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 warnings
from .generation import TFGenerationMixin
class UpperCamelCase__( lowerCAmelCase ):
# warning at import time
warnings.warn(
"Importing `TFGenerationMixin` from `src/transformers/generation_tf_utils.py` is deprecated and will "
"be remove... | 91 |
'''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 | 1 |
'''simple docstring'''
import datasets
import faiss
import numpy as np
import streamlit as st
import torch
from elasticsearch import Elasticsearch
from elia_utils import (
embed_questions_for_retrieval,
make_qa_sas_model,
qa_sas_generate,
query_es_index,
query_qa_dense_index,
)
import transfo... | 91 |
'''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 | 1 |
'''simple docstring'''
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 ... | 91 |
'''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 | 1 |
'''simple docstring'''
import math
from collections.abc import Callable
def lowerCamelCase__ ( A : Callable[[float], float] , A : float , A : float ):
'''simple docstring'''
UpperCAmelCase = xa
UpperCAmelCase ... | 91 |
'''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 | 1 |
'''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... | 91 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers import LiltConfig, 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_common im... | 91 |
'''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 | 1 |
'''simple docstring'''
import collections
import inspect
import unittest
from transformers import FocalNetConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_backbone_... | 91 |
'''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 | 1 |
'''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 ):
_... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
import warnings
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : Tuple = ["image_processor", "tokenizer"]
__magic_name__ : Any = "CLIPImagePr... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available
_lowercase : str = {
"""configuration_timesformer""": ["""TIMESFORMER_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TimesformerConfig"""],
}
try:
if... | 91 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import Iterator
from typing import Generic, TypeVar
_lowercase : Optional[int] = TypeVar("""T""")
class UpperCamelCase__( Generic[T] ):
def __init__( self : Any , lowerCAmelC... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding, PaddingStrategy, PreTokenizedInput, TextInput, TruncationStrategy
from ...utils import TensorType
class UpperCamelCase__( lowerCAmelCas... | 91 |
'''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 | 1 |
'''simple docstring'''
import inspect
import unittest
import warnings
from math import ceil, floor
from transformers import LevitConfig
from transformers.file_utils import cached_property, is_torch_available, is_vision_available
from transformers.models.auto import get_values
from transformers.testing_utils impo... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_tf_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : List[Any] = {
"""configuration_funnel""": ["""FUNNEL_PRETRAIN... | 91 |
'''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 | 1 |
'''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... | 91 |
'''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 | 1 |
'''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 < ... | 91 |
'''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 | 1 |
'''simple docstring'''
import unittest
from accelerate import debug_launcher
from accelerate.test_utils import require_cpu, test_ops, test_script
@require_cpu
class UpperCamelCase__( unittest.TestCase ):
def a__( self : List[str] )-> Union[str, Any]:
"""simple ... | 91 |
'''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 | 1 |
'''simple docstring'''
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] ... | 91 |
'''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 | 1 |
'''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... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
import os
import re
import shutil
from argparse import ArgumentParser, Namespace
from datasets.commands import BaseDatasetsCLICommand
from datasets.utils.logging import get_logger
_lowercase : List[Any] = """<<<<<<< This should probably be modified because it men... | 91 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
def lowerCamelCase__ ( A : list[int | float] , A : int , A : int ):
'''simple docstring'''
if len(A ) == 0:
raise ValueError('''find_max() arg is an empty... | 91 |
'''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 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( A : list ):
'''simple docstring'''
UpperCAmelCase = len(A )
for i in range(1 , A ):
UpperCAmelCase = collection[i]
UpperCAmelCase = 0
... | 91 |
'''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 | 1 |
'''simple docstring'''
# Copyright 2022 The HuggingFace Team and The OpenBMB 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... | 91 |
'''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 | 1 |
'''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 (
... | 91 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 1 |
'''simple docstring'''
import logging
import os
from typing import Dict, List, Optional, Union
import torch
import torch.nn as nn
from accelerate.utils.imports import (
is_abit_bnb_available,
is_abit_bnb_available,
is_bnb_available,
)
from ..big_modeling import dispatch_model, init_empty_weights
fr... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import torch
from transformers import GPTaConfig, GPTaModel, load_tf_weights_in_gpta
from transformers.utils import CONFIG_NAME, WEIGHTS_NAME, logging
logging.set_verbosity_info()
def lowerCamelCase__ ( A : Optional[int] , A : List... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import Dict, List, Optional, Union
import numpy as np
from ...image_processing_utils import BaseImageProcessor, BatchFeature, get_size_dict
from ...image_transforms import (
center_crop,
get_resize_output_image_size,
normalize,
rescale,
resize,
to_chann... | 91 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
import unittest
from transformers import is_tf_available
from transformers.testing_utils import require_sentencepiece, require_tf, require_tokenizers, slow
if is_tf_available():
import numpy as np
import tensorflow as tf
from transformers import TF... | 91 |
'''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 | 1 |
'''simple docstring'''
from functools import reduce
_lowercase : Union[str, Any] = (
"""73167176531330624919225119674426574742355349194934"""
"""96983520312774506326239578318016984801869478851843"""
"""85861560789112949495459501737958331952853208805511"""
"""1254069874715... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import os
import re
import torch
from flax.traverse_util import flatten_dict
from tax import checkpoints
from transformers import (
AutoTokenizer,
PixaStructConfig,
PixaStructForConditionalGeneration,
PixaStructImageProcessor,
PixaStructProcessor,
P... | 91 |
'''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 | 1 |
'''simple docstring'''
from copy import deepcopy
from typing import Optional, Union
import numpy as np
from ...processing_utils import ProcessorMixin
from ...tokenization_utils_base import BatchEncoding
from ...utils import TensorType, is_tf_available, is_torch_available
if is_torch_available():
import torch... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_tf_available, is_torch_available
_lowercase : List[str] = {
"""configuration_tapas""": ["""TAPAS_PRETRAINED_CONFIG_ARCHIVE_MAP""", """TapasConfig"""],
""... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import re
from flax.traverse_util import flatten_dict, unflatten_dict
from tax import checkpoints
from transformers import SwitchTransformersConfig, SwitchTransformersForConditionalGeneration
from transformers.modeling_flax_pytorch_utils import load_flax_weights_in_pytorch... | 91 |
'''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 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( A : int = 1_00 ):
'''simple docstring'''
UpperCAmelCase = 0
UpperCAmelCase = 0
for i in range(1 , n + 1 ):
sum_of_squares += i**2
sum_of_ints += i
... | 91 |
'''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 | 1 |
'''simple docstring'''
import functools
import operator
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Any = logging.get_logger(__name__)
_lowercase : Dict = {
"""asapp/sew-d-tiny-100k""": """https://huggingfa... | 91 |
'''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 | 1 |
'''simple docstring'''
# Lint as: python3
import dataclasses
import re
from dataclasses import dataclass
from functools import total_ordering
from typing import Optional, Union
_lowercase : List[str] = re.compile(r"""^(?P<major>\d+)""" r"""\.(?P<minor>\d+)""" r"""\.(?P<patch>\d+)$""")
... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...file_utils import _LazyModule, is_tokenizers_available, is_torch_available
from ...utils import OptionalDependencyNotAvailable
_lowercase : List[Any] = {"""configuration_gpt_neox""": ["""GPT_NEOX_PRETRAINED_CONFIG_ARCHIVE_... | 91 |
'''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 | 1 |
'''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_... | 91 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
from collections.abc import MutableSequence
class UpperCamelCase__:
def __init__( self : Optional[int] , lowerCAmelCase : int , lowerCAmelCase : MutableSequence[float] )-> None:
"""simple do... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''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... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import (
OptionalDependencyNotAvailable,
_LazyModule,
is_sentencepiece_available,
is_tokenizers_available,
is_torch_available,
)
_lowercase : int = {}
try:
if not is_sentencepiece_available():
... | 91 |
'''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 | 1 |
'''simple docstring'''
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 DPRC... | 91 |
'''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 | 1 |
'''simple docstring'''
from pathlib import Path
import numpy as np
from PIL import Image
def lowerCamelCase__ ( A : np.ndarray ):
'''simple docstring'''
UpperCAmelCase , UpperCAmelCase , UpperCAmelCase = rgb[:, :, 0], rgb[:, :, 1], rgb[:, :, 2... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import json
import os
import re
import torch
from transformers import BloomConfig, BloomModel
from transformers.file_utils import CONFIG_NAME, WEIGHTS_NAME
from transformers.utils import logging
logging.set_verbosity_info()
_lowercase : Tuple = ... | 91 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( A : List[str] , A : Union[str, Any] ):
'''simple docstring'''
UpperCAmelCase = [1]
for i in range(2 , A ):
factorials.append(factorials[-1] * i )
asser... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
from ....utils import logging
_lowercase : Any = logging.get_logger(__name__)
class UpperCamelCase__( lowerCAmelCase ):
def __init__( self : Tuple , lowerCAmelCase : Optional[Any] , lowerCAmelCase : Any=None ... | 91 |
'''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 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_deit import DeiTImageProcessor
_lowercase : Optional[Any] = logging.get_logger(__name__)
class UpperCamelCase__( lowerCAmelCase ):
def __init__( self : List[str] ,... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acceler... | 91 |
'''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 | 1 |
'''simple docstring'''
import darl # noqa
import gym
import tqdm
from diffusers.experimental import ValueGuidedRLPipeline
_lowercase : List[str] = {
"""n_samples""": 64,
"""horizon""": 32,
"""num_inference_steps""": 20,
"""n_guide_steps""": 2, # can set to 0 for faster... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : Optional[int] = {
"""configuration_mobilenet_v2""": [
"""MOBILENET_V2_PRETRAINED_CONFIG_ARCHIVE_MAP... | 91 |
'''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 | 1 |
'''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""": ... | 91 |
'''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 | 1 |
'''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, AutoTo... | 91 |
'''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 | 1 |
'''simple docstring'''
import copy
from dataclasses import dataclass, field
from typing import ClassVar, Dict
from ..features import ClassLabel, Features, Value
from .base import TaskTemplate
@dataclass(frozen=lowerCAmelCase )
class UpperCamelCase__( lowerCAmelCase ):
# `task` is not a ClassVar ... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
import os
import re
import warnings
from shutil import copyfile
from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
import sentencepiece as spm
from ...tokenization_utils import PreTrainedTokenizer
if TYPE_CHECKING:
from ...tokenization_utils_base import TextInput
from .... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import List, Union
from ..utils import (
add_end_docstrings,
is_tf_available,
is_torch_available,
is_vision_available,
logging,
requires_backends,
)
from .base import PIPELINE_INIT_ARGS, Pipeline
if is_vision_available():
from PIL import Image
from ... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import TYPE_CHECKING
from ...utils import OptionalDependencyNotAvailable, _LazyModule, is_torch_available, is_vision_available
_lowercase : str = {"""configuration_glpn""": ["""GLPN_PRETRAINED_CONFIG_ARCHIVE_MAP""", """GLPNConfig"""]}
try:
if not is... | 91 |
'''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 | 1 |
'''simple docstring'''
import os
import sys
import tempfile
import unittest
import unittest.mock as mock
from pathlib import Path
from huggingface_hub import HfFolder, delete_repo
from huggingface_hub.file_download import http_get
from requests.exceptions import HTTPError
from transformers import (
AlbertTo... | 91 |
'''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 | 1 |
'''simple docstring'''
import json
import multiprocessing as mp
import re
from collections import defaultdict
from functools import partial
from typing import Dict, List, Optional, Set, Tuple, Type
from datasets import Dataset
from datasketch import MinHash, MinHashLSH
from dpu_utils.utils.iterators import Threa... | 91 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
import math
import numpy as np
from numpy.linalg import norm
def lowerCamelCase__ ( A : np.ndarray , A : np.ndarray ):
'''simple docstring'''
return math.sqrt(sum(pow(a - b , 2 ... | 91 |
'''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 | 1 |
'''simple docstring'''
import json
import os
import sys
import tempfile
import unittest
from pathlib import Path
from shutil import copyfile
from huggingface_hub import HfFolder, Repository, create_repo, delete_repo
from requests.exceptions import HTTPError
import transformers
from transformers import (
CON... | 91 |
'''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 | 1 |
'''simple docstring'''
class UpperCamelCase__:
def __init__( self : Dict , lowerCAmelCase : Optional[Any] )-> Tuple:
"""simple docstring"""
UpperCAmelCase = arr.split(''',''' )
def a__( self : Union[str, Any] )-> ... | 91 |
'''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 | 1 |
'''simple docstring'''
# Usage:
# ./gen-card-allenai-wmt16.py
import os
from pathlib import Path
def lowerCamelCase__ ( A : List[str] , A : Tuple , A : List[Any] , A : Any ):
'''simple docstring'''
UpperCAme... | 91 |
'''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 | 1 |
'''simple docstring'''
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.kand... | 91 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 1 |
'''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 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
_lowercase : str = """ABCDEFGHIJKLMNOPQRSTUVWXYZ"""
def lowerCamelCase__ ( ):
'''simple docstring'''
UpperCAmelCase = input('''Enter message: ''' )
UpperCAmelCase = input('''Enter key [alphanumeric]: '... | 91 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Dict = logging.get_logger(__name__)
_lowercase : List[Any] = {
"""uclanlp/visualbert-vqa""": """https://huggingface.co/uclanlp/visualbert-vq... | 91 |
'''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 | 1 |
'''simple docstring'''
import unittest
from transformers import BigBirdTokenizer, BigBirdTokenizerFast
from transformers.testing_utils import get_tests_dir, require_sentencepiece, require_tokenizers, require_torch, slow
from transformers.utils import cached_property
from ...test_tokenization_common import Token... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
from diffusers.pipelines.stable_diffusion.convert_from_ckpt import download_controlnet_from_original_ckpt
if __name__ == "__main__":
_lowercase : str = argparse.ArgumentParser()
parser.add_argument(
"""--checkpoint_path""", default=None, t... | 91 |
'''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 | 1 |
'''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''... | 91 |
'''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 | 1 |
'''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 |
'''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 | 1 |
'''simple docstring'''
import argparse
import json
from pathlib import Path
import requests
import torch
from huggingface_hub import hf_hub_download
from PIL import Image
from transformers import BeitConfig, BeitForImageClassification, BeitForMaskedImageModeling, BeitImageProcessor
from transformers.image_utils... | 91 |
'''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 | 1 |
'''simple docstring'''
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 transfo... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import os
import evaluate
import torch
from datasets import load_dataset
from torch.optim import AdamW
from torch.utils.data import DataLoader
from transformers import AutoModelForSequenceClassification, AutoTokenizer, get_linear_schedule_with_warmup, set_seed
from acceler... | 91 |
'''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 | 1 |
'''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:
Uppe... | 91 |
'''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 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( A : str , A : str ):
'''simple docstring'''
def get_matched_characters(A : str , A : str ) -> str:
UpperCAmelCase = []
UpperCAmelCase... | 91 |
'''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 | 1 |
'''simple docstring'''
import pyarrow.parquet as pq
import pytest
from datasets import Audio, Dataset, DatasetDict, Features, NamedSplit, Sequence, Value, config
from datasets.features.image import Image
from datasets.io.parquet import ParquetDatasetReader, ParquetDatasetWriter, get_writer_batch_size
from ..uti... | 91 |
'''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 | 1 |
'''simple docstring'''
from manim import *
class UpperCamelCase__( lowerCAmelCase ):
def a__( self : str )-> int:
"""simple docstring"""
UpperCAmelCase = Rectangle(height=0.5 , width=0.5 )
UpperCAmelCase = ... | 91 |
'''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 | 1 |
'''simple docstring'''
import math
class UpperCamelCase__:
def __init__( self : Optional[int] , lowerCAmelCase : Union[str, Any]=0 )-> str: # a graph with Node 0,1,...,N-1
"""simple docstring"""
UpperCAmelCase = n
UpperCAmel... | 91 |
'''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 | 1 |
'''simple docstring'''
from typing import List, Optional, Union
import torch
from ...models import UNetaDConditionModel, VQModel
from ...pipelines import DiffusionPipeline
from ...pipelines.pipeline_utils import ImagePipelineOutput
from ...schedulers import DDPMScheduler
from ...utils import (
is_accelerate... | 91 |
'''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 | 1 |
'''simple docstring'''
def lowerCamelCase__ ( A : list[int] ):
'''simple docstring'''
UpperCAmelCase = []
if len(A ) == 1:
return [nums.copy()]
for _ in range(len(A ) ):
UpperCAmelCase = nums.pop(0 ... | 91 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
from ...utils.backbone_utils import BackboneConfigMixin, get_aligned_output_features_output_indices
_lowercase : List[str] = logging.get_logger(__name__)
class UpperCamelCase__... | 91 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : str = logging.get_logger(__name__)
_lowercase : List[str] = {}
class UpperCamelCase__( lowerCAmelCase ):
__magic_name__ : ... | 91 |
'''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 | 1 |
'''simple docstring'''
from ...utils import (
OptionalDependencyNotAvailable,
is_torch_available,
is_transformers_available,
is_transformers_version,
)
try:
if not (is_transformers_available() and is_torch_available() and is_transformers_version(""">=""", """4.25.0""")):
raise OptionalDepende... | 91 |
'''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 | 1 |
'''simple docstring'''
import argparse
import logging
import pickle
from collections import Counter
logging.basicConfig(
format="""%(asctime)s - %(levelname)s - %(name)s - %(message)s""", datefmt="""%m/%d/%Y %H:%M:%S""", level=logging.INFO
)
_lowercase : str = logging.getLogger(__na... | 91 |
'''simple docstring'''
from .data_collator import (
DataCollatorForLanguageModeling,
DataCollatorForPermutationLanguageModeling,
DataCollatorForSeqaSeq,
DataCollatorForSOP,
DataCollatorForTokenClassification,
DataCollatorForWholeWordMask,
DataCollatorWithPadding,
DefaultDataCollato... | 91 | 1 |
'''simple docstring'''
import warnings
from ...utils import logging
from .image_processing_donut import DonutImageProcessor
_lowercase : Tuple = logging.get_logger(__name__)
class UpperCamelCase__( lowerCAmelCase ):
def __init__( self : int , *lowerCAm... | 91 |
'''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 | 1 |
'''simple docstring'''
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... | 91 |
'''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 | 1 |
'''simple docstring'''
from ...configuration_utils import PretrainedConfig
from ...utils import logging
_lowercase : Union[str, Any] = logging.get_logger(__name__)
_lowercase : Any = {
"""facebook/s2t-small-librispeech-asr""": (
"""https://huggingfa... | 91 |
'''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 | 1 |
'''simple docstring'''
from math import isqrt, loga
def lowerCamelCase__ ( A : int ):
'''simple docstring'''
UpperCAmelCase = [True] * max_number
for i in range(2 , isqrt(max_number - 1 ) + 1 ):
if is_prime[i]:
... | 91 |
'''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 | 1 |
'''simple docstring'''
# Copyright 2023 The HuggingFace Inc. team. All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.... | 91 |
'''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 | 1 |
'''simple docstring'''
import os
from shutil import copyfile
from typing import List, Optional, Tuple
from tokenizers import processors
from ...tokenization_utils import AddedToken, BatchEncoding
from ...tokenization_utils_fast import PreTrainedTokenizerFast
from ...utils import is_sentencepiece_available, logg... | 91 |
'''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 | 1 |
'''simple docstring'''
from __future__ import annotations
from random import choice
def lowerCamelCase__ ( A : Tuple ):
'''simple docstring'''
return choice(A )
def lowerCamelCase__ ( A : list[int] , A : int ):
... | 91 |
'''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 | 1 |
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