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 |
|---|---|---|---|---|
'''simple docstring'''
import unittest
from transformers.utils.backbone_utils import (
BackboneMixin,
get_aligned_output_features_output_indices,
verify_out_features_out_indices,
)
class UpperCamelCase__( unittest.TestCase ):
def a__( self : Optional[int] )-> int... | 370 |
'''simple docstring'''
_lowercase : Any = range(2, 20 + 1)
_lowercase : str = [10**k for k in range(ks[-1] + 1)]
_lowercase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase__ ( A : int , A ... | 91 | 0 |
'''simple docstring'''
import os
from collections import deque
import torch
from torch.utils.data import Dataset
class UpperCamelCase__( _a ):
def __init__( self : int , lowerCAmelCase : Optional[int]="" , lowerCAmelCase : Union[str, Any]="train" )-> s... | 371 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTok... | 91 | 0 |
'''simple docstring'''
from collections import OrderedDict
from typing import Any, List, Mapping, Optional
from ... import PreTrainedTokenizer, TensorType, is_torch_available
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfigWithPast, PatchingSpec
from ...utils import logging
_l... | 350 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 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-2.0
#... | 351 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
while a != 0:
UpperCAmelCase , UpperCAmelCase = b % a, a
return b
def lowerCamelCase__ ( A : int , ... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_flax_available,
is_tf_available,
is_torch_available,
)
_lowercase : Union[str, Any] = {
"""configuration_roberta_prelayernorm""": [
... | 352 |
'''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__:
__magic_name__ : List[str]
__magic_name_... | 91 | 0 |
'''simple docstring'''
import unittest
import numpy as np
def lowerCamelCase__ ( A : List[str] , A : Optional[int] , A : List[Any] , A : Optional[int] = None , ):
'''simple docstring'''
UpperCAmelCase ... | 353 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 )-> None:
"""simple docstring""... | 91 | 0 |
'''simple docstring'''
import inspect
import unittest
from huggingface_hub import hf_hub_download
from transformers import ASTConfig
from transformers.testing_utils import require_torch, require_torchaudio, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_torchaudio_avai... | 354 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class UpperCamelCase__:
__magic_name__ : int
__magic_name__ : TreeNode | None = None
__magic_name__ : TreeNode | None = None
... | 91 | 0 |
import shutil
import tempfile
import unittest
import numpy as np
import pytest
from transformers import is_speech_available, is_vision_available
from transformers.testing_utils import require_torch
if is_vision_available():
from transformers import TvltImageProcessor
if is_speech_available():
from transformer... | 355 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 | 0 |
'''simple docstring'''
from manim import *
class UpperCamelCase__( snake_case_ ):
def a__( self : Optional[Any] )-> Any:
"""simple docstring"""
UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase ... | 356 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : List[Any] = ["image_processor", "tokenizer"]
__magic_name__ : Tuple = "ViTIm... | 91 | 0 |
'''simple docstring'''
# flake8: noqa
# Lint as: python3
from typing import Dict, List, Optional, Type
from .. import config
from ..utils import logging
from .formatting import (
ArrowFormatter,
CustomFormatter,
Formatter,
PandasFormatter,
PythonFormatter,
TensorFormatter,
format_tab... | 357 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json... | 91 | 0 |
'''simple docstring'''
from __future__ import annotations
from functools import lru_cache
from math import ceil
_lowercase : Any = 100
_lowercase : List[Any] = set(range(3, NUM_PRIMES, 2))
primes.add(2)
_lowercase : Optional[int] = 42
... | 358 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowerCamelCase__ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' ... | 91 | 0 |
'''simple docstring'''
import logging
import torch
from accelerate import Accelerator
from arguments import EvaluationArguments
from datasets import load_dataset
from torch.utils.data import IterableDataset
from torch.utils.data.dataloader import DataLoader
from transformers import AutoModelForCausalLM, AutoTok... | 359 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
... | 91 | 0 |
'''simple docstring'''
import string
# frequency taken from https://en.wikipedia.org/wiki/Letter_frequency
_lowercase : List[Any] = {
"""E""": 12.70,
"""T""": 9.06,
"""A""": 8.17,
"""O""": 7.51,
"""I""": 6.97,
"""N""": 6.75,
"""S""": 6.33,
"""H""": 6.09,
... | 360 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
fr... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : Optional[int] = {
"""configuration_xlm""": ["""XLM_PRETRAINED_CONFIG_ARCHIVE_MAP""", """XLMConfig""", """XLMOnn... | 361 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers... | 91 | 0 |
'''simple docstring'''
from random import randint, random
def lowerCamelCase__ ( A : Any , A : str , A : Optional[int] , A : List[Any] = False , A : List[Any] = False , A : Optional[Any] = 5 ,... | 362 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 91 | 0 |
'''simple docstring'''
import argparse
import logging
import os
import re
import tensorflow as tf
from transformers import (
AutoConfig,
AutoTokenizer,
DataCollatorForLanguageModeling,
PushToHubCallback,
TFAutoModelForMaskedLM,
create_optimizer,
)
_lowercase : Dict ... | 363 |
'''simple docstring'''
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 ... | 91 | 0 |
'''simple docstring'''
from math import log
from scipy.constants import Boltzmann, physical_constants
_lowercase : List[Any] = 300 # TEMPERATURE (unit = K)
def lowerCamelCase__ ( A : str , A : Any , A : List[str] , ):... | 364 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowerCamelCase__ ( A : int , A : int , A : int , A : int , A : int , A ... | 91 | 0 |
'''simple docstring'''
import inspect
import os
import unittest
from pathlib import Path
import torch
import accelerate
from accelerate.test_utils import execute_subprocess_async
from accelerate.test_utils.testing import run_command
class UpperCamelCase__( unittest.TestCase ):
__magic_name__ ... | 365 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Union[str, Any] = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 91 | 0 |
from .testing import (
are_the_same_tensors,
execute_subprocess_async,
require_bnb,
require_cpu,
require_cuda,
require_huggingface_suite,
require_mps,
require_multi_gpu,
require_multi_xpu,
require_safetensors,
require_single_gpu,
require_single_xpu,
require_torch_m... | 366 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[str] = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP"""... | 91 | 0 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase__ ( A : list , A : int | None = None , A : int | None = None ):
'''simple docstring'''
if start is None:
UpperCAmelCase = 0
... | 367 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import ji... | 91 | 0 |
import copy
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
from ..auto import CONFIG_MAPPING
_lowercase : Optional[int] = logging.... | 368 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch... | 91 | 0 |
'''simple docstring'''
import collections.abc
from typing import Optional, Tuple, Union
import torch
import torch.utils.checkpoint
from torch import nn
from torch.nn import BCEWithLogitsLoss, CrossEntropyLoss, MSELoss
from ...activations import ACTaFN
from ...modeling_outputs import BaseModelOutputWithNoAttenti... | 369 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase__( nn.Module ):
__magic_name__ : int
__magic_name__ : int
... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tokenizers_available, is_torch_available
_lowercase : Tuple = {
"""configuration_canine""": ["""CANINE_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CanineConfig"""],
... | 370 |
'''simple docstring'''
_lowercase : Any = range(2, 20 + 1)
_lowercase : str = [10**k for k in range(ks[-1] + 1)]
_lowercase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase__ ( A : int , A ... | 91 | 0 |
'''simple docstring'''
import argparse
import json
from collections import OrderedDict
import torch
from huggingface_hub import cached_download, hf_hub_url
from transformers import AutoImageProcessor, CvtConfig, CvtForImageClassification
def lowerCamelCase__ ( A : Optional[Any] ):
... | 371 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTok... | 91 | 0 |
'''simple docstring'''
import re
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
UpperCAmelCase = re.compile(
R'''^(?:0|94|\+94|0{2}94)''' R'''7(0|1|2|4|5|6|7|8)''' R'''(-| |)''' R'''\d{7}$''' )
return bool(re.search(lowerCame... | 350 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
class UpperCamelCase__( __SCREAMING_SNAKE_CASE ):
__magic_name__ : Union[str, Any] = "timm_backbone"
... | 351 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
while a != 0:
UpperCAmelCase , UpperCAmelCase = b % a, a
return b
def lowerCamelCase__ ( A : int , ... | 91 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from datasets import load_dataset
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, pre... | 352 |
'''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__:
__magic_name__ : List[str]
__magic_name_... | 91 | 0 |
'''simple docstring'''
import argparse
import torch
from torch import nn
from transformers import MBartConfig, MBartForConditionalGeneration
def lowerCamelCase__ ( A : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase = [
'''encoder.vers... | 353 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 )-> None:
"""simple docstring""... | 91 | 0 |
'''simple docstring'''
_lowercase : str = '''Alexander Joslin'''
import operator as op
from .stack import Stack
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
UpperCAmelCase = {"*": op.mul, "/": op.truediv, "+": op.add, "-... | 354 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class UpperCamelCase__:
__magic_name__ : int
__magic_name__ : TreeNode | None = None
__magic_name__ : TreeNode | None = None
... | 91 | 0 |
import time
from dataclasses import dataclass
from multiprocessing import Pool
from unittest import TestCase
from unittest.mock import patch
import multiprocess
import numpy as np
import pytest
from datasets.utils.py_utils import (
NestedDataStructure,
asdict,
iflatmap_unordered,
map_nested,
te... | 355 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : List[str] = {
'configuration_lxmert': ['LXMERT_PRETRAINED... | 356 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : List[Any] = ["image_processor", "tokenizer"]
__magic_name__ : Tuple = "ViTIm... | 91 | 0 |
'''simple docstring'''
import unittest
from transformers import AlbertTokenizer, AlbertTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowercase : Any = ge... | 357 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json... | 91 | 0 |
'''simple docstring'''
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
... | 358 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowerCamelCase__ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' ... | 91 | 0 |
'''simple docstring'''
import json
import logging
import os
import socket
import git
import numpy as np
import torch
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - PID: %(process)d - %(message)s""",
datefmt="""%m/%d/%Y %H:%M:%S""",
level=logging.INFO,
)
_lowercase : ... | 359 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
... | 91 | 0 |
'''simple docstring'''
import re
from ..models.auto import AutoProcessor
from ..models.vision_encoder_decoder import VisionEncoderDecoderModel
from ..utils import is_vision_available
from .base import PipelineTool
if is_vision_available():
from PIL import Image
class UpperCamelCase__( Upper... | 360 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
fr... | 91 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Any = {
"""google/fnet-base""": """https://huggingface.co/google/fnet-base/resol... | 361 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers... | 91 | 0 |
'''simple docstring'''
import fire
from transformers import AutoConfig, AutoModelForSeqaSeqLM, AutoTokenizer
def lowerCamelCase__ ( A : str , A : Tuple , **A : List[str] ):
'''simple docstring'''
UpperCAmelCase = Aut... | 362 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 91 | 0 |
'''simple docstring'''
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... | 363 |
'''simple docstring'''
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 ... | 91 | 0 |
'''simple docstring'''
import inspect
import unittest
import numpy as np
from tests.test_modeling_common import floats_tensor
from transformers import DetrConfig, MaskFormerConfig, SwinConfig, is_torch_available, is_vision_available
from transformers.testing_utils import require_torch, require_torch_multi_gpu, ... | 364 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowerCamelCase__ ( A : int , A : int , A : int , A : int , A : int , A ... | 91 | 0 |
'''simple docstring'''
from math import factorial
def lowerCamelCase__ ( A : int = 1_00 ):
'''simple docstring'''
return sum(int(snake_case__ ) for x in str(factorial(snake_case__ ) ) )
if __name__ == "__main__":
print(solution(int(input("""Ent... | 365 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Union[str, Any] = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 91 | 0 |
import inspect
import os
import re
from transformers.configuration_utils import PretrainedConfig
from transformers.utils import direct_transformers_import
# All paths are set with the intent you should run this script from the root of the repo with the command
# python utils/check_config_docstrings.py
_lowercase ... | 366 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[str] = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP"""... | 91 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( A : int = 10_00 ):
'''simple docstring'''
UpperCAmelCase = 3
UpperCAmelCase = 0
while a < n:
if a % 3 == 0 or a % 5 == 0:
result += a
elif a % 15 ... | 367 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import ji... | 91 | 0 |
import argparse
from collections import OrderedDict
from pathlib import Path
import requests
import torch
from PIL import Image
from transformers import GLPNConfig, GLPNForDepthEstimation, GLPNImageProcessor
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase : Union[str, Any... | 368 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch... | 91 | 0 |
'''simple docstring'''
import argparse
import gc
import json
import os
import re
import torch
from huggingface_hub import hf_hub_download
from transformers import AutoModelForCausalLM, AutoTokenizer, PreTrainedTokenizerFast, RwkvConfig
from transformers.modeling_utils import WEIGHTS_INDEX_NAME, shard_checkpoint... | 369 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase__( nn.Module ):
__magic_name__ : int
__magic_name__ : int
... | 91 | 0 |
'''simple docstring'''
from collections import defaultdict
class UpperCamelCase__:
def __init__( self : int , lowerCAmelCase : str , lowerCAmelCase : List[Any] )-> int:
"""simple docstring"""
UpperCAmelCase = total # total no... | 370 |
'''simple docstring'''
_lowercase : Any = range(2, 20 + 1)
_lowercase : str = [10**k for k in range(ks[-1] + 1)]
_lowercase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase__ ( A : int , A ... | 91 | 0 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from transformers.utils import is_vision_available
from transformers.utils.generic import TensorType
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
... | 371 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTok... | 91 | 0 |
'''simple docstring'''
import unittest
from transformers import GPTSwaTokenizer
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, slow
from ...test_tokenization_common import TokenizerTesterMixin
_lowercase : Optional[int] = get_tests_dir... | 350 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import ViTMSNConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import Confi... | 351 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
while a != 0:
UpperCAmelCase , UpperCAmelCase = b % a, a
return b
def lowerCamelCase__ ( A : int , ... | 91 | 0 |
'''simple docstring'''
import copy
from typing import Any, Dict, List, Optional, Union
import numpy as np
import torch
from ...audio_utils import mel_filter_bank, spectrogram, window_function
from ...feature_extraction_sequence_utils import SequenceFeatureExtractor
from ...feature_extraction_utils import BatchF... | 352 |
'''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__:
__magic_name__ : List[str]
__magic_name_... | 91 | 0 |
'''simple docstring'''
import pickle
import numpy as np
from matplotlib import pyplot as plt
class UpperCamelCase__:
def __init__( self : Union[str, Any] , lowerCAmelCase : Optional[int] , lowerCAmelCase : List[str] , lowerCAmelCase : Optional[Any] ,... | 353 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 )-> None:
"""simple docstring""... | 91 | 0 |
'''simple docstring'''
from typing import List, Optional, Union
from ...image_utils import ImageInput
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class ... | 354 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class UpperCamelCase__:
__magic_name__ : int
__magic_name__ : TreeNode | None = None
__magic_name__ : TreeNode | None = None
... | 91 | 0 |
import sys
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 token... | 355 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : Tuple = {
"configuration_clipseg": [
"CLIPSEG_PRETRAINED_CONFIG_ARCHIVE_MAP",
"CLIPSegConfig",
"CLIP... | 356 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : List[Any] = ["image_processor", "tokenizer"]
__magic_name__ : Tuple = "ViTIm... | 91 | 0 |
'''simple docstring'''
import math
import unittest
from transformers import BioGptConfig, 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_mode... | 357 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json... | 91 | 0 |
'''simple docstring'''
from importlib import import_module
from .logging import get_logger
_lowercase : Optional[Any] = get_logger(__name__)
class UpperCamelCase__:
def __init__( self : str , lowerCAmelCase : List[Any] , lowerCAmelCase : A... | 358 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowerCamelCase__ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' ... | 91 | 0 |
'''simple docstring'''
import copy
import os
from typing import TYPE_CHECKING, List, Union
if TYPE_CHECKING:
pass
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : Optional[i... | 359 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
... | 91 | 0 |
'''simple docstring'''
class UpperCamelCase__:
def __init__( self : Dict , lowerCAmelCase : list[int] )-> int:
"""simple docstring"""
UpperCAmelCase = len(__A )
UpperCAmelCase = [0] * len_array
if len_arra... | 360 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
fr... | 91 | 0 |
'''simple docstring'''
import unittest
from transformers import (
MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TF_MODEL_FOR_SEQ_TO_SEQ_CAUSAL_LM_MAPPING,
TextaTextGenerationPipeline,
pipeline,
)
from transformers.testing_utils import is_pipeline_test, require_tf, require_torch
from transformers.utils ... | 361 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers... | 91 | 0 |
'''simple docstring'''
import contextlib
import csv
import json
import os
import sqlitea
import tarfile
import textwrap
import zipfile
import pyarrow as pa
import pyarrow.parquet as pq
import pytest
import datasets
import datasets.config
@pytest.fixture(scope='''session''' )
def lowerCamelCase__ ( )... | 362 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 91 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
if n_term == "":
return []
UpperCAmelCase = []
for temp in range(int(SCREAMING_SNAKE_CASE_ ) ):
series.append(f"""1/{temp + 1}""" if s... | 363 |
'''simple docstring'''
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 ... | 91 | 0 |
'''simple docstring'''
import re
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
if len(re.findall('''[ATCG]''' , snake_case__ ) ) != len(snake_case__ ):
raise ValueError('''Invalid Strand''' )
return dna.translate(... | 364 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowerCamelCase__ ( A : int , A : int , A : int , A : int , A : int , A ... | 91 | 0 |
'''simple docstring'''
from random import randint
from tempfile import TemporaryFile
import numpy as np
def lowerCamelCase__ ( A : Optional[int] , A : Optional[Any] , A : str ):
'''simple docstring'''
UpperCAmelCase = ... | 365 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Union[str, Any] = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 91 | 0 |
import argparse
import json
from typing import List
from ltp import LTP
from transformers.models.bert.tokenization_bert import BertTokenizer
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
if (
(cp >= 0x4e00 and cp <= 0x9fff)
or (cp >= 0x34... | 366 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[str] = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP"""... | 91 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : List[Any] = logging.get_logger(__name__)
_lowercase : Tuple = {
'studio-ousia/luke-base': 'https://huggingface.co/studio-ousia/luke-base/res... | 367 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import ji... | 91 | 0 |
import enum
import warnings
from ..tokenization_utils import TruncationStrategy
from ..utils import add_end_docstrings, is_tf_available, is_torch_available, logging
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_tf_available():
import tensorflow as tf
from ..models.auto.modeling_tf_auto import TF_MODEL_F... | 368 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch... | 91 | 0 |
'''simple docstring'''
from __future__ import annotations
from decimal import Decimal
from math import * # noqa: F403
from sympy import diff
def lowerCamelCase__ ( A : List[Any] , A : Tuple , A : List[str] = 10**-10 ):
'''simple docstrin... | 369 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase__( nn.Module ):
__magic_name__ : int
__magic_name__ : int
... | 91 | 0 |
'''simple docstring'''
from __future__ import annotations
import queue
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : Optional[int] )-> List[str]:
"""simple docstring"""
UpperCAmelCase = data
UpperCAmelCase... | 370 |
'''simple docstring'''
_lowercase : Any = range(2, 20 + 1)
_lowercase : str = [10**k for k in range(ks[-1] + 1)]
_lowercase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase__ ( A : int , A ... | 91 | 0 |
'''simple docstring'''
import operator as op
def lowerCamelCase__ ( A : Tuple ):
'''simple docstring'''
UpperCAmelCase = []
UpperCAmelCase = lambda A , A : int(x / y ) # noqa: E731 integer division operation
UpperC... | 371 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTok... | 91 | 0 |
'''simple docstring'''
import copy
import os
from typing import Union
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Optional[Any] = logging.get_logger(__name__)
_lowercase : Tuple = {
"""Salesforce/blip-vqa-b... | 350 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ....utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : Tuple = {
"""configuration_trajectory_transformer""": [
"""TRAJECTORY_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""",
... | 351 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
while a != 0:
UpperCAmelCase , UpperCAmelCase = b % a, a
return b
def lowerCamelCase__ ( A : int , ... | 91 | 0 |
'''simple docstring'''
import unittest
from diffusers.pipelines.pipeline_utils import is_safetensors_compatible
class UpperCamelCase__( unittest.TestCase ):
def a__( self : Optional[int] )-> List[Any]:
"""simple docstring"""
UpperCAmelCase ... | 352 |
'''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__:
__magic_name__ : List[str]
__magic_name_... | 91 | 0 |
'''simple docstring'''
import inspect
import unittest
from transformers import BitConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_common import BackboneTe... | 353 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 )-> None:
"""simple docstring""... | 91 | 0 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_segformer import SegformerImageProcessor
_lowercase : int = logging.get_logger(__name__)
class UpperCamelCase__( lowerCAmelCase ):
def __init__( self : Any , *lower... | 354 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class UpperCamelCase__:
__magic_name__ : int
__magic_name__ : TreeNode | None = None
__magic_name__ : TreeNode | None = None
... | 91 | 0 |
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():
from .tokenization_albert import Alb... | 355 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 | 0 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPT... | 356 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : List[Any] = ["image_processor", "tokenizer"]
__magic_name__ : Tuple = "ViTIm... | 91 | 0 |
'''simple docstring'''
from math import factorial
def lowerCamelCase__ ( A : int , A : int , A : float ):
'''simple docstring'''
if successes > trials:
raise ValueError('''successes must be lower or equal to trials''... | 357 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json... | 91 | 0 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
_lowercase : Tuple = {
"""google/tapas-base-finetuned-sqa""": (
"""https://huggingface.co/google/tapas-base-finetuned-sqa/resolve/main/config.json"""
),
"""google/tapas-base-finetuned-wtq""": ... | 358 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowerCamelCase__ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' ... | 91 | 0 |
'''simple docstring'''
import unittest
from transformers import load_tool
from .test_tools_common import ToolTesterMixin
class UpperCamelCase__( unittest.TestCase , lowerCAmelCase ):
def a__( self : Dict )-> Union[str, Any]:
"""simple docstring"""
... | 359 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
... | 91 | 0 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase__( nn.Module ):
__magic_name__ : int
__magic_name__ : int
... | 360 |
'''simple docstring'''
import copy
import inspect
import unittest
from transformers import AutoBackbone
from transformers.configuration_utils import PretrainedConfig
from transformers.testing_utils import require_timm, require_torch, torch_device
from transformers.utils.import_utils import is_torch_available
fr... | 91 | 0 |
'''simple docstring'''
from dataclasses import dataclass
from typing import List, Optional, Union
import numpy as np
import PIL
from ...utils import BaseOutput, OptionalDependencyNotAvailable, is_torch_available, is_transformers_available
from .timesteps import (
fastaa_timesteps,
smartaa_timesteps,
... | 361 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
if TYPE_CHECKING:
from transformers... | 91 | 0 |
'''simple docstring'''
def lowerCamelCase__ ( A : list ):
'''simple docstring'''
if len(A ) < 2:
return collection
def circle_sort_util(A : list , A : int , A : int ) -> bool:
Upper... | 362 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModelWithProjection, CLIPTokenizer
from diffusers import HeunDiscreteScheduler, PriorTransformer, ShapEPipeline
from diffusers.pipelines.shap_e import ShapERenderer
from diffusers.ut... | 91 | 0 |
'''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__:
__magic_name__ : List[str]
__magic_name_... | 363 |
'''simple docstring'''
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 ... | 91 | 0 |
'''simple docstring'''
from typing import List, Optional, TypeVar
from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenat... | 364 |
'''simple docstring'''
import numpy as np
from cva import COLOR_BGR2GRAY, CV_8UC3, cvtColor, filteraD, imread, imshow, waitKey
def lowerCamelCase__ ( A : int , A : int , A : int , A : int , A : int , A ... | 91 | 0 |
'''simple docstring'''
import argparse
import json
import os
import tensorstore as ts
import torch
from flax import serialization
from flax.traverse_util import flatten_dict, unflatten_dict
from tensorflow.io import gfile
from transformers.modeling_utils import dtype_byte_size
from transformers.models.switch_tr... | 365 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Union[str, Any] = {
"""configuration_poolformer""": [
"""POOLFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""... | 91 | 0 |
from __future__ import annotations
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
UpperCAmelCase = []
create_all_state(1 , A , A , [] , A )
return result
def low... | 366 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[str] = {
"""configuration_time_series_transformer""": [
"""TIME_SERIES_TRANSFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP"""... | 91 | 0 |
'''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
_lowercase : List[Any] = logging.getLogger(__name__)
... | 367 |
'''simple docstring'''
import random
import unittest
import numpy as np
import transformers
from transformers import is_flax_available, is_torch_available
from transformers.testing_utils import is_pt_flax_cross_test, require_flax
if is_flax_available():
import os
import jax.numpy as jnp
from jax import ji... | 91 | 0 |
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : Optional[int] = ["image_processor", "tokenizer"]
__magic_name__ : List[str] = "ChineseCLIPImageProcess... | 368 |
'''simple docstring'''
import gc
import unittest
import numpy as np
import torch
from transformers import CLIPTextConfig, CLIPTextModel, CLIPTokenizer
from diffusers import (
AutoencoderKL,
DDIMScheduler,
StableDiffusionSAGPipeline,
UNetaDConditionModel,
)
from diffusers.utils import slow, torch... | 91 | 0 |
'''simple docstring'''
import unittest
import numpy as np
from datasets import load_dataset
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, pre... | 369 |
'''simple docstring'''
import flax.linen as nn
import jax.numpy as jnp
from .attention_flax import FlaxTransformeraDModel
from .resnet_flax import FlaxDownsampleaD, FlaxResnetBlockaD, FlaxUpsampleaD
class UpperCamelCase__( nn.Module ):
__magic_name__ : int
__magic_name__ : int
... | 91 | 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 UpperCamelCase__( lowerCAmelCase ):
__ma... | 370 |
'''simple docstring'''
_lowercase : Any = range(2, 20 + 1)
_lowercase : str = [10**k for k in range(ks[-1] + 1)]
_lowercase : dict[int, dict[int, list[list[int]]]] = {}
def lowerCamelCase__ ( A : int , A ... | 91 | 0 |
'''simple docstring'''
from manim import *
class UpperCamelCase__( lowerCAmelCase ):
def a__( self : str )-> int:
"""simple docstring"""
UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase = ... | 371 |
'''simple docstring'''
import json
from typing import TYPE_CHECKING, List, Optional, Tuple
from tokenizers import pre_tokenizers
from ...tokenization_utils_base import BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import logging
from .tokenization_gpta import GPTaTok... | 91 | 0 |
'''simple docstring'''
import torch
from accelerate import PartialState
from accelerate.utils.operations import broadcast, gather, gather_object, pad_across_processes, reduce
def lowerCamelCase__ ( A : List[str] ):
'''simple docstring'''
return (torch.arange(state.nu... | 350 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 0 |
'''simple docstring'''
import argparse
import shutil
import time
from json import JSONDecodeError
from logging import getLogger
from pathlib import Path
from typing import Dict, List
import torch
from torch.utils.data import DataLoader
from tqdm import tqdm
from transformers import AutoModelForSeqaSeqLM, AutoToken... | 351 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
while a != 0:
UpperCAmelCase , UpperCAmelCase = b % a, a
return b
def lowerCamelCase__ ( A : int , ... | 91 | 0 |
'''simple docstring'''
import pytest
_lowercase : Any = """__dummy_dataset1__"""
_lowercase : Union[str, Any] = """
import json
import os
import datasets
REPO_URL = \"https://huggingface.co/datasets/albertvillanova/tests-raw-jsonl/resolve/main/\"
URLS = {\"t... | 352 |
'''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__:
__magic_name__ : List[str]
__magic_name_... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
# rely on isort to merge the imports
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : str = {"""configuration_focalnet""": ["""FOCALNET_PRETRAINED_CONFIG_ARCHIVE_MAP""", """FocalNet... | 353 |
'''simple docstring'''
from __future__ import annotations
from typing import Any
class UpperCamelCase__:
def __init__( self : Any , lowerCAmelCase : int , lowerCAmelCase : int , lowerCAmelCase : float = 0 )-> None:
"""simple docstring""... | 91 | 0 |
'''simple docstring'''
import json
import os
from collections import Counter
import torch
import torchvision
import torchvision.transforms as transforms
from PIL import Image
from torch import nn
from torch.utils.data import Dataset
_lowercase : Optional[Any] = {1: (1, 1), 2: (2, 1), 3: (... | 354 |
'''simple docstring'''
from __future__ import annotations
from collections import namedtuple
from dataclasses import dataclass
@dataclass
class UpperCamelCase__:
__magic_name__ : int
__magic_name__ : TreeNode | None = None
__magic_name__ : TreeNode | None = None
... | 91 | 0 |
from collections import OrderedDict
from typing import Mapping
from ...configuration_utils import PretrainedConfig
from ...onnx import OnnxConfig
from ...utils import logging
_lowercase : str = logging.get_logger(__name__)
_lowercase : List[str] = {
"""robert... | 355 |
'''simple docstring'''
# limitations under the License.
# NOTE: This file is deprecated and will be removed in a future version.
# It only exists so that temporarely `from diffusers.pipelines import DiffusionPipeline` works
from .pipelines import DiffusionPipeline, ImagePipelineOutput # noqa: F401
from .utils ... | 91 | 0 |
'''simple docstring'''
import os
def lowerCamelCase__ ( A : str ):
'''simple docstring'''
UpperCAmelCase = len(grid[0] )
UpperCAmelCase = len(A )
UpperCAmelCase = 0
UpperCAmelCase = 0
... | 356 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : List[Any] = ["image_processor", "tokenizer"]
__magic_name__ : Tuple = "ViTIm... | 91 | 0 |
'''simple docstring'''
import torch
from diffusers import DDIMParallelScheduler
from .test_schedulers import SchedulerCommonTest
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : Optional[int] = (DDIMParallelScheduler,)
__magic_name__ : Any = (("eta", 0.0), ("num_... | 357 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : int = logging.get_logger(__name__)
_lowercase : Optional[Any] = {"""openai-gpt""": """https://huggingface.co/openai-gpt/resolve/main/config.json... | 91 | 0 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : Optional[int] = {
"""configuration_ctrl""": ["""CTRL_PRETRAINED_CONFIG_ARCHIVE_MAP""", """CTRLConfig"""],
"... | 358 |
'''simple docstring'''
def lowerCamelCase__ ( A : int , A : int ):
'''simple docstring'''
return int(input_a == input_a == 0 )
def lowerCamelCase__ ( ):
'''simple docstring'''
print('''Truth Table of NOR Gate:''' ... | 91 | 0 |
'''simple docstring'''
from __future__ import annotations
import math
def lowerCamelCase__ ( A : int , A : int , A : bool , A : list[int] , A : float ):
'''simple docstring'''
if depth < ... | 359 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : List[Any] = {
"""configuration_x_clip""": [
"""XCLIP_PRETRAINED_CONFIG_ARCHIVE_MAP""",
"""XCLIPConfig""",
... | 91 | 0 |
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