From bc876878b2e2a9c5a84493b9669fbb228d20222d Mon Sep 17 00:00:00 2001
From: artemnih <23387542+artemnih@users.noreply.github.com>
Date: Tue, 17 Sep 2024 14:48:45 -0400
Subject: [PATCH] fix: SMP segmentation conditions markup

---
 .../polus-smp-training-plugin/ict.yaml        | 30 +++++++++----------
 .../polus-smp-training-plugin/plugin.json     | 30 +++++++++----------
 2 files changed, 30 insertions(+), 30 deletions(-)

diff --git a/segmentation/polus-smp-training-plugin/ict.yaml b/segmentation/polus-smp-training-plugin/ict.yaml
index 8fcd6fa3f..ca8eef83c 100644
--- a/segmentation/polus-smp-training-plugin/ict.yaml
+++ b/segmentation/polus-smp-training-plugin/ict.yaml
@@ -166,12 +166,12 @@ ui:
   key: inputs.inferenceMode
   title: inferenceMode
   type: select
-- condition: inputs.inferenceMode==active
+- condition: inputs.inferenceMode=='active'
   description: Collection containing images on which to run inference.
   key: inputs.imagesInferenceDir
   title: imagesInferenceDir
   type: path
-- condition: inputs.inferenceMode==active
+- condition: inputs.inferenceMode=='active'
   description: Filename pattern for images on which to run inference.
   key: inputs.inferencePattern
   title: inferencePattern
@@ -347,7 +347,7 @@ ui:
   key: inputs.encoderWeights
   title: encoderWeights
   type: select
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Name of optimization algorithm to use for training the model. Required
     if starting fresh.
   fields:
@@ -365,40 +365,40 @@ ui:
   key: inputs.optimizerName
   title: optimizerName
   type: select
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Size of each batch for training. If left unspecified, we use the maximum
     possible based on memory constraints.
   key: inputs.batchSize
   title: batchSize
   type: number
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Collection containing images to use for training.
   key: inputs.imagesTrainDir
   title: imagesTrainDir
   type: path
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Collection containing labels, i.e. the ground-truth, for the training
     images.
   key: inputs.labelsTrainDir
   title: labelsTrainDir
   type: path
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Filename pattern for training images and labels.
   key: inputs.trainPattern
   title: trainPattern
   type: text
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Collection containing images to use for validation.
   key: inputs.imagesValidDir
   title: imagesValidDir
   type: path
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Collection containing labels, i.e. the ground-truth, for the validation
     images.
   key: inputs.labelsValidDir
   title: labelsValidDir
   type: path
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Filename pattern for validation images and labels.
   key: inputs.validPattern
   title: validPattern
@@ -407,12 +407,12 @@ ui:
   key: inputs.device
   title: device
   type: text
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: How often to save model checkpoints
   key: inputs.checkpointFrequency
   title: checkpointFrequency
   type: number
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   description: Name of loss function to use.
   fields:
   - JaccardLoss
@@ -426,19 +426,19 @@ ui:
   key: inputs.lossName
   title: lossName
   type: select
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   default: 100
   description: Maximum number of epochs for which to continue training the model.
   key: inputs.maxEpochs
   title: maxEpochs
   type: number
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   default: 10
   description: Maximum number of epochs to wait for model to improve.
   key: inputs.patience
   title: patience
   type: number
-- condition: inputs.inferenceMode==inactive
+- condition: inputs.inferenceMode=='inactive'
   default: 0.0001
   description: Minimum improvement in loss to reset patience.
   key: inputs.minDelta
diff --git a/segmentation/polus-smp-training-plugin/plugin.json b/segmentation/polus-smp-training-plugin/plugin.json
index 611246b8f..29daf7b5b 100644
--- a/segmentation/polus-smp-training-plugin/plugin.json
+++ b/segmentation/polus-smp-training-plugin/plugin.json
@@ -370,14 +370,14 @@
             "key": "inputs.imagesInferenceDir",
             "title": "imagesInferenceDir",
             "description": "Collection containing images on which to run inference.",
-            "condition": "model.inputs.inferenceMode==active"
+            "condition": "model.inputs.inferenceMode=='active'"
         },
         {
             "key": "inputs.inferencePattern",
             "title": "inferencePattern",
             "description": "Filename pattern for images on which to run inference.",
             "default": ".*",
-            "condition": "model.inputs.inferenceMode==active"
+            "condition": "model.inputs.inferenceMode=='active'"
         },
         {
             "key": "inputs.pretrainedModel",
@@ -413,51 +413,51 @@
             "title": "optimizerName",
             "description": "Name of optimization algorithm to use for training the model. Required if starting fresh.",
             "default": "Adam",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.batchSize",
             "title": "batchSize",
             "description": "Size of each batch for training. If left unspecified, we use the maximum possible based on memory constraints.",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.imagesTrainDir",
             "title": "imagesTrainDir",
             "description": "Collection containing images to use for training.",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.labelsTrainDir",
             "title": "labelsTrainDir",
             "description": "Collection containing labels, i.e. the ground-truth, for the training images.",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.trainPattern",
             "title": "trainPattern",
             "description": "Filename pattern for training images and labels.",
             "default": ".*",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.imagesValidDir",
             "title": "imagesValidDir",
             "description": "Collection containing images to use for validation.",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.labelsValidDir",
             "title": "labelsValidDir",
             "description": "Collection containing labels, i.e. the ground-truth, for the validation images.",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.validPattern",
             "title": "validPattern",
             "description": "Filename pattern for validation images and labels.",
             "default": ".*",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.device",
@@ -469,35 +469,35 @@
             "key": "inputs.checkpointFrequency",
             "title": "checkpointFrequency",
             "description": "How often to save model checkpoints",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.lossName",
             "title": "lossName",
             "description": "Name of loss function to use.",
             "default": "JaccardLoss",
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.maxEpochs",
             "title": "maxEpochs",
             "description": "Maximum number of epochs for which to continue training the model.",
             "default": 100,
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.patience",
             "title": "patience",
             "description": "Maximum number of epochs to wait for model to improve.",
             "default": 10,
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         },
         {
             "key": "inputs.minDelta",
             "title": "minDelta",
             "description": "Minimum improvement in loss to reset patience.",
             "default": 0.0001,
-            "condition": "model.inputs.inferenceMode==inactive"
+            "condition": "model.inputs.inferenceMode=='inactive'"
         }
     ],
     "validators": [