code stringlengths 82 54.1k | code_codestyle int64 0 699 | style_context stringlengths 111 35.6k | style_context_codestyle int64 0 699 | label int64 0 1 |
|---|---|---|---|---|
from math import atan, cos, radians, sin, tan
from .haversine_distance import haversine_distance
UpperCamelCase_ = 6_3_7_8_1_3_7.0
UpperCamelCase_ = 6_3_5_6_7_5_2.3_1_4_2_4_5
UpperCamelCase_ = 6_37_81_37
def _UpperCAmelCase ( A , A ,... | 625 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 1 |
import argparse
import os
import re
UpperCamelCase_ = 'src/transformers/models/auto'
# re pattern that matches mapping introductions:
# SUPER_MODEL_MAPPING_NAMES = OrderedDict or SUPER_MODEL_MAPPING = OrderedDict
UpperCamelCase_ = re.compile(R'[A-Z_]+_MAPPING(\s+|_[A-Z... | 625 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 1 |
from typing import List, Optional, Tuple, Union
import torch
from torch import nn
from torch.nn import CrossEntropyLoss
from ... import AutoBackbone
from ...modeling_outputs import SemanticSegmenterOutput
from ...modeling_utils import PreTrainedModel
from ...utils import add_start_docstrings, add... | 625 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 1 |
import os
import unittest
from transformers.models.transfo_xl.tokenization_transfo_xl import VOCAB_FILES_NAMES, TransfoXLTokenizer
from ...test_tokenization_common import TokenizerTesterMixin
class snake_case_ ( a, unittest.TestCase ):
'''simple docstring'''
... | 625 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 1 |
# Imports
import numpy as np
class snake_case_ :
'''simple docstring'''
def __init__( self, A_=None, A_=None, A_=None, A_=None, A_=None ) -> Tuple:
self.set_matricies(red=A_, green=A_, blue=A_, red_edge=A_, nir=A_ )
def __UpperCAmelCase ( ... | 625 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 1 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 1 |
from dataclasses import dataclass
from typing import Tuple
import numpy as np
import torch
@dataclass
class snake_case_ :
'''simple docstring'''
__UpperCamelCase = 42 # [batch_size x 3]
__UpperCamelCase = 42 # [batch_size x 3]
__UpperCamelC... | 625 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 1 |
class snake_case_ :
'''simple docstring'''
def __init__( self, A_ ) -> int:
UpperCAmelCase__ =n
UpperCAmelCase__ =[None] * self.n
UpperCAmelCase__ =0 # index of the first element
UpperCAmelCase__ =0
UpperCAmelCase__ =... | 625 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 1 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 1 |
from typing import List, Optional, Union
import numpy as np
import PIL
import torch
from PIL import Image
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMSched... | 625 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 1 |
from ...processing_utils import ProcessorMixin
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'WhisperFeatureExtractor'
__UpperCamelCase = 'WhisperTokenizer'
def __init__( self, A_, A_ ) -> List[str]:
su... | 625 |
import inspect
import unittest
from transformers import YolosConfig
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
... | 625 | 1 |
import unittest
import numpy as np
import timeout_decorator # noqa
from transformers import BlenderbotSmallConfig, is_flax_available
from transformers.testing_utils import require_flax, slow
from ...generation.test_flax_utils import FlaxGenerationTesterMixin
from ...test_modeling_flax_common im... | 625 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 1 |
import copy
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ..auto.configuration_auto import CONFIG_MAPPING
UpperCamelCase_ = logging.get_logger(__name__)
class snake_case_ ( a ):
'''simple docstring'''
__Up... | 625 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 1 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
if not numbers:
return 0
if not isinstance(A , (list, tuple) ) or not all(
isinstance(A , A ) for number in numbers ):
raise ValueError("numbers must be an iterable of i... | 625 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 1 |
def _UpperCAmelCase ( A = 4000000 ):
'''simple docstring'''
UpperCAmelCase__ =[]
UpperCAmelCase__ , UpperCAmelCase__ =0, 1
while b <= n:
if b % 2 == 0:
even_fibs.append(A )
UpperCAmelCase__ , UpperCAmelCase__ =... | 625 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 1 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 1 |
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unl... | 625 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 1 |
import os
def _UpperCAmelCase ( ):
'''simple docstring'''
with open(os.path.dirname(A ) + "/p022_names.txt" ) as file:
UpperCAmelCase__ =str(file.readlines()[0] )
UpperCAmelCase__ =names.replace("\"" , "" ).split("," ... | 625 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 1 |
def _UpperCAmelCase ( A = 1000 ):
'''simple docstring'''
UpperCAmelCase__ =3
UpperCAmelCase__ =0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 == 0:
result -= a
a += 1
return result
if __na... | 625 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 1 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class snake_case_ ( a, unittes... | 625 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 1 |
from __future__ import annotations
def __lowercase ( snake_case, snake_case = None, snake_case = None ):
"""simple docstring"""
if start is None:
__magic_name__ :int = 0
if end is None:
__magic_name__ :Optional[Any] = len(snake_case ) - 1
if... | 0 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
import gc
import unittest
import numpy as np
import torch
from diffusers import AutoencoderKL, DDIMScheduler, DiTPipeline, DPMSolverMultistepScheduler, TransformeraDModel
from diffusers.utils import is_xformers_available, load_numpy, slow, torch_device
from diffusers.utils.testing_utils import enable_fu... | 1 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
from collections.abc import Callable
from math import pi, sqrt
from random import uniform
from statistics import mean
def SCREAMING_SNAKE_CASE_ ( _snake_case :int ) -> Dict:
# A local function to see if a dot lands in the circle.
def is_in_circle(_snake_case :float , _snake_case... | 2 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''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 SCREAMING_SNAKE_CASE__ ( snake_case_):
d... | 3 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
"""simple docstring"""
from __future__ import annotations
from sys import maxsize
from typing import Generic, TypeVar
__UpperCamelCase : int = TypeVar('''T''')
def _SCREAMING_SNAKE_CASE (_UpperCAmelCase : int ):
return (position - 1) // 2
def _SCREAMING_SNAKE_CASE (_Upp... | 4 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
'''simple docstring'''
import datasets
from .nmt_bleu import compute_bleu # From: https://github.com/tensorflow/nmt/blob/master/nmt/scripts/bleu.py
_lowercase = """\
@INPROCEEDINGS{Papineni02bleu:a,
author = {Kishore Papineni and Salim Roukos and Todd Ward and Wei-jing Zhu},
title = {BLEU:... | 5 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
import inspect
import unittest
from transformers import DecisionTransformerConfig, is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester
from ...test_modeling_co... | 6 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
"""simple docstring"""
from __future__ import annotations
a = list[list[int]]
# assigning initial values to the grid
a = [
[3, 0, 6, 5, 0, 8, 4, 0, 0],
[5, 2, 0, 0, 0, 0, 0, 0, 0],
[0, 8, 7, 0, 0, 0, 0, 3, 1],
[0, 0, 3, 0, 1, 0, 0, 8, 0],
[9, 0, 0, 8, 6, 3, 0,... | 7 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 0 |
'''simple docstring'''
# Copyright 2022 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/lic... | 8 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
SCREAMING_SNAKE_CASE__ = {
'''n_samples''': 6_4,
'''horizon''': 3_2,
'''num_inference_steps''': 2_0,
'''n_guide_steps''': 2, # can set to 0 for faster sampling, does not use value network
... | 9 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
from collections.abc import Generator
from math import sin
def _snake_case ( __snake_case ):
if len(__snake_case ) != 32:
raise ValueError('''Input must be of length 32''' )
_UpperCamelCase = B''''''
for i in [3, 2, 1, 0]:
little_endian += string_aa[8 ... | 10 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
'''simple docstring'''
import os
import numpy
import onnx
def lowerCAmelCase (__A , __A):
"""simple docstring"""
_a = a.name
_a = b.name
_a = ''''''
_a = ''''''
_a = a == b
_a ... | 11 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
import collections
from typing import List, Optional, Union
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, add_end_docstrings, add_start_docstrings, logging
from ..bert.tokenization_bert_fast import BertTokenizerFast
from .tokenization_dpr import DPRContextEncoderTokenize... | 12 |
import inspect
import unittest
from transformers import YolosConfig
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
... | 625 | 0 |
'''simple docstring'''
from typing import Optional
import numpy as np
import torch
from torch import nn
from transformers import GPTaConfig, GPTaLMHeadModel
from transformers.modeling_utils import ModuleUtilsMixin
from ...configuration_utils import ConfigMixin, register_to_config
from ...models import ModelMixi... | 13 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
def __UpperCAmelCase ( __a : str ) -> str:
"""simple docstring"""
if not all(char in '''01''' for char in bin_string ):
raise ValueError('''Non-binary value was passed to the function''' )
if not bin_string:
raise ValueError('''Empty stri... | 14 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import DetrConfig, DetrForObjectDetection, DetrForSegmentation, DetrImageProcessor, ResNetConfig
from transformers.utils import logging
... | 15 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
import inspect
from typing import Callable, List, Optional, Union
import torch
from transformers import (
CLIPImageProcessor,
CLIPTextModel,
CLIPTokenizer,
WhisperForConditionalGeneration,
WhisperProcessor,
)
from diffusers import (
AutoencoderKL,
DDIMScheduler,
Diff... | 16 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
from __future__ import annotations
import inspect
import unittest
from typing import List, Tuple
from transformers import RegNetConfig
from transformers.testing_utils import require_tf, require_vision, slow
from transformers.utils import cached_property, is_tf_available, is_vision_available
from ...test_configurat... | 17 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import EsmConfig, is_tf_available
from transformers.testing_utils import require_tf, slow
from ...test_configuration_common import ConfigTester
from ...test_modeling_tf_common import TFModelTesterMixin, floats_tensor,... | 18 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
"""simple docstring"""
from timeit import timeit
_a = {
"""MALAYALAM""": True,
"""String""": False,
"""rotor""": True,
"""level""": True,
"""A""": True,
"""BB""": True,
"""ABC""": False,
"""amanaplanacanalpanama""": True, # "a man a plan a canal panam... | 19 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
import os
import unittest
from transformers.models.bartpho.tokenization_bartpho import VOCAB_FILES_NAMES, BartphoTokenizer
from transformers.testing_utils import get_tests_dir
from ...test_tokenization_common import TokenizerTesterMixin
_lowerCAmelCase: List[str] = get_tests_dir('fixtures/test_s... | 20 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
from abc import ABC, abstractmethod
from argparse import ArgumentParser
class __A ( UpperCamelCase__ ):
@staticmethod
@abstractmethod
def A__ ( __snake_case :ArgumentParser ):
'''simple docstring'''
raise NotImplementedError()
... | 21 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
'''simple docstring'''
import argparse
from collections import defaultdict
import yaml
_snake_case : int = 'docs/source/en/_toctree.yml'
def snake_case_ (UpperCamelCase : List[Any] ):
'''simple docstring'''
_a = defaultdict(Up... | 22 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
import os
from typing import Dict, List, Tuple, TypeVar, Union
snake_case__ : int = TypeVar("""T""")
snake_case__ : str = Union[List[T], Tuple[T, ...]]
snake_case__ : Any = Union[T, List[T], Dict[str, T]]
snake_case__ : Tuple... | 23 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
'''simple docstring'''
import glob
import os
import random
from string import ascii_lowercase, digits
import cva
import numpy as np
# Parrameters
UpperCAmelCase_ : Any = (7_2_0, 1_2_8_0) # Height, Width
UpperCAmelCase_ : List[Any] = (0.4, 0.6) # if height or width lower than this sca... | 24 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
from PIL import Image
def lowerCamelCase__ ( _a):
SCREAMING_SNAKE_CASE ,SCREAMING_SNAKE_CASE : Tuple = image.size
SCREAMING_SNAKE_CASE : Tuple = 0
SCREAMING_SNAKE_CASE : Tuple = image.load()
for i in range(_a):
for j in range(_a):
SCREAMING_SNAKE_CASE : ... | 25 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
import argparse
import torch
from transformers import BlenderbotConfig, BlenderbotForConditionalGeneration
from transformers.utils import logging
logging.set_verbosity_info()
__UpperCamelCase = logging.get_logger(__name__)
__UpperCamelCase ... | 26 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
# DISCLAIMER: This file is strongly influenced by https://github.com/yang-song/score_sde_pytorch
import math
from typing import Union
import torch
from ..configuration_utils import ConfigMixin, register_to_config
from ..utils import randn_tensor
from .scheduling_utils import SchedulerMixin
... | 27 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
'''simple docstring'''
from math import ceil, sqrt
def lowercase__( __UpperCamelCase: int = 1_00_00_00 ):
"""simple docstring"""
SCREAMING_SNAKE_CASE : Union[str, Any] = 0
for outer_width in range(3 ,(limit // 4) + 2 )... | 28 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
"""simple docstring"""
import multiprocessing
import os
from typing import BinaryIO, Optional, Union
import fsspec
from .. import Dataset, Features, NamedSplit, config
from ..formatting import query_table
from ..packaged_modules.json.json import Json
from ..utils import logging
from ..utils.typing import NestedDat... | 29 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 0 |
import gc
import random
import unittest
import numpy as np
import torch
from PIL import Image
from transformers import XLMRobertaTokenizerFast
from diffusers import DDIMScheduler, KandinskyInpaintPipeline, KandinskyPriorPipeline, UNetaDConditionModel, VQModel
from diffusers.pipelines.kandinsky.text_encoder impor... | 30 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
lowerCamelCase__ : Optional[int] = {'configuration_mmbt': ['MMBTConfig']}
try:
if not is_torch_available():
raise OptionalDependencyNotAvailable()
except OptionalD... | 31 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
import re
import string
import numpy as np
import datasets
UpperCAmelCase_ = "\nReturns the rate at which the input predicted strings exactly match their references, ignoring any strings input as part of the regexes_to_ignore list.\n"
UpperCAmelCase_ = "\nArgs:\n predictions: List of p... | 32 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import re
import tempfile
from pathlib import Path
import pytest
import yaml
from datasets.utils.readme import ReadMe
# @pytest.fixture
# def example_yaml_structure():
lowerCamelCase__ : Tuple = yaml.safe_load(
"""\
name: \"\"
allow_empty: false
allow_empty_text: tru... | 33 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
"""simple docstring"""
import argparse
from typing import Dict
import tensorflow as tf
import torch
from tqdm import tqdm
from transformers import BigBirdPegasusConfig, BigBirdPegasusForConditionalGeneration
SCREAMING_SNAKE_CASE_ = [
# tf -> hf
('/', '.'),
('layer_', 'layers.'),
... | 34 |
import inspect
import unittest
from transformers import YolosConfig
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
... | 625 | 0 |
from heapq import heappop, heappush
import numpy as np
def a ( A__ , A__ , A__ , A__ , ) -> tuple[float | int, list[tuple[int, int]]]:
'''simple docstring'''
SCREAMING_SNAKE_CASE__ , SCREAMING_SNAKE_CASE__ : Union[str, Any] =... | 35 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
from dataclasses import dataclass, field
from typing import Optional
@dataclass
class _A :
'''simple docstring'''
__lowerCamelCase : Optional[str] = field(
default='''codeparrot/codeparrot''' , metadata={'''help''': '''Model name or path of model to be trained.'''} ... | 36 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
import numpy as np
import torch
from torch.utils.data import Dataset
from utils import logger
class A__ ( A__ ):
"""simple docstring"""
def __init__( self : Dict , lowerCamelCase__ : Any , lowerCamelCase__ : Any ):
a__ : str = params
a__ : Any ... | 37 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
import os
import sys
import unittest
A_ : Dict = os.path.abspath(os.path.dirname(os.path.dirname(os.path.dirname(__file__))))
sys.path.append(os.path.join(git_repo_path, "utils"))
import get_test_info # noqa: E402
from get_test_info import ( # noqa: E402
get_model_to... | 38 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
lowerCAmelCase_ = logging.get_logger(__name__)
lowerCAmelCase_ = {
'''microsoft/biogpt''': '''https://huggingface.co/microsoft/biogpt/resolve/main/config.json''',
# See all BioGPT models at ... | 39 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
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 OptionalDependencyNotAvailable:
from ...utils... | 40 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
'''simple docstring'''
def _A ( A__ ):
"""simple docstring"""
if not isinstance(A__ , A__ ):
raise ValueError('''check_bouncy() accepts only integer arguments''' )
__lowercase = str(A__ )
__lowercase = ''''''.join(sorted(A__ ) )
return sorted_str_n != str_... | 41 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 0 |
'''simple docstring'''
A_ = {
"A": ".-", "B": "-...", "C": "-.-.", "D": "-..", "E": ".", "F": "..-.", "G": "--.",
"H": "....", "I": "..", "J": ".---", "K": "-.-", "L": ".-..", "M": "--", "N": "-.",
"O": "---", "P": ".--.", "Q": "--.-", "R": ".-.", "S": "...", "T": "-", "U": "..-",
"V": "...-", "W... | 42 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
lowerCAmelCase = logging.get_logger(__name__)
class _a ( UpperCamelCase__ ):
def __init__( self: Union[str, Any] , *UpperCamelCase_: Tuple , **Up... | 43 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
'''simple docstring'''
import math
def A_ ( _lowerCAmelCase : float , _lowerCAmelCase : float ):
"""simple docstring"""
if initial_intensity < 0:
raise ValueError("The value of intensity cannot be negative" )
# handling of nega... | 44 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
from math import factorial
def A ( lowercase__ : int , lowercase__ : int ) -> int:
# If either of the conditions are true, the function is being asked
# to calculate a factorial of a negative number, which is not possible
if n < k or k < 0:
raise ValueError("""Please enter positive inte... | 45 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
"""simple docstring"""
import argparse
import intel_extension_for_pytorch as ipex
import torch
from diffusers import DPMSolverMultistepScheduler, StableDiffusionPipeline
_lowerCAmelCase : Any = argparse.ArgumentParser('''Stable Diffusion script with intel optimization''', add_help=False)
pa... | 46 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
SCREAMING_SNAKE_CASE__ = '''Tobias Carryer'''
from time import time
class _UpperCamelCase:
def __init__( self : Optional[Any] , SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CASE__ : Optional[int] , SCREAMING_SNAKE_CAS... | 47 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
'''simple docstring'''
import collections
import json
import os
import re
from typing import TYPE_CHECKING, List, Optional, Tuple
import numpy as np
from ...tokenization_utils_fast import PreTrainedTokenizer
from ...utils import logging
if TYPE_CHECKING:
from transformers.pipelines.conversational import Convers... | 48 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
"""simple docstring"""
import gc
import random
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DiffusionPipeline,
EulerDiscreteScheduler,
S... | 49 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
'''simple docstring'''
import time
import unittest
from transformers import is_torch_available
from transformers.testing_utils import require_torch, torch_device
from ..test_modeling_common import ids_tensor
if is_torch_available():
import torch
from transformers.generation import (
... | 50 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
'''simple docstring'''
def __snake_case ( SCREAMING_SNAKE_CASE_ : int = 1_000_000 ) -> int:
"""simple docstring"""
UpperCAmelCase = set(range(3 , SCREAMING_SNAKE_CASE_ , 2 ) )
primes.add(2 )
for p in range(3 , SCREAMING_SNAKE_CASE_ , 2 ):
... | 51 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 0 |
"""simple docstring"""
import argparse
import json
import logging
import os
import sys
from unittest.mock import patch
from transformers.testing_utils import TestCasePlus, get_gpu_count, slow
A = [
os.path.join(os.path.dirname(__file__), dirname)
for dirname in [
... | 52 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 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, prepare_image_inputs
if is_torch_available():
import ... | 53 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 0 |
import random
import unittest
import numpy as np
from diffusers import (
DPMSolverMultistepScheduler,
EulerAncestralDiscreteScheduler,
EulerDiscreteScheduler,
LMSDiscreteScheduler,
OnnxStableDiffusionImgaImgPipeline,
PNDMScheduler,
)
from diffusers.utils import floats_... | 54 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
import string
def UpperCAmelCase ( a_ ) -> None:
"""simple docstring"""
for key in range(len(string.ascii_uppercase ) ):
__A = ""
for symbol in message:
if symbol in string.ascii_uppercase:
__A = string.ascii_up... | 55 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available, is_vision_available
from ...utils import OptionalDependencyNotAvailable
_a : int = {"configuration_dpt": ["DPT_PRETRAINED_CONFIG_ARCHIVE_MAP", "DPTConfig... | 56 |
import inspect
import unittest
from transformers import YolosConfig
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
... | 625 | 0 |
from __future__ import annotations
import math
def snake_case (UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ , UpperCAmelCase__ ) -> int:
if depth < 0:
raise ValueError('Depth cannot be less than 0' ... | 57 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
"""simple docstring"""
import csv
from collections import defaultdict
from dataclasses import dataclass, field
from typing import List, Optional
import matplotlib.pyplot as plt
import numpy as np
from matplotlib.ticker import ScalarFormatter
from transformers import HfArgumentParser
def ... | 58 |
import argparse
import json
import pickle
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import MaskFormerConfig, MaskFormerForInstanceSegmentation, MaskFormerImageProcessor, SwinConfig
from transformers.... | 625 | 0 |
import os
import unittest
from transformers.models.cpmant.tokenization_cpmant import VOCAB_FILES_NAMES, CpmAntTokenizer
from transformers.testing_utils import require_jieba, tooslow
from ...test_tokenization_common import TokenizerTesterMixin
@require_jieba
class _SCREAMING_SNAKE_CASE ( __SCREAMING_S... | 59 |
import argparse
import shutil
from pathlib import Path
from tqdm import tqdm
from transformers import AutoTokenizer
def _UpperCAmelCase ( A , A , A , A=1024 ):
'''simple docstring'''
UpperCAmelCase__ , UpperCAmelCase__ ... | 625 | 0 |
def lowerCamelCase_ ( _UpperCamelCase ) -> str:
"""simple docstring"""
return " ".join(
''''''.join(word[::-1] ) if len(_UpperCamelCase ) > 4 else word for word in sentence.split() )
if __name__ == "__main__":
import doctest
doctest.testmod()
print(rever... | 60 |
import argparse
import os
import gluonnlp as nlp
import mxnet as mx
import numpy as np
import torch
from gluonnlp.base import get_home_dir
from gluonnlp.model.bert import BERTEncoder
from gluonnlp.model.utils import _load_vocab
from gluonnlp.vocab import Vocab
from packaging import version
from... | 625 | 0 |
from __future__ import annotations
from collections import deque
class __lowerCamelCase :
"""simple docstring"""
def __init__( self : Any , SCREAMING_SNAKE_CASE__ : list[str] ) -> Optional[int]:
lowerCAmelCase__ = []
self.a... | 61 |
from math import factorial
def _UpperCAmelCase ( A = 20 ):
'''simple docstring'''
UpperCAmelCase__ =2 * n # middle entry of odd rows starting at row 3 is the solution for n = 1,
# 2, 3,...
UpperCAmelCase__ =n // 2
return int(factorial(A ... | 625 | 0 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
snake_case = {
"""configuration_convbert""": ["""CONVBERT_PRETRAINED_CONFIG_ARCHIVE_MAP""", """ConvBertConfig""... | 62 |
import re
import time
from typing import Optional
import IPython.display as disp
from ..trainer_callback import TrainerCallback
from ..trainer_utils import IntervalStrategy, has_length
def _UpperCAmelCase ( A ):
'''simple docstring'''
UpperCAmelCase__ ... | 625 | 0 |
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
a : int = argparse.ArgumentParser()
parser.add_argument(
"--checkpoint_path", default=None, type=str, r... | 63 |
from __future__ import annotations
import requests
UpperCamelCase_ = set(
'approved_at_utc approved_by author_flair_background_color\nauthor_flair_css_class author_flair_richtext author_flair_template_id author_fullname\nauthor_premium can_mod_post category clicked content_categories c... | 625 | 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, prepare_image_inputs
if is_torch_available():
import torch... | 64 |
import argparse
import json
import os
import fairseq
import torch
from fairseq.data import Dictionary
# Register SEW's fairseq modules
from sew_asapp import tasks # noqa: F401
from transformers import (
SEWConfig,
SEWForCTC,
SEWModel,
WavaVecaCTCTokenizer,
WavaVecaFea... | 625 | 0 |
"""simple docstring"""
import copy
import os
import cva
import numpy as np
from matplotlib import pyplot as plt
class __lowercase :
def __init__( self : int ):
'''simple docstring'''
UpperCAmelCase__ : Dict = """"""
Upper... | 65 |
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_tokenizers_available,
is_torch_available,
is_vision_available,
)
UpperCamelCase_ = {
'configuration_owlvit':... | 625 | 0 |
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import cached_download, hf_hub_download, hf_hub_url
from PIL import Image
from transformers import DetaConfig, DetaForObjectDetection, DetaImageProcessor, SwinConfig
from transformers.utils import logging
l... | 66 |
from typing import Optional, Tuple, Union
import flax
import flax.linen as nn
import jax
import jax.numpy as jnp
from flax.core.frozen_dict import FrozenDict
from ..configuration_utils import ConfigMixin, flax_register_to_config
from ..utils import BaseOutput
from .embeddings_flax import FlaxTim... | 625 | 0 |
import re
from pathlib import Path
from unittest import TestCase
import pytest
@pytest.mark.integration
class A_ ( UpperCAmelCase ):
"""simple docstring"""
def __UpperCAmelCase ( self : Union[str, Any] ,__A : ... | 67 |
import inspect
import unittest
from transformers import DPTConfig
from transformers.file_utils import is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from ...test_config... | 625 | 0 |
def lowercase__ ( A_: int ) -> int:
"""simple docstring"""
if not isinstance(A_ , A_ ):
raise TypeError("""only integers accepted as input""" )
else:
__UpperCAmelCase =str(abs(A_ ) )
__UpperCAmelCase ... | 68 |
def _UpperCAmelCase ( A ):
'''simple docstring'''
for i in range(len(A ) - 1 , 0 , -1 ):
UpperCAmelCase__ =False
for j in range(A , 0 , -1 ):
if unsorted[j] < unsorted[j - 1]:
UpperCAme... | 625 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import SegformerConfig, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from ...test_configuration_common import ... | 69 |
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'microsoft/wavlm-base': 'https://huggingface.co/microsoft/wavlm-base/resolve/main/confi... | 625 | 0 |
from PIL import Image
def _SCREAMING_SNAKE_CASE ( lowercase : Image ):
'''simple docstring'''
lowerCamelCase_ , lowerCamelCase_ = image.size
lowerCamelCase_ = 0
lowerCamelCase_ = image.load()
for i in ... | 70 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'junnyu/roformer_chinese_... | 625 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_glpn import GLPNImageProcessor
_lowerCamelCase = logging.get_logger(__name__)
class _snake_case (__SCREAMING_SNAKE_CASE):
def __init__( self ,*_snake_case ,**_snake_case ... | 71 |
import os
from typing import List, Optional, Union
from ...image_processing_utils import BatchFeature
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...... | 625 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_UpperCAmelCase : Any = {
'''configuration_clap''': [
'''CLAP_PRETRAINED_MODEL_ARCHIVE_LIST''',
'''ClapAudioConfig''',
'''ClapConfig''',
... | 72 |
from ...configuration_utils import PretrainedConfig
from ...utils import logging
UpperCamelCase_ = logging.get_logger(__name__)
UpperCamelCase_ = {
'naver-clova-ix/donut-base': 'https://huggingface.co/naver-clova-ix/donut-base/resolve/main/config.json',
# See all Don... | 625 | 0 |
# Author: OMKAR PATHAK, Nwachukwu Chidiebere
# Use a Python dictionary to construct the graph.
from __future__ import annotations
from pprint import pformat
from typing import Generic, TypeVar
a_ : Tuple = TypeVar('T')
class _snake_case ( Generic[T] ):
def __init__( se... | 73 |
import collections
import tempfile
import unittest
import numpy as np
from transformers.testing_utils import (
is_pt_flax_cross_test,
require_flax,
require_torch,
require_vision,
slow,
torch_device,
)
from transformers.utils import is_flax_available, is_torch_availabl... | 625 | 0 |
import gc
import random
import unittest
import torch
from diffusers import (
IFImgaImgPipeline,
IFImgaImgSuperResolutionPipeline,
IFInpaintingPipeline,
IFInpaintingSuperResolutionPipeline,
IFPipeline,
IFSuperResolutionPipeline,
)
from diffusers.models.attention_processor import AttnAddedKVPro... | 74 |
from typing import List, Optional
import numpy as np
from ...processing_utils import ProcessorMixin
from ...utils import to_numpy
class snake_case_ ( a ):
'''simple docstring'''
__UpperCamelCase = 'EncodecFeatureExtractor'
__UpperCamelCase ... | 625 | 0 |
'''simple docstring'''
from typing import List, Optional, Tuple, Union
import torch
from ...utils import logging, randn_tensor
from ..pipeline_utils import AudioPipelineOutput, DiffusionPipeline
UpperCamelCase__ = logging.get_logger(__name__) # pylint: disable=invalid-name
class ... | 75 |
import os
import zipfile
import requests
from get_ci_error_statistics import download_artifact, get_artifacts_links
def _UpperCAmelCase ( A , A=7 ):
'''simple docstring'''
UpperCAmelCase__ =None
if token is not None:
UpperCAmelCase__ ... | 625 | 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
| 76 |
import os
import tempfile
import unittest
import uuid
from pathlib import Path
from transformers.testing_utils import get_tests_dir, require_soundfile, require_torch, require_vision
from transformers.tools.agent_types import AgentAudio, AgentImage, AgentText
from transformers.utils import is_soundf... | 625 | 0 |
"""simple docstring"""
import unittest
import numpy as np
import torch
from .utils_summarization import build_mask, compute_token_type_ids, process_story, truncate_or_pad
class a__ ( unittest.TestCase ):
def a_ ( self : List[Any]):
"""simple docstring"""
__Up... | 77 |
import warnings
from typing import Dict
import numpy as np
from ..utils import ExplicitEnum, add_end_docstrings, is_tf_available, is_torch_available
from .base import PIPELINE_INIT_ARGS, GenericTensor, Pipeline
if is_tf_available():
from ..models.auto.modeling_tf_auto import TF_MODEL_FOR_S... | 625 | 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, prepare_image_inputs
if is_torch_ava... | 78 |
import inspect
import unittest
from transformers import YolosConfig
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
... | 625 | 0 |
import argparse
import logging
from collections import namedtuple
import torch
from model_bertabs import BertAbsSummarizer
from models.model_builder import AbsSummarizer # The authors' implementation
from transformers import BertTokenizer
logging.basicConfig(level=logging.INFO)
SCREAMING_... | 79 |
import os
import torch
from ..logging import get_logger
from .constants import FSDP_PYTORCH_VERSION, MODEL_NAME, OPTIMIZER_NAME
from .versions import is_torch_version
if is_torch_version('>=', FSDP_PYTORCH_VERSION):
import torch.distributed.checkpoint as dist_cp
from torch.distributed... | 625 | 0 |
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