Merge pull request #908 from Vafilor/fix/release.command.repo

fix: updated repo in generate release notes as the name has changed

CONTRIBUTING.md

@@ -4,6 +4,8 @@
 
 Note: Up migrations are automatically executed when the application is run.
 
+#### Linux / Mac
+
 ```bash
 docker run --rm --mount type=bind,source="${PWD}",target=/root onepanel/helper:v1.0.0 goose -dir db/sql create <name> sql  # Create migration in db/sql folder
 docker run --rm --mount type=bind,source="${PWD}",target=/root onepanel/helper:v1.0.0 goose -dir db postgres "${DB_DATASOURCE_NAME}" up # Migrate the DB to the most recent version available
@@ -11,6 +13,15 @@ docker run --rm --mount type=bind,source="${PWD}",target=/root onepanel/helper:v
 docker run --rm --mount type=bind,source="${PWD}",target=/root onepanel/helper:v1.0.0 goose help  # See all available commands
 ```
 
+#### Windows
+
+```bash
+docker run --rm --mount type=bind,source="%CD%",target=/root onepanel/helper:v1.0.0 goose -dir db/sql create wow sql  # Create migration in db/sql folder
+docker run --rm --mount type=bind,source="%CD%",target=/root onepanel/helper:v1.0.0 goose -dir db postgres "${DB_DATASOURCE_NAME}" up # Migrate the DB to the most recent version available
+docker run --rm --mount type=bind,source="%CD%",target=/root onepanel/helper:v1.0.0 goose -dir db postgres "${DB_DATASOURCE_NAME}" down # Roll back the version by 1
+docker run --rm --mount type=bind,source="%CD%",target=/root onepanel/helper:v1.0.0 goose help  # See all available commands
+```
+
 ### Local 
 
 Install `goose`:
@@ -64,86 +75,27 @@ Make sure that your `$GOBIN` is in your `$PATH`.
 
 ### Docker
 
-Generate Go and Swagger APIs:
+Generate Go and Swagger APIs
+
+#### Linux / Mac
+
 ```bash
-docker run --rm --mount type=bind,source="${PWD}",target=/root onepanel-helper:v1.0.0 make api version=1.0.0
+docker run --rm --mount type=bind,source="${PWD}",target=/root onepanel/helper:v1.0.0 make api-internal version=1.0.0
+```
+
+#### Windows
+
+```bash
+docker run --rm --mount type=bind,source="%CD%",target=/root onepanel/helper:v1.0.0 make api-internal version=1.0.0
 ```
 
 ### Local Installation
 
 Generate Go and Swagger APIs:
 ```bash
-make api version=1.0.0
+make api-internal version=1.0.0
 ```
 
-## Minikube Debugging and Development
-
-It is possible to access host resources with minikube.
-- This means you can run core and core-ui on your machine, and have minikube
-execute API calls to your machine.
-
-NOTE:
-- Do not use host access with Minikube and VMWare. This has been shown not to work
-in our testing.
-If you have a work-around, feel free to let us know.
-
-To make this work, some setup is needed.
-- Minikube started with driver=virtualbox
-
-Get your Minikube ssh IP
-https://minikube.sigs.k8s.io/docs/handbook/host-access/
-
-```shell script
-minikube ssh "route -n | grep ^0.0.0.0 | awk '{ print \$2 }'"
-```
-Example output:
-```shell script
-10.0.2.2
-```
-
-When running core api, add these ENV variables.
-```shell script
-ONEPANEL_CORE_SERVICE_HOST=10.0.2.2 # IP you just got
-ONEPANEL_CORE_SERVICE_PORT=8888 # HTTP Port set in main.go
-```
-
-DB Access
-- You will need to change the Postgres service from ClusterIP to NodePort
-
-Run
-```shell script
-minikube service list
-```
-
-Look at Postgres, you'll see something like this:
-```shell script
-$ minikube service list
-|----------------------|----------------------------------------|--------------------|--------------------------------|
-|      NAMESPACE       |                  NAME                  |    TARGET PORT     |              URL               |
-|----------------------|----------------------------------------|--------------------|--------------------------------|
-| application-system   | application-controller-manager-service | No node port       |
-| default              | kubernetes                             | No node port       |
-| kube-system          | kube-dns                               | No node port       |
-| kubernetes-dashboard | dashboard-metrics-scraper              | No node port       |
-| kubernetes-dashboard | kubernetes-dashboard                   | No node port       |
-| onepanel             | onepanel-core                          | http/8888          | http://192.168.99.101:32000    |
-|                      |                                        | grpc/8887          | http://192.168.99.101:32001    |
-| onepanel             | onepanel-core-ui                       | http/80            | http://192.168.99.101:32002    |
-| onepanel             | postgres                               |               5432 | http://192.168.99.101:31975    |
-|----------------------|----------------------------------------|--------------------|--------------------------------|
-```
-Grab `http://192.168.99.101:31975`
-Use this in main.go for the following lines:
-
-```shell script
-	databaseDataSourceName := fmt.Sprintf("port=31975 host=%v user=%v password=%v dbname=%v sslmode=disable",
-		"192.168.99.101", config["databaseUsername"], config["databasePassword"], config["databaseName"])
-```
-This should connect your developing core to the minikube db.
-
-After this, build main.go and run the executable.
-- Or use your IDE equivalent
-
 ## Code Structure & Organization
 
 ### `utils` dir

README.md

@@ -1,6 +1,6 @@
 <img width="200px" src="img/logo.png">
 
-![build](https://img.shields.io/github/workflow/status/onepanelio/core/Publish%20dev%20docker%20image/master?color=01579b)
+![build](https://img.shields.io/github/workflow/status/onepanelio/onepanel/Publish%20dev%20docker%20image/master?color=01579b)
 ![code](https://img.shields.io/codacy/grade/d060fc4d1ac64b85b78f85c691ead86a?color=01579b)
 [![release](https://img.shields.io/github/v/release/onepanelio/core?color=01579b)](https://github.com/onepanelio/core/releases)
 [![sdk](https://img.shields.io/pypi/v/onepanel-sdk?color=01579b&label=sdk)](https://pypi.org/project/onepanel-sdk/)

cmd/gen-release-md/gen-release-md.go

@@ -52,7 +52,7 @@ See https://docs.onepanel.ai
 
 ` + "```" + `
 # Download the binary
-curl -sLO https://github.com/onepanelio/core/releases/download/v%s/opctl-linux-amd64
+curl -sLO https://github.com/onepanelio/onepanel/releases/download/v%s/opctl-linux-amd64
 
 # Make binary executable
 chmod +x opctl-linux-amd64
@@ -68,7 +68,7 @@ opctl version
 
 ` + "```" + `
 # Download the binary
-curl -sLO https://github.com/onepanelio/core/releases/download/v%s/opctl-macos-amd64
+curl -sLO https://github.com/onepanelio/onepanel/releases/download/v%s/opctl-macos-amd64
 
 # Make binary executable
 chmod +x opctl-macos-amd64
@@ -82,7 +82,7 @@ opctl version
 
 ## Windows
 
-Download the [attached executable](https://github.com/onepanelio/core/releases/download/v%s/opctl-windows-amd64.exe), rename it to "opctl" and move it to a folder that is in your PATH environment variable.
+Download the [attached executable](https://github.com/onepanelio/onepanel/releases/download/v%s/opctl-windows-amd64.exe), rename it to "opctl" and move it to a folder that is in your PATH environment variable.
 `
 
 var repositories = []string{

db/go/20210323175655_update_templates_for_pns.go

@@ -0,0 +1,58 @@
+package migration
+
+import (
+	"database/sql"
+	"github.com/pressly/goose"
+	"path/filepath"
+)
+
+func initialize20210323175655() {
+	if _, ok := initializedMigrations[20210323175655]; !ok {
+		goose.AddMigration(Up20210323175655, Down20210323175655)
+		initializedMigrations[20210323175655] = true
+	}
+}
+
+// Up20210323175655 update workflows to support new PNS mode
+func Up20210323175655(tx *sql.Tx) error {
+	// This code is executed when the migration is applied.
+	if err := updateWorkflowTemplateManifest(
+		filepath.Join("workflows", "pytorch-mnist-training", "20210323175655.yaml"),
+		pytorchWorkflowTemplateName,
+		map[string]string{
+			"created-by": "system",
+			"framework":  "pytorch",
+		}); err != nil {
+		return err
+	}
+
+	return updateWorkflowTemplateManifest(
+		filepath.Join("workflows", "tensorflow-mnist-training", "20210323175655.yaml"),
+		tensorflowWorkflowTemplateName,
+		map[string]string{
+			"created-by": "system",
+			"framework":  "tensorflow",
+		})
+}
+
+// Down20210323175655 reverts updating workflows to support PNS
+func Down20210323175655(tx *sql.Tx) error {
+	// This code is executed when the migration is rolled back.
+	if err := updateWorkflowTemplateManifest(
+		filepath.Join("workflows", "tensorflow-mnist-training", "20210118175809.yaml"),
+		tensorflowWorkflowTemplateName,
+		map[string]string{
+			"created-by": "system",
+			"framework":  "tensorflow",
+		}); err != nil {
+		return err
+	}
+
+	return updateWorkflowTemplateManifest(
+		filepath.Join("workflows", "pytorch-mnist-training", "20210118175809.yaml"),
+		pytorchWorkflowTemplateName,
+		map[string]string{
+			"created-by": "system",
+			"framework":  "pytorch",
+		})
+}

db/go/20210329171739_update_workspaces.go

@@ -0,0 +1,55 @@
+package migration
+
+import (
+	"database/sql"
+	"github.com/pressly/goose"
+	"path/filepath"
+)
+
+func initialize20210329171739() {
+	if _, ok := initializedMigrations[20210329171739]; !ok {
+		goose.AddMigration(Up20210329171739, Down20210329171739)
+		initializedMigrations[20210329171739] = true
+	}
+}
+
+// Up20210329171739 updates workspaces to use new images
+func Up20210329171739(tx *sql.Tx) error {
+	// This code is executed when the migration is applied.
+
+	if err := updateWorkspaceTemplateManifest(
+		filepath.Join("workspaces", "cvat", "20210323175655.yaml"),
+		cvatTemplateName); err != nil {
+		return err
+	}
+
+	if err := updateWorkspaceTemplateManifest(
+		filepath.Join("workspaces", "jupyterlab", "20210323175655.yaml"),
+		jupyterLabTemplateName); err != nil {
+		return err
+	}
+
+	return updateWorkspaceTemplateManifest(
+		filepath.Join("workspaces", "vscode", "20210323175655.yaml"),
+		vscodeWorkspaceTemplateName)
+}
+
+// Down20210329171739 rolls back image updates for workspaces
+func Down20210329171739(tx *sql.Tx) error {
+	// This code is executed when the migration is rolled back.
+	if err := updateWorkspaceTemplateManifest(
+		filepath.Join("workspaces", "cvat", "20210224180017.yaml"),
+		cvatTemplateName); err != nil {
+		return err
+	}
+
+	if err := updateWorkspaceTemplateManifest(
+		filepath.Join("workspaces", "jupyterlab", "20210224180017.yaml"),
+		jupyterLabTemplateName); err != nil {
+		return err
+	}
+
+	return updateWorkspaceTemplateManifest(
+		filepath.Join("workspaces", "vscode", "20210224180017.yaml"),
+		vscodeWorkspaceTemplateName)
+}

db/go/20210329194731_conditional_remove_hyperparam_tuning.go

@@ -0,0 +1,109 @@
+package migration
+
+import (
+	"database/sql"
+	uid2 "github.com/onepanelio/core/pkg/util/uid"
+	"github.com/pressly/goose"
+	"path/filepath"
+)
+
+func initialize20210329194731() {
+	if _, ok := initializedMigrations[20210329194731]; !ok {
+		goose.AddMigration(Up20210329194731, Down20210329194731)
+		initializedMigrations[20210329194731] = true
+	}
+}
+
+// Up20210329194731 removes the hyperparameter-tuning workflow if there are no executions
+func Up20210329194731(tx *sql.Tx) error {
+	// This code is executed when the migration is applied.
+	client, err := getClient()
+	if err != nil {
+		return err
+	}
+	defer client.DB.Close()
+
+	namespaces, err := client.ListOnepanelEnabledNamespaces()
+	if err != nil {
+		return err
+	}
+
+	uid, err := uid2.GenerateUID(hyperparameterTuningTemplateName, 30)
+	if err != nil {
+		return err
+	}
+
+	for _, namespace := range namespaces {
+		workflowTemplate, err := client.GetWorkflowTemplateRaw(namespace.Name, uid)
+		if err != nil {
+			return err
+		}
+
+		if workflowTemplate == nil {
+			continue
+		}
+
+		workflowExecutionsCount, err := client.CountWorkflowExecutionsForWorkflowTemplate(workflowTemplate.ID)
+		if err != nil {
+			return err
+		}
+
+		cronWorkflowsCount, err := client.CountCronWorkflows(namespace.Name, uid)
+		if err != nil {
+			return err
+		}
+
+		// Archive the template if we have no resources associated with it
+		if workflowExecutionsCount == 0 && cronWorkflowsCount == 0 {
+			if _, err := client.ArchiveWorkflowTemplate(namespace.Name, uid); err != nil {
+				return err
+			}
+		}
+	}
+
+	return nil
+}
+
+// Down20210329194731 returns the hyperparameter-tuning workflow if it was deleted
+func Down20210329194731(tx *sql.Tx) error {
+	// This code is executed when the migration is rolled back.
+	client, err := getClient()
+	if err != nil {
+		return err
+	}
+	defer client.DB.Close()
+
+	namespaces, err := client.ListOnepanelEnabledNamespaces()
+	if err != nil {
+		return err
+	}
+
+	uid, err := uid2.GenerateUID("hyperparameter-tuning", 30)
+	if err != nil {
+		return err
+	}
+
+	for _, namespace := range namespaces {
+		workflowTemplate, err := client.GetWorkflowTemplateRaw(namespace.Name, uid)
+		if err != nil {
+			return err
+		}
+
+		if workflowTemplate == nil {
+			err := createWorkflowTemplate(
+				filepath.Join("workflows", "hyperparameter-tuning", "20210118175809.yaml"),
+				hyperparameterTuningTemplateName,
+				map[string]string{
+					"framework":  "tensorflow",
+					"tuner":      "TPE",
+					"created-by": "system",
+				},
+			)
+			if err != nil {
+				return err
+			}
+		}
+	}
+
+	return nil
+}

db/go/db.go

@@ -91,6 +91,9 @@ func Initialize() {
 	initialize20210129142057()
 	initialize20210129152427()
 	initialize20210224180017()
+	initialize20210323175655()
+	initialize20210329171739()
+	initialize20210329194731()
 
 	if err := client.DB.Close(); err != nil {
 		log.Printf("[error] closing db %v", err)

db/yaml/workflows/maskrcnn-training/20210118175809.yaml

@@ -103,7 +103,7 @@ templates:
       command:
         - sh
         - -c
-      image: onepanel/dl:0.17.0
+      image: onepanel/dl:v0.20.0
       volumeMounts:
         - mountPath: /mnt/data
           name: processed-data
@@ -112,7 +112,7 @@ templates:
       workingDir: /mnt/src
     sidecars:
       - name: tensorboard
-        image: onepanel/dl:0.17.0
+        image: onepanel/dl:v0.20.0
         command: [ sh, -c ]
         env:
           - name: ONEPANEL_INTERACTIVE_SIDECAR
@@ -155,7 +155,7 @@ templates:
       command:
         - sh
         - -c
-      image: onepanel/dl:0.17.0
+      image: onepanel/dl:v0.20.0
       volumeMounts:
         - mountPath: /mnt/data
           name: data

db/yaml/workflows/pytorch-mnist-training/20210323175655.yaml

@@ -0,0 +1,207 @@
+# source: https://github.com/onepanelio/templates/blob/master/workflows/pytorch-mnist-training/
+arguments:
+  parameters:
+    - name: epochs
+      value: '10'
+    - displayName: Node pool
+      hint: Name of node pool or group to run this workflow task
+      type: select.nodepool
+      name: sys-node-pool
+      value: {{.DefaultNodePoolOption}}
+      visibility: public
+      required: true
+entrypoint: main
+templates:
+  - name: main
+    dag:
+      tasks:
+        - name: train-model
+          template: train-model
+  - name: train-model
+    # Indicates that we want to push files in /mnt/output to object storage
+    outputs:
+      artifacts:
+        - name: output
+          path: /mnt/output
+          optional: true
+    script:
+      image: onepanel/dl:v0.20.0
+      command:
+        - python
+        - '-u'
+      source: |
+        import json
+        import torch
+        import torch.nn as nn
+        import torch.nn.functional as F
+        import torch.optim as optim
+        from torchvision import datasets, transforms
+        from torch.optim.lr_scheduler import StepLR
+        from torch.utils.tensorboard import SummaryWriter
+
+
+        class Net(nn.Module):
+            def __init__(self):
+                super(Net, self).__init__()
+                self.conv1 = nn.Conv2d(1, 32, 3, 1)
+                self.conv2 = nn.Conv2d(32, 64, 3, 1)
+                self.dropout1 = nn.Dropout(0.25)
+                self.dropout2 = nn.Dropout(0.5)
+                self.fc1 = nn.Linear(9216, 128)
+                self.fc2 = nn.Linear(128, 10)
+
+            def forward(self, x):
+                x = self.conv1(x)
+                x = F.relu(x)
+                x = self.conv2(x)
+                x = F.relu(x)
+                x = F.max_pool2d(x, 2)
+                x = self.dropout1(x)
+                x = torch.flatten(x, 1)
+                x = self.fc1(x)
+                x = F.relu(x)
+                x = self.dropout2(x)
+                x = self.fc2(x)
+                output = F.log_softmax(x, dim=1)
+                return output
+
+
+        def train(model, device, train_loader, optimizer, epoch, batch_size, writer):
+            model.train()
+            for batch_idx, (data, target) in enumerate(train_loader):
+                data, target = data.to(device), target.to(device)
+                optimizer.zero_grad()
+                output = model(data)
+                loss = F.nll_loss(output, target)
+                loss.backward()
+                optimizer.step()
+                if batch_idx % 10 == 0:
+                    print('Train Epoch: {} [{}/{} ({:.0f}%)]\tLoss: {:.6f}'.format(
+                        epoch, batch_idx * len(data), len(train_loader.dataset),
+                        100. * batch_idx / len(train_loader), loss.item()))
+
+                    writer.add_scalar('training loss', loss.item(), epoch)
+
+
+        def test(model, device, test_loader, epoch, writer):
+            model.eval()
+            test_loss = 0
+            correct = 0
+            with torch.no_grad():
+                for data, target in test_loader:
+                    data, target = data.to(device), target.to(device)
+                    output = model(data)
+                    test_loss += F.nll_loss(output, target, reduction='sum').item()  # sum up batch loss
+                    pred = output.argmax(dim=1, keepdim=True)  # get the index of the max log-probability
+                    correct += pred.eq(target.view_as(pred)).sum().item()
+
+            loss = test_loss / len(test_loader.dataset)
+            accuracy = correct / len(test_loader.dataset)
+
+            print('\nTest set: Average loss: {}, Accuracy: {}\n'.format(
+                loss, accuracy))
+
+             # Store metrics for this task
+            metrics = [
+              {'name': 'accuracy', 'value': accuracy},
+              {'name': 'loss', 'value': loss}
+            ]
+            with open('/mnt/tmp/sys-metrics.json', 'w') as f:
+              json.dump(metrics, f)
+
+
+        def main(params):
+            writer = SummaryWriter(log_dir='/mnt/output/tensorboard')
+
+            use_cuda = torch.cuda.is_available()
+
+            torch.manual_seed(params['seed'])
+
+            device = torch.device('cuda' if use_cuda else 'cpu')
+
+            train_kwargs = {'batch_size': params['batch_size']}
+            test_kwargs = {'batch_size': params['test_batch_size']}
+            if use_cuda:
+                cuda_kwargs = {'num_workers': 1,
+                               'pin_memory': True,
+                               'shuffle': True}
+                train_kwargs.update(cuda_kwargs)
+                test_kwargs.update(cuda_kwargs)
+
+            transform=transforms.Compose([
+                transforms.ToTensor(),
+                transforms.Normalize((0.1307,), (0.3081,))
+            ])
+            dataset1 = datasets.MNIST('/mnt/data', train=True, download=True,
+                               transform=transform)
+            dataset2 = datasets.MNIST('/mnt/data', train=False,
+                               transform=transform)
+            train_loader = torch.utils.data.DataLoader(dataset1, **train_kwargs)
+            test_loader = torch.utils.data.DataLoader(dataset2, **test_kwargs)
+
+            model = Net().to(device)
+            optimizer = optim.Adadelta(model.parameters(), lr=params['lr'])
+
+            scheduler = StepLR(optimizer, step_size=1, gamma=params['gamma'])
+            for epoch in range(1, params['epochs'] + 1):
+                train(model, device, train_loader, optimizer, epoch, params['batch_size'], writer)
+                test(model, device, test_loader, epoch, writer)
+                scheduler.step()
+
+            # Save model
+            torch.save(model.state_dict(), '/mnt/output/model.pt')
+
+            writer.close()
+
+
+        if __name__ == '__main__':
+            params = {
+                'seed': 1,
+                'batch_size': 64,
+                'test_batch_size': 1000,
+                'epochs': {{workflow.parameters.epochs}},
+                'lr': 0.001,
+                'gamma': 0.7,
+            }
+            main(params)
+      volumeMounts:
+        # TensorBoard sidecar will automatically mount these volumes
+        # The `data` volume is mounted for saving datasets
+        # The `output` volume is mounted to save model output and share TensorBoard logs
+        - name: data
+          mountPath: /mnt/data
+        - name: output
+          mountPath: /mnt/output
+    nodeSelector:
+        {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
+    sidecars:
+      - name: tensorboard
+        image: onepanel/dl:v0.20.0
+        command:
+          - sh
+          - '-c'
+        env:
+          - name: ONEPANEL_INTERACTIVE_SIDECAR
+            value: 'true'
+        args:
+          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+          - tensorboard --logdir /mnt/output/tensorboard
+        ports:
+          - containerPort: 6006
+            name: tensorboard
+volumeClaimTemplates:
+  # Provision volumes for storing data and output
+  - metadata:
+      name: data
+    spec:
+      accessModes: [ "ReadWriteOnce" ]
+      resources:
+        requests:
+          storage: 2Gi
+  - metadata:
+      name: output
+    spec:
+      accessModes: [ "ReadWriteOnce" ]
+      resources:
+        requests:
+          storage: 2Gi

db/yaml/workflows/tensorflow-mnist-training/20210323175655.yaml

@@ -0,0 +1,118 @@
+# source: https://github.com/onepanelio/templates/blob/master/workflows/tensorflow-mnist-training/
+arguments:
+  parameters:
+    - name: epochs
+      value: '10'
+    - displayName: Node pool
+      hint: Name of node pool or group to run this workflow task
+      type: select.nodepool
+      name: sys-node-pool
+      value: {{.DefaultNodePoolOption}}
+      visibility: public
+      required: true
+entrypoint: main
+templates:
+  - name: main
+    dag:
+      tasks:
+        - name: train-model
+          template: train-model
+  - name: train-model
+    # Indicates that we want to push files in /mnt/output to object storage
+    outputs:
+      artifacts:
+        - name: output
+          path: /mnt/output
+          optional: true
+    script:
+      image: onepanel/dl:v0.20.0
+      command:
+        - python
+        - '-u'
+      source: |
+        import json
+        import tensorflow as tf
+
+        mnist = tf.keras.datasets.mnist
+
+        (x_train, y_train),(x_test, y_test) = mnist.load_data()
+        x_train, x_test = x_train / 255.0, x_test / 255.0
+        x_train = x_train[..., tf.newaxis]
+        x_test = x_test[..., tf.newaxis]
+
+        model = tf.keras.Sequential([
+          tf.keras.layers.Conv2D(filters=32, kernel_size=5, activation='relu'),
+          tf.keras.layers.MaxPool2D(pool_size=2),
+          tf.keras.layers.Conv2D(filters=64, kernel_size=5, activation='relu'),
+          tf.keras.layers.MaxPool2D(pool_size=2),
+          tf.keras.layers.Flatten(),
+          tf.keras.layers.Dense(units=124, activation='relu'),
+          tf.keras.layers.Dropout(rate=0.75),
+          tf.keras.layers.Dense(units=10, activation='softmax')
+        ])
+        model.compile(optimizer=tf.keras.optimizers.Adam(lr=0.001),
+                      loss='sparse_categorical_crossentropy',
+                      metrics=['accuracy'])
+
+        # Write TensorBoard logs to /mnt/output
+        log_dir = '/mnt/output/tensorboard/'
+        tensorboard_callback = tf.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1)
+
+        model.fit(x=x_train,
+                  y=y_train,
+                  epochs={{workflow.parameters.epochs}},
+                  validation_data=(x_test, y_test),
+                  callbacks=[tensorboard_callback])
+
+        # Store metrics for this task
+        loss, accuracy = model.evaluate(x_test, y_test)
+        metrics = [
+          {'name': 'accuracy', 'value': accuracy},
+          {'name': 'loss', 'value': loss}
+        ]
+        with open('/mnt/tmp/sys-metrics.json', 'w') as f:
+          json.dump(metrics, f)
+
+        # Save model
+        model.save('/mnt/output/model.h5')
+      volumeMounts:
+        # TensorBoard sidecar will automatically mount these volumes
+        # The `data` volume is mounted to support Keras datasets
+        # The `output` volume is mounted to save model output and share TensorBoard logs
+        - name: data
+          mountPath: /home/root/.keras/datasets
+        - name: output
+          mountPath: /mnt/output
+    nodeSelector:
+        {{.NodePoolLabel}}: '{{workflow.parameters.sys-node-pool}}'
+    sidecars:
+      - name: tensorboard
+        image: onepanel/dl:v0.20.0
+        command:
+          - sh
+          - '-c'
+        env:
+          - name: ONEPANEL_INTERACTIVE_SIDECAR
+            value: 'true'
+        args:
+          # Read logs from /mnt/output - this directory is auto-mounted from volumeMounts
+          - tensorboard --logdir /mnt/output/tensorboard
+        ports:
+          - containerPort: 6006
+            name: tensorboard
+volumeClaimTemplates:
+  # Provision volumes for storing data and output
+  - metadata:
+      name: data
+    spec:
+      accessModes: [ "ReadWriteOnce" ]
+      resources:
+        requests:
+          storage: 2Gi
+  - metadata:
+      name: output
+    spec:
+      accessModes: [ "ReadWriteOnce" ]
+      resources:
+        requests:
+          storage: 2Gi

db/yaml/workspaces/cvat/20210323175655.yaml

@@ -0,0 +1,134 @@
+containers:
+  - name: cvat-db
+    image: postgres:10-alpine
+    env:
+      - name: POSTGRES_USER
+        value: root
+      - name: POSTGRES_DB
+        value: cvat
+      - name: POSTGRES_HOST_AUTH_METHOD
+        value: trust
+      - name: PGDATA
+        value: /var/lib/psql/data
+    ports:
+      - containerPort: 5432
+        name: tcp
+    volumeMounts:
+      - name: db
+        mountPath: /var/lib/psql
+  - name: cvat-redis
+    image: redis:4.0-alpine
+    ports:
+      - containerPort: 6379
+        name: tcp
+  - name: cvat
+    image: onepanel/cvat:v0.19.0_cvat.1.0.0
+    env:
+      - name: DJANGO_MODWSGI_EXTRA_ARGS
+        value: ""
+      - name: ALLOWED_HOSTS
+        value: '*'
+      - name: CVAT_REDIS_HOST
+        value: localhost
+      - name: CVAT_POSTGRES_HOST
+        value: localhost
+      - name: CVAT_SHARE_URL
+        value: /cvat/data
+      - name: CVAT_SHARE_DIR
+        value: /share
+      - name: CVAT_DATA_DIR
+        value: /cvat/data
+      - name: CVAT_MEDIA_DATA_DIR
+        value: /cvat/data/data
+      - name: CVAT_KEYS_DIR
+        value: /cvat/data/keys
+      - name: CVAT_MODELS_DIR
+        value: /cvat/data/models
+      - name: CVAT_LOGS_DIR
+        value: /cvat/logs
+      - name: CVAT_ANNOTATIONS_OBJECT_STORAGE_PREFIX
+        value: 'artifacts/$(ONEPANEL_RESOURCE_NAMESPACE)/annotations/'
+      - name: CVAT_ONEPANEL_WORKFLOWS_LABEL
+        value: 'key=used-by,value=cvat'
+      - name: NVIDIA_VISIBLE_DEVICES
+        value: all
+      - name: NVIDIA_DRIVER_CAPABILITIES
+        value: compute,utility
+      - name: NVIDIA_REQUIRE_CUDA
+        value: "cuda>=10.0 brand=tesla,driver>=384,driver<385 brand=tesla,driver>=410,driver<411"
+      - name: ONEPANEL_MAIN_CONTAINER
+        value: 'true'
+    ports:
+      - containerPort: 8080
+        name: http
+    volumeMounts:
+      - name: cvat-data
+        mountPath: /cvat
+      - name: share
+        mountPath: /share
+      - name: sys-namespace-config
+        mountPath: /etc/onepanel
+        readOnly: true
+  - name: cvat-ui
+    image: onepanel/cvat-ui:v0.19.0_cvat.1.0.0
+    ports:
+      - containerPort: 80
+        name: http
+  - name: sys-filesyncer
+    image: onepanel/filesyncer:v0.20.0
+    imagePullPolicy: Always
+    args:
+      - server
+      - -server-prefix=/sys/filesyncer
+    volumeMounts:
+      - name: share
+        mountPath: /share
+      - name: sys-namespace-config
+        mountPath: /etc/onepanel
+        readOnly: true
+ports:
+  - name: cvat-ui
+    port: 80
+    protocol: TCP
+    targetPort: 80
+  - name: cvat
+    port: 8080
+    protocol: TCP
+    targetPort: 8080
+  - name: fs
+    port: 8888
+    protocol: TCP
+    targetPort: 8888
+routes:
+  - match:
+      - uri:
+          prefix: /sys/filesyncer
+    route:
+      - destination:
+          port:
+            number: 8888
+  - match:
+      - uri:
+          regex: /api/.*|/git/.*|/tensorflow/.*|/onepanelio/.*|/tracking/.*|/auto_annotation/.*|/analytics/.*|/static/.*|/admin/.*|/documentation/.*|/dextr/.*|/reid/.*
+      - queryParams:
+          id:
+            regex: \d+.*
+    route:
+      - destination:
+          port:
+            number: 8080
+  - match:
+      - uri:
+          prefix: /
+    route:
+      - destination:
+          port:
+            number: 80
+volumeClaimTemplates:
+  - metadata:
+      name: db
+    spec:
+      accessModes: ["ReadWriteOnce"]
+      resources:
+        requests:
+          storage: 20Gi

db/yaml/workspaces/jupyterlab/20210323175655.yaml

@@ -0,0 +1,101 @@
+containers:
+  - name: jupyterlab
+    image: onepanel/dl:v0.20.0
+    command: ["/bin/bash", "-c", "pip install onepanel-sdk && start.sh LD_LIBRARY_PATH=/usr/local/nvidia/lib:/usr/local/nvidia/lib64 jupyter lab --LabApp.token='' --LabApp.allow_remote_access=True --LabApp.allow_origin=\"*\" --LabApp.disable_check_xsrf=True --LabApp.trust_xheaders=True --LabApp.base_url=/ --LabApp.tornado_settings='{\"headers\":{\"Content-Security-Policy\":\"frame-ancestors * 'self'\"}}' --notebook-dir='/data' --allow-root"]
+    workingDir: /data
+    env:
+      - name: tornado
+        value: "'{'headers':{'Content-Security-Policy':\"frame-ancestors\ *\ 'self'\"}}'"
+      - name: TENSORBOARD_PROXY_URL
+        value: '//$(ONEPANEL_RESOURCE_UID)--$(ONEPANEL_RESOURCE_NAMESPACE).$(ONEPANEL_DOMAIN)/tensorboard'
+      - name: ONEPANEL_MAIN_CONTAINER
+        value: 'true'
+    ports:
+      - containerPort: 8888
+        name: jupyterlab
+      - containerPort: 6006
+        name: tensorboard
+      - containerPort: 8080
+        name: nni
+    volumeMounts:
+      - name: data
+        mountPath: /data
+    lifecycle:
+      postStart:
+        exec:
+          command:
+            - /bin/sh
+            - -c
+            - >
+              condayml="/data/.environment.yml";
+              jupytertxt="/data/.jupexported.txt";
+              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+              if [ -f "$jupytertxt" ]; then cat $jupytertxt | xargs -n 1 jupyter labextension install --no-build && jupyter lab build --minimize=False; fi;
+      preStop:
+        exec:
+          command:
+            - /bin/sh
+            - -c
+            - >
+              conda env export > /data/.environment.yml -n base;
+              jupyter labextension list 1>/dev/null 2> /data/.jup.txt;
+              cat /data/.jup.txt | sed -n '2,$p' | awk 'sub(/v/,"@", $2){print $1$2}' > /data/.jupexported.txt;
+  - name: sys-filesyncer
+    image: onepanel/filesyncer:v0.20.0
+    imagePullPolicy: Always
+    args:
+      - server
+      - -host=localhost:8889
+      - -server-prefix=/sys/filesyncer
+    volumeMounts:
+      - name: data
+        mountPath: /data
+      - name: sys-namespace-config
+        mountPath: /etc/onepanel
+        readOnly: true
+ports:
+  - name: jupyterlab
+    port: 80
+    protocol: TCP
+    targetPort: 8888
+  - name: tensorboard
+    port: 6006
+    protocol: TCP
+    targetPort: 6006
+  - name: nni
+    port: 8080
+    protocol: TCP
+    targetPort: 8080
+  - name: fs
+    port: 8889
+    protocol: TCP
+    targetPort: 8889
+routes:
+  - match:
+      - uri:
+          prefix: /sys/filesyncer
+    route:
+      - destination:
+          port:
+            number: 8889
+  - match:
+      - uri:
+          prefix: /tensorboard
+    route:
+      - destination:
+          port:
+            number: 6006
+  - match:
+      - uri:
+          prefix: /nni
+    route:
+      - destination:
+          port:
+            number: 8080
+  - match:
+      - uri:
+          prefix: /
+    route:
+      - destination:
+          port:
+            number: 80

db/yaml/workspaces/vscode/20210323175655.yaml

@@ -0,0 +1,68 @@
+containers:
+  - name: vscode
+    image: onepanel/vscode:v0.20.0_code-server.3.9.1
+    command: ["/bin/bash", "-c", "pip install onepanel-sdk && /usr/bin/entrypoint.sh --bind-addr 0.0.0.0:8080 --auth none ."]
+    env:
+      - name: ONEPANEL_MAIN_CONTAINER
+        value: 'true'
+    ports:
+      - containerPort: 8080
+        name: vscode
+    volumeMounts:
+      - name: data
+        mountPath: /data
+    lifecycle:
+      postStart:
+        exec:
+          command:
+            - /bin/sh
+            - -c
+            - >
+              condayml="/data/.environment.yml";
+              vscodetxt="/data/.vscode-extensions.txt";
+              if [ -f "$condayml" ]; then conda env update -f $condayml; fi;
+              if [ -f "$vscodetxt" ]; then cat $vscodetxt | xargs -n 1 code-server --install-extension; fi;
+      preStop:
+        exec:
+          command:
+            - /bin/sh
+            - -c
+            - >
+              conda env export > /data/.environment.yml -n base;
+              code-server --list-extensions | tail -n +2 > /data/.vscode-extensions.txt;
+  - name: sys-filesyncer
+    image: onepanel/filesyncer:v0.20.0
+    imagePullPolicy: Always
+    args:
+      - server
+      - -server-prefix=/sys/filesyncer
+    volumeMounts:
+      - name: data
+        mountPath: /data
+      - name: sys-namespace-config
+        mountPath: /etc/onepanel
+        readOnly: true
+ports:
+  - name: vscode
+    port: 8080
+    protocol: TCP
+    targetPort: 8080
+  - name: fs
+    port: 8888
+    protocol: TCP
+    targetPort: 8888
+routes:
+  - match:
+      - uri:
+          prefix: /sys/filesyncer
+    route:
+      - destination:
+          port:
+            number: 8888
+  - match:
+      - uri:
+          prefix: /
+    route:
+      - destination:
+          port:
+            number: 8080

main.go

@@ -4,6 +4,14 @@ import (
 	"context"
 	"flag"
 	"fmt"
+	migrations "github.com/onepanelio/core/db/go"
+	"github.com/pressly/goose"
+	"math"
+	"net"
+	"net/http"
+	"path/filepath"
+	"strings"
+
 	"github.com/gorilla/handlers"
 	grpc_middleware "github.com/grpc-ecosystem/go-grpc-middleware"
 	grpc_logrus "github.com/grpc-ecosystem/go-grpc-middleware/logging/logrus"
@@ -11,12 +19,10 @@ import (
 	"github.com/grpc-ecosystem/grpc-gateway/v2/runtime"
 	"github.com/jmoiron/sqlx"
 	api "github.com/onepanelio/core/api/gen"
-	migrations "github.com/onepanelio/core/db/go"
 	v1 "github.com/onepanelio/core/pkg"
 	"github.com/onepanelio/core/pkg/util/env"
 	"github.com/onepanelio/core/server"
 	"github.com/onepanelio/core/server/auth"
-	"github.com/pressly/goose"
 	log "github.com/sirupsen/logrus"
 	"github.com/tmc/grpc-websocket-proxy/wsproxy"
 	"google.golang.org/grpc"
@@ -29,11 +35,6 @@ import (
 	"k8s.io/apimachinery/pkg/watch"
 	"k8s.io/client-go/kubernetes"
 	"k8s.io/client-go/tools/cache"
-	"math"
-	"net"
-	"net/http"
-	"path/filepath"
-	"strings"
 )
 
 var (

pkg/workflow_execution.go

@@ -2,11 +2,19 @@ package v1
 
 import (
 	"bufio"
-	"cloud.google.com/go/storage"
 	"database/sql"
 	"encoding/json"
 	"errors"
 	"fmt"
+	"io"
+	"io/ioutil"
+	"net/http"
+	"regexp"
+	"strconv"
+	"strings"
+	"time"
+
+	"cloud.google.com/go/storage"
 	sq "github.com/Masterminds/squirrel"
 	"github.com/argoproj/argo/persist/sqldb"
 	"github.com/argoproj/argo/workflow/hydrator"
@@ -19,17 +27,10 @@ import (
 	uid2 "github.com/onepanelio/core/pkg/util/uid"
 	"golang.org/x/net/context"
 	"gopkg.in/yaml.v2"
-	"io"
-	"io/ioutil"
 	networking "istio.io/api/networking/v1alpha3"
 	"k8s.io/apimachinery/pkg/util/intstr"
 	"k8s.io/apimachinery/pkg/watch"
-	"net/http"
-	"regexp"
 	yaml2 "sigs.k8s.io/yaml"
-	"strconv"
-	"strings"
-	"time"
 
 	wfv1 "github.com/argoproj/argo/pkg/apis/workflow/v1alpha1"
 	"github.com/argoproj/argo/workflow/common"
@@ -307,7 +308,6 @@ func injectEnvironmentVariables(container *corev1.Container, systemConfig System
 func (c *Client) injectAutomatedFields(namespace string, wf *wfv1.Workflow, opts *WorkflowExecutionOptions) (err error) {
 	if opts.PodGCStrategy == nil {
 		if wf.Spec.PodGC == nil {
-			//TODO - Load this data from onepanel config-map or secret
 			podGCStrategy := env.Get("ARGO_POD_GC_STRATEGY", "OnPodCompletion")
 			strategy := PodGCStrategy(podGCStrategy)
 			wf.Spec.PodGC = &wfv1.PodGC{
@@ -334,6 +334,23 @@ func (c *Client) injectAutomatedFields(namespace string, wf *wfv1.Workflow, opts
 				Medium: corev1.StorageMediumMemory,
 			},
 		},
+	}, corev1.Volume{ // Artifacts out
+		Name: "tmp",
+		VolumeSource: corev1.VolumeSource{
+			EmptyDir: &corev1.EmptyDirVolumeSource{
+				Medium: corev1.StorageMediumMemory,
+			},
+		},
+	})
+
+	// Create artifacts out volume
+	wf.Spec.Volumes = append(wf.Spec.Volumes, corev1.Volume{
+		Name: "out",
+		VolumeSource: corev1.VolumeSource{
+			EmptyDir: &corev1.EmptyDirVolumeSource{
+				Medium: corev1.StorageMediumMemory,
+			},
+		},
 	})
 
 	systemConfig, err := c.GetSystemConfig()
@@ -367,6 +384,12 @@ func (c *Client) injectAutomatedFields(namespace string, wf *wfv1.Workflow, opts
 				Name:      "sys-dshm",
 				MountPath: "/dev/shm",
 			})
+
+			template.Container.VolumeMounts = append(template.Container.VolumeMounts, corev1.VolumeMount{
+				Name:      "tmp",
+				MountPath: "/mnt/tmp",
+			})
+
 			err = c.injectHostPortAndResourcesToContainer(template, opts, systemConfig)
 			if err != nil {
 				return err
@@ -386,7 +409,7 @@ func (c *Client) injectAutomatedFields(namespace string, wf *wfv1.Workflow, opts
 			// Always add output artifacts for metrics but make them optional
 			template.Outputs.Artifacts = append(template.Outputs.Artifacts, wfv1.Artifact{
 				Name:     "sys-metrics",
-				Path:     "/tmp/sys-metrics.json",
+				Path:     "/mnt/tmp/sys-metrics.json",
 				Optional: true,
 				Archive: &wfv1.ArchiveStrategy{
 					None: &wfv1.NoneStrategy{},
@@ -2424,3 +2447,17 @@ func (c *Client) ListWorkflowExecutionsField(namespace, field string) (value []s
 
 	return
 }
+
+// CountWorkflowExecutionsForWorkflowTemplate returns the number of workflow executions associated with the workflow template identified by it's id.
+func (c *Client) CountWorkflowExecutionsForWorkflowTemplate(workflowTemplateID uint64) (count int, err error) {
+	err = sb.Select("COUNT(*)").
+		From("workflow_executions we").
+		Join("workflow_template_versions wtv ON we.workflow_template_version_id = wtv.id").
+		Join("workflow_templates wt ON wtv.workflow_template_id = wt.id").
+		Where(sq.Eq{"wt.id": workflowTemplateID}).
+		RunWith(c.DB).
+		QueryRow().
+		Scan(&count)
+
+	return
+}

pkg/workflow_template.go

@@ -402,6 +402,21 @@ func (c *Client) getWorkflowTemplateById(id uint64) (workflowTemplate *WorkflowT
 	return
 }
 
+func (c *Client) getWorkflowTemplateRaw(namespace, uid string) (workflowTemplate *WorkflowTemplate, err error) {
+	workflowTemplate = &WorkflowTemplate{}
+
+	query := sb.Select(getWorkflowTemplateColumns("wt", "")...).
+		From("workflow_templates wt").
+		Where(sq.Eq{
+			"namespace": namespace,
+			"uid":       uid,
+		})
+
+	err = c.DB.Getx(workflowTemplate, query)
+
+	return
+}
+
 // getWorkflowTemplate gets the workflowtemplate given the input data.
 // it also loads the argo workflow and labels data.
 // If version is <= 0, the latest workflow template is fetched.
@@ -737,6 +752,16 @@ func (c *Client) UpdateWorkflowTemplateVersion(wtv *WorkflowTemplateVersion) err
 	return updateWorkflowTemplateVersionDB(c.DB, wtv)
 }
 
+// GetWorkflowTemplateRaw returns the WorkflowTemplate without any version information
+func (c *Client) GetWorkflowTemplateRaw(namespace, uid string) (workflowTemplate *WorkflowTemplate, err error) {
+	workflowTemplate, err = c.getWorkflowTemplateRaw(namespace, uid)
+	if err != nil && strings.Contains(err.Error(), "sql: no rows in result set") {
+		return nil, nil
+	}
+
+	return
+}
+
 // GetWorkflowTemplate returns a WorkflowTemplate with data loaded from various sources
 // If version is 0, it returns the latest version data.
 //
@@ -905,6 +930,8 @@ func (c *Client) getLatestWorkflowTemplate(namespace, uid string) (*WorkflowTemp
 	return c.getWorkflowTemplate(namespace, uid, 0) //version=0 means latest
 }
 
+// ArchiveWorkflowTemplate will mark the workflow template identified by the (namespace, uid) as archived
+// and will archive or delete resources where appropriate.
 func (c *Client) ArchiveWorkflowTemplate(namespace, uid string) (archived bool, err error) {
 	workflowTemplate, err := c.getLatestWorkflowTemplate(namespace, uid)
 	if err != nil {

pkg/workspace.go

@@ -392,7 +392,7 @@ func generateNodeCaptureContainer(workspace *Workspace, config SystemConfig) map
 		"ports": []interface{}{
 			map[string]interface{}{
 				"name":          "node-capturer",
-				"hostPort":      80,
+				"hostPort":      49151,
 				"containerPort": 80,
 			},
 		},