code stringlengths 87 55.2k | code_codestyle int64 0 349 | style_context stringlengths 135 49.1k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_torch_available
from transformers.testing_utils import require_torch, torch_device
if is_torch_available():
from transformers import PyTorchBenchmark, PyTorchBenchmarkArguments
@require_torch
class _l... | 21 |
"""simple docstring"""
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 imp... | 249 | 0 |
'''simple docstring'''
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from dataclasses import dataclass
from typing import Optional, Tuple, Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import ... | 22 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
# This model implementation is heavily inspired by https://github.com/haofanwang/ControlNet-for-Diffusers/
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTe... | 23 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
import argparse
import OmegaConf
import torch
from diffusers import DDIMScheduler, LDMPipeline, UNetLDMModel, VQModel
def lowerCamelCase__ ( snake_case_ : Optional[int] , snake_case_ : Union[str, Any] , snake_case_ : Optional[int] ) -> Unio... | 24 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
"""simple docstring"""
import sys
import turtle
def lowercase_ ( _snake_case ,_snake_case ):
return (pa[0] + pa[0]) / 2, (pa[1] + pa[1]) / 2
def lowercase_ ( _snake_case ,_snake_case ,_snake_case ,_snake_case ,):
my_pen.up()
my_pen.goto(vertexa[0] ,vertex... | 25 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
class lowercase :
def __init__( self ) -> List[str]:
_A : List[Any] = {}
def a__ ( self ) -> None:
print(self.vertex )
for i in self.vertex:
print(_a , """ -> """ , """ -> """.... | 26 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedu... | 249 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
__lowercase : Union[str, Any] = logging.get_logger(__name__)
__lowercase : Tuple = {
... | 27 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
'''simple docstring'''
from math import sqrt
def __lowerCamelCase ( A__ ) -> int:
"""simple docstring"""
UpperCamelCase = 0
for i in range(1 , int(sqrt(A__ ) + 1 ) ):
if n % i == 0 and i != sqrt(A__ ):
total ... | 28 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
import json
import os
import shutil
import tempfile
import unittest
from multiprocessing import get_context
from pathlib import Path
import datasets
import numpy as np
from datasets import load_dataset
from parameterized import parameterized
from transformers import AutoProcessor
from tran... | 29 |
"""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 Opt... | 249 | 0 |
import unittest
import numpy as np
from transformers.testing_utils import require_torch, require_vision
from transformers.utils import is_torch_available, is_vision_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin
if is_torch_available():
import torch
if is... | 30 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__SCREAMING_SNAKE_CASE : Any = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 31 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
from __future__ import annotations
import matplotlib.pyplot as plt # type: ignore
import numpy
# initial triangle of Koch snowflake
UpperCAmelCase_ : Tuple = numpy.array([0, 0])
UpperCAmelCase_ : Any = numpy.array([0.5, 0.8_6_6_0_2_5_4])
UpperCAmelCase_ : Tuple ... | 32 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
"""simple docstring"""
import sys
def lowercase ( __snake_case : Dict ):
lowercase_ : int = len(__snake_case )
lowercase_ : Tuple = [[0 for x in range(__snake_case )] for x in range(__snake_case )]
lowercase_ : int = [[0 fo... | 33 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
class _a :
def __init__( self : List[str] ):
'''simple docstring'''
UpperCAmelCase = ''''''
UpperCAmelCase = ''''''
UpperCAmelCase = []
def A ( self : List[Any] , ... | 34 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
'''simple docstring'''
from __future__ import annotations
import inspect
import unittest
import numpy as np
from transformers import ResNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from... | 35 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
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
_snake_case = logging.get_logger(__name__)
def A ( _lowerCamelCase , _lowerCamelCase ):
'''simple docstr... | 36 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
'''simple docstring'''
import json
from typing import List, Optional, Tuple
from tokenizers import normalizers
from ....tokenization_utils_fast import PreTrainedTokenizerFast
from ....utils import logging
from .tokenization_retribert import RetriBertTokenizer
_lowerCAmelCase = logging.get_logger... | 37 |
"""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/... | 249 | 0 |
import numpy as np
class _SCREAMING_SNAKE_CASE :
def __init__( self : int ):
UpperCamelCase :int = (0, 0)
UpperCamelCase :List[str] = None
UpperCamelCase :Union[str, Any] = 0
UpperCamelCase :Optional[Any] = 0
UpperCamelCase ... | 38 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
import pytest
import requests
from datasets.utils.file_utils import http_head
from .utils import OfflineSimulationMode, RequestWouldHangIndefinitelyError, offline
@pytest.mark.integration
def __A ( )-> str:
"""simple docstring"""
with offline(OfflineSimu... | 39 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""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,
... | 40 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import MobileNetVaConfig
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 ...... | 41 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
'''simple docstring'''
from math import isclose, sqrt
def SCREAMING_SNAKE_CASE__ ( __A , __A , __A ) -> tuple[float, float, float]:
_snake_case = point_y / 4 / point_x
_snake_case = 2 * normal_gradient / (1 + normal_gradient * normal_gradient)
_snake_case ... | 42 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
from string import ascii_lowercase, ascii_uppercase
def lowerCamelCase ( SCREAMING_SNAKE_CASE ):
'''simple docstring'''
if not sentence:
return ""
__UpperCamelCase :Optional[Any] = dict(zip(SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE ) )
return lower_to_upper.get(sentenc... | 43 |
"""simple docstring"""
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 imp... | 249 | 0 |
"""simple docstring"""
from ...utils import is_torch_available, is_transformers_available
if is_transformers_available() and is_torch_available():
from .pipeline_vq_diffusion import LearnedClassifierFreeSamplingEmbeddings, VQDiffusionPipeline
| 44 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
"""simple docstring"""
def lowercase ( lowerCAmelCase__ : List[Any] , lowerCAmelCase__ : List[Any] ) -> Optional[Any]:
return (pointa[0] - pointa[0]) ** 2 + (pointa[1] - pointa[1]) ** 2
def lowercase ( lowerCAmelCase__ : int , lowerCAmelC... | 45 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
"""simple docstring"""
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_uti... | 46 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
'''simple docstring'''
import os
import sys
import unittest
lowerCamelCase : Optional[Any] = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
... | 47 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
import json
import os
import tempfile
from unittest.mock import patch
import torch
from torch.utils.data import DataLoader, TensorDataset
from accelerate import DistributedType, infer_auto_device_map, init_empty_weights
from accelerate.accelerator import Accelerator
from accelerate.state import Gr... | 48 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedu... | 249 | 0 |
from __future__ import annotations
from math import pi
# Define the Reduced Planck Constant ℏ (H bar), speed of light C, value of
# Pi and the function
__snake_case :List[Any] = 1.054571817E-34 # unit of ℏ : J * s
__snake_case :List[str] = 3E8 # unit of c : m * s^-1
def ... | 49 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
from ..utils import DummyObject, requires_backends
class lowerCAmelCase ( metaclass=__UpperCamelCase ):
UpperCAmelCase__ = ["""torch"""]
def __init__( self : List[Any] , *UpperCAmelCase : Optional[Any] , **UpperCAmelCase : List[str] ) -> int:
... | 50 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
import hashlib
import unittest
from transformers import MODEL_FOR_DEPTH_ESTIMATION_MAPPING, is_torch_available, is_vision_available
from transformers.pipelines import DepthEstimationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
... | 51 |
"""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 Opt... | 249 | 0 |
def A_ ( _lowerCAmelCase = 50 ) -> int:
UpperCamelCase : List[Any] = [[0] * 3 for _ in range(length + 1 )]
for row_length in range(length + 1 ):
for tile_length in range(2 , 5 ):
for tile_start in range(row_length - tile_length + 1 ):
different_co... | 52 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
a__ : List[str] =argparse.ArgumentParser()
parser.add_argument(
'''--checkpoint_path''', default=None, type=st... | 53 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import deque
class UpperCamelCase_ :
"""simple docstring"""
def __init__( self : str , UpperCAmelCase__ : list[str] ) -> Any:
__SCREAMING_SNAKE_CASE = []
self.adlist.append(
... | 54 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ : Union[str, Any] = logging.get_logger(__name__)
a_ : Optional[Any] = {
"""microsoft/unispeech-sat-base-100h-libri-ft""": (
""... | 55 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
'''simple docstring'''
import io
import json
import unittest
from parameterized import parameterized
from transformers import FSMTForConditionalGeneration, FSMTTokenizer
from transformers.testing_utils import get_tests_dir, require_torch, slow, torch_device
from utils import calculate_bleu
a : Any ... | 56 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
"""simple docstring"""
# Lint as: python3
import itertools
import os
import re
A : Dict = re.compile(R"([A-Z]+)([A-Z][a-z])")
A : Union[str, Any] = re.compile(R"([a-z\d])([A-Z])")
A : Any = re.compile(R"(?<!_)_(?!_)")
A : List[Any] = re.compile(R"(_{2,})")... | 57 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
import torch
import accelerate
from accelerate import debug_launcher
from accelerate.test_utils import (
execute_subprocess_async,
require_cpu,
require_huggingface_suite,
require_multi_gpu,
require_single_gpu,
)
from accelerate... | 58 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
import os
import unittest
from huggingface_hub.utils import are_progress_bars_disabled
import transformers.models.bart.tokenization_bart
from transformers import logging
from transformers.testing_utils import CaptureLogger, mockenv, mockenv_context
from transformers.utils.logging import disable_progress_bar... | 59 |
"""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/... | 249 | 0 |
"""simple docstring"""
import pickle
import unittest
import torch
from accelerate import Accelerator
from accelerate.state import AcceleratorState
from accelerate.test_utils import require_cpu
@require_cpu
class snake_case_( unittest.TestCase ):
def lowerCamelCase__ ( self : ... | 60 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
"""simple docstring"""
class A_ :
'''simple docstring'''
def __init__( self ):
"""simple docstring"""
UpperCAmelCase_ : List[Any] = ""
UpperCAmelCase_ : Optional[int] = ""
UpperCAmelCase_ : Optional[Any] = []
def ... | 61 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
def _UpperCAmelCase ( SCREAMING_SNAKE_CASE__ : str , SCREAMING_SNAKE_CASE__ : int ):
return [sentence[i : i + ngram_size] for i in range(len(SCREAMING_SNAKE_CASE__ ) - ngram_size + 1 )]
if __name__ == "__main__":
from doctest import testmod
testmod()
| 62 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
'''simple docstring'''
import random
import torch
from huggingface_hub import HfApi
from diffusers import UNetaDModel
lowerCAmelCase_ : List[str] = HfApi()
lowerCAmelCase_ : str = {}
# fmt: off
lowerCAmelCase_ : Any = torch.tensor([
-0.7_515, -1.6_883, ... | 63 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
"""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,
... | 64 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
from collections.abc import Iterator, MutableMapping
from dataclasses import dataclass
from typing import Generic, TypeVar
UpperCamelCase__ = TypeVar('KEY')
UpperCamelCase__ = TypeVar('VAL')
@dataclass(frozen=UpperCAmelCase_ , slots=UpperCAmelCase_ )
class A ... | 65 |
"""simple docstring"""
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 imp... | 249 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
__a = {
"configuration_data2vec_audio": ["DATA2VEC_AUDIO_PRETRAINED_CONFIG_ARCHIVE_MAP", "Data2VecAudioConfig"],
"configuration_data2vec_te... | 66 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
from google.protobuf import descriptor as _descriptor
from google.protobuf import descriptor_pool as _descriptor_pool
from google.protobuf import symbol_database as _symbol_database
from google.protobuf.internal import builder as _builder
# @@protoc_insertion_point(imports)
__UpperCAmelCas... | 67 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
import string
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_: str ) -> None:
'''simple docstring'''
for key in range(len(string.ascii_uppercase ) ):
A__ = ""
for symbol in message:
if symbol in string.ascii_uppercase:
... | 68 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
"""simple docstring"""
import json
import logging
import math
import os
import sys
from dataclasses import dataclass, field
from typing import Optional
from datasets import Dataset, load_dataset
import transformers
from transformers import (
CONFIG_MAPPING,
MODEL_FOR_MASKED_LM_MAPPING,
AutoConfig,
A... | 69 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
'''simple docstring'''
import unittest
from transformers import DonutProcessor
A__ : Union[str, Any] ='''naver-clova-ix/donut-base'''
class UpperCAmelCase ( unittest.TestCase ):
def lowercase__ ( self : List[Any] ) -> int:
... | 70 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedu... | 249 | 0 |
import random
def A ( a_ ,a_ ,a_ = False ) -> dict:
__UpperCamelCase : dict ={i: [] for i in range(a_ )}
# if probability is greater or equal than 1, then generate a complete graph
if probability >= 1:
... | 71 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
def snake_case_ ( A_ : list[int] ):
'''simple docstring'''
if len(A_ ) == 0:
return array
_lowerCamelCase , _lowerCamelCase : List[str] = min(A_ ), max... | 72 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
import os
import unicodedata
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import AddedToken, PreTrainedTokenizer
from ...utils import logging
a =logging.get_logger(__name__)
a ={"""vocab_file""": """spiece.mo... | 73 |
"""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 Opt... | 249 | 0 |
"""simple docstring"""
import shutil
import tempfile
import unittest
from transformers import (
SPIECE_UNDERLINE,
AddedToken,
BatchEncoding,
NllbTokenizer,
NllbTokenizerFast,
is_torch_available,
)
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_se... | 74 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
'''simple docstring'''
from PIL import Image
def a_ ( __snake_case : Image , __snake_case : int ) -> Image:
"""simple docstring"""
lowerCamelCase_ =(259 * (level + 255)) / (255 * (259 - level))
def contrast(__snake_case ... | 75 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
import importlib
import inspect
import json
import os
import re
import shutil
import sys
from pathlib import Path
from typing import Dict, Optional, Union
from urllib import request
from huggingface_hub import HfFolder, cached_download, hf_hub_download, model_info
from packaging import version
from .. import __vers... | 76 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
import unittest
import numpy as np
from transformers import BlipTextConfig
from transformers.testing_utils import require_tf, slow
from transformers.utils import is_tf_available
from ...test_configuration_common import ConfigTester
from ...test_modeling... | 77 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
"""simple docstring"""
import argparse
import torch
# Step 1. clone https://github.com/microsoft/unilm
# Step 2. git checkout to https://github.com/microsoft/unilm/commit/b94ec76c36f02fb2b0bf0dcb0b8554a2185173cd
# Step 3. cd unilm
# Step 4. ln -s $(realpath wavlm/modules.py) ./ # create simlink
... | 78 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
'''simple docstring'''
from __future__ import annotations
lowerCamelCase_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __lowercase ( __lowercase , __lowercase , __lowercase , __lowercase , __lowercase , ) -> ... | 79 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
'''simple docstring'''
import numpy as np
def _UpperCamelCase ( __A ) -> np.ndarray:
'''simple docstring'''
return 1 / (1 + np.exp(-vector ))
def _UpperCamelCase ( __A ) -> np.ndarray:
'''simple docstring'''
return vect... | 80 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
import math
from collections.abc import Callable
def _A ( lowercase , lowercase , lowercase , lowercase = 1_00 , ):
"""simple docstring"""
a =x_start
a =fnc(... | 81 |
"""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/... | 249 | 0 |
import numpy as np
import torch
from torch.nn import CrossEntropyLoss
from transformers import AutoModelForCausalLM, AutoTokenizer
import datasets
from datasets import logging
A__ = """\
"""
A__ = """
Perplexity (PPL) is one of the most common metrics for evaluating language models.
It ... | 82 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
'''simple docstring'''
def A__ ( UpperCAmelCase_ ):
if num < 0:
return False
_UpperCamelCase : int = num
_UpperCamelCase : int = 0
while num > 0:
_UpperCamelCase : str = rev_num * 1_0 + (num % 1_0)
num //= 1_0... | 83 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class _SCREAMING_SNAKE_CASE :
UpperCAmelCase_ :int
UpperCAmelCase_ :TreeNode | None = None
UpperCAmelCase_ :TreeNode | Non... | 84 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
'''simple docstring'''
from __future__ import annotations
import collections
import pprint
from pathlib import Path
def UpperCamelCase_( snake_case : str ):
'''simple docstring'''
return "".join(sorted(snake_case ) )
def UpperCamelCase_( snake_case ... | 85 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
"""simple docstring"""
import unittest
from transformers import BarthezTokenizer, BarthezTokenizerFast, BatchEncoding
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow
from ...test_tokenization_common import TokenizerTesterMixin
@require_tokenizers
@requ... | 86 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
from transformers import BertTokenizer, EncoderDecoderModel, SeqaSeqTrainer, SeqaSeqTrainingArguments
from transformers.testing_utils import TestCasePlus, require_torch, slow
from transformers.utils import is_datasets_available
if is_datasets_available():
import datasets
class snake_case_ (... | 87 |
"""simple docstring"""
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 imp... | 249 | 0 |
import shutil
import tempfile
import unittest
from transformers import ClapFeatureExtractor, ClapProcessor, RobertaTokenizer, RobertaTokenizerFast
from transformers.testing_utils import require_sentencepiece, require_torchaudio
from .test_feature_extraction_clap import floats_list
@require_torchaudi... | 88 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
def __lowerCamelCase ( lowerCAmelCase_ ) -> Optional[Any]:
_a : Optional[Any] = []
_a : List[str] = set({'(', '[', '{'} )
_a : List[str] = set({')', ']', '}'} )
_a : Optional[int] ... | 89 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
__A = {
"configuration_xlm_roberta_xl": [
"XLM_ROBERTA_XL_PRETRAINED_CONFIG_ARCHIVE_MAP",
"XLMRobertaXLConfig",
"XLMRobertaXLOnnxConfig",
... | 90 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
class lowerCAmelCase__ :
'''simple docstring'''
def __init__( self : Any , lowercase_ : int = 0):
'''simple docstring'''
SCREAMING_SNAKE_CASE_ : List[Any] ... | 91 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
from __future__ import annotations
UpperCamelCase__ = 1.6021E-19 # units = C
def _a ( SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , SCREAMING_SNAKE_CASE_ : float , ):
if (conductivity, electron_conc, mobilit... | 92 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedu... | 249 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Union[str, Any] = {
"configuration_mask2former": [
"MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE... | 93 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
snake_case : List[str] = {
'''A''': '''.-''', '''B''': '''-...''', '''C''': '''-.-.''', '''D''': '''-..''', '''E''': '''.''', '''F''': '''..-.''', '''G''': '''--.''',
'''H''': '''....''', '''I''': '''..''', '''J''': '''.---''', '''K''': '''-.-''', '''L''': '''.-..''', '''M''': '''--''', '... | 94 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
import inspect
import unittest
from transformers import ViTMSNConfig
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_configuration_common import ConfigTester... | 95 |
"""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 Opt... | 249 | 0 |
"""simple docstring"""
import unittest
from transformers import MobileBertConfig, is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
from ...test_configurati... | 96 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
from ...utils import logging
__snake_case = logging.get_logger(__name__)
__snake_case = ... | 97 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
"""simple docstring"""
import os
from collections import namedtuple
import pytest
from datasets import ClassLabel, Features, Sequence, Value
from datasets.commands.test import TestCommand
from datasets.info import DatasetInfo, DatasetInfosDict
lowerCAmelCase__ : Union[str, Any] = namedtuple(
'... | 98 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
import json
import os
import shutil
import warnings
from argparse import ArgumentParser, Namespace
from pathlib import Path
from typing import List
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from cookiecutter.main import cookiecutter
lowercase : Union[str, Any... | 99 |
"""simple docstring"""
from __future__ import annotations
a_ = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase , __UpperCamelCase , __Up... | 249 | 0 |
"""simple docstring"""
import numpy
class SCREAMING_SNAKE_CASE_ :
"""simple docstring"""
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__):
__SCREAMING_SNAKE_CASE = input_array
# Random initial weights are assigned where first argument is the
# ... | 100 |
"""simple docstring"""
def __UpperCAmelCase ( __UpperCamelCase ):
__lowercase : str = [1]
__lowercase ,__lowercase ,__lowercase : List[str] = 0, 0, 0
__lowercase : List[str] = ugly_nums[ia] * 2
__lowerca... | 249 | 0 |
import sys
lowercase__ :Union[str, Any] = (
"73167176531330624919225119674426574742355349194934"
"96983520312774506326239578318016984801869478851843"
"85861560789112949495459501737958331952853208805511"
"12540698747158523863050715693290963295227443043557"
"66896648950445244523161731856403098... | 101 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
a_ = logging.get_logger(__name__)
a_ = {
'MIT/ast-finetuned-audioset-10-10-0.4593': (
'https://huggingface.co/MIT/ast-finetuned-audioset-10-10-0.4593/resolve/main... | 249 | 0 |
"""simple docstring"""
import sys
from collections import defaultdict
class _UpperCAmelCase :
'''simple docstring'''
def __init__(self ):
'''simple docstring'''
__snake_case : Optional[int] = []
def SCREAMING_SNAKE_CASE (self , a_ ):
'''sim... | 102 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import Tuple
from ..utils import cached_property, is_torch_available, is_torch_tpu_available, logging, requires_backends
from .benchmark_args_utils import BenchmarkArguments
if is_torch_available():
import torch... | 249 | 0 |
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('''>=''', '''4.25.0''')):
raise OptionalDependencyNotAvai... | 103 |
"""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/... | 249 | 0 |
'''simple docstring'''
from __future__ import annotations
from random import random
class lowercase_ :
"""simple docstring"""
def __init__( self : Union[str, Any] ,lowercase__ : int | None = None ):
__lowercase = value
__lowercase = random()
... | 104 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
a_ = {
'configuration_convnext': ['CONVNEXT_PRETRAINED_CONFIG_ARCHIVE_MA... | 249 | 0 |
"""simple docstring"""
import gc
import unittest
from diffusers import FlaxControlNetModel, FlaxStableDiffusionControlNetPipeline
from diffusers.utils import is_flax_available, load_image, slow
from diffusers.utils.testing_utils import require_flax
if is_flax_available():
import jax
... | 105 |
"""simple docstring"""
import unittest
from transformers import (
MODEL_FOR_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_CAUSAL_LM_MAPPING,
TextGenerationPipeline,
logging,
pipeline,
)
from transformers.testing_utils import (
CaptureLogger,
is_pipeline_test,
require_ac... | 249 | 0 |
"""simple docstring"""
from typing import Any
class SCREAMING_SNAKE_CASE :
"""simple docstring"""
def __init__( self : Any ,lowercase_ : Any ):
lowerCAmelCase__ : List[str] = data
lowerCAmelCase__ : Any = None
class S... | 106 |
"""simple docstring"""
class UpperCAmelCase_ :
def __init__( self , UpperCamelCase_ ) -> Tuple:
__lowercase : Any = n
__lowercase : Any = [None] * self.n
__lowercase : Optional[int] = 0 # index of the first... | 249 | 0 |
import unittest
from transformers import MODEL_FOR_ZERO_SHOT_OBJECT_DETECTION_MAPPING, is_vision_available, pipeline
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_tf,
require_torch,
require_vision,
slow,
)
from .test_pipelines_common import ANY
if i... | 107 |
"""simple docstring"""
import math
def __UpperCAmelCase ( __UpperCamelCase , __UpperCamelCase ):
if initial_intensity < 0:
raise ValueError('''The value of intensity cannot be negative''' )
# handling of negative values of initial intensi... | 249 | 0 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase__ = logging.get_logger(__name__)
lowerCAmelCase__ = {
'''MIT/ast-finetuned-audioset-10-10-0.4593''': (
'''https://huggingface.co/MIT/ast-finetuned-audiose... | 108 |
"""simple docstring"""
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import Features, Sequence, Value
from .base import TaskTemplate
@dataclass(frozen=snake_case )
class UpperCAmelCase_ ( snake_case ):
# `task` is not a Clas... | 249 | 0 |
"""simple docstring"""
import unittest
import numpy as np
from transformers import RobertaConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...test_modeling_flax_common import FlaxModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_flax_available():
... | 109 |
"""simple docstring"""
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 imp... | 249 | 0 |
def lowerCamelCase_ ( UpperCamelCase__ : Optional[Any] , UpperCamelCase__ : int ) -> Any:
"""simple docstring"""
__lowerCamelCase = ''''''
for i in table:
res += inp[i - 1]
return res
def lower... | 90 |
"""simple docstring"""
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
a_ = '\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbo... | 249 | 0 |
'''simple docstring'''
import os
import jsonlines
import numpy as np
from tqdm import tqdm
lowerCAmelCase: Tuple = 2_0_4_8
lowerCAmelCase: str = 4_0_9_6
lowerCAmelCase: Optional[int] = 4_2
lowerCAmelCase: str = os.environ.p... | 297 |
"""simple docstring"""
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class UpperCAmelCase_ ( snake_case ):
@staticmethod
@abstractmethod
def _lowerCamelCase ( UpperCamelCase_ ) -> Union[str, Any]:
raise NotImplementedError()
... | 249 | 0 |
"""simple docstring"""
from __future__ import annotations
def UpperCAmelCase__ ( SCREAMING_SNAKE_CASE : Optional[Any] ):
'''simple docstring'''
lowerCAmelCase = len(__UpperCamelCase ) // 2
# choose the middle 3 elements
lowerCAmelCase ... | 46 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import datasets
import numpy as np
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
EvalPrediction,
HfArgumentParser,
... | 249 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import rescale, resize, to_channel_dimension_format
from ...image_utils import (
Chann... | 276 |
"""simple docstring"""
from argparse import ArgumentParser, Namespace
from typing import Any, List, Optional
from ..pipelines import Pipeline, get_supported_tasks, pipeline
from ..utils import logging
from . import BaseTransformersCLICommand
try:
from fastapi import Body, FastAPI, HTTP... | 249 | 0 |
import csv
import tweepy
# Twitter API credentials
lowerCAmelCase__ :int = ''''''
lowerCAmelCase__ :Tuple = ''''''
lowerCAmelCase__ :Union[str, Any] = ''''''
lowerCAmelCase__ :Tuple = ''''''
def lowerCAmelCase__ ( a__: List[Any] ) -> Union[str, Any... | 329 |
"""simple docstring"""
import gc
import random
import tempfile
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMInverseScheduler,
DDIMSchedu... | 249 | 0 |
"""simple docstring"""
import warnings
from ...utils import logging
from .image_processing_deformable_detr import DeformableDetrImageProcessor
UpperCAmelCase = logging.get_logger(__name__)
class UpperCAmelCase_ ( _lowercase):
def __init__( self : Dict , *__U... | 256 |
"""simple docstring"""
from __future__ import annotations
from typing import Dict
from ...configuration_utils import PretrainedConfig
a_ = {
'susnato/ernie-m-base_pytorch': 'https://huggingface.co/susnato/ernie-m-base_pytorch/blob/main/config.json',
'susnato/ernie-m-large_p... | 249 | 0 |
import json
import os
import torch
from diffusers import UNetaDModel
os.makedirs("""hub/hopper-medium-v2/unet/hor32""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/unet/hor128""", exist_ok=True)
os.makedirs("""hub/hopper-medium-v2/value_function""", exist_ok=True)
def A_ ( A__ ) -> Tuple:
... | 99 |
"""simple docstring"""
import argparse
import json
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import SegformerImageProcessor, SwinConfig, UperNetConfig, UperNetForSemanticSegmentation
def __UpperCAmelCas... | 249 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available
__a = {"tokenization_herbert": ["HerbertTokenizer"]}
try:
if not is_tokenizers_available():
raise OptionalDependencyNotAvailable()
except Op... | 66 |
"""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 Opt... | 249 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class A__ ( __SCREAMING_SNAKE_CASE):
_UpperCAmelCase : Optional[Any] = ["""image_processor""", """tokenizer"""]
_UpperCAmelCase : Union[str, Any] ... | 287 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_sentencepiece_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
a_ = {
'con... | 249 | 0 |
import numpy
class __A:
"""simple docstring"""
def __init__(self , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ):
UpperCamelCase__ = input_array
# Random initial weights are assigned where first argument is the
# number of nodes in previous layer and ... | 244 |
"""simple docstring"""
import itertools
from dataclasses import dataclass
from typing import List, Optional
import pyarrow as pa
import pyarrow.parquet as pq
import datasets
from datasets.table import table_cast
a_ = datasets.utils.logging.get_logger(__name__)
@dataclass
clas... | 249 | 0 |
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
__snake_case = (7_20, 12_80) # Height, Width
__snake_case = (0.4, 0.6) # if height or width lower than this scale, drop it.
__snake_case = 1 / 1_00
__snake_case = ''... | 348 |
"""simple docstring"""
import unittest
import numpy as np
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_imag... | 249 | 0 |
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