code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
'''simple docstring'''
import gc
import unittest
from transformers import CTRLConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
fr... | 489 |
from __future__ import annotations
from typing import Any
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
UpperCAmelCase__: Optional[int] = num_of_nodes
UpperCAmelCase__: list[list[int]] = []
UpperCAmel... | 113 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowerCAmelCase : Optional[Any] = logging.get_logger(__name__)
lowerCAmelCase : Dict = {
"""andr... | 214 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accelera... | 113 | 0 |
"""simple docstring"""
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
__SCREAMING_SNAKE_CASE = {1: (1, 1), 2: (2, 1), 3: (3, 1), 4: (2, 2... | 388 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : Union[str, Any] ={
"""configuration_clap""": [
"""CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
"""ClapAudioConfig""",
"""ClapConfig""",
"""C... | 113 | 0 |
import webbrowser
from sys import argv
from urllib.parse import parse_qs, quote
import requests
from bsa import BeautifulSoup
from fake_useragent import UserAgent
if __name__ == "__main__":
lowercase_ = """%20""".join(argv[1:]) if len(argv) > 1 else quote(str(input("""Search: "... | 235 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Arr... | 113 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import is_flax_available
from transformers.testing_utils import require_flax
from ..test_modeling_flax_common import ids_tensor
if is_flax_available():
import jax
import jax.numpy as jnp
f... | 103 |
import fire
from utils import calculate_rouge, save_json
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE=None ,**SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Tuple = [x.strip() for x in open(SCREAMING_SNAKE_CASE ).readlines()]
UpperCAmelCase__: Dict = [x.... | 113 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__magic_name__ = {"""configuration_vit_msn""": ["""VIT_MSN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ViTMSNConfig"""]}
try:
if not is_torch_available():
... | 232 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __UpperCamelCase ( _a ,_a ):
'''simple docstring'''
@register_to_config
def __init__( self , *,
lowerCamelCase__ = 4 ... | 113 | 0 |
import math
def lowercase__ ( _UpperCamelCase = 1_00) -> str:
"""simple docstring"""
UpperCamelCase = sum(i * i for i in range(1 , n + 1))
UpperCamelCase = int(math.pow(sum(range(1 , n + 1)) , 2))
return squ... | 280 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __UpperCamelCase ( _a ):
'''simple do... | 113 | 0 |
from timeit import timeit
UpperCAmelCase_ = {
"""MALAYALAM""": True,
"""String""": False,
"""rotor""": True,
"""level""": True,
"""A""": True,
"""BB""": True,
"""ABC""": False,
"""amanaplanacanalpanama""": True, # "a man a plan a canal panama"
}
# Ensure our t... | 2 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def _A ( SCREAMING_SNAKE_CASE ):
return input_array.reshape((input_array.size, 1) )
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SC... | 113 | 0 |
'''simple docstring'''
def UpperCamelCase_ ( ) -> Optional[int]:
"""simple docstring"""
_UpperCAmelCase : List[str] = 0
for i in range(1 , 1_001 ):
total += i**i
return str(_UpperCAmelCase )[-10:]
if __name... | 244 |
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 : int ="""src/transformers"""
# This is to make sure the ... | 113 | 0 |
import unittest
from transformers import DonutProcessor
lowerCAmelCase_ = """naver-clova-ix/donut-base"""
class A (unittest.TestCase ):
def __a ( self ) -> Optional[int]:
'''simple docstring'''
_snake_case : Any = DonutProce... | 326 |
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__ , UpperCAmelCase__: int = [], []
while len(SCREAMING_SNAKE_CASE ) > 1:
UpperCAmelCase__ , UpperCAmelCase__: str = min(SCREAMING_SNAKE_CASE ), max(SCREAMING_SNAKE_CASE )
start.append(SCREAMING_SNAK... | 113 | 0 |
__lowerCAmelCase : Tuple = """
# 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 ... | 529 |
def _A ( SCREAMING_SNAKE_CASE ): # noqa: E741
UpperCAmelCase__: int = len(SCREAMING_SNAKE_CASE )
UpperCAmelCase__: Dict = 0
UpperCAmelCase__: Optional[int] = [0] * n
UpperCAmelCase__: List[str] = [False] * n
UpperCAmelCase__: List[str] = [False] * n
de... | 113 | 0 |
'''simple docstring'''
from collections import Counter
from pathlib import Path
from typing import Optional, Tuple
import yaml
class UpperCamelCase__ ( yaml.SafeLoader ):
def __a ( self : Union[str, Any] , lowerCamelCase : Tuple ):
... | 489 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_a... | 113 | 0 |
import functools
from typing import Any
def _lowercase ( __UpperCamelCase : str , __UpperCamelCase : List[Any] ):
# Validation
if not isinstance(__UpperCamelCase , __UpperCamelCase ) or len(__UpperCamelCase ) == 0:
raise ValueError("""the string should b... | 214 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Tuple ={
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""MobileNetV2Config""",
"... | 113 | 0 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoderDecoderModel,
XLMRobert... | 388 |
_lowerCAmelCase : int ="""
# 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+https://github.com/huggingface/transformers.g... | 113 | 0 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils i... | 235 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
AutoT... | 113 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
snake_case = logging.get_logger(__name__)
snake_case = {
"""xl... | 103 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
log... | 113 | 0 |
"""simple docstring"""
from collections import OrderedDict
from ...utils import logging
from .auto_factory import _BaseAutoModelClass, _LazyAutoMapping, auto_class_update
from .configuration_auto import CONFIG_MAPPING_NAMES
__magic_name__ = logging.get_logger(__name__)
__magic_name__ = ... | 232 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EX... | 113 | 0 |
import os
import random
import sys
from . import cryptomath_module as cryptoMath # noqa: N812
from . import rabin_miller as rabinMiller # noqa: N812
def lowercase__ ( ) -> int:
"""simple docstring"""
print('Making key files...')
make_key_files('rsa' , 10... | 280 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _A ( SCREAMING_SNAKE_CASE ):
# A local function to see if a dot lands in the circle.
def is_in_circle(SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ) -> bool:
UpperCAmelCase... | 113 | 0 |
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
UpperCAmelCase... | 2 |
def _A ( SCREAMING_SNAKE_CASE ):
stooge(SCREAMING_SNAKE_CASE ,0 ,len(SCREAMING_SNAKE_CASE ) - 1 )
return arr
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ):
if i >= h:
return
# If first element is smaller than the last then swap them
if arr[i... | 113 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import MobileBertConfig, is_tf_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_... | 244 |
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Tuple = int(SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(SCREAMING_SNAKE_CASE )
UpperCAmelCase__ , UpperCAmelCase__: Union[str, Any] = divmod(SCREAMING_SNAKE_CASE ,2 ... | 113 | 0 |
import io
import itertools
import json
from dataclasses import dataclass
from typing import Optional
import pyarrow as pa
import pyarrow.json as paj
import datasets
from datasets.table import table_cast
from datasets.utils.file_utils import readline
lowerCAmelCase_ = datasets.utils.logging.get_logger(__nam... | 326 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_lowerCAmelCase : int ="""scheduler_config.json"""
class __UpperCamelCase ( _a ):
'''simple docstring'''
... | 113 | 0 |
def a__ ( A_ ):
'''simple docstring'''
__magic_name__ = [1]
__magic_name__ = 0, 0, 0
__magic_name__ = ugly_nums[ia] * 2
__magic_name__ = ugly_nums[ia] * 3
__magic_name__ = ugly_nums[ia] * 5
for _ in range(1, A_ ):
... | 529 |
import unittest
from transformers import DonutProcessor
_lowerCAmelCase : str ="""naver-clova-ix/donut-base"""
class __UpperCamelCase ( unittest.TestCase ):
'''simple docstring'''
def _UpperCAmelCase ( self ):
UpperCAmelCase__: Any = DonutProcessor.f... | 113 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
import torch.nn as nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .embeddings import GaussianFourierProjection, TimestepEmb... | 489 |
from __future__ import annotations
from typing import Any
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
UpperCAmelCase__: Optional[int] = num_of_nodes
UpperCAmelCase__: list[list[int]] = []
UpperCAmel... | 113 | 0 |
from bisect import bisect
from itertools import accumulate
def _lowercase ( __UpperCamelCase : Union[str, Any] , __UpperCamelCase : Optional[Any] , __UpperCamelCase : List[str] , __UpperCamelCase : List[str] ):
snake_case__ = sorted(zip(__UpperCamelCase , ... | 214 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accelera... | 113 | 0 |
"""simple docstring"""
import copy
import inspect
import unittest
from transformers import PretrainedConfig, SwiftFormerConfig
from transformers.testing_utils import (
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import cached_property, is_torch_available, is_visi... | 388 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : Union[str, Any] ={
"""configuration_clap""": [
"""CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
"""ClapAudioConfig""",
"""ClapConfig""",
"""C... | 113 | 0 |
import warnings
from ...utils import logging
from .image_processing_flava import FlavaImageProcessor
lowercase_ = logging.get_logger(__name__)
class SCREAMING_SNAKE_CASE (_a ):
def __init__( self : List[Any] , *a : List[Any] , **a ... | 235 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Arr... | 113 | 0 |
"""simple docstring"""
import argparse
from pathlib import Path
from typing import Dict, OrderedDict, Tuple
import torch
from audiocraft.models import MusicGen
from transformers import (
AutoFeatureExtractor,
AutoTokenizer,
EncodecModel,
MusicgenDecoderConfig,
Musi... | 103 |
import fire
from utils import calculate_rouge, save_json
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE=None ,**SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Tuple = [x.strip() for x in open(SCREAMING_SNAKE_CASE ).readlines()]
UpperCAmelCase__: Dict = [x.... | 113 | 0 |
"""simple docstring"""
from pathlib import Path
import fire
from tqdm import tqdm
def _lowerCamelCase ( UpperCAmelCase__="ro",UpperCAmelCase__="en",UpperCAmelCase__="wmt16",UpperCAmelCase__=None ) -> List[str]:
'''simple docstring'''
try:
import datasets
except (ModuleNotFound... | 232 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __UpperCamelCase ( _a ,_a ):
'''simple docstring'''
@register_to_config
def __init__( self , *,
lowerCamelCase__ = 4 ... | 113 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import AutoencoderKL, CycleDiffusionPipeline, DDIMScheduler, UNetaDConditionModel
from diffusers.utils import floats_tensor, load_image, l... | 280 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __UpperCamelCase ( _a ):
'''simple do... | 113 | 0 |
from jiwer import compute_measures
import datasets
UpperCAmelCase_ = """\
@inproceedings{inproceedings,
author = {Morris, Andrew and Maier, Viktoria and Green, Phil},
year = {2004},
month = {01},
pages = {},
title = {From WER and RIL to MER and WIL: improved evaluation measures... | 2 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def _A ( SCREAMING_SNAKE_CASE ):
return input_array.reshape((input_array.size, 1) )
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SC... | 113 | 0 |
'''simple docstring'''
from __future__ import annotations
class lowerCamelCase_ :
'''simple docstring'''
def __init__( self : int , A : Optional[Any]=None ):
_UpperCAmelCase : Union[str, Any] = data
_UpperCAmelCase : List[str] ... | 244 |
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 : int ="""src/transformers"""
# This is to make sure the ... | 113 | 0 |
import torch
from diffusers import CMStochasticIterativeScheduler
from .test_schedulers import SchedulerCommonTest
class A (_a ):
_SCREAMING_SNAKE_CASE = (CMStochasticIterativeScheduler,)
_SCREAMING_SNAKE_CASE = 10
def __a ( self , **lowercase_ ... | 326 |
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__ , UpperCAmelCase__: int = [], []
while len(SCREAMING_SNAKE_CASE ) > 1:
UpperCAmelCase__ , UpperCAmelCase__: str = min(SCREAMING_SNAKE_CASE ), max(SCREAMING_SNAKE_CASE )
start.append(SCREAMING_SNAK... | 113 | 0 |
import math
def a__ ( A_, A_ ):
'''simple docstring'''
if (
not isinstance(A_, (int, float) )
or power_factor < -1
or power_factor > 1
):
raise ValueError("""power_factor must be a valid float value between -1 and 1.""" )
return apparent_pow... | 529 |
def _A ( SCREAMING_SNAKE_CASE ): # noqa: E741
UpperCAmelCase__: int = len(SCREAMING_SNAKE_CASE )
UpperCAmelCase__: Dict = 0
UpperCAmelCase__: Optional[int] = [0] * n
UpperCAmelCase__: List[str] = [False] * n
UpperCAmelCase__: List[str] = [False] * n
de... | 113 | 0 |
'''simple docstring'''
import os
from math import logaa
def _lowerCamelCase (__lowerCamelCase : Optional[int] = "base_exp.txt" ) -> Tuple:
a__ = 0
a__ = 0
for i, line in enumerate(open(os.path.join(os.path.dirname(__lowerCamelCase ) , __lowerCamelCase ) ... | 489 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_a... | 113 | 0 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format='''%(message)s''')
def _lowercase ( __UpperCamelCase : Any ):
return input_array.reshape((input_array.size, 1) )
def _lowercase ( __UpperCamelCas... | 214 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Tuple ={
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""MobileNetV2Config""",
"... | 113 | 0 |
"""simple docstring"""
import collections
import os
import re
from pathlib import Path
__SCREAMING_SNAKE_CASE = """src/transformers"""
# Matches is_xxx_available()
__SCREAMING_SNAKE_CASE = re.compile(r"""is\_([a-z_]*)_available()""")
# Catches a one-line _import_struct = {xxx}
__SCREAMING... | 388 |
_lowerCAmelCase : int ="""
# 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+https://github.com/huggingface/transformers.g... | 113 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowercase_ = {
"""configuration_chinese_clip""": [
"""CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""ChineseCLIPConfig""",... | 235 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
AutoT... | 113 | 0 |
"""simple docstring"""
import os
try:
from .build_directory_md import good_file_paths
except ImportError:
from build_directory_md import good_file_paths # type: ignore
snake_case = list(good_file_paths())
assert filepaths, "good_file_paths() failed!"
snake_case ... | 103 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
log... | 113 | 0 |
"""simple docstring"""
import os
from argparse import ArgumentParser, Namespace
from ..data import SingleSentenceClassificationProcessor as Processor
from ..pipelines import TextClassificationPipeline
from ..utils import is_tf_available, is_torch_available, logging
from . import BaseTransformersCLICommand
if not ... | 232 |
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CONFIG_MAPPING,
FEATURE_EX... | 113 | 0 |
def lowercase__ ( _UpperCamelCase) -> List[Any]:
"""simple docstring"""
UpperCamelCase = hex_num.strip()
if not hex_num:
raise ValueError('No value was passed to the function')
UpperCamelCase = hex_num[0] == "-"
if is_nega... | 280 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def _A ( SCREAMING_SNAKE_CASE ):
# A local function to see if a dot lands in the circle.
def is_in_circle(SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ) -> bool:
UpperCAmelCase... | 113 | 0 |
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
UpperCAmelCase_ = TypeVar("""T""")
class lowerCamelCase__ ( Generic[T]):
"""simple docstring"""
a__ : Any = 42 # Cache store of keys
a__ : Any = 42 ... | 2 |
def _A ( SCREAMING_SNAKE_CASE ):
stooge(SCREAMING_SNAKE_CASE ,0 ,len(SCREAMING_SNAKE_CASE ) - 1 )
return arr
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ):
if i >= h:
return
# If first element is smaller than the last then swap them
if arr[i... | 113 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, loggin... | 244 |
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Tuple = int(SCREAMING_SNAKE_CASE )
if decimal in (0, 1): # Exit cases for the recursion
return str(SCREAMING_SNAKE_CASE )
UpperCAmelCase__ , UpperCAmelCase__: Union[str, Any] = divmod(SCREAMING_SNAKE_CASE ,2 ... | 113 | 0 |
import datetime
import platform
import subprocess
from typing import Optional, Tuple, Union
import numpy as np
def A_ ( lowercase_ , lowercase_ ) -> Any:
_snake_case : Optional[int] = f'''{sampling_rate}'''
_snake_case : Optional[Any] = "1"
... | 326 |
import importlib
import os
from dataclasses import dataclass
from enum import Enum
from typing import Any, Dict, Optional, Union
import torch
from ..utils import BaseOutput
_lowerCAmelCase : int ="""scheduler_config.json"""
class __UpperCamelCase ( _a ):
'''simple docstring'''
... | 113 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
__lowerCAmelCase : Dict = {
"""configuration_nezha""": ["""NEZHA_PRETRAINED_CONFIG_ARCHIVE_MAP""", """NezhaConfig"""],
}
try:
if not is_tor... | 529 |
import unittest
from transformers import DonutProcessor
_lowerCAmelCase : str ="""naver-clova-ix/donut-base"""
class __UpperCamelCase ( unittest.TestCase ):
'''simple docstring'''
def _UpperCAmelCase ( self ):
UpperCAmelCase__: Any = DonutProcessor.f... | 113 | 0 |
'''simple docstring'''
# Copyright 2021 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/li... | 489 |
from __future__ import annotations
from typing import Any
class __UpperCamelCase :
'''simple docstring'''
def __init__( self , lowerCamelCase__ ):
UpperCAmelCase__: Optional[int] = num_of_nodes
UpperCAmelCase__: list[list[int]] = []
UpperCAmel... | 113 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
lowerCAmelCase : Any = {
"""configuration_mvp""": ["""MVP_PRETRAINED_CONFIG_ARCHIVE_MAP""", """MvpConfig""", """MvpOnnxConfig"""],
"""tokenizati... | 214 |
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate_available,
is_accelera... | 113 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __snake_case :
"""simple docstring"""
lowerCAmelCase_ : Any = 42
lowerCAmelCase_ : Optional[int] = None
low... | 388 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : Union[str, Any] ={
"""configuration_clap""": [
"""CLAP_PRETRAINED_MODEL_ARCHIVE_LIST""",
"""ClapAudioConfig""",
"""ClapConfig""",
"""C... | 113 | 0 |
import argparse
import torch
from transformers import OpenAIGPTConfig, OpenAIGPTModel, load_tf_weights_in_openai_gpt
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def __UpperCamelCase (_SCREAMING_SNAKE_CASE , _SCREAMING_SNAK... | 235 |
import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import Arr... | 113 | 0 |
"""simple docstring"""
import tempfile
import torch
from diffusers import IPNDMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCAmelCase ( _a ):
A__ : Dict = (IPNDMScheduler,)
A__ : List[Any] = (('''num_inference_steps'''... | 103 |
import fire
from utils import calculate_rouge, save_json
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE=None ,**SCREAMING_SNAKE_CASE ):
UpperCAmelCase__: Tuple = [x.strip() for x in open(SCREAMING_SNAKE_CASE ).readlines()]
UpperCAmelCase__: Dict = [x.... | 113 | 0 |
"""simple docstring"""
def _lowerCamelCase ( ) -> Optional[Any]:
'''simple docstring'''
a__ = []
a__ = 1
while len(UpperCAmelCase__ ) < 1e6:
constant.append(str(UpperCAmelCase__ ) )
i += 1
a__ = "".join(UpperCAmelCase__ )
retu... | 232 |
import torch
from torch import nn
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixin
class __UpperCamelCase ( _a ,_a ):
'''simple docstring'''
@register_to_config
def __init__( self , *,
lowerCamelCase__ = 4 ... | 113 | 0 |
from itertools import product
from cva import COLOR_BGR2GRAY, cvtColor, imread, imshow, waitKey
from numpy import dot, exp, mgrid, pi, ravel, square, uinta, zeros
def lowercase__ ( _UpperCamelCase , _UpperCamelCase) -> Union[str, Any]:
"""simple docstring"""
UpperC... | 280 |
from typing import Callable, Dict, Optional, Tuple
import torch
from torch import nn
from torch.distributions import (
AffineTransform,
Distribution,
Independent,
NegativeBinomial,
Normal,
StudentT,
TransformedDistribution,
)
class __UpperCamelCase ( _a ):
'''simple do... | 113 | 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
UpperCAmelCase_ = logging.get_logger(__name__)
UpperCAmelCase_ = {
"""fac... | 2 |
import logging
import numpy as np
import pytest
from scipy.linalg import eigh
logging.basicConfig(level=logging.INFO, format="""%(message)s""")
def _A ( SCREAMING_SNAKE_CASE ):
return input_array.reshape((input_array.size, 1) )
def _A ( SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE ,SC... | 113 | 0 |
'''simple docstring'''
from math import pi
def UpperCamelCase_ ( _UpperCAmelCase : str , _UpperCAmelCase : str ) -> Union[str, Any]:
"""simple docstring"""
return 2 * pi * radius * (angle / 360)
if __name__ == "__main__":
print(arc_length(90, 1... | 244 |
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 : int ="""src/transformers"""
# This is to make sure the ... | 113 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
lowerCAmelCase_ = {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}
try:
if not is_vision_available():
raise OptionalDep... | 326 |
def _A ( SCREAMING_SNAKE_CASE ):
UpperCAmelCase__ , UpperCAmelCase__: int = [], []
while len(SCREAMING_SNAKE_CASE ) > 1:
UpperCAmelCase__ , UpperCAmelCase__: str = min(SCREAMING_SNAKE_CASE ), max(SCREAMING_SNAKE_CASE )
start.append(SCREAMING_SNAK... | 113 | 0 |
from __future__ import annotations
from typing import Any
class UpperCAmelCase_ :
'''simple docstring'''
def __init__( self : Any , UpperCamelCase__ : Any ) -> List[Any]:
"""simple docstring"""
__m... | 529 |
def _A ( SCREAMING_SNAKE_CASE ): # noqa: E741
UpperCAmelCase__: int = len(SCREAMING_SNAKE_CASE )
UpperCAmelCase__: Dict = 0
UpperCAmelCase__: Optional[int] = [0] * n
UpperCAmelCase__: List[str] = [False] * n
UpperCAmelCase__: List[str] = [False] * n
de... | 113 | 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/li... | 489 |
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_a... | 113 | 0 |
# 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]' when switching between checkout... | 214 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowerCAmelCase : Tuple ={
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""MobileNetV2Config""",
"... | 113 | 0 |
"""simple docstring"""
from __future__ import annotations
from math import pi, sqrt
def __a ( a, a ):
"""simple docstring"""
if inductance <= 0:
raise ValueError("Inductance cannot be 0 or negative" )
elif capacitance <= 0:
rais... | 388 |
_lowerCAmelCase : int ="""
# 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+https://github.com/huggingface/transformers.g... | 113 | 0 |
from unittest import TestCase
from datasets import Dataset
from minhash_deduplication import deduplicate_dataset, make_duplicate_clusters
def __UpperCamelCase () -> Dict:
lowercase__ = {
"repo_name": ["test_repo1", "test_repo2", "test_repo3"],
"path"... | 235 |
import logging
import os
import random
import sys
from dataclasses import dataclass, field
from typing import Optional
import datasets
import evaluate
import numpy as np
from datasets import load_dataset
import transformers
from transformers import (
AutoConfig,
AutoModelForSequenceClassification,
AutoT... | 113 | 0 |
"""simple docstring"""
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
snake_case = {
"""<""": operator.lt,
"""<=""": operator.le,
"""==""": operator.eq,
"""!=""": operator.ne,
""... | 103 |
import argparse
import torch
from transformers import (
SpeechTaConfig,
SpeechTaFeatureExtractor,
SpeechTaForSpeechToSpeech,
SpeechTaForSpeechToText,
SpeechTaForTextToSpeech,
SpeechTaProcessor,
SpeechTaTokenizer,
logging,
)
from transformers.tokenization_utils import AddedToken
log... | 113 | 0 |
import json
import os
from functools import lru_cache
from typing import Dict, List, Optional, Tuple, Union
import regex as re
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...tokenization_utils_base import BatchEncoding, EncodedInput
from ...utils import PaddingStrategy, logging
_low... | 114 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
_lowerCamelCase = transfo... | 114 | 1 |
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxSeqaSeqConfigWithPast
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'google/umt5-small': 'https://huggingface.co/google/umt5-... | 114 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'CLIPSegVisionCon... | 114 | 1 |
import unittest
from transformers import TrOCRConfig
from transformers.testing_utils import is_torch_available, require_torch, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_t... | 114 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 114 | 1 |
import random
class __A :
"""simple docstring"""
@staticmethod
def __snake_case ( a__):
"""simple docstring"""
_lowerCamelCase : str = [ord(a__) for i in text]
_lowerCamelCase : List[Any] =... | 114 |
def __UpperCAmelCase( lowercase_ , lowercase_ ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_lowerCamelCase : int = (boundary[1] - boundary[0]) / steps
_lowerCamelCase : Any = boundary[0]
_lowerCamelCase : Tuple ... | 114 | 1 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ , lowercase_ ):
if (direction == 1 and array[indexa] > array[indexa]) or (
direction == 0 and array[indexa] < array[indexa]
):
_lowerCamelCase, _lowerCame... | 114 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import... | 114 | 1 |
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate.utils import patch_envi... | 114 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def __UpperCAmelCase( lowercase_ ):
# vision encoder
if "img_encoder.pos_embed" in name:
_lowerCamelCase : Tuple = name.replace(... | 114 | 1 |
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, prepare_image_inputs
if i... | 114 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCame... | 114 | 1 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorTy... | 114 |
import os
def __UpperCAmelCase( ):
with open(os.path.dirname(lowercase_ ) + '''/p022_names.txt''' ) as file:
_lowerCamelCase : Optional[int] = str(file.readlines()[0] )
_lowerCamelCase : List[Any] = names.replace('''"''' , '''''' ).split(... | 114 | 1 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import... | 114 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Config... | 114 | 1 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ ):
if partitions <= 0:
raise ValueError('''partitions must be a positive number!''' )
if partitions > number_of_bytes:
raise ValueError('''partitions can not > number_of_byte... | 114 |
import mpmath # for roots of unity
import numpy as np
class __A :
"""simple docstring"""
def __init__( self , a__=None , a__=None):
"""simple docstring"""
_lowerCamelCase : List[str] = list(poly_a or [0])[:]
... | 114 | 1 |
import inspect
import unittest
from transformers import RegNetConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from transformers.utils import cached_property, is_vision_available
from ...test_configuration_common import ConfigTester
from ...test_modeling_flax_common import Fla... | 114 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_lowerCamelCase = '\\n\n'
_lowerCamelCase = '\nPerplexity (PPL) is one of the most common metrics for eval... | 114 | 1 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class __A ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 114 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class __A :
"""simple docstring"""
def __init__( self , a__):
"""simple docstring"""
_lowerCamelCase : str = list_of_points
# ... | 114 | 1 |
_lowerCamelCase = [
(1000, 'M'),
(900, 'CM'),
(500, 'D'),
(400, 'CD'),
(100, 'C'),
(90, 'XC'),
(50, 'L'),
(40, 'XL'),
(10, 'X'),
(9, 'IX'),
(5, 'V'),
(4, 'IV'),
(1, 'I'),
]
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : L... | 114 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , **a__):
... | 114 | 1 |
from __future__ import annotations
from random import random
class __A :
"""simple docstring"""
def __init__( self , a__ = None):
"""simple docstring"""
_lowerCamelCase : Any = value
_lowerCamelCase : Lis... | 114 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorTy... | 114 | 1 |
_lowerCamelCase = {'a': ['c', 'b'], 'b': ['d', 'e'], 'c': [], 'd': [], 'e': []}
_lowerCamelCase = ['a', 'b', 'c', 'd', 'e']
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
_lowerCamelCase : Optional[int] = start
# add current t... | 114 |
import doctest
from collections import deque
import numpy as np
class __A :
"""simple docstring"""
def __init__( self):
"""simple docstring"""
_lowerCamelCase : Any = [2, 1, 2, -1]
_lowerCamelCase : Optional[i... | 114 | 1 |
import logging
from dataclasses import dataclass, field
from pathlib import Path
from typing import Optional, Union
from .generation.configuration_utils import GenerationConfig
from .training_args import TrainingArguments
from .utils import add_start_docstrings
_lowerCamelCase = logging.getLogger... | 114 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ = None , lowercase_ = None , lowercase_ = False , ):
_lowerCamelCase : Tuple = cipher_alphabet or [chr(lowercase_ ) for i in range(97 , 1_23 )]
# If the argument is No... | 114 | 1 |
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import TransformeraDModel, VQDiffusionPipeline, VQDiffusionScheduler, VQModel
from diffusers.pipelines.vq_diffusion.pipeline_vq_diffusion import LearnedClassifierFreeSam... | 114 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at... | 114 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowerCamelCase = {
'configuration_rag': ['RagConfig'],
'retrieval_rag': ['RagRetriever'],
'tokenization_rag': ['RagTokenizer'],
}
try:
if not... | 114 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
... | 114 | 1 |
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 = {
'xlm-roberta-base': 'https://hugging... | 114 |
import inspect
from typing import List, Optional, Tuple, Union
import torch
from ...models import UNetaDModel, VQModel
from ...schedulers import DDIMScheduler
from ...utils import randn_tensor
from ..pipeline_utils import DiffusionPipeline, ImagePipelineOutput
class __A ( lowerCamelCase__ )... | 114 | 1 |
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/n... | 114 |
import copy
import random
from transformers import CLIPTokenizer
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , **a__):
"""simple docstring"""
super().__init__(*a__ , **a__)
... | 114 | 1 |
from __future__ import annotations
from typing import Any
def __UpperCAmelCase( lowercase_ ):
if not postfix_notation:
return 0
_lowerCamelCase : Any = {'''+''', '''-''', '''*''', '''/'''}
_lowerCamelCase : list[Any] = []
for token in postf... | 114 |
import unittest
import numpy as np
import requests
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_available... | 114 | 1 |
from typing import Any
class __A :
"""simple docstring"""
def __init__( self , a__):
"""simple docstring"""
_lowerCamelCase : int = data
_lowerCamelCase : Optional[Any] = None
def __repr__( ... | 114 |
import argparse
import torch
from transformers import GPTaLMHeadModel, RobertaForMaskedLM
if __name__ == "__main__":
_lowerCamelCase = argparse.ArgumentParser(
description=(
'Extraction some layers of the full RobertaForMaskedLM or GPT2LMHeadModel for Transfer Le... | 114 | 1 |
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'BAAI/AltCLIP': 'https://huggingface.co/BAAI/AltCLIP/resolve/main/config.json',
... | 114 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
_lowerCamelCase = transfo... | 114 | 1 |
import importlib
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
import transformers.models.auto
from transformers.models.auto.configuration_auto import CONFIG_MAPPING, AutoConfig
from transformers.models.bert.configuration_bert import BertConfig
from... | 114 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'CLIPSegVisionCon... | 114 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowerCamelCase = {
'configuration_convbert': ['CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'ConvBertConfig', '... | 114 |
import json
import os
import unittest
from transformers import OpenAIGPTTokenizer, OpenAIGPTTokenizerFast
from transformers.models.openai.tokenization_openai import VOCAB_FILES_NAMES
from transformers.testing_utils import require_ftfy, require_spacy, require_tokenizers
from ...test_tokenization_common import To... | 114 | 1 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ ):
_lowerCamelCase : List[str] = get_failure_array(lowercase_ )
# 2) Step through text searching for pattern
_lowerCamelCase, _lowerCamelCase : Dict = 0, 0 # index into text... | 114 |
def __UpperCAmelCase( lowercase_ , lowercase_ ):
# "extended trapezoidal rule"
# int(f) = dx/2 * (f1 + 2f2 + ... + fn)
_lowerCamelCase : int = (boundary[1] - boundary[0]) / steps
_lowerCamelCase : Any = boundary[0]
_lowerCamelCase : Tuple ... | 114 | 1 |
import json
import os
import pickle
import shutil
import tempfile
from unittest import TestCase
from unittest.mock import patch
import numpy as np
from datasets import Dataset
from transformers import is_faiss_available
from transformers.models.bart.configuration_bart import BartConfig
from transformers.models.... | 114 |
import json
import os
import subprocess
import unittest
from ast import literal_eval
import pytest
from parameterized import parameterized_class
from . import is_sagemaker_available
if is_sagemaker_available():
from sagemaker import Session, TrainingJobAnalytics
from sagemaker.huggingface import... | 114 | 1 |
import doctest
from collections import deque
import numpy as np
class __A :
"""simple docstring"""
def __init__( self):
"""simple docstring"""
_lowerCamelCase : Any = [2, 1, 2, -1]
_lowerCamelCase : Optional[i... | 114 |
import argparse
import requests
import torch
from PIL import Image
from transformers import CLIPProcessor, GroupViTConfig, GroupViTModel
def __UpperCAmelCase( lowercase_ ):
# vision encoder
if "img_encoder.pos_embed" in name:
_lowerCamelCase : Tuple = name.replace(... | 114 | 1 |
import json
import os
import unittest
from transformers import BatchEncoding, LEDTokenizer, LEDTokenizerFast
from transformers.models.led.tokenization_led import VOCAB_FILES_NAMES
from transformers.testing_utils import require_tokenizers, require_torch
from transformers.utils import cached_property
from ...test... | 114 |
import json
import os
from pathlib import Path
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple, Union
import sentencepiece
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCame... | 114 | 1 |
import argparse
from collections import defaultdict
import yaml
_lowerCamelCase = 'docs/source/en/_toctree.yml'
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : int = defaultdict(lowercase_ )
_lowerCamelCase : str = []
_lowerCamelCase : ... | 114 |
import os
def __UpperCAmelCase( ):
with open(os.path.dirname(lowercase_ ) + '''/p022_names.txt''' ) as file:
_lowerCamelCase : Optional[int] = str(file.readlines()[0] )
_lowerCamelCase : List[Any] = names.replace('''"''' , '''''' ).split(... | 114 | 1 |
import json
import logging
import os
import re
import sys
from dataclasses import dataclass, field
from typing import Any, Dict, List, Optional, Union
import datasets
import numpy as np
import torch
import torchaudio
from packaging import version
from torch import nn
import transformers
from transformers import... | 114 |
from __future__ import annotations
import unittest
from transformers import BlenderbotSmallConfig, BlenderbotSmallTokenizer, is_tf_available
from transformers.testing_utils import require_tf, require_tokenizers, slow
from transformers.utils import cached_property
from ...test_configuration_common import Config... | 114 | 1 |
import logging
import os
import sys
from pathlib import Path
from unittest.mock import patch
from parameterized import parameterized
from run_eval import run_generate
from run_eval_search import run_search
from transformers.testing_utils import CaptureStdout, TestCasePlus, slow
from utils import ROUGE_KEYS
lo... | 114 |
import mpmath # for roots of unity
import numpy as np
class __A :
"""simple docstring"""
def __init__( self , a__=None , a__=None):
"""simple docstring"""
_lowerCamelCase : List[str] = list(poly_a or [0])[:]
... | 114 | 1 |
import copy
import random
from transformers import CLIPTokenizer
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , **a__):
"""simple docstring"""
super().__init__(*a__ , **a__)
... | 114 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
_lowerCamelCase = '\\n\n'
_lowerCamelCase = '\nPerplexity (PPL) is one of the most common metrics for eval... | 114 | 1 |
import warnings
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, optimal_fft_length, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ... | 114 |
from __future__ import annotations
from scipy.special import comb # type: ignore
class __A :
"""simple docstring"""
def __init__( self , a__):
"""simple docstring"""
_lowerCamelCase : str = list_of_points
# ... | 114 | 1 |
from typing import List
from .keymap import KEYMAP, get_character
def __UpperCAmelCase( lowercase_ ):
def decorator(lowercase_ ):
_lowerCamelCase : Tuple = getattr(lowercase_ , '''handle_key''' , [] )
handle += [key]
setattr(low... | 114 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class __A ( lowerCamelCase__ ):
"""simple docstring"""
def __init__( self , *a__ , **a__):
... | 114 | 1 |
import argparse
import torch
from transformers import RemBertConfig, RemBertModel, load_tf_weights_in_rembert
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase( lowercase_ , lowercase_ , lowercase_ ):
# Initialise PyTorch model
_lowerCa... | 114 |
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchFeature
from ...utils import TensorTy... | 114 | 1 |
import os
import sys
import unittest
_lowerCamelCase = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, 'utils'))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to_test_mapping,
... | 114 |
import doctest
from collections import deque
import numpy as np
class __A :
"""simple docstring"""
def __init__( self):
"""simple docstring"""
_lowerCamelCase : Any = [2, 1, 2, -1]
_lowerCamelCase : Optional[i... | 114 | 1 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCamelCase = {
'configuration_clipseg': [
'CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP',
'CLIPSegConfig',
'CLIPSegTextConfig',
'CLIPSegVisionCon... | 114 |
from __future__ import annotations
def __UpperCAmelCase( lowercase_ , lowercase_ = None , lowercase_ = None , lowercase_ = False , ):
_lowerCamelCase : Tuple = cipher_alphabet or [chr(lowercase_ ) for i in range(97 , 1_23 )]
# If the argument is No... | 114 | 1 |
import re
def __UpperCAmelCase( lowercase_ ):
return [char.split() for char in re.split(r'''[^ a-z A-Z 0-9 \s]''' , str_ )]
def __UpperCAmelCase( lowercase_ ):
_lowerCamelCase : Any = split_input(str_ )
return "".join(
[''''''.join([char.capita... | 114 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowerCamelCase = logging.get_logger(__name__)
_lowerCamelCase = {
'sayakpaul/vit-msn-base': 'https://huggingface.co/sayakpaul/vit-msn-base/resolve/main/config.json',
# See all ViT MSN models at... | 114 | 1 |
import argparse
from transformers import (
TapasConfig,
TapasForMaskedLM,
TapasForQuestionAnswering,
TapasForSequenceClassification,
TapasModel,
TapasTokenizer,
load_tf_weights_in_tapas,
)
from transformers.utils import logging
logging.set_verbosity_info()
def __UpperCAmelCase(... | 114 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers.testing_utils import require_vision
from transformers.utils import is_vision_available
if is_vision_available():
from PIL import Image
from transformers import (
AutoProcessor,
... | 114 | 1 |
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