171 lines
4.3 KiB
Python
171 lines
4.3 KiB
Python
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# Weights layers
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# Combinators
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from .add import add
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# Array manipulation
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from .array_getitem import array_getitem
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from .bidirectional import bidirectional
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from .cauchysimilarity import CauchySimilarity
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from .chain import chain
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from .clipped_linear import ClippedLinear, HardSigmoid, HardTanh, ReluK
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from .clone import clone
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from .concatenate import concatenate
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from .dish import Dish
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from .dropout import Dropout
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from .embed import Embed
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from .expand_window import expand_window
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from .gelu import Gelu
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from .hard_swish import HardSwish
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from .hard_swish_mobilenet import HardSwishMobilenet
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from .hashembed import HashEmbed
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from .layernorm import LayerNorm
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from .linear import Linear
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# Data-type transfers
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from .list2array import list2array
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from .list2padded import list2padded
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from .list2ragged import list2ragged
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from .logistic import Logistic
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from .lstm import LSTM, PyTorchLSTM
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from .map_list import map_list
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from .maxout import Maxout
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from .mish import Mish
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from .multisoftmax import MultiSoftmax
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from .mxnetwrapper import MXNetWrapper
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from .noop import noop
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from .padded2list import padded2list
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from .parametricattention import ParametricAttention
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from .parametricattention_v2 import ParametricAttention_v2
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from .premap_ids import premap_ids
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from .pytorchwrapper import (
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PyTorchRNNWrapper,
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PyTorchWrapper,
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PyTorchWrapper_v2,
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PyTorchWrapper_v3,
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)
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from .ragged2list import ragged2list
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# Pooling
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from .reduce_first import reduce_first
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from .reduce_last import reduce_last
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from .reduce_max import reduce_max
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from .reduce_mean import reduce_mean
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from .reduce_sum import reduce_sum
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from .relu import Relu
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from .remap_ids import remap_ids, remap_ids_v2
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from .residual import residual
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from .resizable import resizable
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from .siamese import siamese
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from .sigmoid import Sigmoid
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from .sigmoid_activation import sigmoid_activation
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from .softmax import Softmax, Softmax_v2
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from .softmax_activation import softmax_activation
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from .sparselinear import SparseLinear, SparseLinear_v2
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from .strings2arrays import strings2arrays
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from .swish import Swish
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from .tensorflowwrapper import TensorFlowWrapper, keras_subclass
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from .torchscriptwrapper import TorchScriptWrapper_v1, pytorch_to_torchscript_wrapper
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from .tuplify import tuplify
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from .uniqued import uniqued
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from .with_array import with_array
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from .with_array2d import with_array2d
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from .with_cpu import with_cpu
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from .with_debug import with_debug
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from .with_flatten import with_flatten
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from .with_flatten_v2 import with_flatten_v2
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from .with_getitem import with_getitem
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from .with_list import with_list
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from .with_nvtx_range import with_nvtx_range
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from .with_padded import with_padded
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from .with_ragged import with_ragged
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from .with_reshape import with_reshape
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from .with_signpost_interval import with_signpost_interval
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# fmt: off
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__all__ = [
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"CauchySimilarity",
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"Linear",
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"Dropout",
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"Embed",
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"expand_window",
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"HashEmbed",
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"LayerNorm",
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"LSTM",
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"Maxout",
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"Mish",
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"MultiSoftmax",
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"ParametricAttention",
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"ParametricAttention_v2",
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"PyTorchLSTM",
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"PyTorchWrapper",
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"PyTorchWrapper_v2",
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"PyTorchWrapper_v3",
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"PyTorchRNNWrapper",
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"Relu",
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"sigmoid_activation",
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"Sigmoid",
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"softmax_activation",
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"Softmax",
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"Softmax_v2",
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"SparseLinear",
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"SparseLinear_v2",
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"TensorFlowWrapper",
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"TorchScriptWrapper_v1",
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"add",
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"bidirectional",
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"chain",
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"clone",
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"concatenate",
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"noop",
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"residual",
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"uniqued",
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"siamese",
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"reduce_first",
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"reduce_last",
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"reduce_max",
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"reduce_mean",
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"reduce_sum",
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"resizable",
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"list2array",
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"list2ragged",
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"list2padded",
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"ragged2list",
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"padded2list",
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"with_reshape",
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"with_getitem",
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"with_array",
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"with_array2d",
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"with_cpu",
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"with_list",
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"with_ragged",
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"with_padded",
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"with_flatten",
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"with_flatten_v2",
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"with_debug",
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"with_nvtx_range",
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"with_signpost_interval",
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"remap_ids",
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"remap_ids_v2",
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"premap_ids",
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"softmax_activation",
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"Logistic",
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"Sigmoid",
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"ClippedLinear",
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"ReluK",
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"HardTanh",
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"HardSigmoid",
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"Dish",
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"HardSwish",
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"HardSwishMobilenet",
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"Swish",
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"Gelu",
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"keras_subclass",
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"MXNetWrapper",
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"map_list",
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"strings2arrays",
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"array_getitem",
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"tuplify",
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"pytorch_to_torchscript_wrapper",
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]
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# fmt: on
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