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 |
|---|---|---|---|---|
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def lowercase ( ) -> List[str]:
'''simple docstring'''
with offline(OfflineSimulationMode.CONNECT... | 205 |
"""simple docstring"""
import warnings
from typing import Dict, List, Optional, Tuple
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
A = logging.get_logger(__name__)
class a__ ( __magic_name__ ):
lowercase_ = ["input_ids", "att... | 77 | 0 |
from __future__ import annotations
def lowerCAmelCase__(__snake_case ,__snake_case ) -> Tuple:
'''simple docstring'''
if len(__snake_case ) <= 1 or n <= 1:
return
insert_next(__snake_case ,n - 1 )
rec_insertion_sort(__snake_case ,n - 1 )
def lowerCAmelCase__(... | 481 |
"""simple docstring"""
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_mode... | 77 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCamelCase ( __a ):
@staticmethod
@abstractmethod
def A_ (__UpperCamelCase ) -> Any:
raise NotImplementedError()
@abstractmethod
... | 635 |
"""simple docstring"""
from scipy.stats import spearmanr
import datasets
A = """
The Spearman rank-order correlation coefficient is a measure of the
relationship between two datasets. Like other correlation coefficients,
this one varies between -1 and +1 with 0 implying no correlation.
Positive co... | 77 | 0 |
import argparse
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import (
RobertaTokenizer,
TrOCRConfig,
TrOCRForCausalLM,
TrOCRProcessor,
VisionEncoderDecoderModel,
ViTConfig,
ViTImageProcessor,
ViTModel,
)
from transformers.utils import l... | 408 |
"""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 = logging.get_logger(__name__)
A = {"""vocab_file""": """spie... | 77 | 0 |
from ..utils import DummyObject, requires_backends
class _lowerCAmelCase( metaclass=UpperCAmelCase_ ):
"""simple docstring"""
a : List[Any] =['''torch''']
def __init__( self , *_lowerCamelCase , ... | 57 |
"""simple docstring"""
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
from accelerate import ... | 77 | 0 |
'''simple docstring'''
import math
import os
from copy import deepcopy
import datasets
import evaluate
import torch
import transformers
from datasets import load_dataset
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer
fr... | 267 |
"""simple docstring"""
import math
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase = 0 , UpperCamelCase = 0 ) -> list:
"""simple docstring"""
__UpperCAmelCase : Union[str, Any] = end or len(UpperCamelCase )
for i in ... | 77 | 0 |
"""simple docstring"""
import argparse
import json
import os
import time
import zipfile
from get_ci_error_statistics import download_artifact, get_artifacts_links
from transformers import logging
SCREAMING_SNAKE_CASE__ : List[str] =logging.get_logger(__name__)
def UpperCamelCase... | 434 |
"""simple docstring"""
import numpy as np
from PIL import Image
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase , UpperCamelCase ) -> np.ndarray:
"""simple docstring"""
__UpperCAmelCase : str = np.array(UpperCamelCase )... | 77 | 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
from transformers.generation import (... | 182 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():
from .tokenization_pegasus import PegasusTokeni... | 77 | 0 |
import os
import sys
import transformers
UpperCAmelCase_ : Optional[Any] = "3"
print("Python version:", sys.version)
print("transformers version:", transformers.__version__)
try:
import torch
print("Torch version:", torch.__version__)
print("Cuda available:", torch.cud... | 491 |
"""simple docstring"""
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()... | 77 | 0 |
import itertools
import os
import random
import tempfile
import unittest
import numpy as np
from datasets import load_dataset
from transformers import is_speech_available
from transformers.testing_utils import check_json_file_has_correct_format, require_torch, require_torchaudio
from transfor... | 79 |
"""simple docstring"""
from typing import Union
import fire
import torch
from tqdm import tqdm
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase = "cpu" , UpperCamelCase = None ) -> None:
"""simple docstring"""
__UpperCAmelCase : Union[str,... | 77 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE__ = {"configuration_mmbt": ["MMBTConfig"]}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
... | 631 |
"""simple docstring"""
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
A = pd.read_csv("""sample_data.csv""", header=None)
A = ... | 77 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
SCREAMING_SNAKE_CASE__ : Optional[Any] = {
"configuration_maskformer": ["MASKFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP", "MaskFormerConfig"],
"configur... | 205 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartTokenizer, MBartTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokeniz... | 77 | 0 |
import os
import re
import unicodedata
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple, Union
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import is_torch_available, logging
if is_torch_available():
import tor... | 481 |
"""simple docstring"""
from typing import Any
class a__ :
def __init__( self : List[str] , UpperCamelCase_ : Any):
"""simple docstring"""
__UpperCAmelCase : str = data
__UpperCAmelCase : Optional[Any] = None
... | 77 | 0 |
import numpy as np
import pandas as pd
from sklearn.preprocessing import MinMaxScaler
from tensorflow.keras.layers import LSTM, Dense
from tensorflow.keras.models import Sequential
if __name__ == "__main__":
SCREAMING_SNAKE_CASE : Union[str, Any] = pd.read_csv("sample_data.csv", header=None)
SCR... | 635 |
"""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/LICENS... | 77 | 0 |
from __future__ import annotations
snake_case__ : Union[str, Any] = []
def lowerCamelCase__ ( _lowerCamelCase , _lowerCamelCase , _lowerCamelCase ) ->bool:
for i in range(len(_lowerCamelCase ) ):
if board[row][i] == 1:
return False
for i in range(len(_lowerCamelCase ) ):... | 408 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tensorflow_text_available, is_torch_available
A = {
"""configuration_ernie""": ["""ERNIE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ErnieConfig""", """ErnieOnnxConfig"""],
}
... | 77 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
A_ : Dict = ''
A_ : str = ''
A_ : int = ''
A_ : List[str] = 1 # (0 is vertical, 1 is horizontal)
def ... | 57 |
"""simple docstring"""
import os
import unittest
from tempfile import TemporaryDirectory
import torch
import torch.nn as nn
from accelerate.utils import (
OffloadedWeightsLoader,
extract_submodules_state_dict,
load_offloaded_weight,
offload_state_dict,
offload_weight,
)
class a__ ... | 77 | 0 |
'''simple docstring'''
from __future__ import annotations
import sys
from collections import deque
from typing import Generic, TypeVar
SCREAMING_SNAKE_CASE__ = TypeVar("T")
class snake_case (Generic[T] ):
lowerCAmelCase__ :List[str] = 42 # Cache store ... | 267 |
"""simple docstring"""
def _UpperCamelCase ( UpperCamelCase , UpperCamelCase ) -> int:
"""simple docstring"""
__UpperCAmelCase : Dict = 1 # To kept the Calculated Value
# Since C(n, k) = C(n, n-k)
if k > (n - k):
__UpperCAmelC... | 77 | 0 |
"""simple docstring"""
def UpperCamelCase ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) ->Optional[Any]:
if index == r:
for j in range(SCREAMING_SNAKE_CASE_ ):
... | 434 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_speech_available,
is_torch_available,
)
A = {
"""configuration_trocr""": ["""TROCR_PRETRAINED_CONFIG_ARCHIVE_MAP""", ""... | 77 | 0 |
"""simple docstring"""
import inspect
import jax
import jax.lax as lax
import jax.numpy as jnp
from ..utils import add_start_docstrings
from ..utils.logging import get_logger
_A = get_logger(__name__)
_A = R"""
Args:
input_ids (`jnp.ndarray` of shape `(batch_size, sequence_length)`):
... | 182 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torc... | 77 | 0 |
def UpperCamelCase ( _A : Dict = 600851475143 )-> int:
"""simple docstring"""
try:
A__ = int(_A )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int or castable to int." )
if n <= 0:
raise Va... | 491 |
"""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(0.00454, 264.172),
"""cubicyard""": f... | 77 | 0 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int = 10_00 ) -> int:
'''simple docstring'''
return sum(e for e in range(3 , snake_case_ ) if e % 3 == 0 or e % 5 == 0 )
if __name__ == "__main__":
print(f"{solution() = }")
| 78 | '''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
f... | 78 | 1 |
'''simple docstring'''
from math import sqrt
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
assert isinstance(snake_case_ , snake_case_ ) and (
number >= 0
), "'number' must been an int and positive"
Upper... | 78 | '''simple docstring'''
import requests
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> None:
'''simple docstring'''
UpperCAmelCase_ = {"Content-Type": "application/json"}
UpperCAmelCase_ = requests.post(snake... | 78 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_: Optional[int] =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: List[str] ={
'asapp/sew-d-tiny-100k': 'https://huggingface.co/asapp/sew-d-... | 78 | '''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_... | 78 | 1 |
'''simple docstring'''
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def lowerCAmelCase_ ( snake_case_ : int ) -> str:
'''simple docstring'''
def is_in_circle(snake_case_ : float , ... | 78 | '''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
do... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> None:
'''simple docstring'''
UpperCAmelCase_ = generate_pascal_triangle(snake_case_ )
for row_idx in range(snake_case_ ):
# Print left spaces
for _ in range(n... | 78 | '''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __A :
a__ : int
a__ : TreeNode | None = None
a__ : TreeNode | None = None
SCREAMING_SNAKE_CASE_: Union[str, Any] =namedtu... | 78 | 1 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase_ ( snake_case_ : Union[str, Any] ) -> Union[str, Any]:
'''simple docstring'''
UpperCAmelCase_ = FileLock(str(tmpdir / "f... | 78 | '''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_... | 78 | 1 |
'''simple docstring'''
import json
import sys
def lowerCAmelCase_ ( snake_case_ : Any , snake_case_ : Tuple ) -> List[str]:
'''simple docstring'''
with open(snake_case_ , encoding="utf-8" ) as f:
UpperCAmelCase_ = json... | 78 | '''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
SCREAMING_SNAKE_CASE_: Any =False
try:
SCREA... | 78 | 1 |
'''simple docstring'''
import sacrebleu as scb
from packaging import version
from sacrebleu import CHRF
import datasets
SCREAMING_SNAKE_CASE_: int ='\\n@inproceedings{popovic-2015-chrf,\n title = "chr{F}: character n-gram {F}-score for automatic {MT} evaluation",\n author = "Popovi{\'c}, Maja",\n bo... | 78 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_: Optional[int] ={'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Be... | 78 | 1 |
'''simple docstring'''
from math import pi, sqrt, tan
def lowerCAmelCase_ ( snake_case_ : float ) -> float:
'''simple docstring'''
if side_length < 0:
raise ValueError("surface_area_cube() only accepts non-negative values" )
return 6 * side_leng... | 78 | '''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBer... | 78 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from transformers import SPIECE_UNDERLINE, BatchEncoding, MBartaaTokenizer, MBartaaTokenizerFast, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenize... | 78 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
do... | 78 | '''simple docstring'''
import logging
from transformers import PretrainedConfig
SCREAMING_SNAKE_CASE_: Any =logging.getLogger(__name__)
SCREAMING_SNAKE_CASE_: Any ={
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/conf... | 78 | 1 |
'''simple docstring'''
import warnings
from contextlib import contextmanager
from ....processing_utils import ProcessorMixin
class __A ( UpperCamelCase__ ):
a__ : int = """MCTCTFeatureExtractor"""
a__ : int = """AutoTokenizer"""
def __init__(self : Di... | 78 | '''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 78 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
SCREAMING_SNAKE_CASE_: Optional[int] ={
'configuration_llama': ['LLAMA_PRETRAINED_CONF... | 78 | '''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 78 | 1 |
'''simple docstring'''
import copy
import re
class __A :
a__ : Optional[int] = """hp"""
a__ : Optional[Any] = {}
a__ : List[Any] = None
@classmethod
def _lowercase (cls : Optional[int] , __a : str , __a : ... | 78 | '''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 78 | 1 |
'''simple docstring'''
from unittest import TestCase
from datasets import Sequence, Value
from datasets.arrow_dataset import Dataset
class __A ( UpperCamelCase__ ):
def _lowercase (self : List[Any] ):
return [
{"col_1": 3, "col_2": "a"},
... | 78 | '''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : list[int] ) -> float:
'''simple docstring'''
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
UpperCAmelCase_ = sum(snake_case_ ) / len(... | 78 | '''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 78 | 1 |
'''simple docstring'''
from typing import Any
def lowerCAmelCase_ ( snake_case_ : list , snake_case_ : list , snake_case_ : dict , snake_case_ : dict , snake_case_ : dict , ) -> list:
'''simple docstring'''
... | 78 | '''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... | 78 | 1 |
'''simple docstring'''
import dataclasses
import json
import sys
import types
from argparse import ArgumentDefaultsHelpFormatter, ArgumentParser, ArgumentTypeError
from copy import copy
from enum import Enum
from inspect import isclass
from pathlib import Path
from typing import Any, Callable, Dict, Iterable, List... | 78 | '''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowerCAmelCase_ ( snake_case_ : Union[dict, list, ... | 78 | 1 |
'''simple docstring'''
import unittest
from transformers import DebertaVaTokenizer, DebertaVaTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
SCREAMING_SNAKE_CASE_: Optional[Any] =... | 78 | '''simple docstring'''
import copy
import re
class __A :
a__ : Optional[int] = """hp"""
a__ : Optional[Any] = {}
a__ : List[Any] = None
@classmethod
def _lowercase (cls : Optional[int] , __a : str , __a : ... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : Dict ) -> Union[str, Any]:
'''simple docstring'''
stooge(snake_case_ , 0 , len(snake_case_ ) - 1 )
return arr
def lowerCAmelCase_ ( snake_case_ : Optional[i... | 78 | '''simple docstring'''
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_image... | 78 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0... | 78 | '''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
SCREAMING_SNAKE_CASE_: Dict =[
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_embeddi... | 78 | 1 |
'''simple docstring'''
import unittest
from transformers.testing_utils import CaptureStdout
from transformers.tools.python_interpreter import evaluate
def lowerCAmelCase_ ( snake_case_ : Tuple ) -> List[str]:
'''simple docstring'''
return x + 2
class __A... | 78 | '''simple docstring'''
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase_ ( snake_case_ : ndarray ) -> float:
'''simple docstring'''
return np.dot(snake_case_ , snake_case_ )
... | 78 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from transformers import XLMRobertaTokenizer
from diffusers import (
AltDiffusionImgaImgPipeline,
AutoencoderKL,
PNDMScheduler,
UNetaDConditionModel,
)
from diffusers.image_processor import VaeImageProc... | 78 | '''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
f... | 78 | 1 |
'''simple docstring'''
import pytest
from datasets.splits import SplitDict, SplitInfo
from datasets.utils.py_utils import asdict
@pytest.mark.parametrize(
"split_dict" , [
SplitDict(),
SplitDict({"train": SplitInfo(name="train" , num_bytes=13_37 , num_examples=42 ... | 78 | '''simple docstring'''
import requests
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> None:
'''simple docstring'''
UpperCAmelCase_ = {"Content-Type": "application/json"}
UpperCAmelCase_ = requests.post(snake... | 78 | 1 |
'''simple docstring'''
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 lowerCAmelCase_ ( snake_case_ : Union[str, Any]... | 78 | '''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_... | 78 | 1 |
'''simple docstring'''
import requests
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> None:
'''simple docstring'''
UpperCAmelCase_ = {"Content-Type": "application/json"}
UpperCAmelCase_ = requests.post(snake... | 78 | '''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
do... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int = 60_08_51_47_51_43 ) -> int:
'''simple docstring'''
try:
UpperCAmelCase_ = int(snake_case_ )
except (TypeError, ValueError):
raise TypeError("Parameter n must be int ... | 78 | '''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __A :
a__ : int
a__ : TreeNode | None = None
a__ : TreeNode | None = None
SCREAMING_SNAKE_CASE_: Union[str, Any] =namedtu... | 78 | 1 |
'''simple docstring'''
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
Pi... | 78 | '''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> bool:
'''simple docstring'''
UpperCAmelCase_ = len(snake_case_ )
UpperCAmelCase_ = len(snake_case_ )
UpperCAmelCase_ = ... | 78 | '''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
SCREAMING_SNAKE_CASE_: Any =False
try:
SCREA... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> int:
'''simple docstring'''
if not isinstance(snake_case_ , snake_case_ ):
UpperCAmelCase_ = f"""Input value of [number={number}] must be an integer"""
raise T... | 78 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_: Optional[int] ={'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Be... | 78 | 1 |
'''simple docstring'''
import unittest
import numpy as np
def lowerCAmelCase_ ( snake_case_ : np.ndarray , snake_case_ : np.ndarray , snake_case_ : np.ndarray , snake_case_ : np.ndarray | None = None , ) -> np.ndarray:
'''simp... | 78 | '''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBer... | 78 | 1 |
'''simple docstring'''
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
SCREAMING_SNAKE_CASE_: Optional[int] =logging.g... | 78 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available... | 78 | 1 |
'''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_configurat... | 78 | '''simple docstring'''
import logging
from transformers import PretrainedConfig
SCREAMING_SNAKE_CASE_: Any =logging.getLogger(__name__)
SCREAMING_SNAKE_CASE_: Any ={
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/conf... | 78 | 1 |
'''simple docstring'''
from math import asin, atan, cos, radians, sin, sqrt, tan
SCREAMING_SNAKE_CASE_: int =6378137.0
SCREAMING_SNAKE_CASE_: List[Any] =6356752.314245
SCREAMING_SNAKE_CASE_: Dict =6_37_81_37
def lowerCAmelCase_ ( snake_case_ : float , snake_case_ : ... | 78 | '''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 78 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, ids_tensor, random_attention_mask
if is_flax_available():
import jax
from transforme... | 78 | '''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 78 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCAmelCase_ ( snake_case_ : list[int] ) -> list[int]: # This function is recursive
'''simple docstring'''
UpperCAmelCase_ = len(snake_case_ )
# If the array contains only one ele... | 78 | '''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 78 | 1 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
SCREAMING_SNAKE_CASE_: Any =get_tests_dir('fixtures/test_sentence... | 78 | '''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 78 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_c... | 78 | '''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 78 | 1 |
'''simple docstring'''
from pathlib import Path
from typing import List
from transformers import is_torch_available, is_vision_available
from transformers.testing_utils import get_tests_dir, is_tool_test
from transformers.tools.agent_types import AGENT_TYPE_MAPPING, AgentAudio, AgentImage, AgentText
if is_torch... | 78 | '''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... | 78 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import numpy as np
import PIL.Image
from ...image_processing_utils import BaseImageProcessor, BatchFeature
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
ChannelDimension,
PILImageRe... | 78 | '''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowerCAmelCase_ ( snake_case_ : Union[dict, list, ... | 78 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
if 1 < number < 4:
# 2 and 3 are primes
return True
elif number < 2 or number % 2 == 0 or numb... | 78 | '''simple docstring'''
import copy
import re
class __A :
a__ : Optional[int] = """hp"""
a__ : Optional[Any] = {}
a__ : List[Any] = None
@classmethod
def _lowercase (cls : Optional[int] , __a : str , __a : ... | 78 | 1 |
'''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)
warnings.warn(
... | 78 | '''simple docstring'''
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_image... | 78 | 1 |
'''simple docstring'''
import json
import os
import unittest
from typing import Tuple
from transformers import WavaVecaPhonemeCTCTokenizer
from transformers.models.wavaveca.tokenization_wavaveca import VOCAB_FILES_NAMES
from transformers.models.wavaveca_phoneme.tokenization_wavaveca_phoneme import WavaVecaPhoneme... | 78 | '''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
SCREAMING_SNAKE_CASE_: Dict =[
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_embeddi... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : list , snake_case_ : list , snake_case_ : int ) -> int:
'''simple docstring'''
if len(snake_case_ ) != len(snake_case_ ):
raise ValueError("The length of profit and... | 78 | '''simple docstring'''
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase_ ( snake_case_ : ndarray ) -> float:
'''simple docstring'''
return np.dot(snake_case_ , snake_case_ )
... | 78 | 1 |
'''simple docstring'''
from torch import nn
def lowerCAmelCase_ ( snake_case_ : int ) -> Dict:
'''simple docstring'''
if act_fn in ["swish", "silu"]:
return nn.SiLU()
elif act_fn == "mish":
return nn.Mish()
elif act_fn == "gelu":
... | 78 | '''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
f... | 78 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_: List[Any] ={
'configuration_luke': ['LUKE_PRETRAINED_CONFIG_ARCHIVE_MAP', 'LukeConfig'],
'tokenization_luke': ['LukeTokenizer'],
}
try:
... | 78 | '''simple docstring'''
import requests
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> None:
'''simple docstring'''
UpperCAmelCase_ = {"Content-Type": "application/json"}
UpperCAmelCase_ = requests.post(snake... | 78 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_flax_available,
is_torch_available,
is_transformers_available,
)
try:
if not (is_transformers_available() and is_torch_available()):
raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvai... | 78 | '''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_... | 78 | 1 |
'''simple docstring'''
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
SCREAMING_SNAKE_CASE_: str ... | 78 | '''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
do... | 78 | 1 |
'''simple docstring'''
import argparse
import hashlib # hashlib is only used inside the Test class
import struct
class __A :
def __init__(self : str , __a : Any ):
UpperCAmelCase_ = data
UpperCAmelCase_ = [0X67_45_23_01, 0Xef_cd_... | 78 | '''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __A :
a__ : int
a__ : TreeNode | None = None
a__ : TreeNode | None = None
SCREAMING_SNAKE_CASE_: Union[str, Any] =namedtu... | 78 | 1 |
'''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : list ) -> list:
'''simple docstring'''
UpperCAmelCase_ = len(snake_case_ )
for _ in range(snake_case_ ):
for i in range(_ % 2 , arr_size - 1 , 2 ):
... | 78 | '''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_... | 78 | 1 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transforme... | 78 | '''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
SCREAMING_SNAKE_CASE_: Any =False
try:
SCREA... | 78 | 1 |
'''simple docstring'''
import random
import timeit
from functools import wraps
from typing import Callable, Optional
from ..configuration_utils import PretrainedConfig
from ..models.auto.modeling_tf_auto import TF_MODEL_MAPPING, TF_MODEL_WITH_LM_HEAD_MAPPING
from ..utils import is_pyanvml_available, is_tf_availab... | 78 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_: Optional[int] ={'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Be... | 78 | 1 |
'''simple docstring'''
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 ... | 78 | '''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBer... | 78 | 1 |
'''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 78 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available... | 78 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_ava... | 78 | '''simple docstring'''
import logging
from transformers import PretrainedConfig
SCREAMING_SNAKE_CASE_: Any =logging.getLogger(__name__)
SCREAMING_SNAKE_CASE_: Any ={
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/conf... | 78 | 1 |
'''simple docstring'''
from __future__ import annotations
from math import gcd
def lowerCAmelCase_ ( snake_case_ : int , snake_case_ : int = 2 , snake_case_ : int = 1 , snake_case_ : int = 3 , ) -> int | None:
'''simple docstr... | 78 | '''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 78 | 1 |
'''simple docstring'''
from math import acos, sin
from typing import List, Tuple, Union
import numpy as np
import torch
from PIL import Image
from ...models import AutoencoderKL, UNetaDConditionModel
from ...schedulers import DDIMScheduler, DDPMScheduler
from ...utils import randn_tensor
from ..pipeline_utils im... | 78 | '''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 78 | 1 |
'''simple docstring'''
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
from transformers import (
HubertConfig,
HubertForCTC,
HubertModel,
WavaVecaCTCTokenizer,
WavaVecaFeatureExtractor,
WavaVecaProcessor,
logging,
)
logging.set_... | 78 | '''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 78 | 1 |
'''simple docstring'''
from datetime import datetime as dt
import os
from github import Github
SCREAMING_SNAKE_CASE_: int =[
'good first issue',
'good second issue',
'good difficult issue',
'feature request',
'new model',
'wip',
]
def lowerCAmelCase_ ( ) -> Tu... | 78 | '''simple docstring'''
import argparse
import re
import requests
import torch
# git clone https://github.com/salesforce/BLIP.git
from models.blip import blip_decoder
from models.blip_itm import blip_itm
from models.blip_vqa import blip_vqa
from PIL import Image
from torchvision import transforms
from torchvision... | 78 | 1 |
'''simple docstring'''
SCREAMING_SNAKE_CASE_: List[str] ={
'A': '.-', 'B': '-...', 'C': '-.-.', 'D': '-..', 'E': '.', 'F': '..-.', 'G': '--.',
'H': '....', 'I': '..', 'J': '.---', 'K': '-.-', 'L': '.-..', 'M': '--', 'N': '-.',
'O': '---', 'P': '.--.', 'Q': '--.-', 'R': '.-.', 'S': '...', 'T': '-', '... | 78 | '''simple docstring'''
import math
from collections import defaultdict
from typing import List, Optional, Tuple, Union
import numpy as np
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from .scheduling_utils import KarrasDiffusionSchedulers, SchedulerMixin, SchedulerOutput
de... | 78 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
def lowerCAmelCase_ ( snake_case_ : float , snake_case_ : float , snake_case_ : float ) -> tuple:
'''simple docstring'''
UpperCAmelCase_ ... | 78 | '''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... | 78 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_: Optional[Any] ={
'configuration_perceiver': ['PERCEIVER_PRETRAINED_CON... | 78 | '''simple docstring'''
import logging
import math
from functools import partial
from typing import Any, Callable, Dict, Iterable, List, Optional, Sequence, Tuple, Union
import torch
from .tensor_utils import tensor_tree_map, tree_map
def lowerCAmelCase_ ( snake_case_ : Union[dict, list, ... | 78 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
SCREAMING_SNAKE_CASE_: Union[str, Any] ={'configuration_swin': ['SWIN_PRETRAINED_CONFIG_ARCHIVE_MAP', 'SwinConfig', 'SwinOnnxConfig']}
try:
if no... | 78 | '''simple docstring'''
import copy
import re
class __A :
a__ : Optional[int] = """hp"""
a__ : Optional[Any] = {}
a__ : List[Any] = None
@classmethod
def _lowercase (cls : Optional[int] , __a : str , __a : ... | 78 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
SCREAMING_SNAKE_CASE_: Union[str, Any] =logging.get_logger(__name__)
class __A ( UpperCamelCase__ ):
def __init__(self : List[Any] , *__a : ... | 78 | '''simple docstring'''
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_image... | 78 | 1 |
'''simple docstring'''
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 lowerCAmelCase_ ( snake_case_ : Optional[int] , snake_case_ : List[Any] ) -... | 78 | '''simple docstring'''
import argparse
import os.path as osp
import re
import torch
from safetensors.torch import load_file, save_file
# =================#
# UNet Conversion #
# =================#
SCREAMING_SNAKE_CASE_: Dict =[
# (stable-diffusion, HF Diffusers)
('time_embed.0.weight', 'time_embeddi... | 78 | 1 |
'''simple docstring'''
import argparse
import os
import pickle
import sys
import torch
from transformers import TransfoXLConfig, TransfoXLLMHeadModel, load_tf_weights_in_transfo_xl
from transformers.models.transfo_xl import tokenization_transfo_xl as data_utils
from transformers.models.transfo_xl.tokenization_tr... | 78 | '''simple docstring'''
import numpy as np
from numpy import ndarray
from scipy.optimize import Bounds, LinearConstraint, minimize
def lowerCAmelCase_ ( snake_case_ : ndarray ) -> float:
'''simple docstring'''
return np.dot(snake_case_ , snake_case_ )
... | 78 | 1 |
'''simple docstring'''
import math
import os
import sys
def lowerCAmelCase_ ( snake_case_ : str ) -> str:
'''simple docstring'''
UpperCAmelCase_ = ""
try:
with open(snake_case_ , "rb" ) as binary_file:
UpperCAmel... | 78 | '''simple docstring'''
from collections import OrderedDict
from typing import Any, Mapping, Optional, Union
from ...configuration_utils import PretrainedConfig
from ...feature_extraction_utils import FeatureExtractionMixin
from ...onnx import OnnxConfig
from ...onnx.utils import compute_effective_axis_dimension
f... | 78 | 1 |
'''simple docstring'''
import unittest
import torch
from torch import nn
from accelerate.test_utils import require_cuda
from accelerate.utils.memory import find_executable_batch_size, release_memory
def lowerCAmelCase_ ( ) -> Any:
'''simple docstring'''
raise RuntimeError... | 78 | '''simple docstring'''
import requests
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : str ) -> None:
'''simple docstring'''
UpperCAmelCase_ = {"Content-Type": "application/json"}
UpperCAmelCase_ = requests.post(snake... | 78 | 1 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def lowerCAmelCase_ ( snake_case_ : str , snake_case_ : float | Decimal , snake_case_ : float = 10**-10 ) ->... | 78 | '''simple docstring'''
from typing import Callable, List, Optional, Union
import PIL
import torch
from transformers import (
CLIPImageProcessor,
CLIPSegForImageSegmentation,
CLIPSegProcessor,
CLIPTextModel,
CLIPTokenizer,
)
from diffusers import DiffusionPipeline
from diffusers.configuration_... | 78 | 1 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
SCREAMING_SNAKE_CASE_: List[Any] ='docs/source/en/_toctree.yml'
def lowerCAmelCase_ ( snake_case_ : Dict ) -> Optional[Any]:
'''simple docstring'''
UpperCAmelCase_ ... | 78 | '''simple docstring'''
def lowerCAmelCase_ ( snake_case_ : int ) -> bool:
'''simple docstring'''
if number < 0:
raise ValueError("number must not be negative" )
return number & (number - 1) == 0
if __name__ == "__main__":
import doctest
do... | 78 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
SCREAMING_SNAKE_CASE_: Tuple =logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_: int =[
['attention',... | 78 | '''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class __A :
a__ : int
a__ : TreeNode | None = None
a__ : TreeNode | None = None
SCREAMING_SNAKE_CASE_: Union[str, Any] =namedtu... | 78 | 1 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
import torch.nn.functional as F
from transformers import (
ClapTextConfig,
ClapTextModelWithProjection,
RobertaTokenizer,
SpeechTaHifiGan,
SpeechTaHifiGanConfig,
)
from diffusers import (
AudioLDMPipeline,
... | 78 | '''simple docstring'''
import argparse
import json
import logging
import os
import shutil
import sys
import tempfile
import unittest
from unittest import mock
import torch
from accelerate.utils import write_basic_config
from transformers.testing_utils import TestCasePlus, get_gpu_count, run_command, slow, torch_... | 78 | 1 |
'''simple docstring'''
import argparse
import collections
import json
import os
import re
import string
import sys
import numpy as np
SCREAMING_SNAKE_CASE_: Tuple =re.compile(r'\b(a|an|the)\b', re.UNICODE)
SCREAMING_SNAKE_CASE_: Optional[int] =None
def lowerCAmelCase_ ( ) -> int:... | 78 | '''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
SCREAMING_SNAKE_CASE_: Any =False
try:
SCREA... | 78 | 1 |
'''simple docstring'''
from collections import OrderedDict
from typing import List, Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_: List[Any] =logging.get_logger(__name__)
SCREAMING_... | 78 | '''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_torch_available,
is_vision_available,
)
SCREAMING_SNAKE_CASE_: Optional[int] ={'configuration_beit': ['BEIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Be... | 78 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
SCREAMING_SNAKE_CASE_: List[str] ={
'configuration_git': ['GIT_PRETRAINED_CONFIG_ARCHIVE_MAP', 'GitConfig', 'GitVisionConfig'],
'processing_git': ['GitProcessor... | 78 | '''simple docstring'''
import argparse
import json
import os
import pickle
import shutil
import numpy as np
import torch
from distiller import Distiller
from lm_seqs_dataset import LmSeqsDataset
from transformers import (
BertConfig,
BertForMaskedLM,
BertTokenizer,
DistilBertConfig,
DistilBer... | 78 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import DecisionTransformerConfig, 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... | 78 | '''simple docstring'''
import gc
import unittest
import torch
from parameterized import parameterized
from diffusers import AutoencoderKL
from diffusers.utils import floats_tensor, load_hf_numpy, require_torch_gpu, slow, torch_all_close, torch_device
from diffusers.utils.import_utils import is_xformers_available... | 78 | 1 |
'''simple docstring'''
import shutil
import tempfile
import unittest
from unittest.mock import patch
from transformers import (
DefaultFlowCallback,
IntervalStrategy,
PrinterCallback,
ProgressCallback,
Trainer,
TrainerCallback,
TrainingArguments,
is_torch_available,
)
from transfor... | 78 | '''simple docstring'''
import logging
from transformers import PretrainedConfig
SCREAMING_SNAKE_CASE_: Any =logging.getLogger(__name__)
SCREAMING_SNAKE_CASE_: Any ={
'bertabs-finetuned-cnndm': 'https://huggingface.co/remi/bertabs-finetuned-cnndm-extractive-abstractive-summarization/resolve/main/conf... | 78 | 1 |
'''simple docstring'''
import json
import os
from dataclasses import dataclass
from functools import partial
from typing import Callable
import flax.linen as nn
import jax
import jax.numpy as jnp
import joblib
import optax
import wandb
from flax import jax_utils, struct, traverse_util
from flax.serialization impo... | 78 | '''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from timm import create_model
from timm.data import resolve_data_config
from timm.data.transforms_factory import create_transform
from transfo... | 78 | 1 |
'''simple docstring'''
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
SCREAMING_SNAKE_CASE_: Any =get_tests_dir('f... | 78 | '''simple docstring'''
import json
import sys
import tempfile
import unittest
from pathlib import Path
import transformers
from transformers import (
CONFIG_MAPPING,
IMAGE_PROCESSOR_MAPPING,
AutoConfig,
AutoImageProcessor,
CLIPConfig,
CLIPImageProcessor,
)
from transformers.testing_utils i... | 78 | 1 |
'''simple docstring'''
import logging
import os
from typing import List, TextIO, Union
from conllu import parse_incr
from utils_ner import InputExample, Split, TokenClassificationTask
SCREAMING_SNAKE_CASE_: str =logging.getLogger(__name__)
class __A ( UpperCamelCase__ ):
def __init__(s... | 78 | '''simple docstring'''
import os
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, Optional, Union
import numpy as np
import pyarrow as pa
from .. import config
from ..download.streaming_download_manager import xopen, xsplitext
from ..table imp... | 78 | 1 |
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