str )-> list:
if n_term == "":
return []
_snake_case : list = []
for temp in range(int(lowerCAmelCase ) ):
series.append(F"""1/{temp + 1}""" if series else '1' )
return series
if __name__ == "__main__":
lowerCAme... | 714 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c... | 669 | 0 |
from __future__ import annotations
from collections.abc import Generator
import requests
from bsa import BeautifulSoup
lowerCAmelCase_ = """https://www.indeed.co.in/jobs?q=mobile+app+development&l="""
def lowerCamelCase_ ( lowerCAmelCase: str = "mumbai" )-> Generator[tuple[str, str], Non... | 715 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: bool = True , lowerCAmelCase: float = math.inf , lowerCAmelCase: float = -math.inf , lowerCAmelCase: float = math.... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: int = 1_00 )-> int:
_snake_case : str = n * (n + 1) * (2 * n + 1) / 6
_snake_case : int = (n * (n + 1) / 2) ** 2
return int(square_of_sum - sum_of_squares )
if __name__ == "__main__":
print(F"""{solution() = }""")
... | 716 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor imp... | 669 | 0 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {name: getattr(transformers, n... | 717 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> int:
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
_snake_case : Union[str, Any] = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCAmelCase )
if number < 1:
_snake_... | 669 | 0 |
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowerCamelCase_ ( lowerCAmelCase: str , lowerCAmelCase: str , **lowerCAmelCase: Tuple )-> str:
_snake_case : List[str] = AutoConfig.from_pretrained(lowerCAmelCase , ... | 718 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowerCAmelCase_ = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}
... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: float , lowerCAmelCase: float )-> float:
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if __name__ == "__ma... | 719 |
from __future__ import annotations
from random import random
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Dict , UpperCamelCase : int | None = None ):
'''simple docstring'''
_snake_case : str = ... | 669 | 0 |
from __future__ import annotations
lowerCAmelCase_ = """Muhammad Umer Farooq"""
lowerCAmelCase_ = """MIT"""
lowerCAmelCase_ = """1.0.0"""
lowerCAmelCase_ = """Muhammad Umer Farooq"""
lowerCAmelCase_ = """contact@muhammadumerfarooq.me"""
lowerCAmelCase_ ... | 720 |
from functools import reduce
lowerCAmelCase_ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66... | 669 | 0 |
import math
import flax.linen as nn
import jax.numpy as jnp
def lowerCamelCase_ ( lowerCAmelCase: jnp.ndarray , lowerCAmelCase: int , lowerCAmelCase: float = 1 , lowerCAmelCase: float = 1 , lowerCAmelCase: float = 1.0E4 , lowerCAmelCase: bool = False , ... | 721 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCamelCase_ ( )-> Any:
_snake_case : List[str] = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
'path': ['test_... | 669 | 0 |
from PIL import Image
def lowerCamelCase_ ( lowerCAmelCase: Image , lowerCAmelCase: float )-> Image:
def brightness(lowerCAmelCase: int ) -> float:
return 1_28 + level + (c - 1_28)
if not -2_55.0 <= level <= 2_55.0:
raise ValueError('level must be between -255.0 (black) an... | 700 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
a_ : Union[str, Any] =["""image_processor""", """tokenizer"""]
a_ : ... | 669 | 0 |
'''simple docstring'''
# tests directory-specific settings - this file is run automatically
# by pytest before any tests are run
import sys
import warnings
from os.path import abspath, dirname, join
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]'... | 701 |
import json
import os
from pathlib import Path
import pytest
from datasets.download.download_config import DownloadConfig
from datasets.download.download_manager import DownloadManager
from datasets.utils.file_utils import hash_url_to_filename
lowerCAmelCase_ = """http://www.mocksite.com/file1.txt"... | 669 | 0 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, ... | 702 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""roberta-base""": """https://huggingface... | 669 | 0 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: bool = True , lowerCAmelCase: float = math.inf , lowerCAmelCase: float = -math.inf , lowerCAmelCase: float = math.... | 703 |
from random import randint, random
def lowerCamelCase_ ( lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: int , lowerCAmelCase: bool = False , lowerCAmelCase: bool = False , lowerCAmelCase: int = 5 , )-> list:
_snake_case : Dict ... | 669 | 0 |
lowerCAmelCase_ = {
"""Pillow""": """Pillow""",
"""accelerate""": """accelerate>=0.11.0""",
"""compel""": """compel==0.1.8""",
"""black""": """black~=23.1""",
"""datasets""": """datasets""",
"""filelock""": """filelock""",
"""flax""": """flax>=0.4.1""",
"""hf-doc-builder... | 704 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import PaddingStrategy, logging
from .tokenization_realm import RealmTokenizer
lowerCAmelCas... | 669 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
class lowe... | 705 |
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {name: getattr(transformers, name + """Fast""") for name i... | 669 | 0 |
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class _lowerCAmelCase :
'''simple docstring'''
a_ : int
a_ : TreeNode | None =None
a_ : TreeNode | None =None
lower... | 706 |
def lowerCamelCase_ ( lowerCAmelCase: bytes )-> str:
return "".join([hex(lowerCAmelCase )[2:].zfill(2 ).upper() for byte in list(lowerCAmelCase )] )
def lowerCamelCase_ ( lowerCAmelCase: str )-> bytes:
# Check data validity, following RFC3548
# https://www.ietf.org/rf... | 669 | 0 |
import json
import os
from datetime import date
from pathlib import Path
from tabulate import DataRow, TableFormat, tabulate
lowerCAmelCase_ = TableFormat(
lineabove=None,
linebelowheader=None,
linebetweenrows=None,
linebelow=None,
headerrow=DataRow("""""", """|""", """|"""),
... | 707 |
import csv
import tweepy
# Twitter API credentials
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
lowerCAmelCase_ = """"""
def lowerCamelCase_ ( lowerCAmelCase: str )-> None:
# authorize twitter, initialize tweepy
_snake_... | 669 | 0 |
import gc
import unittest
from parameterized import parameterized
from diffusers import FlaxUNetaDConditionModel
from diffusers.utils import is_flax_available
from diffusers.utils.testing_utils import load_hf_numpy, require_flax, slow
if is_flax_available():
import jax
import jax.numpy as jnp
... | 708 |
import copy
from dataclasses import dataclass
from pathlib import Path
from typing import Dict, Optional, Union
@dataclass
class _lowerCAmelCase :
'''simple docstring'''
a_ : Optional[Union[str, Path]] =None
a_ : bool =False
a_ : bool ... | 669 | 0 |
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Conversation
lowerCA... | 709 |
import unittest
from pathlib import Path
from tempfile import TemporaryDirectory
from transformers import AutoConfig, TFGPTaLMHeadModel, is_keras_nlp_available, is_tf_available
from transformers.models.gpta.tokenization_gpta import GPTaTokenizer
from transformers.testing_utils import require_keras_nlp, require_t... | 669 | 0 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotConfig, is_flax_available
from transformers.testing_utils import jax_device, require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common import Fl... | 710 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> list:
_snake_case : List[Any] = int(lowerCAmelCase )
if n_element < 1:
_snake_case : int = ValueError('a should be a positive number' )
raise my_error
_snake_case : Union[str, Any] ... | 669 | 0 |
from __future__ import annotations
import math
def lowerCamelCase_ ( lowerCAmelCase: float , lowerCAmelCase: int )-> float:
_snake_case : Tuple = u
for i in range(1 , lowerCAmelCase ):
_snake_case : Optional[int] = temp * (u - i)
return ... | 711 |
import json
import unittest
import numpy as np
from huggingface_hub import hf_hub_download
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, prep... | 669 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""andreasmadsen/efficient_mlm_m0.40""": (... | 712 |
# 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
#
# Unless required by app... | 669 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docstring'''
@staticmethod
@abstractmethod
def UpperCamelCase_ ( UpperCamelCase : ArgumentParser ):
'''simple docstring'''
... | 713 |
# Function to print upper half of diamond (pyramid)
def lowerCamelCase_ ( lowerCAmelCase: Optional[Any] )-> List[str]:
for i in range(0 , lowerCAmelCase ):
for _ in range(0 , n - i - 1 ): # printing spaces
print(' ' , end='' )
for _ in range(0 ... | 669 | 0 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> list:
_snake_case : List[Any] = int(lowerCAmelCase )
if n_element < 1:
_snake_case : int = ValueError('a should be a positive number' )
raise my_error
_snake_case : Union[str, Any] ... | 714 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""MIT/ast-finetuned-audioset-10-10-0.4593""": (
"""https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main/c... | 669 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""google/pegasus-large""": """https://huggingface.co/google/pegasus-large/resolve/main/config.json""",
# See all PEGASUS models at http... | 715 |
import math
import random
from typing import Any
from .hill_climbing import SearchProblem
def lowerCamelCase_ ( lowerCAmelCase: Tuple , lowerCAmelCase: bool = True , lowerCAmelCase: float = math.inf , lowerCAmelCase: float = -math.inf , lowerCAmelCase: float = math.... | 669 | 0 |
import contextlib
import importlib
import io
import unittest
import transformers
# Try to import everything from transformers to ensure every object can be loaded.
from transformers import * # noqa F406
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, require_tf, require_torch
from tran... | 716 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor imp... | 669 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
"""microsoft/trocr-base-handwritten""": (
"""https://huggingface.co/microsoft/trocr-base-handwritten/... | 717 |
def lowerCamelCase_ ( lowerCAmelCase: int )-> int:
if not isinstance(lowerCAmelCase , lowerCAmelCase ):
_snake_case : Union[str, Any] = F"""Input value of [number={number}] must be an integer"""
raise TypeError(lowerCAmelCase )
if number < 1:
_snake_... | 669 | 0 |
import tempfile
import torch
from diffusers import (
DEISMultistepScheduler,
DPMSolverMultistepScheduler,
DPMSolverSinglestepScheduler,
UniPCMultistepScheduler,
)
from .test_schedulers import SchedulerCommonTest
class _lowerCAmelCase ( UpperCAmelCase_ ):
'''simple docst... | 718 |
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from .tokenization_lxmert import LxmertTokenizer
lowerCAmelCase_ = {"""vocab_file""": """vocab.txt""", """tokenizer_file""": """tokenizer.json"""}
... | 669 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Generic, TypeVar
lowerCAmelCase_ = TypeVar("""T""")
lowerCAmelCase_ = TypeVar("""U""")
class _lowerCAmelCase ( Generic[T, U] ):
'''simple docstring'''
def __init__( ... | 719 |
from __future__ import annotations
from random import random
class _lowerCAmelCase :
'''simple docstring'''
def __init__( self : Dict , UpperCamelCase : int | None = None ):
'''simple docstring'''
_snake_case : str = ... | 669 | 0 |
import math_equivalence # From: git+https://github.com/hendrycks/math.git
import datasets
lowerCAmelCase_ = """\
@article{hendrycksmath2021,
title={Measuring Mathematical Problem Solving With the MATH Dataset},
author={Dan Hendrycks
and Collin Burns
and Saurav Kadavath
and Akul Aror... | 720 |
from functools import reduce
lowerCAmelCase_ = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""12540698747158523863050715693290963295227443043557"""
"""66... | 669 | 0 |
from typing import Optional
from torch import nn
from .transformer_ad import TransformeraDModel, TransformeraDModelOutput
class _lowerCAmelCase ( nn.Module ):
'''simple docstring'''
def __init__( self : Optional[int] , UpperCamelCase : int = 16 ... | 721 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def lowerCamelCase_ ( )-> Any:
_snake_case : List[str] = {
'repo_name': ['test_repo1', 'test_repo2', 'test_repo3'],
'path': ['test_... | 669 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCamelCase_ : Union[str, Any] = {
"""configuration_altclip""": [
"""ALTCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""AltCLIPConfig""",
... | 670 |
import warnings
from ..trainer import Trainer
from ..utils import logging
lowerCamelCase_ : Dict = logging.get_logger(__name__)
class _UpperCamelCase ( _A ):
'''simple docstring'''
def __init__( self : List[str] , snake_case_ : Tuple=None , **sn... | 670 | 1 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 670 |
import argparse
import numpy as np
import torch
from transformers import SpeechTaHifiGan, SpeechTaHifiGanConfig, logging
logging.set_verbosity_info()
lowerCamelCase_ : Optional[int] = logging.get_logger("""transformers.models.speecht5""")
def A__ ( lowerCamelCase , lower... | 670 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Optional[Any] = logging.get_logger(__name__)
lowerCamelCase_ : Tuple = {
"""facebook/nllb-moe-54B""": """https://huggingface.co/facebook/nllb-moe-54b/resolve/main/config.json""",
}
cla... | 670 |
lowerCamelCase_ : Optional[Any] = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface/transformers.git
"""
lowerCamelCase_ ... | 670 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ : Optional[int] = logging.get_logger(__name__)
lowerCamelCase_ : str = {
"""s-JoL/Open-Llama-V1""": """https://huggingface.co/s-JoL/Open-Llama-V1/blob/main/config.json""",
}
class ... | 670 |
import cva
import numpy as np
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : Dict , snake_case_ : float , snake_case_ : int ):
if k in (0.04, 0.06):
UpperCamelCase_: Union[str, Any] = k
UpperCam... | 670 | 1 |
import operator as op
def A__ ( lowerCamelCase ) -> Optional[int]:
UpperCamelCase_: Optional[int] = []
UpperCamelCase_: Optional[int] = lambda lowerCamelCase , lowerCamelCase : int(x / y ) # noqa: E731 integer division operation
UpperCame... | 670 |
import random
def A__ ( lowerCamelCase , lowerCamelCase , lowerCamelCase = False ) -> dict:
UpperCamelCase_: dict = {i: [] for i in range(lowerCamelCase )}
# if probability is greater or equal than 1, then generate a complete graph
if probability ... | 670 | 1 |
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..utils import assert_arrow_memor... | 670 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar, enable_... | 670 | 1 |
from manim import *
class _UpperCamelCase ( _A ):
'''simple docstring'''
def lowerCAmelCase__ ( self : Union[str, Any] ):
UpperCamelCase_: Tuple = Rectangle(height=0.5 , width=0.5 )
UpperCamelCase_: Dict = Rectangle(heigh... | 670 |
import os
from huggingface_hub.constants import HUGGINGFACE_HUB_CACHE, hf_cache_home
lowerCamelCase_ : Optional[int] = HUGGINGFACE_HUB_CACHE
lowerCamelCase_ : List[str] = """config.json"""
lowerCamelCase_ : Any = """diffusion_pytorch_model.bin"""
lowerCamelCase_ : Un... | 670 | 1 |
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : List[str] , snake_case_ : int , snake_case_ : Optional[Any]=None , snake_case_ : List[str]=None ):
UpperCamelCase_: List[Any] = data
UpperCamelCase_: ... | 670 |
import inspect
import os
import sys
import unittest
import accelerate
from accelerate.test_utils import execute_subprocess_async, require_tpu
class _UpperCamelCase ( unittest.TestCase ):
'''simple docstring'''
def lowerCAmelCase__ ( self : Optional[int] ):
Up... | 670 | 1 |
from collections import defaultdict
class _UpperCamelCase :
'''simple docstring'''
def __init__( self : List[str] , snake_case_ : Optional[Any] , snake_case_ : List[str] ):
UpperCamelCase_: Optional[Any] = total # total no of tasks (N)
... | 670 |
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@require_sentencepiece
@slow # see ht... | 670 | 1 |
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 _UpperCamelCase ( _A ):
'''simple docstring'''
... | 670 |
def A__ ( lowerCamelCase , lowerCamelCase ) -> int:
while second != 0:
UpperCamelCase_: Optional[Any] = first & second
first ^= second
UpperCamelCase_: Any = c << 1
return first
if __name__ == "__main__":
import doctest
... | 670 | 1 |
from __future__ import annotations
from collections.abc import Sequence
from typing import Literal
def A__ ( lowerCamelCase , lowerCamelCase ) -> str | Literal[False]:
UpperCamelCase_: Dict = list(lowerCamelCase )
UpperCamelCase_: int = list(lower... | 670 |
import logging
import os
import sys
from dataclasses import dataclass, field
from itertools import chain
from typing import Optional, Union
import datasets
import numpy as np
import torch
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
... | 670 | 1 |
from math import pow, sqrt
def A__ ( *lowerCamelCase ) -> bool:
UpperCamelCase_: Tuple = len(lowerCamelCase ) > 0 and all(value > 0.0 for value in values )
return result
def A__ ( lowerCamelCase , lowerCamelCase ) -> float | ... | 670 |
import json
import logging
import os
import sys
from pathlib import Path
import finetune_rag
from transformers.file_utils import is_apex_available
from transformers.testing_utils import (
TestCasePlus,
execute_subprocess_async,
require_ray,
require_torch_gpu,
require_torch_multi_gpu,
)
logging.... | 670 | 1 |
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