all layer types implemented
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Luis Fernando Molina committed
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@@ -583,6 +583,54 @@
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{
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"type": "Advanced Activation Layers",
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"menuItems": [
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Elu Layer",
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"relatedUiObject": "Elu Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Leaky Relu Layer",
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"relatedUiObject": "Leaky Relu Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Prelu Layer",
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"relatedUiObject": "Prelu Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Relu Layer",
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"relatedUiObject": "Relu Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Softmax Layer",
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"relatedUiObject": "Softmax Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Thresholded Relu Layer",
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"relatedUiObject": "Thresholded Relu Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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@@ -599,6 +647,169 @@
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"compatibleTypes": "->Secuential Layer->"
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},
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"propertyNameAtParent": "layerType",
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"childrenNodesProperties": [
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{
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"name": "layer",
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"type": "node",
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"childType": "Elu Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Leaky Relu Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Prelu Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Relu Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Softmax Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Thresholded Relu Layer"
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}
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],
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"icon": "tensorflow"
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},
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{
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"type": "Elu Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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"confirmationLabel": "Confirm to Delete",
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"label": "Delete",
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"iconPathOn": "delete-entity",
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"iconPathOff": "delete-entity",
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"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Advanced Activation Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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{
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"type": "Leaky Relu Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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"confirmationLabel": "Confirm to Delete",
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"label": "Delete",
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"iconPathOn": "delete-entity",
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"iconPathOff": "delete-entity",
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"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Advanced Activation Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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{
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"type": "Prelu Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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"confirmationLabel": "Confirm to Delete",
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"label": "Delete",
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"iconPathOn": "delete-entity",
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"iconPathOff": "delete-entity",
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"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Advanced Activation Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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{
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"type": "Relu Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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"confirmationLabel": "Confirm to Delete",
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"label": "Delete",
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"iconPathOn": "delete-entity",
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"iconPathOff": "delete-entity",
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"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Advanced Activation Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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{
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"type": "Softmax Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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"confirmationLabel": "Confirm to Delete",
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"label": "Delete",
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"iconPathOn": "delete-entity",
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"iconPathOff": "delete-entity",
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"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Advanced Activation Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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{
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"type": "Thresholded Relu Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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"confirmationLabel": "Confirm to Delete",
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"label": "Delete",
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"iconPathOn": "delete-entity",
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"iconPathOff": "delete-entity",
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"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Advanced Activation Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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@@ -943,6 +1154,70 @@
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{
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"type": "Convolutional Layers",
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"menuItems": [
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Conv 1D Layer",
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"relatedUiObject": "Conv 1D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Conv 2D Layer",
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"relatedUiObject": "Conv 2D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Conv 2D Transpose Layer",
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"relatedUiObject": "Conv 2D Transpose Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Conv 3D Layer",
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"relatedUiObject": "Conv 3D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Cropping 2D Layer",
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"relatedUiObject": "Cropping 2D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Depthwise Conv 2D Layer",
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"relatedUiObject": "Depthwise Conv 2D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Separable Conv 2D Layer",
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"relatedUiObject": "Separable Conv 2D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Add UI Object",
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"disableIfPropertyIsDefined": true,
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"propertyToCheckFor": "layer",
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"label": "Add Up Sampling 2D Layer",
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"relatedUiObject": "Up Sampling 2D Layer",
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"actionFunction": "payload.executeAction"
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},
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
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@@ -959,6 +1234,223 @@
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"compatibleTypes": "->Secuential Layer->"
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},
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"propertyNameAtParent": "layerType",
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"childrenNodesProperties": [
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{
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"name": "layer",
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"type": "node",
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"childType": "Conv 1D Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Conv 2D Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Conv 2D Transpose Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Conv 3D Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Cropping 2D Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Depthwise Conv 2D Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Separable Conv 2D Layer"
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},
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{
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"name": "layer",
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"type": "node",
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"childType": "Up Sampling 2D Layer"
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}
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],
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"icon": "tensorflow"
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},
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{
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"type": "Conv 1D Layer",
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"menuItems": [
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{
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"action": "Delete UI Object",
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"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
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}
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],
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
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"compatibleTypes": "->Convolutional Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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},
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{
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"type": "Conv 2D Layer",
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"menuItems": [
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||||
{
|
||||
"action": "Delete UI Object",
|
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"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
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],
|
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"addLeftIcons": true,
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"level": 3,
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"attachingRules": {
|
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"compatibleTypes": "->Convolutional Layers->"
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},
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"propertyNameAtParent": "layer",
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"childrenNodesProperties": [],
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"icon": "tensorflow"
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||||
},
|
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{
|
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"type": "Conv 2D Transpose Layer",
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"menuItems": [
|
||||
{
|
||||
"action": "Delete UI Object",
|
||||
"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
|
||||
],
|
||||
"addLeftIcons": true,
|
||||
"level": 3,
|
||||
"attachingRules": {
|
||||
"compatibleTypes": "->Convolutional Layers->"
|
||||
},
|
||||
"propertyNameAtParent": "layer",
|
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"childrenNodesProperties": [],
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||||
"icon": "tensorflow"
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||||
},
|
||||
{
|
||||
"type": "Conv 3D Layer",
|
||||
"menuItems": [
|
||||
{
|
||||
"action": "Delete UI Object",
|
||||
"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
|
||||
],
|
||||
"addLeftIcons": true,
|
||||
"level": 3,
|
||||
"attachingRules": {
|
||||
"compatibleTypes": "->Convolutional Layers->"
|
||||
},
|
||||
"propertyNameAtParent": "layer",
|
||||
"childrenNodesProperties": [],
|
||||
"icon": "tensorflow"
|
||||
},
|
||||
{
|
||||
"type": "Cropping 2D Layer",
|
||||
"menuItems": [
|
||||
{
|
||||
"action": "Delete UI Object",
|
||||
"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
|
||||
],
|
||||
"addLeftIcons": true,
|
||||
"level": 3,
|
||||
"attachingRules": {
|
||||
"compatibleTypes": "->Convolutional Layers->"
|
||||
},
|
||||
"propertyNameAtParent": "layer",
|
||||
"childrenNodesProperties": [],
|
||||
"icon": "tensorflow"
|
||||
},
|
||||
{
|
||||
"type": "Depthwise Conv 2D Layer",
|
||||
"menuItems": [
|
||||
{
|
||||
"action": "Delete UI Object",
|
||||
"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
|
||||
],
|
||||
"addLeftIcons": true,
|
||||
"level": 3,
|
||||
"attachingRules": {
|
||||
"compatibleTypes": "->Convolutional Layers->"
|
||||
},
|
||||
"propertyNameAtParent": "layer",
|
||||
"childrenNodesProperties": [],
|
||||
"icon": "tensorflow"
|
||||
},
|
||||
{
|
||||
"type": "Separable Conv 2D Layer",
|
||||
"menuItems": [
|
||||
{
|
||||
"action": "Delete UI Object",
|
||||
"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
|
||||
],
|
||||
"addLeftIcons": true,
|
||||
"level": 3,
|
||||
"attachingRules": {
|
||||
"compatibleTypes": "->Convolutional Layers->"
|
||||
},
|
||||
"propertyNameAtParent": "layer",
|
||||
"childrenNodesProperties": [],
|
||||
"icon": "tensorflow"
|
||||
},
|
||||
{
|
||||
"type": "Up Sampling 2D Layer",
|
||||
"menuItems": [
|
||||
{
|
||||
"action": "Delete UI Object",
|
||||
"askConfirmation": true,
|
||||
"confirmationLabel": "Confirm to Delete",
|
||||
"label": "Delete",
|
||||
"iconPathOn": "delete-entity",
|
||||
"iconPathOff": "delete-entity",
|
||||
"actionFunction": "payload.executeAction"
|
||||
}
|
||||
],
|
||||
"addLeftIcons": true,
|
||||
"level": 3,
|
||||
"attachingRules": {
|
||||
"compatibleTypes": "->Convolutional Layers->"
|
||||
},
|
||||
"propertyNameAtParent": "layer",
|
||||
"childrenNodesProperties": [],
|
||||
"icon": "tensorflow"
|
||||
},
|
||||
|
||||
@@ -0,0 +1,14 @@
|
||||
{
|
||||
"type": "Activation Layer",
|
||||
"definition": {
|
||||
"text": "Applies an activation function to an output. ",
|
||||
"updated": 1613213636961
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "This layer applies element-wise activation function. Other layers, notably dense can also apply activation functions. Use this isolated activation function to extract the values before and after the activation.",
|
||||
"updated": 1613213641004
|
||||
}
|
||||
]
|
||||
}
|
||||
+1
-1
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"type": "Advanced Activation Layer",
|
||||
"type": "Advanced Activation Layers",
|
||||
"definition": {
|
||||
"text": "Use this type of layer when you want to apply an advanced activation function.",
|
||||
"updated": 1613210798694
|
||||
+1
-1
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"type": "Basic Layer",
|
||||
"type": "Basic Layers",
|
||||
"definition": {
|
||||
"text": "Basic Layers are the most common layers you can use.",
|
||||
"updated": 1613210641501
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Conv 1D Layer",
|
||||
"definition": {
|
||||
"text": "1D convolution layer (e.g., temporal convolution). This layer creates a convolution kernel that is convolved with the layer input over a single spatial (or temporal) dimension to produce a tensor of outputs.",
|
||||
"updated": 1613218586883
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Conv 2D Layer",
|
||||
"definition": {
|
||||
"text": "2D convolution layer (e.g. spatial convolution over images). This layer creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs.",
|
||||
"updated": 1613218624550
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,22 @@
|
||||
{
|
||||
"type": "Conv 2D Transpose Layer",
|
||||
"definition": {
|
||||
"text": "Transposed convolutional layer (sometimes called Deconvolution). The need for transposed convolutions generally arises from the desire to use a transformation going in the opposite direction of a normal convolution, i.e., from something that has the shape of the output of some convolution to something that has the shape of its input while maintaining a connectivity pattern that is compatible with said convolution.",
|
||||
"updated": 1613218678919
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "When using this layer as the first layer in a model, provide the configuration inputShape (Array of integers, does not include the sample axis), e.g., inputShape: [128, 128, 3] for 128x128 RGB pictures in dataFormat: 'channelsLast'.",
|
||||
"updated": 1613218856414
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: 4D tensor with shape: [batch, channels, rows, cols] if dataFormat is 'channelsFirst'. or 4D tensor with shape [batch, rows, cols, channels] if dataFormat is 'channelsLast."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: 4D tensor with shape: [batch, filters, newRows, newCols] if dataFormat is 'channelsFirst'. or 4D tensor with shape: [batch, newRows, newCols, filters] if dataFormat is 'channelsLast'."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Conv 3D Layer",
|
||||
"definition": {
|
||||
"text": "3D convolution layer (e.g. spatial convolution over volumes). This layer creates a convolution kernel that is convolved with the layer input to produce a tensor of outputs.",
|
||||
"updated": 1613218709328
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
+1
-1
@@ -1,5 +1,5 @@
|
||||
{
|
||||
"type": "Convolutional Layer",
|
||||
"type": "Convolutional Layers",
|
||||
"definition": {
|
||||
"text": "Use this type of layer to create a convolution kernel.",
|
||||
"updated": 1613210887837
|
||||
@@ -0,0 +1,34 @@
|
||||
{
|
||||
"type": "Cropping 2D Layer",
|
||||
"definition": {
|
||||
"text": "Cropping layer for 2D input (e.g., image). This layer can crop an input at the top, bottom, left and right side of an image tensor.",
|
||||
"updated": 1613218755900
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: 4D tensor with shape:",
|
||||
"updated": 1613218787273
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "If dataFormat is \"channelsLast\": [batch, rows, cols, channels]"
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "If data_format is \"channels_first\": [batch, channels, rows, cols]."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: 4D with shape:"
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "If dataFormat is \"channelsLast\": [batch, croppedRows, croppedCols, channels]"
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "If dataFormat is \"channelsFirst\": [batch, channels, croppedRows, croppedCols]."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Dense Layer",
|
||||
"definition": {
|
||||
"text": "Creates a dense (fully connected) layer.",
|
||||
"updated": 1613213671494
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Depthwise Conv 2D Layer",
|
||||
"definition": {
|
||||
"text": "Depthwise separable 2D convolution. Depthwise Separable convolutions consists in performing just the first step in a depthwise spatial convolution (which acts on each input channel separately). The depthMultplier argument controls how many output channels are generated per input channel in the depthwise step.",
|
||||
"updated": 1613218906419
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Dropout Layer",
|
||||
"definition": {
|
||||
"text": "Applies dropout to the input. Dropout consists in randomly setting a fraction rate of input units to 0 at each update during training time, which helps prevent overfitting.",
|
||||
"updated": 1613213791502
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,26 @@
|
||||
{
|
||||
"type": "Elu Layer",
|
||||
"definition": {
|
||||
"text": "Exponetial Linear Unit (ELU).",
|
||||
"updated": 1613216664718
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Title",
|
||||
"text": "It Follows",
|
||||
"updated": 1613216728404
|
||||
},
|
||||
{
|
||||
"style": "Javascript",
|
||||
"text": "f(x) = alpha * (exp(x) - 1.) for x < 0, f(x) = x for x >= 0."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary. Use the configuration inputShape when using this layer as the first layer in a model."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: Same shape as the input."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,26 @@
|
||||
{
|
||||
"type": "Embedding Layer",
|
||||
"definition": {
|
||||
"text": "Maps positive integers (indices) into dense vectors of fixed size. ",
|
||||
"updated": 1613213823616
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Title",
|
||||
"text": "Example",
|
||||
"updated": 1613213848804
|
||||
},
|
||||
{
|
||||
"style": "Javascript",
|
||||
"text": "[[4], [20]] -> [[0.25, 0.1], [0.6, -0.2]]"
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Input shape:* 2D tensor with shape: [batchSize, sequenceLength]."
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Output shape:* 3D tensor with shape: [batchSize, sequenceLength, outputDim]."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Flatten Layer",
|
||||
"definition": {
|
||||
"text": "Flattens the input. Does not affect the batch size. A Flatten layer flattens each batch in its inputs to 1D (making the output 2D).",
|
||||
"updated": 1613213956160
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,26 @@
|
||||
{
|
||||
"type": "Leaky Relu Layer",
|
||||
"definition": {
|
||||
"text": "Leaky version of a rectified linear unit.",
|
||||
"updated": 1613216814199
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "It allows a small gradient when the unit is not active: ",
|
||||
"updated": 1613216841876
|
||||
},
|
||||
{
|
||||
"style": "Javascript",
|
||||
"text": "f(x) = alpha * x for x < 0. f(x) = x for x >= 0."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary. Use the configuration inputShape when using this layer as the first layer in a model."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: Same shape as the input."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Permute Layer",
|
||||
"definition": {
|
||||
"text": "Permutes the dimensions of the input according to a given pattern. Useful for, e.g., connecting RNNs and convnets together.",
|
||||
"updated": 1613214015429
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,27 @@
|
||||
{
|
||||
"type": "Prelu Layer",
|
||||
"definition": {
|
||||
"text": "Parameterized version of a leaky rectified linear unit.",
|
||||
"updated": 1613216882813
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Title",
|
||||
"text": "It Follows ",
|
||||
"updated": 1613216907058
|
||||
},
|
||||
{
|
||||
"style": "Javascript",
|
||||
"text": "f(x) = alpha * x for x < 0. f(x) = x for x >= 0. wherein alpha is a trainable weight",
|
||||
"updated": 1613216938490
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary. Use the configuration inputShape when using this layer as the first layer in a model."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: Same shape as the input."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"type": "Relu Layer",
|
||||
"definition": {
|
||||
"text": "Rectified Linear Unit activation function.",
|
||||
"updated": 1613216977133
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary. Use the config field inputShape (Array of integers, does not include the sample axis) when using this layer as the first layer in a model.",
|
||||
"updated": 1613216997299
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: Same shape as the input."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,13 @@
|
||||
{
|
||||
"type": "Repeat Vector Layer",
|
||||
"definition": {
|
||||
"text": "Repeats the input n times in a new dimension.",
|
||||
"updated": 1613214045190
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Left click and select the pencil button to enter edit mode."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"type": "Reshape Layer",
|
||||
"definition": {
|
||||
"text": "Reshapes an input to a certain shape.",
|
||||
"updated": 1613214077391
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary, although all dimensions in the input shape must be fixed. Use the configuration inputShape when using this layer as the first layer in a model.",
|
||||
"updated": 1613214162552
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: [batchSize, targetShape[0], targetShape[1], ..., targetShape[targetShape.length - 1]]."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,22 @@
|
||||
{
|
||||
"type": "Separable Conv 2D Layer",
|
||||
"definition": {
|
||||
"text": "Depthwise separable 2D convolution. Separable convolution consists of first performing a depthwise spatial convolution (which acts on each input channel separately) followed by a pointwise convolution which mixes together the resulting output channels. The depthMultiplier argument controls how many output channels are generated per input channel in the depthwise step.",
|
||||
"updated": 1613218940003
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "Intuitively, separable convolutions can be understood as a way to factorize a convolution kernel into two smaller kernels, or as an extreme version of an Inception block.",
|
||||
"updated": 1613218949720
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: 4D tensor with shape: [batch, channels, rows, cols] if data_format='channelsFirst' or 4D tensor with shape: [batch, rows, cols, channels] if data_format='channelsLast'."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: 4D tensor with shape: [batch, filters, newRows, newCols] if data_format='channelsFirst' or 4D tensor with shape: [batch, newRows, newCols, filters] if data_format='channelsLast'. rows and cols values might have changed due to padding."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"type": "Softmax Layer",
|
||||
"definition": {
|
||||
"text": "Softmax activation layer. A function that provides probabilities for each possible class in a multi-class classification model. The probabilities add up to exactly 1.0. For example, softmax might determine that the probability of a particular image being a dog at 0.9, a cat at 0.08, and a horse at 0.02.",
|
||||
"updated": 1613217104730
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary. Use the configuration inputShape when using this layer as the first layer in a model.",
|
||||
"updated": 1613217039070
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: Same shape as the input."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"type": "Spatial Dropout 1D Layer",
|
||||
"definition": {
|
||||
"text": "Spatial 1D version of Dropout.",
|
||||
"updated": 1613214223035
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "This Layer type performs the same function as the Dropout layer, but it drops entire 1D feature maps instead of individual elements. For example, if an input example consists of 3 timesteps and the feature map for each timestep has a size of 4, a spatialDropout1d layer may zero out the feature maps of the 1st timesteps and 2nd timesteps completely while sparing all feature elements of the 3rd timestep.",
|
||||
"updated": 1613214250740
|
||||
},
|
||||
{
|
||||
"style": "Text",
|
||||
"text": "If adjacent frames (timesteps) are strongly correlated (as is normally the case in early convolution layers), regular dropout will not regularize the activation and will otherwise just result in merely an effective learning rate decrease. In this case, spatialDropout1d will help promote independence among feature maps and should be used instead."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,26 @@
|
||||
{
|
||||
"type": "Thresholded Relu Layer",
|
||||
"definition": {
|
||||
"text": "Thresholded Rectified Linear Unit.",
|
||||
"updated": 1613217166999
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "Title",
|
||||
"text": "It Follows ",
|
||||
"updated": 1613217193348
|
||||
},
|
||||
{
|
||||
"style": "Javascript",
|
||||
"text": "f(x) = x for x > theta, f(x) = 0 otherwise."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: Arbitrary. Use the configuration inputShape when using this layer as the first layer in a model."
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: Same shape as the input."
|
||||
}
|
||||
]
|
||||
}
|
||||
@@ -0,0 +1,18 @@
|
||||
{
|
||||
"type": "Up Sampling 2D Layer",
|
||||
"definition": {
|
||||
"text": "Upsampling layer for 2D inputs. Repeats the rows and columns of the data by size[0] and size[1] respectively.",
|
||||
"updated": 1613219000480
|
||||
},
|
||||
"paragraphs": [
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Input shape: 4D tensor with shape: - If dataFormat is \"channelsLast\": [batch, rows, cols, channels] - If dataFormat is \"channelsFirst\": [batch, channels, rows, cols]",
|
||||
"updated": 1613219012908
|
||||
},
|
||||
{
|
||||
"style": "List",
|
||||
"text": "Output shape: 4D tensor with shape: - If dataFormat is \"channelsLast\": [batch, upsampledRows, upsampledCols, channels] - If dataFormat is \"channelsFirst\": [batch, channels, upsampledRows, upsampledCols]"
|
||||
}
|
||||
]
|
||||
}
|
||||
Reference in new issue
Block a user