From 3c22c20ca661b76eb8fbfed65221839b53f02c77 Mon Sep 17 00:00:00 2001
From: Chizkiyahu <chizkiyahur@altair-semi.com>
Date: Sat, 7 Oct 2023 21:21:36 +0300
Subject: [PATCH] fix layer shring inputs and outputs

---
 source/keras.js | 30 +++++++++++++++++++++++++-----
 1 file changed, 25 insertions(+), 5 deletions(-)

diff --git a/source/keras.js b/source/keras.js
index b864520d4e5..f03afda5056 100644
--- a/source/keras.js
+++ b/source/keras.js
@@ -755,14 +755,17 @@ keras.Node = class {
 
         const innerType = this.inner ? this.inner.type : null;
         const innerMetadata = innerType ? metadata.type(innerType) : null;
+
+        // handle layer sharing
         let inputIndex = 0;
         let inputTypes = [];
+        const outputTypes = [];
         if (this._type && this._type.inputs) {
             for (let i = 0; i < this._type.inputs.length; i++) {
-                if (i === 0 && layer.inbound_nodes) {
+                if (layer.inbound_nodes && layer.inbound_nodes.length > 1 && layer.inbound_nodes[0].length > i) {
                     for (let j = 0; j < layer.inbound_nodes.length; j++) {
                         const inputType = JSON.parse(JSON.stringify(this._type.inputs[i]));
-                        inputType.name = inputType.name + " edge " + j;
+                        inputType.name =  j + ": "+ inputType.name;
                         inputTypes.push(inputType);
                     }
                 } else {
@@ -770,12 +773,28 @@ keras.Node = class {
                 }
             }
         }
+        if (this._type && this._type.outputs) {
+            for (let i = 0; i < this._type.outputs.length; i++) {
+                if (layer.inbound_nodes && layer.inbound_nodes.length > 1 && layer.inbound_nodes[0].length > i) {
+                    for (let j = 0; j < layer.inbound_nodes.length; j++) {
+                        const outputType = JSON.parse(JSON.stringify(this._type.outputs[i]));
+                        outputType.name = j + ": "+ outputType.name;
+                        outputTypes.push(outputType);
+                    }
+                } else {
+                    outputTypes.push(this._type.inputs[i]);
+                }
+            }
+        }
+        const inbound_nodes_size = layer.inbound_nodes ? layer.inbound_nodes.length : 1;
+        outputs = Array(inbound_nodes_size).fill(outputs).flat();
+
         while (inputs.length > 0) {
             let list = false;
             let name = null;
             let visible = true;
             if (!innerMetadata || inputIndex == 0) {
-                if (this._type && inputTypes && inputIndex < inputTypes.length) {
+                if (inputTypes && inputIndex < inputTypes.length) {
                     const input = inputTypes[inputIndex];
                     name = input.name;
                     if (type === 'BatchNormalization' && name === 'gamma' && config.scale === false) {
@@ -813,7 +832,8 @@ keras.Node = class {
                         break;
                 }
             }
-            const input = !list ? [ inputs.shift() ] : inputs.splice(0, inputs.length);
+            const size = !layer.inbound_nodes  ? 1 : layer.inbound_nodes.length;
+            const input = !list ? [ inputs.shift() ] : inputs.splice(0, size);
             const inputArguments = input.map((input) => {
                 if (input.name) {
                     return value(input.name, null, initializers[input.name]);
@@ -842,7 +862,7 @@ keras.Node = class {
 
         for (let i = 0; i < outputs.length; i++) {
             const output = outputs[i];
-            const outputName = (this._type && this._type.outputs && i < this._type.outputs.length && this._type.outputs[i] && this._type.outputs[i].name) ? this._type.outputs[i].name : i.toString();
+            const outputName = (outputTypes[i] && outputTypes[i].name) ? outputTypes[i].name : i.toString();
             const args = output.length === 0 ? [] : [ value(output) ];
             const argument = new keras.Argument(outputName, true, args);
             this._outputs.push(argument);