code stringlengths 86 54.5k | code_codestyle int64 0 371 | style_context stringlengths 87 49.2k | style_context_codestyle int64 0 349 | label int64 0 1 |
|---|---|---|---|---|
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionAttendAndExcitePipeline,
UNetaDConditionModel,
)
from diffusers.utils import load_numpy, skip_mps, ... | 326 |
import inspect
import re
from hashlib import shaaaa
from typing import Dict, List
from .arrow import arrow
from .audiofolder import audiofolder
from .csv import csv
from .imagefolder import imagefolder
from .json import json
from .pandas import pandas
from .parquet import parquet
from .sql import sql... | 32 | 0 |
from __future__ import annotations
def a ( SCREAMING_SNAKE_CASE_ : list[int] , SCREAMING_SNAKE_CASE_ : list[int] , SCREAMING_SNAKE_CASE_ : int ):
"""simple docstring"""
UpperCamelCase : Tuple = list(rang... | 360 |
import unittest
import numpy as np
from transformers.testing_utils import require_pytesseract, require_torch
from transformers.utils import is_pytesseract_available, is_torch_available
from ...test_image_processing_common import ImageProcessingSavingTestMixin, prepare_image_inputs
if is_torch_avail... | 315 | 0 |
'''simple docstring'''
import unittest
from transformers import AutoTokenizer, FalconConfig, 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
from ...test_m... | 145 | '''simple docstring'''
import unittest
from huggingface_hub import hf_hub_download
from transformers import MODEL_FOR_VIDEO_CLASSIFICATION_MAPPING, VideoMAEFeatureExtractor
from transformers.pipelines import VideoClassificationPipeline, pipeline
from transformers.testing_utils import (
is_pipeline_test,
... | 145 | 1 |
def lowerCAmelCase__ ( SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> list:
lowerCAmelCase__ : int = word.split()
def justify(SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ , SCREAMING_SNAKE_CASE_ ) -> str:
lowerCAmelCase__ : Any ... | 307 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCamelCase__ = {
"""configuration_blip""": [
"""BLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
""... | 307 | 1 |
from __future__ import annotations
import time
from math import sqrt
# 1 for manhattan, 0 for euclidean
A__ : Tuple = 0
A__ : Any = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0... | 207 |
from typing import Dict
import numpy as np
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline, PipelineException
if is_tf_available():
import tensorflow as tf
from ..tf_utils import stable_softmax
... | 207 | 1 |
'''simple docstring'''
import unittest
from transformers import BertGenerationTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCamelCase... | 366 |
'''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_dimensio... | 337 | 0 |
from __future__ import annotations
def A ( _UpperCAmelCase : str , _UpperCAmelCase : list[str] | None = None ) -> list[list[str]]:
'''simple docstring'''
_UpperCAmelCase = word_bank or []
# create a table
_UpperCAmelCase = len(_UpperCAme... | 339 |
import os
import sys
import unittest
UpperCAmelCase__ = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import check_dummies # noqa: E402
from check_dummies import create_dummy_files, create_dummy_object, find_backend, re... | 339 | 1 |
import random
def UpperCamelCase__ ( lowerCAmelCase , lowerCAmelCase , lowerCAmelCase = False ):
"""simple docstring"""
_lowerCAmelCase = {i: [] for i in range(_UpperCamelCase )}
# if probability is greater or equal than... | 359 |
'''simple docstring'''
import logging
import os
import threading
import time
try:
import warnings
except ImportError:
A__ : Tuple =None
try:
import msvcrt
except ImportError:
A__ : str =None
try:
impo... | 220 | 0 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterable, Iterator
from dataclasses import dataclass
a__ : Union[str, Any] =(3, 9, -11, 0, 7, 5, 1, -1)
a__ : Optional[int] =(4, 6, 2, 0, 8, 10, 3, -2)
@dataclass
class snake_case :
"""si... | 53 |
"""simple docstring"""
from __future__ import annotations
from decimal import Decimal
from numpy import array
def _snake_case ( _snake_case : list[list[float]] ):
lowerCAmelCase : str = Decimal
# Check if the provided matrix has 2 rows and 2 columns
# since this implement... | 60 | 0 |
'''simple docstring'''
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
a_ = 6378137.0
a_ = 6356752.314245
a_ = 6_3_7_8_1_3_7
def _a( UpperCamelCase__ : float, UpperCamelCase__ : float, UpperCamelCase__ : float... | 222 |
'''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'\n Args:\n input_ids (`jnp.ndarray` of shape `(batch_size, s... | 222 | 1 |
"""simple docstring"""
from __future__ import annotations
import time
lowerCamelCase_ = list[tuple[int, int]]
lowerCamelCase_ = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0,... | 191 |
"""simple docstring"""
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCamelCase_ = logging.get_logger(__name__)
lowerCamelCase_ = {}
class _SCREAMING_SNAKE_CASE( A ):
SCREAMING_SNAKE_CASE_ : List[Any] ... | 191 | 1 |
'''simple docstring'''
import inspect
import unittest
from transformers import ConvNextVaConfig
from transformers.models.auto import get_values
from transformers.models.auto.modeling_auto import MODEL_FOR_BACKBONE_MAPPING_NAMES, MODEL_MAPPING_NAMES
from transformers.testing_utils import require_torch, require_vision... | 199 |
'''simple docstring'''
import numpy as np
from scipy.spatial.distance import cdist
from sklearn.metrics import fa_score
import datasets
_snake_case = '\\n @inproceedings{kakwani2020indicnlpsuite,\n title={{IndicNLPSuite: Monolingual Corpora, Evaluation Benchmarks and Pre-trained Multilingual Languag... | 199 | 1 |
'''simple docstring'''
from collections.abc import Sequence
def _A ( A__ , A__ ):
"""simple docstring"""
return sum(c * (x**i) for i, c in enumerate(A__ ) )
def _A ( A__ , A__ ):
"""simple docstring"""
__lowercase = 0.0
for c... | 104 |
import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...test_pip... | 214 | 0 |
import importlib.metadata
import operator
import re
import sys
from typing import Optional
from packaging import version
snake_case : List[str] = {
'''<''': operator.lt,
'''<=''': operator.le,
'''==''': operator.eq,
'''!=''': operator.ne,
'''>=''': operator.ge,
'''>''... | 362 |
from __future__ import annotations
def __lowercase ( __lowerCAmelCase : List[Any] , __lowerCAmelCase : Optional[Any] , __lowerCAmelCase : str , __lowerCAmelCase : List[str] ): # noqa: E741
while r - l > 1:
a__ = (l + r... | 109 | 0 |
import gc
import unittest
from transformers import MODEL_FOR_MASKED_LM_MAPPING, TF_MODEL_FOR_MASKED_LM_MAPPING, FillMaskPipeline, pipeline
from transformers.pipelines import PipelineException
from transformers.testing_utils import (
is_pipeline_test,
is_torch_available,
nested_simplify,
require_t... | 10 |
"""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_utils im... | 315 | 0 |
"""simple docstring"""
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2... | 157 |
"""simple docstring"""
import inspect
import unittest
from transformers import RegNetConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_configuration_common imp... | 157 | 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,
logg... | 3 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
... | 258 | 0 |
'''simple docstring'''
import torch
from diffusers import DDPMScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase_ ( __magic_name__ ):
lowercase = (DDPMScheduler,)
def _lowercase( self , **A ) -> int:
UpperCAmelCase ... | 356 |
'''simple docstring'''
from math import loga
def __lowerCamelCase ( _lowercase ) -> int:
if a < 0:
raise ValueError("""Input value must be a positive integer""" )
elif isinstance(_lowercase , _lowercase ):
raise TypeError("""Input value must be... | 338 | 0 |
def a ( _UpperCAmelCase : Optional[Any] = 4_00_00_00 ):
'''simple docstring'''
__UpperCAmelCase : int = []
__UpperCAmelCase : str = 0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(_UpperCamel... | 226 |
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class __SCREAMING_SNAKE_CASE ( A__ ):
A : Union[List[np.... | 337 | 0 |
import requests
from bsa import BeautifulSoup
def _A ( SCREAMING_SNAKE_CASE : str , SCREAMING_SNAKE_CASE : dict ):
"""simple docstring"""
a__ : Optional[Any] =BeautifulSoup(requests.get(SCREAMING_SNAKE_CASE , params=SCREAMING_SNAKE_CASE ).cont... | 148 |
UpperCAmelCase : Dict = [0, 2, 4, 6, 8]
UpperCAmelCase : Tuple = [1, 3, 5, 7, 9]
def _A ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : list[int] , SCREAMING_SNAKE_CASE : int ):
"... | 148 | 1 |
"""simple docstring"""
import argparse
import torch
from datasets import load_dataset
from donut import DonutModel
from transformers import (
DonutImageProcessor,
DonutProcessor,
DonutSwinConfig,
DonutSwinModel,
MBartConfig,
MBartForCausalLM,
VisionEncoder... | 40 |
"""simple docstring"""
# limitations under the License.
from typing import Optional, Tuple, Union
import torch
from diffusers import DiffusionPipeline, ImagePipelineOutput
class a ( a_ ):
def __init__( self , _lowerCamelCase , _lowerCamelCase ):
super()... | 220 | 0 |
"""simple docstring"""
import os
import tempfile
import unittest
from transformers import FlaubertConfig, is_torch_available
from transformers.testing_utils import require_torch, require_torch_gpu, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 38 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import MutableSequence
class lowerCAmelCase :
'''simple docstring'''
def __init__( self , lowerCAmelCase__ , lowerCAmelCase__ ) -> None:
if len(lowerCAme... | 38 | 1 |
from collections.abc import Callable
def a_ ( _A , _A , _A ) -> float:
"""simple docstring"""
snake_case__ = a
snake_case__ = b
if function(_A ) == 0: # one of the a or b is a root for the function
... | 307 |
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.war... | 307 | 1 |
'''simple docstring'''
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from diffusers import (
DDIMScheduler,
KandinskyVaaControlnetImgaImgPipeline,
KandinskyVaaPriorEmbaEmbPipeline,
UNetaDConditionModel,
VQModel,
)
from diffusers.utils impor... | 355 |
'''simple docstring'''
from ..utils import DummyObject, requires_backends
class _snake_case ( metaclass=lowercase_ ):
lowerCAmelCase_ : Dict = ["flax"]
def __init__( self , *a__ , **a__ ) -> List[Any]:
'''simple docstring'''
... | 92 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
lowercase__ : Tuple = logging.get_logger(__name__)
class UpperCAmelCase ( lowerCamelCase_ , ... | 187 |
'''simple docstring'''
from datasets.utils.patching import _PatchedModuleObj, patch_submodule
from . import _test_patching
def _UpperCamelCase ( ):
'''simple docstring'''
import os as original_os
from os import path as original_path
from os import rename as original_rename
from os.path im... | 346 | 0 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, PriorTransfo... | 355 |
_UpperCAmelCase = {0: [2, 3], 1: [0], 2: [1], 3: [4], 4: []}
_UpperCAmelCase = {0: [1, 2, 3], 1: [2], 2: [0], 3: [4], 4: [5], 5: [3]}
def _SCREAMING_SNAKE_CASE ( SCREAMING_SNAKE_CASE :dict[int, list[int]] , SCREAMING_SNAKE_CASE :int , SCREAMING_SNAKE_CAS... | 232 | 0 |
import gc
import math
import unittest
import torch
from diffusers import UNetaDModel
from diffusers.utils import floats_tensor, logging, slow, torch_all_close, torch_device
from diffusers.utils.testing_utils import enable_full_determinism
from .test_modeling_common import ModelTesterMixin, UNetTesterMixin
_lo... | 14 |
"""simple docstring"""
from __future__ import annotations
class SCREAMING_SNAKE_CASE__ :
def __init__( self , _SCREAMING_SNAKE_CASE ) -> None:
'''simple docstring'''
UpperCAmelCase : Any = data
UpperCAmelCase : Node | None = None
UpperCAmelCase : ... | 109 | 0 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class __A ( a ):
def _snake_case ( self , UpperCAmelCase_ ):
with open(UpperCAmelCase_ , encoding="""utf-8""" ) as input_file:
lowerCamelCase ... | 358 |
import logging
import os
from dataclasses import dataclass, field
from typing import Dict, Optional
import numpy as np
from utils_multiple_choice import MultipleChoiceDataset, Split, processors
import transformers
from transformers import (
AutoConfig,
AutoModelForMultipleChoice,
AutoTokenizer,
... | 262 | 0 |
import warnings
from ...utils import is_sklearn_available, requires_backends
if is_sklearn_available():
from scipy.stats import pearsonr, spearmanr
from sklearn.metrics import fa_score, matthews_corrcoef
_snake_case = (
'''This metric will be removed from the library soon, metrics should b... | 157 | def _UpperCamelCase ( snake_case__ ) -> bool:
if not isinstance(snake_case__, snake_case__ ):
raise ValueError("check_bouncy() accepts only integer arguments" )
__UpperCAmelCase : Optional[int] = str(snake_case__ )
__UpperCAmelC... | 157 | 1 |
import doctest
import sys
import warnings
from os.path import abspath, dirname, join
import _pytest
from transformers.testing_utils import HfDoctestModule, HfDocTestParser
# allow having multiple repository checkouts and not needing to remember to rerun
# 'pip install -e .[dev]' when switching betwee... | 362 |
import argparse
import datetime
import json
import time
import warnings
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoTokenizer
from utils import calculate_bleu, calculate_rou... | 282 | 0 |
'''simple docstring'''
from math import factorial
class a__:
def __init__( self : Optional[Any] , __snake_case : List[str] , __snake_case : Dict ):
a : str = real
if isinstance(__SCREAMING_SNAKE_CASE , __SCREAMING_SNAKE_CASE ):
... | 297 | import unittest
from transformers import EsmConfig, is_torch_available
from transformers.testing_utils import TestCasePlus, require_torch, slow, torch_device
from ...test_configuration_common import ConfigTester
from ...test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
from ...tes... | 338 | 0 |
"""simple docstring"""
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from ...tokenization_utils import AddedToken
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logging
if is_sentencepiece_available():... | 356 | import argparse
import struct
import unittest
class _snake_case :
def __init__( self: Tuple , __lowerCamelCase: bytes ) -> None:
__UpperCAmelCase : Tuple = data
# Initialize hash values
__UpperCAmelCase : An... | 342 | 0 |
"""simple docstring"""
def UpperCamelCase__ ( lowercase__ : int ):
snake_case : List[Any] = (1 + 24 * n) ** 0.5
return ((1 + root) / 6) % 1 == 0
def UpperCamelCase__ ( lowercase__ : int = 5000 ):
snake_case : Dict = [(i * (3 ... | 148 |
"""simple docstring"""
import torch
from diffusers import StableDiffusionPipeline
__A = "path-to-your-trained-model"
__A = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.floataa).to("cuda")
__A = "A photo of sks dog in a bucket"
__A ... | 148 | 1 |
import unittest
from transformers import PegasusTokenizer, PegasusTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import TokenizerTesterMixin
UpperCAm... | 267 |
import argparse
import requests
import torch
# pip3 install salesforce-lavis
# I'm actually installing a slightly modified version: pip3 install git+https://github.com/nielsrogge/LAVIS.git@fix_lavis
from lavis.models import load_model_and_preprocess
from PIL import Image
from transformers import (
AutoTokeniz... | 267 | 1 |
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def SCREAMING_SNAKE_CASE_ ( __magic_name__ : Dict ) -> Any:
"""simple docstring"""
return 1... | 38 |
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPImageProcessor, CLIPVisionConfig, CLIPVisionModel
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEImgaImgPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.utils im... | 38 | 1 |
"""simple docstring"""
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def A ( snake_case :int , snake_case :int , snake_case :int , snake_case :int , snake_case :int , snake_case :int ) -> np.ndarray... | 263 |
"""simple docstring"""
def A ( snake_case :int ) -> int:
__UpperCamelCase = abs(snake_case )
__UpperCamelCase = 0
while n > 0:
res += n % 1_0
n //= 1_0
return res
def A ( snake_case :int ) -> int:
__UpperCamelCase = abs(snake_case )
... | 263 | 1 |
"""simple docstring"""
from math import pi, sqrt
def lowercase_ ( _snake_case ):
if num <= 0:
raise ValueError("""math domain error""" )
if num > 171.5:
raise OverflowError("""math range error""" )
elif num - int(_snake_case ) no... | 25 |
import argparse
import os
import re
import packaging.version
UpperCamelCase__ = """examples/"""
UpperCamelCase__ = {
"""examples""": (re.compile(R"""^check_min_version\(\"[^\"]+\"\)\s*$""", re.MULTILINE), """check_min_version(\"VERSION\")\n"""),
"""init""": (re.compile(R"""^__version__\s... | 92 | 0 |
"""simple docstring"""
from __future__ import annotations
lowerCamelCase__ = 10
def __lowerCAmelCase (_UpperCamelCase ):
__lowerCAmelCase : List[Any] = 1
__lowerCAmelCase : Dict = max(_UpperCamelCase )
while placement <= max_digit:
# declare ... | 371 |
"""simple docstring"""
lowerCamelCase__ = """0.21.0"""
from .accelerator import Accelerator
from .big_modeling import (
cpu_offload,
cpu_offload_with_hook,
disk_offload,
dispatch_model,
init_empty_weights,
init_on_device,
load_checkpoint_and_dispatch,
)
from .data_loader imp... | 182 | 0 |
"""simple docstring"""
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import torch
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
@dataclass
class __magic_name__ ( __lowercase ... | 291 |
import unittest
import numpy as np
import torch
from torch import nn
from transformers import (
CLIPImageProcessor,
CLIPTextConfig,
CLIPTextModelWithProjection,
CLIPTokenizer,
CLIPVisionConfig,
CLIPVisionModelWithProjection,
)
from diffusers import KandinskyVaaPriorPipeline, Pr... | 232 | 0 |
import unittest
from transformers import (
MODEL_FOR_OBJECT_DETECTION_MAPPING,
AutoFeatureExtractor,
AutoModelForObjectDetection,
ObjectDetectionPipeline,
is_vision_available,
pipeline,
)
from transformers.testing_utils import (
is_pipeline_test,
nested_simplify,
require_pytes... | 355 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase__ = logging.get_logger(__name__)
UpperCamelCase__ = {
"facebook/s2t-wav2vec2-large-en-de": (
"https://huggingface.co/facebook/s2t-wav2vec2-large-en-de/resolve/main/config.json"
),
# See a... | 87 | 0 |
"""simple docstring"""
from __future__ import annotations
UpperCAmelCase__ : Union[str, Any] = list[tuple[int, int]]
UpperCAmelCase__ : Any = [
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0... | 25 |
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_available():
import to... | 262 | 0 |
"""simple docstring"""
import os
import socket
from contextlib import contextmanager
import torch
from ..commands.config.default import write_basic_config # noqa: F401
from ..state import PartialState
from .dataclasses import DistributedType
from .imports import is_deepspeed_available, is_tpu_available
from .tra... | 73 |
"""simple docstring"""
import argparse
from collections import defaultdict
def lowerCAmelCase_( lowercase_ : str , lowercase_ : Dict , lowercase_ : Tuple , lowercase_ : str , lowercase_ : str ) -> Optional[int]:
_low... | 73 | 1 |
"""simple docstring"""
from collections import deque
def UpperCAmelCase ( UpperCAmelCase ) -> int:
snake_case_ = len(UpperCAmelCase )
snake_case_ = deque()
snake_case_ = [False for _ in range(UpperCAmelCase )]
snake_c... | 69 |
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 S... | 282 | 0 |
import torch
from diffusers import DPMSolverSDEScheduler
from diffusers.utils import torch_device
from diffusers.utils.testing_utils import require_torchsde
from .test_schedulers import SchedulerCommonTest
@require_torchsde
class a ( __lowerCamelCase ):
__lowerCAmelCase : ... | 44 |
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from transformers import MaMaaaTokenizer, is_torch_available
from transformers.testing_utils import (
get_tests_dir,
nested_simplify,
require_sentencepiece,
require_tokenizers,
require_torch,
... | 44 | 1 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
SCREAMING_SNAKE_CASE_ = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_ = {
"""mi... | 296 |
from typing import Callable, Optional
from .. import Features
from ..packaged_modules.generator.generator import Generator
from .abc import AbstractDatasetInputStream
class UpperCamelCase__ ( lowerCAmelCase_ ):
'''simple docstring'''
def __init__( self : Un... | 296 | 1 |
def SCREAMING_SNAKE_CASE__ ( lowerCamelCase__ , lowerCamelCase__ ) -> List[str]:
if density <= 0:
raise ValueError('Impossible fluid density' )
if bulk_modulus <= 0:
raise ValueError('Impossible bulk modulus' )
return (bulk_modulus / density) ** 0.5
if __name__... | 370 |
from __future__ import annotations
import unittest
from transformers import is_tf_available, is_torch_available
from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, SMALL_MODEL_IDENTIFIER, is_pt_tf_cross_test, slow
if is_tf_available():
from transformers import (
AutoConfig,
... | 113 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
snake_case_ = {"""configuration_encoder_decoder""": ["""EncoderDecoderConfig"""]}
try:
if not is_torch... | 24 |
import argparse
import collections
import os
import re
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_table.py
_UpperCAmelCase : Optional[int] ="""src/transformers"""
_Up... | 262 | 0 |
import math
import os
import sys
def UpperCamelCase ( _A ):
"""simple docstring"""
__magic_name__ : Dict = """"""
try:
with open(_A, """rb""" ) as binary_file:
__magic_name__ : Optional[int] ... | 138 |
from collections import OrderedDict
from typing import Any, Mapping, Optional
from ... import PreTrainedTokenizer
from ...configuration_utils import PretrainedConfig
from ...file_utils import TensorType, is_torch_available
from ...onnx import OnnxConfig, OnnxConfigWithPast, OnnxSeqaSeqConfigWithPast
from ...onn... | 138 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Callable
def __UpperCAmelCase ( A : Callable[[int | float], int | float] , A : int | float , A : int | float , A : int = 1_0_0 , ) -> float:
UpperCAm... | 304 |
'''simple docstring'''
import logging
from transformers.configuration_utils import PretrainedConfig
_UpperCamelCase : Any = logging.getLogger(__name__)
class snake_case__ ( UpperCamelCase):
a_ = "masked_bert"
def __init__( self : str , _A : ... | 304 | 1 |
'''simple docstring'''
import time
from contextlib import contextmanager
from pathlib import Path
import pytest
import requests
from huggingface_hub.hf_api import HfApi, HfFolder
SCREAMING_SNAKE_CASE_: Union[str, Any] ='__DUMMY_TRANSFORMERS_USER__'
SCREAMING_SNAKE_CASE_: Optional[Any] ='Dummy User'
SC... | 367 | '''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowerCAmelCase_ ( snake_case_ : Union[str, Any] ) -> Optional[int]:
'''simple docstring'''
UpperCAmelCase_ = FileLock(str(tmpdir / "foo.lock" ... | 106 | 0 |
"""simple docstring"""
import argparse
from collections import defaultdict
import yaml
_lowercase = 'docs/source/en/_toctree.yml'
def _snake_case ( snake_case__ : str ):
A = defaultdict(_lowercase )
A = []
A = []
for doc in doc_list:
... | 74 | from math import ceil
def A ( _lowercase = 1_001 ):
SCREAMING_SNAKE_CASE : Any = 1
for i in range(1 , int(ceil(n / 2.0 ) ) ):
SCREAMING_SNAKE_CASE : Union[str, Any] = 2 * i + 1
SCREAMING_SNAKE_CASE ... | 182 | 0 |
'''simple docstring'''
import argparse
import os
import transformers
from .convert_slow_tokenizer import SLOW_TO_FAST_CONVERTERS
from .utils import logging
logging.set_verbosity_info()
A : int = logging.get_logger(__name__)
A : List[Any] = {name: getattr(transformers... | 367 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
A : Optional[int] = {
'''configuration_mask2former''': [
'''MASK2FORMER_PRETRAINED_CONFIG_ARCHIVE_MAP''',
'... | 227 | 0 |
'''simple docstring'''
from .integrations import (
is_optuna_available,
is_ray_available,
is_sigopt_available,
is_wandb_available,
run_hp_search_optuna,
run_hp_search_ray,
run_hp_search_sigopt,
run_hp_search_wandb,
)
from .trainer_utils import (
HPSearchBackend,
default... | 80 | import warnings
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class snake_case_ ( __A ):
__A :... | 87 | 0 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import _LazyModule
__SCREAMING_SNAKE_CASE : str = {"tokenization_wav2vec2_phoneme": ["Wav2Vec2PhonemeCTCTokenizer"]}
if TYPE_CHECKING:
from .tokenization_wavaveca_phoneme import WavaVecaPhonemeCTCTokenizer
else:
i... | 359 |
"""simple docstring"""
from __future__ import annotations
from collections.abc import Iterator
class __A :
'''simple docstring'''
def __init__( self : Any , UpperCAmelCase_ : int ) ->None:
"""simple docstring"""
snake... | 233 | 0 |
# Copyright 2021 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless requ... | 73 |
from __future__ import annotations
import time
a =list[tuple[int, int]]
a =[
[0, 0, 0, 0, 0, 0, 0],
[0, 1, 0, 0, 0, 0, 0], # 0 are free path whereas 1's are obstacles
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0],
[1, 0, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, ... | 73 | 1 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
UpperCamelCase = {
'configuration_wav2vec2': ['WAV_2_VEC_2_PRETRAINED_CONFIG_ARCHIVE_MAP', 'Wav2Vec2C... | 221 |
from __future__ import annotations
UpperCamelCase = [
[-1, 0], # left
[0, -1], # down
[1, 0], # right
[0, 1], # up
]
def _A ( lowerCAmelCase_ : list[list[int]] , lowerCAmelCase_ : list[int] , lowerCAmelCase_ : list[i... | 221 | 1 |
"""simple docstring"""
import argparse
import os
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_task_guides.py
_a : Optional[Any] = 'src/transformers'
_a ... | 44 | """simple docstring"""
def SCREAMING_SNAKE_CASE ( _lowerCamelCase : Any ) -> List[Any]: # noqa: E741
_lowerCAmelCase : Optional[int] = len(_lowerCamelCase )
_lowerCAmelCase : str = 0
_lowerCAmelCase : Any = [0] * n
... | 44 | 1 |
# Copyright 2023 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless require... | 369 |
import re
import warnings
from contextlib import contextmanager
from ...processing_utils import ProcessorMixin
class UpperCAmelCase_ ( _a):
'''simple docstring'''
__UpperCamelCase : int = ["image_processor", "tokenizer"]
__UpperCamelCase : List[st... | 315 | 0 |
class __lowerCamelCase :
"""simple docstring"""
def __init__( self , UpperCAmelCase ):
"""simple docstring"""
_UpperCAmelCase = val
_UpperCAmelCase = None
_UpperCAmelCase = None
def ... | 39 |
"""simple docstring"""
def lowercase (SCREAMING_SNAKE_CASE_ : int = 10_00 ) -> int:
SCREAMING_SNAKE_CASE = 2**power
SCREAMING_SNAKE_CASE = 0
while n:
SCREAMING_SNAKE_CASE , SCREAMING_SNAKE_CASE = ... | 113 | 0 |
'''simple docstring'''
import json
import os
import tempfile
from transformers.testing_utils import check_json_file_has_correct_format
class lowercase :
"""simple docstring"""
UpperCAmelCase = None
def _snake_case ( self ) -> ... | 360 |
'''simple docstring'''
from typing import Optional
import pyspark
from .. import Features, NamedSplit
from ..download import DownloadMode
from ..packaged_modules.spark.spark import Spark
from .abc import AbstractDatasetReader
class lowercase ( _lowerCamelCase ):
"""simple docstring"""
de... | 349 | 0 |
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__A : Union[str, Any] = logging.get_logger(__name__)
__A : Optional[int] = {... | 138 |
__A : dict[tuple[int, int, int], int] = {}
def SCREAMING_SNAKE_CASE__ ( _UpperCAmelCase, _UpperCAmelCase, _UpperCAmelCase ) -> int:
'''simple docstring'''
if late == 3 or absent == 2:
return 0
# if we have no days left, and have not failed any... | 138 | 1 |
import re
from typing import Callable, List, Optional, Union
import tensorflow as tf
try:
from tensorflow.keras.optimizers.legacy import Adam
except ImportError:
from tensorflow.keras.optimizers import Adam
class _A ( tf.keras.optimizers.schedules.LearningRateSchedule ):
... | 116 |
import copy
from typing import Dict, Optional
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
from ..detr import DetrConfig
from ..swin import SwinConfig
lowerCAmelCase_ = {
'facebook/maskformer-swin-base-ade': (
... | 116 | 1 |
from __future__ import annotations
_lowerCamelCase : Optional[Any] = 1.60_21E-19 # units = C
def SCREAMING_SNAKE_CASE ( lowercase_ , lowercase_ , lowercase_ , ) -> tuple[str, float]:
"""simple docstring"""
if (conductivity, electron_conc, mobilit... | 14 |
"""simple docstring"""
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
... | 106 | 0 |
"""simple docstring"""
from ..utils import DummyObject, requires_backends
class UpperCamelCase__ ( metaclass=lowercase_ ):
"""simple docstring"""
_SCREAMING_SNAKE_CASE = ["""transformers""", """torch""", """note_seq"""]
... | 289 |
"""simple docstring"""
import logging
from transformers.configuration_utils import PretrainedConfig
lowercase__ : List[Any] = logging.getLogger(__name__)
class UpperCamelCase__ ( lowercase_ ):
"""simple docstring"""
... | 289 | 1 |
import argparse
import fairseq
import torch
from torch import nn
from transformers import (
MBartaaTokenizer,
MBartConfig,
MBartForCausalLM,
SpeechEncoderDecoderConfig,
SpeechEncoderDecoderModel,
WavaVecaConfig,
WavaVecaFeatureExtractor,
WavaVecaModel,
logging,
)
logging.set_ver... | 231 |
import collections
import json
import math
import os
import re
import time
from fnmatch import fnmatch
from typing import Dict
import requests
from slack_sdk import WebClient
__UpperCAmelCase = WebClient(token=os.environ["CI_SLACK_BOT_TOKEN"])
def A__ ( __lowerCamelCase ):
SCREAMING_SNAK... | 299 | 0 |
import json
import os
import unittest
from transformers.models.biogpt.tokenization_biogpt import VOCAB_FILES_NAMES, BioGptTokenizer
from transformers.testing_utils import slow
from ...test_tokenization_common import TokenizerTesterMixin
class UpperCamelCase ( lowercase__ , uni... | 252 |
from .dependency_versions_table import deps
from .utils.versions import require_version, require_version_core
# define which module versions we always want to check at run time
# (usually the ones defined in `install_requires` in setup.py)
#
# order specific notes:
# - tqdm must be checked before tokeni... | 252 | 1 |
'''simple docstring'''
import unittest
import numpy as np
from transformers import RobertaPreLayerNormConfig, 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_a... | 200 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCAmelCase_ : Dict = logging.get_logger(__name__)
UpperCAmelCase_ : Optional[int] = {
'google/canine-s': 'https://huggingface.co/google/canine-s/resolve/main/config.json',
... | 200 | 1 |
'''simple docstring'''
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMSc... | 359 |
'''simple docstring'''
import re
from filelock import FileLock
try:
import nltk
lowerCAmelCase_ : Optional[int] = True
except (ImportError, ModuleNotFoundError):
lowerCAmelCase_ : Tuple = False
if NLTK_AVAILABLE:
with FileLock('.lock') as lock:
... | 346 | 0 |
"""simple docstring"""
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_li... | 221 | """simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
__lowerCamelCase = {
"configuration_chinese_clip": [
"CHINESE_CLIP_PRETRAINED_CONFIG_ARCHIVE_MAP",
"Chinese... | 221 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_torch_available,
is_vision_available,
)
lowerCAmelCase : int = {
'configuration_blip': [
'BLIP_PRETRAINED_CONFIG_AR... | 251 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCAmelCase : Tuple = {
'configuration_instructblip': [
'INSTRUCTBLIP_PRETRAINED_CONFIG_ARCHIVE_MAP',
'InstructBlipConfig',
... | 251 | 1 |
"""simple docstring"""
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
UpperCamelCase_ = {
'configuration_mgp_str': ['MGP_STR_PRETRAINED_CONFIG_ARCHIVE_MAP', 'MgpstrConfig'],
'processing_mgp_str': ['MgpstrProcessor'],
... | 243 |
"""simple docstring"""
import logging
import re
import pytorch_quantization
import pytorch_quantization.nn as quant_nn
import torch
from pytorch_quantization import calib
from pytorch_quantization.tensor_quant import QuantDescriptor
a = logging.getLogger(__name__)
a = 50 # max width of layer name... | 315 | 0 |
# Copyright 2021 The HuggingFace Team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by appl... | 366 |
from math import factorial
class __lowerCAmelCase :
def __init__( self: Optional[int] , _lowerCAmelCase: List[str] , _lowerCAmelCase: Tuple ):
lowercase :str = real
if isinstance(_lowerCAmelCase , _lowerCAmelCase ):
lowercase ... | 158 | 0 |
'''simple docstring'''
import logging
import torch
from torch import nn
from torch.nn import CrossEntropyLoss, MSELoss
from transformers.file_utils import add_start_docstrings, add_start_docstrings_to_model_forward
from transformers.models.bert.modeling_bert import (
BERT_INPUTS_DOCSTRING,
B... | 254 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def lowercase_ ( lowerCAmelCase__ : Union[str, Any] ):
"""simple docstring"""
__UpperCAmelCase : Optional[int] = FileLock(str(tmpdi... | 254 | 1 |
"""simple docstring"""
A_ : dict[str, float] = {
"km/h": 1.0,
"m/s": 3.6,
"mph": 1.609344,
"knot": 1.852,
}
A_ : dict[str, float] = {
"km/h": 1.0,
"m/s": 0.277777778,
"mph": 0.621371192,
"knot": 0.539956803,
}
def lowerCamelCase_ ( _lowe... | 362 |
"""simple docstring"""
from __future__ import annotations
def lowerCamelCase_ ( _lowerCamelCase , _lowerCamelCase ):
lowerCamelCase__ : list[list[int]] = []
lowerCamelCase__ : list[int] = []
lowerCamelCase__ : List[str] = ... | 316 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
SCREAMING_SNAKE_CASE_:Any = logging.get_logger(__name__)
SCREAMING_SNAKE_CASE_:Dict = {
"""facebook... | 116 |
from dataclasses import dataclass
from typing import Dict, Optional, Union
import torch
import torch.nn.functional as F
from torch import nn
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import BaseOutput
from .attention import BasicTransformerBlock
from .attention_processor impor... | 116 | 1 |
def lowerCamelCase ( a_ ):
lowerCAmelCase_ = [0] * len(a_ )
lowerCAmelCase_ = []
lowerCAmelCase_ = [1] * len(a_ )
for values in graph.values():
for i in values:
indegree[i] +... | 360 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
lowerCamelCase_ ... | 14 | 0 |
"""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
if is_torch_available():
import torc... | 289 | """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_availa... | 289 | 1 |
'''simple docstring'''
import warnings
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
__a = logging.get_logger(__name__)
__a = {
... | 43 |
'''simple docstring'''
from collections import deque
from math import floor
from random import random
from time import time
class UpperCAmelCase_ :
"""simple docstring"""
def __init__( self : Dict ):
snake_case__ : List[str] = {}
def lowerCame... | 43 | 1 |
from typing import List, Optional, Tuple, Union
import PIL
import torch
from torchvision import transforms
from diffusers.pipeline_utils import DiffusionPipeline, ImagePipelineOutput
from diffusers.schedulers import DDIMScheduler
from diffusers.utils import randn_tensor
UpperCAmelCase : Optional[Any] = ... | 252 |
from __future__ import annotations
def __lowerCamelCase ( lowerCamelCase__ : int , lowerCamelCase__ : int ):
'''simple docstring'''
if b == 0:
return (1, 0)
((lowerCamelCase) , (lowerCamelCase)) = extended_euclid(lowerCamelCase__ , a % b... | 252 | 1 |
import argparse
import json
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import (
SegformerConfig,
SegformerForImageClassification,
SegformerForSemanticSegmentation,
S... | 367 |
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowerCAmelCase : Union[str, Any] = {'''configuration_focalnet''': ['''FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''FocalNetConfig''']}
try:
... | 70 | 0 |
# Logistic Regression from scratch
# In[62]:
# In[63]:
# importing all the required libraries
import numpy as np
from matplotlib import pyplot as plt
from sklearn import datasets
def UpperCAmelCase ( lowercase ):
"""simple docstring"""
return 1 / (1 + np.exp(-z ))
... | 210 | import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto import CONFIG_MAPPING
__a : int = logging.get_logger(__name__)
__a : str = {
"""ut/deta""": """https://huggingface.co/ut/deta/resolve/main/config.json""",
}
class _UpperCamelCa... | 210 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as... | 358 |
'''simple docstring'''
lowerCAmelCase : List[str] = """
# Transformers installation
! pip install transformers datasets
# To install from source instead of the last release, comment the command above and uncomment the following one.
# ! pip install git+https://github.com/huggingface... | 25 | 0 |
'''simple docstring'''
import itertools
import os
from collections import Counter, defaultdict
from concurrent.futures import ThreadPoolExecutor, as_completed
import numpy as np
import datasets
from .execute import check_correctness
UpperCamelCase_ = "\\n@misc{chen2021evalu... | 251 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
"microsoft/git-base": "https://huggingface... | 251 | 1 |
from sklearn.metrics import fa_score, matthews_corrcoef
import datasets
from .record_evaluation import evaluate as evaluate_record
_lowerCamelCase : Optional[int] = "\\n@article{wang2019superglue,\n title={SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems},\n author={W... | 159 |
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
_lowerCamelCase : str = "\nHugging Face was founded in 2016 by French entrepreneurs Clément Delangue, Julien Chaumond, and Thomas Wolf originally as a company that developed a chatbot app targeted at teenag... | 159 | 1 |
'''simple docstring'''
from typing import Optional, Tuple, Union
import tensorflow as tf
from ...activations_tf import ACTaFN
from ...file_utils import add_code_sample_docstrings, add_start_docstrings, add_start_docstrings_to_model_forward
from ...modeling_tf_outputs import (
TFBaseModelOutputWith... | 174 |
'''simple docstring'''
from typing import List
import datasets
from datasets.tasks import AudioClassification
from ..folder_based_builder import folder_based_builder
_SCREAMING_SNAKE_CASE = datasets.utils.logging.get_logger(__name__)
class lowerCAmelCase_ ( folder_based_builde... | 158 | 0 |
'''simple docstring'''
import os
import time
import pytest
from datasets.utils.filelock import FileLock, Timeout
def A_( A : List[str]):
UpperCamelCase = FileLock(str(tmpdir / 'foo.lock'))
UpperCamelCase = FileLock(str(tmpdir / 'foo.lock'))
U... | 370 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version('>=', '4.25.0')):
raise O... | 251 | 0 |
"""simple docstring"""
import logging
import os
from dataclasses import dataclass
from enum import Enum
from typing import List, Optional, Union
from filelock import FileLock
from transformers import PreTrainedTokenizer, is_tf_available, is_torch_available
_snake_case : Dict = logging.getLogg... | 292 |
"""simple docstring"""
import argparse
from pathlib import Path
import torch
from packaging import version
from torch.onnx import export
from diffusers import AutoencoderKL
UpperCamelCase : Union[str, Any] = version.parse(version.parse(torch.__version__).base_version) < version.parse("1.11")
def ... | 316 | 0 |
def UpperCAmelCase ( a_ ) -> float:
"""simple docstring"""
if not nums: # Makes sure that the list is not empty
raise ValueError("List is empty" )
__A = sum(a_ ) / len(a_ ) # Calculate the average
return sum(abs(x - average ... | 124 |
from math import log
from scipy.constants import Boltzmann, physical_constants
SCREAMING_SNAKE_CASE :Dict = 300 # TEMPERATURE (unit = K)
def UpperCAmelCase ( a_ , a_ , a_ , ) -> float:
"""simple docstring"""
if donor_conc <= 0:
r... | 124 | 1 |
"""simple docstring"""
def _snake_case ( lowerCamelCase__ : Union[str, Any] ) -> int:
assert column_title.isupper()
lowerCamelCase_ : int =0
lowerCamelCase_ : str =len(lowercase_ ) - 1
lowerCamelCase_ : Union[str, ... | 144 |
from ...processing_utils import ProcessorMixin
class UpperCamelCase_ ( UpperCAmelCase__ ):
'''simple docstring'''
UpperCAmelCase__ = '''SpeechT5FeatureExtractor'''
UpperCAmelCase__ = '''SpeechT5Tokenizer'''
def __init__( self : Any , UpperC... | 14 | 0 |
"""simple docstring"""
from typing import Union
from ..utils import add_end_docstrings, is_torch_available, is_vision_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ..image_utils import load_image
if is_torch_available():
from... | 361 |
"""simple docstring"""
import json
from typing import Iterator, List, Union
from tokenizers import AddedToken, Regex, Tokenizer, decoders, normalizers, pre_tokenizers, trainers
from tokenizers.implementations.base_tokenizer import BaseTokenizer
from tokenizers.models import Unigram
from tokenizers.processor... | 254 | 0 |
import argparse
import json
from tqdm import tqdm
def lowerCamelCase ( ):
'''simple docstring'''
__UpperCamelCase :Tuple = argparse.ArgumentParser()
# Required parameters
parser.add_argument(
'''--src_path''' , type=SCREAMING_SNAKE_CASE , default='''biencoder-nq-dev... | 43 | import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
__lowercase = logging.get_logger(__name__)
__lowercase = {
'''facebook/wav2vec2-base-960h''': '''https://huggingface.co/facebook/wav2vec2-base-960h/resolve/main/config.json''',... | 43 | 1 |
'''simple docstring'''
import coval # From: git+https://github.com/ns-moosavi/coval.git # noqa: F401
from coval.conll import reader, util
from coval.eval import evaluator
import datasets
_UpperCamelCase = datasets.logging.get_logger(__name__)
_UpperCamelCase = '''\\n@I... | 366 |
'''simple docstring'''
import unittest
from parameterized import parameterized
from transformers import LlamaConfig, is_torch_available, set_seed
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configura... | 16 | 0 |
'''simple docstring'''
lowerCamelCase_ = '''2.13.1'''
import platform
import pyarrow
from packaging import version
if version.parse(platform.python_version()) < version.parse('''3.7'''):
raise ImportWarning(
'''To use `datasets`, Python>=3.7 is required, and the current version... | 79 |
'''simple docstring'''
from dataclasses import dataclass, field
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union
import pyarrow as pa
if TYPE_CHECKING:
from .features import FeatureType
@dataclass
class UpperCAmelCase :
_lowercas... | 70 | 0 |
from __future__ import annotations
def lowerCAmelCase_ ( __A ) -> float:
'''simple docstring'''
if not nums:
raise ValueError("List is empty" )
return sum(__A ) / len(__A )
if __name__ == "__main__":
im... | 365 | # Lint as: python3
import itertools
import os
import re
UpperCamelCase__ = re.compile(R'([A-Z]+)([A-Z][a-z])')
UpperCamelCase__ = re.compile(R'([a-z\d])([A-Z])')
UpperCamelCase__ = re.compile(R'(?<!_)_(?!_)')
UpperCamelCase__ = re.compile(R'(_{2,})')
UpperCamelCas... | 143 | 0 |
"""simple docstring"""
from collections import OrderedDict
from typing import Mapping
from packaging import version
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
lowercase__ = logging.get_logger(__name_... | 96 |
"""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 lowerCAmelCase_ (unittest.TestCase ):
"""simple docstring"""
... | 25 | 0 |
'''simple docstring'''
import os
import tempfile
import unittest
from pathlib import Path
from transformers import AutoConfig, is_tf_available
from transformers.testing_utils import require_tf
if is_tf_available():
import tensorflow as tf
from transformers import TensorFlowBenchmark, TensorFl... | 8 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_mobilevit import MobileViTImageProcessor
__A : Optional[int] = logging.get_logger(__name__)
class __UpperCamelCase ( lowercase__ ):
def __init__( self :List[str] ,*_Upp... | 8 | 1 |
import argparse
import logging
import sys
from unittest.mock import patch
import run_glue_deebert
from transformers.testing_utils import TestCasePlus, get_gpu_count, require_torch_non_multi_gpu, slow
logging.basicConfig(level=logging.DEBUG)
SCREAMING_SNAKE_CASE :Tuple = logging.getLo... | 159 |
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 (
center_crop,
convert_to_rgb,
get_resize_output_image_size,
normalize,
rescale,
resize,
... | 159 | 1 |
'''simple docstring'''
def __UpperCAmelCase ( a_: List[str] = 1_000 ) -> Optional[Any]:
_UpperCAmelCase , _UpperCAmelCase : Union[str, Any] = 1, 1
_UpperCAmelCase : str = []
for i in range(1, n + 1 ):
_UpperCAmelCase ... | 352 | '''simple docstring'''
from datetime import datetime
import matplotlib.pyplot as plt
import torch
def __UpperCAmelCase ( a_: str ):
for param in module.parameters():
_UpperCAmelCase : Any = False
def __UpperCAmelCase ( ):
_UpperCAmelCa... | 17 | 0 |
"""simple docstring"""
def a__ ( SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int , SCREAMING_SNAKE_CASE : int ):
'''simple docstring'''
lowerCAmelCase : List[Any] = (num_of_terms / 2) * (2 * first_term + (num_of_terms - 1... | 108 | 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,
PILImageResampling,
get_... | 219 | 0 |
from __future__ import annotations
def UpperCAmelCase ( UpperCamelCase__ ):
"""simple docstring"""
A__ = str(lowerCAmelCase__ )
return n == n[::-1]
def UpperCAmelCase ( UpperCamelCase__ = 1_000_000 ):
... | 366 | """simple docstring"""
import os
def UpperCAmelCase ( ):
"""simple docstring"""
with open(os.path.dirname(UpperCamelCase__ ) + '/grid.txt' ) as f:
A__ = [] # noqa: E741
for _ in range(20 ):
... | 154 | 0 |
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