diff --git a/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items/automl-image-classification-multiclass-task-fridge-items.ipynb b/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items/automl-image-classification-multiclass-task-fridge-items.ipynb index b200de3596..2884b06455 100644 --- a/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items/automl-image-classification-multiclass-task-fridge-items.ipynb +++ b/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multiclass-task-fridge-items/automl-image-classification-multiclass-task-fridge-items.ipynb @@ -87,7 +87,10 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-workspace" + ] }, "outputs": [], "source": [ @@ -440,7 +443,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-compute" + ] + }, "outputs": [], "source": [ "from azure.ai.ml.entities import AmlCompute\n", @@ -475,7 +482,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.1. Automatic hyperparameter sweeping for your models (AutoMode)\n", "\n", @@ -518,7 +529,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -542,7 +557,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### Submitting an AutoML job for Computer Vision tasks\n", "Once you've configured your job, you can submit it as a job in the workspace in order to train a vision model using your training dataset." @@ -551,7 +570,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -565,7 +588,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -573,7 +600,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.2. Individual runs\n", "\n", @@ -596,7 +627,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -618,7 +653,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -630,7 +669,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -638,7 +681,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.2.1 Individual runs with models from Hugging Face (Preview)\n", "\n", @@ -650,7 +697,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "registry_ml_client = MLClient(credential, registry_name=\"azureml\")\n", @@ -670,7 +721,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "If you wish to try a model (say `microsoft/beit-base-patch16-224-pt22k-ft22k`), you can specify the job for your AutoML Image runs as follows:" ] @@ -678,7 +733,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -701,7 +760,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -713,7 +776,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -755,7 +822,11 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-scenario", + "validation-trials" + ] }, "outputs": [], "source": [ @@ -857,7 +928,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.3.1 Manual hyperparameter sweeping for models from Hugging Face (Preview)\n", "\n", @@ -869,7 +944,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -920,7 +999,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -934,7 +1017,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job_hf.name)" @@ -1266,7 +1353,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-deployment" + ] + }, "outputs": [], "source": [ "deployment = ManagedOnlineDeployment(\n", diff --git a/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multilabel-task-fridge-items/automl-image-classification-multilabel-task-fridge-items.ipynb b/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multilabel-task-fridge-items/automl-image-classification-multilabel-task-fridge-items.ipynb index 86f5b520e1..c93e1ec5b9 100644 --- a/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multilabel-task-fridge-items/automl-image-classification-multilabel-task-fridge-items.ipynb +++ b/sdk/python/jobs/automl-standalone-jobs/automl-image-classification-multilabel-task-fridge-items/automl-image-classification-multilabel-task-fridge-items.ipynb @@ -84,7 +84,10 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-workspace" + ] }, "outputs": [], "source": [ @@ -419,7 +422,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-compute" + ] + }, "outputs": [], "source": [ "from azure.ai.ml.entities import AmlCompute\n", @@ -454,7 +461,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.1. Automatic hyperparameter sweeping for your models (AutoMode)\n", "\n", @@ -488,11 +499,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [ - "parameters" - ] - }, + "metadata": {}, "outputs": [], "source": [ "# general job parameters\n", @@ -502,7 +509,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -526,7 +537,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### Submitting an AutoML job for Computer Vision tasks\n", "Once you've configured your job, you can submit it as a job in the workspace in order to train a vision model using your training dataset." @@ -535,7 +550,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -547,7 +566,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -555,7 +578,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.2. Individual runs\n", "\n", @@ -578,7 +605,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "image_classification_multilabel_job = automl.image_classification_multilabel(\n", @@ -597,7 +628,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -609,7 +644,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -617,7 +656,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.2.1 Individual runs with models from Hugging Face (Preview)\n", "\n", @@ -629,7 +672,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "registry_ml_client = MLClient(credential, registry_name=\"azureml\")\n", @@ -649,7 +696,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "If you wish to try a model (say `microsoft/beit-base-patch16-224-pt22k-ft22k`), you can specify the job for your AutoML Image runs as follows:" ] @@ -657,7 +708,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -680,7 +735,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -692,7 +751,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -735,7 +798,11 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-scenario", + "validation-trials" + ] }, "outputs": [], "source": [ @@ -840,7 +907,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.3.1 Manual hyperparameter sweeping for models from Hugging Face (Preview)\n", "\n", @@ -852,7 +923,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -907,7 +982,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -921,7 +1000,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job_hf.name)" @@ -1251,7 +1334,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-deployment" + ] + }, "outputs": [], "source": [ "deployment = ManagedOnlineDeployment(\n", diff --git a/sdk/python/jobs/automl-standalone-jobs/automl-image-instance-segmentation-task-fridge-items/automl-image-instance-segmentation-task-fridge-items.ipynb b/sdk/python/jobs/automl-standalone-jobs/automl-image-instance-segmentation-task-fridge-items/automl-image-instance-segmentation-task-fridge-items.ipynb index a203f6fd1a..0391470847 100644 --- a/sdk/python/jobs/automl-standalone-jobs/automl-image-instance-segmentation-task-fridge-items/automl-image-instance-segmentation-task-fridge-items.ipynb +++ b/sdk/python/jobs/automl-standalone-jobs/automl-image-instance-segmentation-task-fridge-items/automl-image-instance-segmentation-task-fridge-items.ipynb @@ -84,7 +84,10 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-workspace" + ] }, "outputs": [], "source": [ @@ -327,7 +330,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 2.4. Convert annotation file from COCO to JSONL\n", "If you want to try with a dataset in COCO format, the scripts below shows how to convert it to `jsonl` format. The file \"odFridgeObjects_coco.json\" consists of annotation information for the `odFridgeObjects` dataset." @@ -336,7 +343,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "import sys\n", @@ -354,7 +365,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "If your COCO segmentation data is encoded in RLE format, it can be converted as follows." ] @@ -362,7 +377,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "import sys\n", @@ -505,7 +524,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-compute" + ] + }, "outputs": [], "source": [ "from azure.ai.ml.entities import AmlCompute\n", @@ -540,7 +563,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.1. Automatic hyperparameter sweeping for your models (AutoMode)\n", "\n", @@ -575,11 +602,7 @@ { "cell_type": "code", "execution_count": null, - "metadata": { - "tags": [ - "parameters" - ] - }, + "metadata": {}, "outputs": [], "source": [ "# general job parameters\n", @@ -589,7 +612,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -613,7 +640,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### Submitting an AutoML job for Computer Vision tasks\n", "Once you've configured your job, you can submit it as a job in the workspace in order to train a vision model using your training dataset." @@ -622,7 +653,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -636,7 +671,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -644,7 +683,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.2. Individual runs\n", "\n", @@ -667,7 +710,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -691,7 +738,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -703,7 +754,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -711,7 +766,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.2.1 Individual runs with models from MMDetection (Preview)\n", "\n", @@ -723,7 +782,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "registry_ml_client = MLClient(credential, registry_name=\"azureml\")\n", @@ -743,7 +806,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "If you wish to try a model (say `mask_rcnn_swin-t-p4-w7_fpn_1x_coco`), you can specify the job for your AutoML Image runs as follows:" ] @@ -751,7 +818,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -774,7 +845,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -786,7 +861,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -829,7 +908,11 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-scenario", + "validation-trials" + ] }, "outputs": [], "source": [ @@ -927,7 +1010,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.3.1 Manual hyperparameter sweeping for models from MMDetection (Preview)\n", "\n", @@ -939,7 +1026,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -987,7 +1078,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -1001,7 +1096,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -1338,7 +1437,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-deployment" + ] + }, "outputs": [], "source": [ "deployment = ManagedOnlineDeployment(\n", diff --git a/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items-batch-scoring/image-object-detection-batch-scoring-non-mlflow-model.ipynb b/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items-batch-scoring/image-object-detection-batch-scoring-non-mlflow-model.ipynb index cfdf057e2a..b8f85a9ae1 100644 --- a/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items-batch-scoring/image-object-detection-batch-scoring-non-mlflow-model.ipynb +++ b/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items-batch-scoring/image-object-detection-batch-scoring-non-mlflow-model.ipynb @@ -69,7 +69,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-workspace" + ] + }, "outputs": [], "source": [ "credential = DefaultAzureCredential()\n", @@ -309,7 +313,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 2.4. Convert annotation file from COCO to JSONL\n", "If you want to try with a dataset in COCO format, the scripts below shows how to convert it to `jsonl` format. The file \"odFridgeObjects_coco.json\" consists of annotation information for the `odFridgeObjects` dataset." @@ -318,7 +326,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "import sys\n", @@ -336,7 +348,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### Visualize bounding boxes\n", "Please refer to the \"Visualize data\" section in the following [tutorial](https://docs.microsoft.com/en-us/azure/machine-learning/tutorial-auto-train-image-models#visualize-data) to see how to easily visualize your ground truth bounding boxes before starting to train." @@ -415,7 +431,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "To create data input from TabularDataset created using V1 sdk, specify the `type` as `AssetTypes.MLTABLE`, `mode` as `InputOutputModes.DIRECT` and `path` in the following format `azureml::`." ] @@ -423,7 +443,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "\"\"\"\n", @@ -453,7 +477,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-compute" + ] + }, "outputs": [], "source": [ "from azure.ai.ml.entities import AmlCompute\n", @@ -538,7 +566,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-scenario" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", diff --git a/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items/automl-image-object-detection-task-fridge-items.ipynb b/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items/automl-image-object-detection-task-fridge-items.ipynb index c153dff6a8..0160612c64 100644 --- a/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items/automl-image-object-detection-task-fridge-items.ipynb +++ b/sdk/python/jobs/automl-standalone-jobs/automl-image-object-detection-task-fridge-items/automl-image-object-detection-task-fridge-items.ipynb @@ -84,7 +84,10 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-workspace" + ] }, "outputs": [], "source": [ @@ -327,7 +330,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 2.4. Convert annotation file from COCO to JSONL\n", "If you want to try with a dataset in COCO format, the scripts below shows how to convert it to `jsonl` format. The file \"odFridgeObjects_coco.json\" consists of annotation information for the `odFridgeObjects` dataset." @@ -336,7 +343,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "import sys\n", @@ -474,7 +485,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-compute" + ] + }, "outputs": [], "source": [ "from azure.ai.ml.entities import AmlCompute\n", @@ -509,7 +524,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.1. Automatic hyperparameter sweeping for your models (AutoMode)\n", "\n", @@ -553,7 +572,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -576,7 +599,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### Submitting an AutoML job for Computer Vision tasks\n", "Once you've configured your job, you can submit it as a job in the workspace in order to train a vision model using your training dataset." @@ -585,7 +612,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -599,7 +630,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -607,7 +642,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "## 4.2. Individual runs\n", "\n", @@ -630,7 +669,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -653,7 +696,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -665,7 +712,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -673,7 +724,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.2.1 Individual runs with models from MMDetection (Preview)\n", "\n", @@ -685,7 +740,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "registry_ml_client = MLClient(credential, registry_name=\"azureml\")\n", @@ -705,7 +764,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "If you wish to try a model (say `vfnet_r50_fpn_mdconv_c3-c5_mstrain_2x_coco`), you can specify the job for your AutoML Image runs as follows:" ] @@ -713,7 +776,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -738,7 +805,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -750,7 +821,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -792,7 +867,10 @@ "transient": { "deleting": false } - } + }, + "tags": [ + "validation-scenario" + ] }, "outputs": [], "source": [ @@ -813,7 +891,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "name": "limit-settings" + "name": "limit-settings", + "tags": [ + "validation-trials" + ] }, "outputs": [], "source": [ @@ -940,7 +1021,11 @@ }, { "cell_type": "markdown", - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "source": [ "### 4.3.1 Manual hyperparameter sweeping for models from MMDetection (Preview)\n", "\n", @@ -952,7 +1037,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Create the AutoML job with the related factory-function.\n", @@ -1007,7 +1096,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "# Submit the AutoML job\n", @@ -1021,7 +1114,11 @@ { "cell_type": "code", "execution_count": null, - "metadata": {}, + "metadata": { + "tags": [ + "validation-remove" + ] + }, "outputs": [], "source": [ "ml_client.jobs.stream(returned_job.name)" @@ -1381,7 +1478,10 @@ "cell_type": "code", "execution_count": null, "metadata": { - "name": "deploy" + "name": "deploy", + "tags": [ + "validation-deployment" + ] }, "outputs": [], "source": [