code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import VOCAB_FILES_NAMES, BertTokenizer
from transformers.testing_utils import... | 41 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 276 | 0 |
'''simple docstring'''
import math
class __UpperCAmelCase :
def lowerCamelCase ( self , lowerCAmelCase_ , lowerCAmelCase_ ):
"""simple docstring"""
_snake_case = 0.0
_snake_case = 0.0
for i in range(len(lower... | 42 |
'''simple docstring'''
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> dict:
_a : Any =F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(_UpperCAmelCa... | 276 | 0 |
from math import pi
def lowerCamelCase ( SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ):
'''simple docstring'''
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 10))
| 43 |
'''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... | 276 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_a : Union[str, Any] = {
'configuration_megatron_bert': ['MEGATRON_BERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MegatronBertConfig'],
}
try:
if not is_... | 44 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 276 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_dpt import DPTImageProcessor
lowercase_ = logging.get_logger(__name__)
class __lowerCAmelCase ( __SCREAMING_SNAKE_CASE ):
'''simple docstring'''
def __init__( sel... | 45 |
'''simple docstring'''
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 ,isqrt(_UpperCAmelCase ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 10**6 ) -... | 276 | 0 |
"""simple docstring"""
import unittest
from transformers import is_vision_available
from transformers.pipelines import pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common ... | 46 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F40... | 276 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
lowerCamelCase : Optional[int] = {
"configuration_roformer": ["ROF... | 47 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" ,[
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""... | 276 | 0 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized, parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
... | 48 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Tuple = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/reso... | 276 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case :Any = logging.get_logger(__name__)
__snake_case :Tuple = {
'''microsoft/markuplm-base''': '''https://huggingface.co/microsoft/markuplm-base/resolve/main/config.json''',
'''micros... | 49 |
'''simple docstring'''
class A__ :
def __init__( self :List[str] ) -> List[Any]:
'''simple docstring'''
_a : Tuple =0
_a : Any =0
_a : int ={}
... | 276 | 0 |
from unittest.mock import Mock, patch
from file_transfer.send_file import send_file
@patch('socket.socket' )
@patch('builtins.open' )
def SCREAMING_SNAKE_CASE ( _UpperCAmelCase , _UpperCAmelCase ) -> Tuple:
# ===== initialization =====
lowerCamelCase__ : Union[str, ... | 50 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
A__: Union[str, Any] = input('''Enter image url: ''').strip()
print(F"Downloading image from {url} ...")
A__: Tuple = Be... | 276 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import is_flaky, 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 is_torch_a... | 51 |
'''simple docstring'''
A__: Tuple = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+http... | 276 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( __snake_case ):
def __init__( self , A_ , A_ ):
'''simple docstring'''
UpperCamelCase : List[str] = params
UpperC... | 52 |
'''simple docstring'''
A__: Optional[int] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: Any = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: int = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''T... | 276 | 0 |
'''simple docstring'''
from math import factorial
class snake_case :
"""simple docstring"""
def __init__( self : List[str] , __A : Any , __A : Tuple ):
__UpperCamelCase = real
if isinstance(__A , __A ):
... | 53 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A__ ( UpperCAmelCase__ ):
__UpperCamelCase : str
__UpperCamelCase : int
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> li... | 276 | 0 |
"""simple docstring"""
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
a__ : Optional[int] = [
# (stable-diffusion, HF Diffusers)
('''time_embed.0.weight'... | 54 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A__: List[str] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_M... | 276 | 0 |
'''simple docstring'''
import torch
def __snake_case ( ):
if torch.cuda.is_available():
lowerCamelCase_ = torch.cuda.device_count()
else:
lowerCamelCase_ = 0
print(F'''Successfully ran on {num_gpus} GPUs''' )
if __name__ == "__main__":
main()
| 55 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] ) -> None:
'''simple docstring'''
_a : dict[str, TrieNode] ={} # Mapping from char to TrieNode
_a : List[str] =False
... | 276 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, ... | 56 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A__: str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 276 | 0 |
"""simple docstring"""
from typing import List, Union
import numpy as np
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging, requires_backends
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_i... | 57 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as ... | 276 | 0 |
'''simple docstring'''
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,... | 58 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__: int = ... | 276 | 0 |
from __future__ import annotations
from typing import Any
class UpperCAmelCase :
def __init__(self : str , snake_case__ : int ) -> None:
'''simple docstring'''
snake_case : str = num_of_nodes
snake_case :... | 59 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :Union[str, Any] , SCREAMING_SNAKE_CASE :str , SCREAMING_SNAKE_CASE :str ) -> Optional[int]:
'''simple docstring''... | 276 | 0 |
"""simple docstring"""
from __future__ import annotations
import copy
import inspect
import unittest
import numpy as np
from transformers import is_tf_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from transformers.utils... | 60 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e... | 276 | 0 |
"""simple docstring"""
from collections import namedtuple
_a = namedtuple('from_to', 'from_ to')
_a = {
'cubicmeter': from_to(1, 1),
'litre': from_to(0.001, 1_000),
'kilolitre': from_to(1, 1),
'gallon': from_to(0.0_0454, 264.172),
'cubicyard': from_to(0.7_6455, 1.... | 61 |
'''simple docstring'''
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sq... | 276 | 0 |
import argparse
import torch
from ...utils import logging
from . import AlbertConfig, AlbertForPreTraining, load_tf_weights_in_albert
logging.set_verbosity_info()
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : Optional[Any] , SCREAMING_SNAKE_CASE... | 62 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: List[str] = logging.get_logger(__name__)
A__: Union[str, Any] ... | 276 | 0 |
'''simple docstring'''
def _lowerCamelCase ( lowercase : float , lowercase : int ) -> float:
if digit_amount > 0:
return round(number - int(lowercase ) , lowercase )
return number - int(lowercase )
if __name__ == "__main__":
... | 63 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 276 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
A_ = {
'''configuration_xlm''': ['''XLM_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''XLMConfig''', '''XLMOnnxConfig'''],
'''token... | 64 |
'''simple docstring'''
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> dict:
_a : Any =F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(_UpperCAmelCa... | 276 | 0 |
import math
def lowerCAmelCase_ ( __A ) -> bool:
'''simple docstring'''
return math.sqrt(__A ) * math.sqrt(__A ) == num
def lowerCAmelCase_ ( __A ) -> bool:
'''simple docstring'''
UpperC... | 65 |
'''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... | 276 | 0 |
"""simple docstring"""
def A_ ( _lowercase = 50 ):
'''simple docstring'''
snake_case_ :Dict = [1] * (length + 1)
for row_length in range(3, length + 1 ):
for block_length in range(3, row_length + 1 ):
for block_start in range(row_length ... | 66 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 276 | 0 |
'''simple docstring'''
import builtins
import sys
from ...utils.imports import _is_package_available
from . import cursor, input
from .helpers import Direction, clear_line, forceWrite, linebreak, move_cursor, reset_cursor, writeColor
from .keymap import KEYMAP
__UpperCAmelCase =False
try:
__UpperCAm... | 67 |
'''simple docstring'''
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 ,isqrt(_UpperCAmelCase ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 10**6 ) -... | 276 | 0 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: int = 6_0_0_8_5_1_4_7_5_1_4_3 ) -> int:
'''simple docstring'''
try:
A__ = int(SCREAMING_SNAKE_CASE_ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )... | 68 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F40... | 276 | 0 |
"""simple docstring"""
import json
import os
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import MgpstrTokenizer
from transformers.models.mgp_str.tokenization_mgp_str import VOCAB_FILES_NAMES
from transformers.testing_utils import require_torch, require_vision
fro... | 69 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" ,[
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""... | 276 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
A__ : List[str] =logging.get_logger(__name__)
... | 70 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Tuple = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/reso... | 276 | 0 |
def A ( a_ ) -> int:
if not isinstance(a_ ,a_ ):
raise ValueError('multiplicative_persistence() only accepts integral values' )
if num < 0:
raise ValueError('multiplicative_persistence() does not accept negative values' )
... | 71 |
'''simple docstring'''
class A__ :
def __init__( self :List[str] ) -> List[Any]:
'''simple docstring'''
_a : Tuple =0
_a : Any =0
_a : int ={}
... | 276 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
lowerCAmelCase__ = {'''configuration_vit_mae''': ['''VIT_MAE_PRETRAINED_CONFIG_ARCHIVE_MAP''', ... | 72 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
A__: Union[str, Any] = input('''Enter image url: ''').strip()
print(F"Downloading image from {url} ...")
A__: Tuple = Be... | 276 | 0 |
from __future__ import annotations
from collections.abc import Callable
from typing import Any, Generic, TypeVar
a =TypeVar("""T""")
class A_ ( Generic[T] ):
def __init__( self : List[str] ,SCREAMING_SNAKE_CASE__ : list[T] ,SCREAMING_SNAKE_CASE__ : Callabl... | 73 |
'''simple docstring'''
A__: Tuple = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+http... | 276 | 0 |
"""simple docstring"""
import argparse
import json
import subprocess
def _snake_case ( snake_case__ : str , snake_case__ : List[Any] ):
A = []
A = (
F'curl -H "Accept: application/vnd.github+json" -H "Authorization: Bearer {token}"'
' https://... | 74 |
'''simple docstring'''
A__: Optional[int] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: Any = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: int = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''T... | 276 | 0 |
'''simple docstring'''
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
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_con... | 75 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A__ ( UpperCAmelCase__ ):
__UpperCamelCase : str
__UpperCamelCase : int
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> li... | 276 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
loggin... | 76 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A__: List[str] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_M... | 276 | 0 |
"""simple docstring"""
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCAmelCase_ ( _a):
lowerCamelCase__ : List[str] = ["image_processor", "tokenizer"]
lowerCamelCase__ : List[str] = "CLIPImageProce... | 77 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] ) -> None:
'''simple docstring'''
_a : dict[str, TrieNode] ={} # Mapping from char to TrieNode
_a : List[str] =False
... | 276 | 0 |
"""simple docstring"""
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as bnb
... | 78 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A__: str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 276 | 0 |
'''simple docstring'''
import argparse
import json
import os
from tensorflow.core.protobuf.saved_model_pba import SavedModel
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_copies.py
lowerCamelCase_ = '''.'''
# ... | 79 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as ... | 276 | 0 |
'''simple docstring'''
import platform
from argparse import ArgumentParser
import huggingface_hub
from .. import __version__ as version
from ..utils import is_accelerate_available, is_torch_available, is_transformers_available, is_xformers_available
from . import BaseDiffusersCLICommand
def _UpperCam... | 80 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__: int = ... | 276 | 0 |
"""simple docstring"""
lowerCamelCase_ : Any = [
"""DownloadConfig""",
"""DownloadManager""",
"""DownloadMode""",
"""StreamingDownloadManager""",
]
from .download_config import DownloadConfig
from .download_manager import DownloadManager, DownloadMode
from .st... | 81 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :Union[str, Any] , SCREAMING_SNAKE_CASE :str , SCREAMING_SNAKE_CASE :str ) -> Optional[int]:
'''simple docstring''... | 276 | 0 |
import os
import unittest
from transformers import BertTokenizerFast
from transformers.models.bert.tokenization_bert import (
VOCAB_FILES_NAMES,
BasicTokenizer,
BertTokenizer,
WordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import requ... | 82 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e... | 276 | 0 |
'''simple docstring'''
import tempfile
import unittest
import numpy as np
from huggingface_hub import HfFolder, delete_repo
from requests.exceptions import HTTPError
from transformers import BertConfig, is_flax_available
from transformers.testing_utils import TOKEN, USER, is_staging_test, require_flax
if is_fla... | 83 |
'''simple docstring'''
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sq... | 276 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin,... | 84 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: List[str] = logging.get_logger(__name__)
A__: Union[str, Any] ... | 276 | 0 |
'''simple docstring'''
import json
import pathlib
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision, slow
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, ... | 85 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 276 | 0 |
"""simple docstring"""
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
neste... | 86 |
'''simple docstring'''
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> dict:
_a : Any =F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(_UpperCAmelCa... | 276 | 0 |
import json
import os
import unittest
from transformers.models.roc_bert.tokenization_roc_bert import (
VOCAB_FILES_NAMES,
RoCBertBasicTokenizer,
RoCBertTokenizer,
RoCBertWordpieceTokenizer,
_is_control,
_is_punctuation,
_is_whitespace,
)
from transformers.testing_utils import r... | 87 |
'''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... | 276 | 0 |
def a__ ( A_ = 10**9 ):
'''simple docstring'''
__magic_name__ = 1
__magic_name__ = 2
__magic_name__ = 0
__magic_name__ = 0
__magic_name__ = 0
while perimeter <= max_perimeter:
perimeter... | 88 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 276 | 0 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 89 |
'''simple docstring'''
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 ,isqrt(_UpperCAmelCase ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 10**6 ) -... | 276 | 0 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from t... | 90 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F40... | 276 | 0 |
"""simple docstring"""
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise Optio... | 91 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" ,[
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""... | 276 | 0 |
from queue import PriorityQueue
from typing import Any
import numpy as np
def _a ( SCREAMING_SNAKE_CASE_ : dict , SCREAMING_SNAKE_CASE_ : str , SCREAMING_SNAKE_CASE_ : set , SCREAMING_SNAKE_CASE_ : set , SCREAMING_SNAKE_... | 92 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Tuple = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/reso... | 276 | 0 |
'''simple docstring'''
from __future__ import annotations
import requests
def snake_case_ ( __SCREAMING_SNAKE_CASE : str ):
"""simple docstring"""
lowercase_ : Any = F'''https://hacker-news.firebaseio.com/v0/item/{story_id}.json... | 93 |
'''simple docstring'''
class A__ :
def __init__( self :List[str] ) -> List[Any]:
'''simple docstring'''
_a : Tuple =0
_a : Any =0
_a : int ={}
... | 276 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
DiffusionPipeline,
... | 94 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
A__: Union[str, Any] = input('''Enter image url: ''').strip()
print(F"Downloading image from {url} ...")
A__: Tuple = Be... | 276 | 0 |
from typing import Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import get_image_size, pad, rescale, to_channel_dimension_format
from ...image_utils import ChannelDimension, ImageInput, make_list_of_images, to_nump... | 95 |
'''simple docstring'''
A__: Tuple = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+http... | 276 | 0 |
"""simple docstring"""
import json
import os
import re
import shutil
import tempfile
import unittest
from typing import Tuple
from transformers import AddedToken, BatchEncoding, PerceiverTokenizer
from transformers.utils import cached_property, is_tf_available, is_torch_available
fro... | 96 |
'''simple docstring'''
A__: Optional[int] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: Any = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: int = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''T... | 276 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = {
'''google/vivit-b-16x2-kinetics400''': (
'''https://huggingface.co/google/vivit-b-16x2-kinetics400/resolv... | 97 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A__ ( UpperCAmelCase__ ):
__UpperCamelCase : str
__UpperCamelCase : int
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> li... | 276 | 0 |
"""simple docstring"""
from __future__ import annotations
import queue
class snake_case :
"""simple docstring"""
def __init__( self : int ,lowerCamelCase__ : List[str] ):
UpperCAmelCase__ = data
UpperCAmelCase__ = None
... | 98 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A__: List[str] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_M... | 276 | 0 |
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 import IterableDatasetDict
fro... | 99 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] ) -> None:
'''simple docstring'''
_a : dict[str, TrieNode] ={} # Mapping from char to TrieNode
_a : List[str] =False
... | 276 | 0 |
"""simple docstring"""
import argparse
import json
from dataclasses import dataclass, field
from functools import partial
from pathlib import Path
from typing import List
import timm
import torch
import torch.nn as nn
from huggingface_hub import hf_hub_download
from torch import Tensor
from transformers import ... | 100 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A__: str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 276 | 0 |
import itertools
from dataclasses import dataclass
from typing import Any, Callable, Dict, List, Optional, Union
import pandas as pd
import pyarrow as pa
import datasets
import datasets.config
from datasets.features.features import require_storage_cast
from datasets.table import table_cast
from datasets.utils.py_uti... | 101 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as ... | 276 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE : Dict = logging.get_logger(__name__)
SCREAMING_S... | 102 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__: int = ... | 276 | 0 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedKV... | 103 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :Union[str, Any] , SCREAMING_SNAKE_CASE :str , SCREAMING_SNAKE_CASE :str ) -> Optional[int]:
'''simple docstring''... | 276 | 0 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Audio, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCamelCase__ )
class lowercase_ (lowerCamelCase__ ):
"""simple docstring"""
... | 104 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e... | 276 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
a : Optional[Any] ... | 105 |
'''simple docstring'''
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sq... | 276 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
from transformers import AutoTokenizer, MBartConfig, is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configur... | 106 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: List[str] = logging.get_logger(__name__)
A__: Union[str, Any] ... | 276 | 0 |
from collections import Counter
import numpy as np
from sklearn import datasets
from sklearn.model_selection import train_test_split
__lowerCAmelCase : Any = datasets.load_iris()
__lowerCAmelCase : List[Any] = np.array(data['data'])
__lowerCAmelCase : List[str] = np.arr... | 107 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 276 | 0 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : list ):
'''simple docstring'''
if len(SCREAMING_SNAKE_CASE ) < 2:
return collection
def circle_sort_util(SCREAMING_SNAKE_CASE : list , SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE... | 108 |
'''simple docstring'''
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> dict:
_a : Any =F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(_UpperCAmelCa... | 276 | 0 |
"""simple docstring"""
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch
if is_torch_available():
import torch
from transformers.generation import DisjunctiveConstraint
@require_torch
class SCREAMING_SNAKE_CASE__ ( unittest... | 109 |
'''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... | 276 | 0 |
import contextlib
import faulthandler
import io
import multiprocessing
import os
import platform
import signal
import tempfile
def SCREAMING_SNAKE_CASE_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ ) -> Tuple:
lowerCAmelCase = multiprocessing.Manager()
... | 338 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 276 | 0 |
from typing import List, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
'''huggingface/time-series-transformer-tourism-monthly''': (
'''https://huggingface.co/huggi... | 92 |
'''simple docstring'''
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 ,isqrt(_UpperCAmelCase ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 10**6 ) -... | 276 | 0 |
import collections
import os
import re
from pathlib import Path
A_ : str = '''src/transformers'''
# Matches is_xxx_available()
A_ : List[str] = re.compile(r'is\_([a-z_]*)_available()')
# Catches a one-line _import_struct = {xxx}
A_ : Optional[int] = re.compile(r'^_i... | 192 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F40... | 276 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
__lowerCamelCase : List[str] = {'''configuration_opt''': ['''OPT_PRETRAINED_CONFIG_ARCH... | 52 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" ,[
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""... | 276 | 0 |
"""simple docstring"""
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
Autoencode... | 64 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Tuple = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/reso... | 276 | 0 |
"""simple docstring"""
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... | 264 |
'''simple docstring'''
class A__ :
def __init__( self :List[str] ) -> List[Any]:
'''simple docstring'''
_a : Tuple =0
_a : Any =0
_a : int ={}
... | 276 | 0 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__snake_case = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
if not is_... | 310 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
A__: Union[str, Any] = input('''Enter image url: ''').strip()
print(F"Downloading image from {url} ...")
A__: Tuple = Be... | 276 | 0 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from ..utils import logging
from . import BaseTransformersCLICommand
def A ( snake_case :Namespace ) -> Union[str, Any]:
return ConvertCommand(
args.model_type , args.tf_checkpoint , args.pytorch... | 316 |
'''simple docstring'''
A__: Tuple = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+http... | 276 | 0 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis_float32 (there's also the fix_lavis branch)
# also note: to convert Vicuna checkpoints, we had to include /home/... | 340 |
'''simple docstring'''
A__: Optional[int] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: Any = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: int = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''T... | 276 | 0 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyImgaImgPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from... | 190 |
'''simple docstring'''
from __future__ import annotations
from typing import TypedDict
class A__ ( UpperCAmelCase__ ):
__UpperCamelCase : str
__UpperCamelCase : int
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> li... | 276 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE, ReformerTokenizer, ReformerTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Tokenizer... | 124 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A__: List[str] = {
'''configuration_chinese_clip''': [
'''CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_M... | 276 | 0 |
class lowercase_ :
"""simple docstring"""
def __init__( self ) ->None:
lowerCAmelCase = {} # Mapping from char to TrieNode
lowerCAmelCase = False
def SCREAMING_SNAKE_CASE_ ( self , __SCREAMING_SNAKE_CASE ) ->None:
for w... | 338 |
'''simple docstring'''
class A__ :
def __init__( self :List[Any] ) -> None:
'''simple docstring'''
_a : dict[str, TrieNode] ={} # Mapping from char to TrieNode
_a : List[str] =False
... | 276 | 0 |
def _a ( SCREAMING_SNAKE_CASE_ : str ):
__lowerCAmelCase = [0 for i in range(len(_UpperCAmelCase ) )]
# initialize interval's left pointer and right pointer
__lowerCAmelCase = 0, 0
for i in range(1 , len(_UpperCAmelCase ) ... | 92 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_sentencepiece_available
A__: str = {}
try:
if not is_sentencepiece_available():
raise OptionalDependencyNotAvailable()
except Optional... | 276 | 0 |
import logging
import os
from .state import PartialState
class _a (logging.LoggerAdapter ):
'''simple docstring'''
@staticmethod
def __A ( A__ ):
A__ : List[Any] = PartialState()
return not main_process_only or (main_process_only and state.is_m... | 192 |
'''simple docstring'''
import importlib.metadata
import warnings
from copy import deepcopy
from packaging import version
from ..utils import logging
from .import_utils import is_accelerate_available, is_bitsandbytes_available
if is_bitsandbytes_available():
import bitsandbytes as ... | 276 | 0 |
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,
BertTokenizer,
BertTokenizerFast,
... | 52 |
'''simple docstring'''
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
A__: int = ... | 276 | 0 |
"""simple docstring"""
import numpy as np
def UpperCAmelCase__ (snake_case__ : np.ndarray , snake_case__ : float ):
"""simple docstring"""
return np.where(vector > 0 , _UpperCAmelCase , (alpha * (np.exp(_UpperCAmelCase ) - 1)) )
if __name... | 64 |
'''simple docstring'''
from __future__ import annotations
class A__ :
def __init__( self :Union[str, Any] , SCREAMING_SNAKE_CASE :str , SCREAMING_SNAKE_CASE :str ) -> Optional[int]:
'''simple docstring''... | 276 | 0 |
"""simple docstring"""
from __future__ import annotations
def __lowercase ( _a , _a , _a , ):
if (electron_conc, hole_conc, intrinsic_conc).count(0 ) != 1:
raise ValueError('''You cannot supply more or less than 2 values''' )
elif electron_conc < 0:
raise ValueErr... | 264 |
'''simple docstring'''
import argparse
import gc
import json
import os
import shutil
import warnings
import torch
from transformers import LlamaConfig, LlamaForCausalLM, LlamaTokenizer
try:
from transformers import LlamaTokenizerFast
except ImportError as e:
warnings.warn(e... | 276 | 0 |
import unittest
from transformers import SPIECE_UNDERLINE
from transformers.models.speechta import SpeechTaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from transformers.tokenization_utils import AddedToken
from ...test_tokenization_commo... | 310 |
'''simple docstring'''
import contextlib
import os
import sqlitea
import pytest
from datasets import Dataset, Features, Value
from datasets.io.sql import SqlDatasetReader, SqlDatasetWriter
from ..utils import assert_arrow_memory_doesnt_increase, assert_arrow_memory_increases, require_sq... | 276 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase : int = logging.get_logger(__name__)
UpperCamelCase : List[str] = {
'''microsoft/trocr-base-handwritten''': (
'''https://huggingface.co/microsoft/trocr-base-handwritten/resol... | 316 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
A__: List[str] = logging.get_logger(__name__)
A__: Union[str, Any] ... | 276 | 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,
)
a_ = {'''configuration_mbart''': ['''MBART_PRETRAINED_CONFIG_A... | 340 |
'''simple docstring'''
from typing import Dict, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import flip_channel_order, resize, to_channel_dimension_format, to_pil_image
from ...image_utils ... | 276 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ : Tuple = logging.get_logger(__name__)
lowercase__ : ... | 190 |
'''simple docstring'''
from __future__ import annotations
import requests
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : str ) -> dict:
_a : Any =F"https://hacker-news.firebaseio.com/v0/item/{story_id}.json?print=pretty"
return requests.get(_UpperCAmelCa... | 276 | 0 |
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F401
from ..controlnet.pipeline_controlnet import StableDiffusionControlNetPipeline # noqa: F401
deprecate(
'stable diffusion controlnet',
'0.22.0',
'Importing `StableDiffusionControlNetPipeline` or... | 124 |
'''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... | 276 | 0 |
from __future__ import annotations
def SCREAMING_SNAKE_CASE_ ( snake_case__ , snake_case__ , snake_case__ , snake_case__ ) -> list:
lowerCAmelCase = []
lowerCAmelCase = input_list[low:mid], input_list[mid : high + 1]
while left and right:
re... | 338 |
'''simple docstring'''
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, id... | 276 | 0 |
from collections import UserDict
from typing import Union
import numpy as np
import requests
from ..utils import (
add_end_docstrings,
logging,
)
from .audio_classification import ffmpeg_read
from .base import PIPELINE_INIT_ARGS, Pipeline
UpperCamelCase__ = logging.get_logger(__name__)
@add_end... | 92 |
'''simple docstring'''
from math import isqrt
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int ) -> bool:
return all(number % divisor != 0 for divisor in range(2 ,isqrt(_UpperCAmelCase ) + 1 ) )
def SCREAMING_SNAKE_CASE_ ( _UpperCAmelCase : int = 10**6 ) -... | 276 | 0 |
from collections.abc import Sequence
def UpperCamelCase (lowercase_: Sequence[float] , lowercase_: bool = False ) -> float:
if not arr:
return 0
A__ : Dict = 0 if allow_empty_subarrays else float("""-inf""" )
A__ : Optional[int] = 0.0
for nu... | 192 |
'''simple docstring'''
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from ...utils import deprecate
from ..controlnet.multicontrolnet import MultiControlNetModel # noqa: F40... | 276 | 0 |
from __future__ import annotations
import os
import tempfile
import unittest
from transformers import ConvBertConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, ids_tens... | 52 |
'''simple docstring'''
import pytest
from datasets.utils.sharding import _distribute_shards, _number_of_shards_in_gen_kwargs, _split_gen_kwargs
@pytest.mark.parametrize(
"""kwargs, expected""" ,[
({"""num_shards""": 0, """max_num_jobs""": 1}, []),
({"""num_shards""... | 276 | 0 |
"""simple docstring"""
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_s... | 64 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
A__: Dict = logging.get_logger(__name__)
A__: Tuple = {
'''weiweishi/roc-bert-base-zh''': '''https://huggingface.co/weiweishi/roc-bert-base-zh/reso... | 276 | 0 |
"""simple docstring"""
import inspect
import unittest
from datasets import load_dataset
from packaging import version
from transformers import BeitConfig
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_torch_multi_gpu, require_vision, slow, torch_devi... | 264 |
'''simple docstring'''
class A__ :
def __init__( self :List[str] ) -> List[Any]:
'''simple docstring'''
_a : Tuple =0
_a : Any =0
_a : int ={}
... | 276 | 0 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common i... | 310 |
'''simple docstring'''
from datetime import datetime
import requests
from bsa import BeautifulSoup
if __name__ == "__main__":
A__: Union[str, Any] = input('''Enter image url: ''').strip()
print(F"Downloading image from {url} ...")
A__: Tuple = Be... | 276 | 0 |
"""simple docstring"""
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,
)
UpperCamelCase : str = {
'''configuration_a... | 316 |
'''simple docstring'''
A__: Tuple = '''
# Installazione di Transformers
! pip install transformers datasets
# Per installare dalla fonte invece dell\'ultima versione rilasciata, commenta il comando sopra e
# rimuovi la modalità commento al comando seguente.
# ! pip install git+http... | 276 | 0 |
import random
def _a ( UpperCamelCase_ : int , UpperCamelCase_ : float , UpperCamelCase_ : bool = False ) -> dict:
"""simple docstring"""
lowerCAmelCase__ = {i: [] for i in range(_UpperCAmelCase )}
# if probability is g... | 340 |
'''simple docstring'''
A__: Optional[int] = [4, 1, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: Any = [3, 7, 7, 4, 2, 6, 4, 1, 5, 3, 7, 5]
A__: int = {
0: '''Sunday''',
1: '''Monday''',
2: '''Tuesday''',
3: '''Wednesday''',
4: '''T... | 276 | 0 |
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