nd4j/samediff-import/samediff-import-onnx/src/main/kotlin/org/nd4j/samediff/frameworkimport/onnx/definitions/implementations/SequenceAt.kt
/*
* ******************************************************************************
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* *
* * This program and the accompanying materials are made available under the
* * terms of the Apache License, Version 2.0 which is available at
* * https://www.apache.org/licenses/LICENSE-2.0.
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* * See the NOTICE file distributed with this work for additional
* * information regarding copyright ownership.
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* * SPDX-License-Identifier: Apache-2.0
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package org.nd4j.samediff.frameworkimport.onnx.definitions.implementations
import org.nd4j.autodiff.samediff.SDVariable
import org.nd4j.autodiff.samediff.SameDiff
import org.nd4j.autodiff.samediff.internal.SameDiffOp
import org.nd4j.linalg.api.ops.impl.shape.tensorops.TensorArray
import org.nd4j.samediff.frameworkimport.ImportGraph
import org.nd4j.samediff.frameworkimport.hooks.PreImportHook
import org.nd4j.samediff.frameworkimport.hooks.annotations.PreHookRule
import org.nd4j.samediff.frameworkimport.registry.OpMappingRegistry
import org.nd4j.shade.protobuf.GeneratedMessageV3
import org.nd4j.shade.protobuf.ProtocolMessageEnum
/**
* A port of sequence_at.py from onnx tensorflow for samediff:
* https://github.com/onnx/onnx-tensorflow/blob/master/onnx_tf/handlers/backend/sequence_at.py
*
* @author Adam Gibson
*/
@PreHookRule(nodeNames = [],opNames = ["SequenceAt"],frameworkName = "onnx")
class SequenceAt : PreImportHook {
override fun doImport(
sd: SameDiff,
attributes: Map<String, Any>,
outputNames: List<String>,
op: SameDiffOp,
mappingRegistry: OpMappingRegistry<GeneratedMessageV3, GeneratedMessageV3, GeneratedMessageV3, GeneratedMessageV3, ProtocolMessageEnum, GeneratedMessageV3, GeneratedMessageV3>,
importGraph: ImportGraph<GeneratedMessageV3, GeneratedMessageV3, GeneratedMessageV3, GeneratedMessageV3, GeneratedMessageV3, GeneratedMessageV3, ProtocolMessageEnum>,
dynamicVariables: Map<String, GeneratedMessageV3>
): Map<String, List<SDVariable>> {
val input = sd.getVariable(op.inputsToOp[0])
val position = if(op.inputsToOp.size < 2) sd.constant(-1) else {
sd.getVariable(op.inputsToOp[1])
}
//access the associated list we are writing to
val outputVar = TensorArray.itemAtIndex(sd,arrayOf(input,position),outputNames[0])
val op = sd.ops[outputVar.name()]
return mapOf(outputVar.name() to listOf(outputVar))
}
}