import { EmbeddingLayer } from "https://deno.land/x/netsaur@0.4.2/web.ts";
Creates an Embedding layer. Embedding layers convert numerical data into dense vectors. They are usually used for text processing.
Parameters
config: EmbeddingLayerConfig
Module
x/netsaur/web.ts>EmbeddingLayer
Powerful Powerful Machine Learning library with GPU, CPU and WASM backends
Latest
benchcratesexamplespackagesSequentialTensorAdamOptimizerConfigBackendDataSetDecaySchedulerConfigNetworkConfigNeuralNetworkOneCycleSchedulerConfigRMSPropOptimizerConfigTensorLikeArray1DArray2DArray3DArray4DArray5DArray6DArrayMapOptimizerPaddingSchedulerShapeShape1DShape2DShape3DShape4DShape5DShape6DAUTOCPUGPUWASMAdamOptimizerAveragePool2DLayerBatchNorm1DLayerBatchNorm2DLayerConv1DLayerConv2DLayerConvTranspose1DLayerConvTranspose2DLayerDenseLayerDropout1DLayerDropout2DLayerEluLayerEmbeddingLayerExponentialDecayFlattenLayerGeluLayerLeakyReluLayerLinearDecayLSTMLayerMaxPool2DLayerNadamOptimizerNoSchedulerOneCycleOPTIONPool2DLayerRelu6LayerReluLayerRMSPropOptimizerSeluLayersetupBackendSGDOptimizerSigmoidLayerSoftmaxLayerTanhLayertensortensor1Dtensor2Dtensor3Dtensor4Dtensor5Dtensor6DActivationBackendTypeCostInitLayerTypeOptimizerTypeRankSchedulerTypeSequentialTensorAdamOptimizerConfigBackendDataSetNetworkConfigNeuralNetworkRMSPropOptimizerConfigTensorLikeArray1DArray2DArray3DArray4DArray5DArray6DArrayMapOptimizerPaddingShapeShape1DShape2DShape3DShape4DShape5DShape6DWASMAdamOptimizerAveragePool2DLayerBatchNorm1DLayerBatchNorm2DLayerConv1DLayerConv2DLayerConvTranspose1DLayerConvTranspose2DLayerDenseLayerDropout1DLayerDropout2DLayerEluLayerEmbeddingLayerFlattenLayerGeluLayerLeakyReluLayerLSTMLayerMaxPool2DLayerNadamOptimizerPool2DLayerRelu6LayerReluLayerRMSPropOptimizerSeluLayersetupBackendSGDOptimizerSigmoidLayerSoftmaxLayerTanhLayertensortensor1Dtensor2Dtensor3Dtensor4Dtensor5Dtensor6DActivationBackendTypeCostInitLayerTypeOptimizerTypeRankSchedulerType
mod.ts (default module)
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web.ts
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