old_contents: from .config import Config, registry
  from .initializers import normal_init, uniform_init, xavier_uniform_init, zero_init
  from .loss import categorical_crossentropy, L1_distance, cosine_distance
  from .model import create_init, Model
  from .optimizers import Adam, RAdam, SGD, Optimizer
  from .schedules import cyclic_triangular, warmup_linear, constant, constant_then
  from .schedules import decaying, slanted_triangular, compounding
  from .types import Ragged, Padded
  from .util import fix_random_seed, is_cupy_array, set_active_gpu
  from .util import prefer_gpu, require_gpu
  from .util import get_shuffled_batches, minibatch, evaluate_model_on_arrays
  from .util import to_categorical, get_width, get_array_module
  from .util import torch2xp, xp2torch, tensorflow2xp, xp2tensorflow
  from .backends import get_ops, set_current_ops, get_current_ops, use_device
  from .backends import Ops, CupyOps, NumpyOps
  from .backends import use_pytorch_for_gpu_memory, use_tensorflow_for_gpu_memory
  
  from .layers import Dropout, Embed, ExtractWindow, HashEmbed, LayerNorm, Linear
  from .layers import Maxout, Mish, MultiSoftmax, ReLu, Residual, Softmax, BiLSTM, LSTM
  from .layers import CauchySimilarity, ParametricAttention, PyTorchWrapper
  from .layers import SparseLinear, StaticVectors, PyTorchBiLSTM, FeatureExtractor
  from .layers import TensorFlowWrapper
  
  from .layers import add, bidirectional, chain, clone, concatenate, foreach, noop
  from .layers import recurrent, uniqued, siamese, list2ragged, ragged2list
  from .layers import with_list2array, with_list2padded, with_reshape, with_getitem
  from .layers import strings2arrays
  
  from .layers import MaxPool, MeanPool, SumPool
  
  
  __all__ = list(locals().keys())
  
new_contents: from .config import Config, registry
  from .initializers import normal_init, uniform_init, xavier_uniform_init, zero_init
  from .loss import categorical_crossentropy, L1_distance, cosine_distance
  from .model import create_init, Model
  from .optimizers import Adam, RAdam, SGD, Optimizer
  from .schedules import cyclic_triangular, warmup_linear, constant, constant_then
  from .schedules import decaying, slanted_triangular, compounding
  from .types import Ragged, Padded, ArgsKwargs
  from .util import fix_random_seed, is_cupy_array, set_active_gpu
  from .util import prefer_gpu, require_gpu
  from .util import get_shuffled_batches, minibatch, evaluate_model_on_arrays
  from .util import to_categorical, get_width, get_array_module
  from .util import torch2xp, xp2torch, tensorflow2xp, xp2tensorflow
  from .backends import get_ops, set_current_ops, get_current_ops, use_device
  from .backends import Ops, CupyOps, NumpyOps
  from .backends import use_pytorch_for_gpu_memory, use_tensorflow_for_gpu_memory
  
  from .layers import Dropout, Embed, ExtractWindow, HashEmbed, LayerNorm, Linear
  from .layers import Maxout, Mish, MultiSoftmax, ReLu, Residual, Softmax, BiLSTM, LSTM
  from .layers import CauchySimilarity, ParametricAttention, PyTorchWrapper
  from .layers import SparseLinear, StaticVectors, PyTorchBiLSTM, FeatureExtractor
  from .layers import TensorFlowWrapper
  
  from .layers import add, bidirectional, chain, clone, concatenate, foreach, noop
  from .layers import recurrent, uniqued, siamese, list2ragged, ragged2list
  from .layers import with_list2array, with_list2padded, with_reshape, with_getitem
  from .layers import strings2arrays
  
  from .layers import MaxPool, MeanPool, SumPool
  
  
  __all__ = list(locals().keys())
  
subject: Add ArgsKwargs to thinc.api