How to train YOLO-NAS model in azure-ml using Blob storage account

I want to train a yolo-nas model for object-detection in azure-ml, where my train and test data is in blob storage account.

So in the config details we will be specifying the data directories will be blob storage account path for train, test and valid.

now I want to know how to feed the data to yolo-nas model or yolo-nas will pull the data for data loading, preprocessing and training.

config example: -

DATA_DIR = 'azureml://subscriptions/xxxxxxxx/resourcegroups/Faucet-poc/workspaces/faucet-ob-poc/datastores/faucetpoc/paths/' #parent directory to where data lives
TRAIN_IMAGES_DIR = 'train/images' #child dir of DATA_DIR where train images are
TRAIN_LABELS_DIR = 'train/labels' #child dir of DATA_DIR where train labels are

VAL_IMAGES_DIR = 'valid/images' #child dir of DATA_DIR where validation images are
VAL_LABELS_DIR = 'valid/labels' #child dir of DATA_DIR where validation labels are

# if you have a test set
TEST_IMAGES_DIR = 'test/images/' #child dir of DATA_DIR where test images are
TEST_LABELS_DIR = 'test/labels' #child dir of DATA_DIR where test labels are

CLASSES = ['faucet','sink','toilet'] #what class names do you have

NUM_CLASSES = len(CLASSES)



dataset_params = {
    'data_dir': DATA_DIR,
    'train_images_dir':TRAIN_IMAGES_DIR,
    'train_labels_dir':TRAIN_LABELS_DIR,
    'val_images_dir':VAL_IMAGES_DIR,
    'val_labels_dir':VAL_LABELS_DIR,
    'test_images_dir':TEST_IMAGES_DIR,
    'test_labels_dir':TEST_LABELS_DIR,
    'classes': CLASSES
}

This the code where we load the data in yolo-nas model

from super_gradients.training.dataloaders.dataloaders import (
    coco_detection_yolo_format_train, coco_detection_yolo_format_val)

train_data = coco_detection_yolo_format_train(
    dataset_params={
        'data_dir': dataset_params['data_dir'],
        'images_dir': dataset_params['train_images_dir'],
        'labels_dir': dataset_params['train_labels_dir'],
        'classes': dataset_params['classes']
    },
    dataloader_params={
        'batch_size': BATCH_SIZE,
        'num_workers': 2
    }
)

val_data = coco_detection_yolo_format_val(
    dataset_params={
        'data_dir': dataset_params['data_dir'],
        'images_dir': dataset_params['val_images_dir'],
        'labels_dir': dataset_params['val_labels_dir'],
        'classes': dataset_params['classes']
    },
    dataloader_params={
        'batch_size': BATCH_SIZE,
        'num_workers': 2
    }
)

test_data = coco_detection_yolo_format_val(
    dataset_params={
        'data_dir': dataset_params['data_dir'],
        'images_dir': dataset_params['test_images_dir'],
        'labels_dir': dataset_params['test_labels_dir'],
        'classes': dataset_params['classes']
    },
    dataloader_params={
        'batch_size': BATCH_SIZE,
        'num_workers': 2
    }
)

When I am running the code, I am facing the Not found error

Error: -

RuntimeError: 
data_dir=azureml://subscriptions/xxxxxxxx/resourcegroups/Faucet- 
poc/workspaces/faucet-ob-poc/datastores/faucetpoc/paths/ not found. 
Please make sure that data_dir points toward your dataset.

I am adding the snippet here for the mount point in azure-ml

I have reproduced the issue based on the scenario.

The training data is uploaded in the datastores.

To access the data in the notebook you can mount the datastore.
Follow the below steps to mount the datastore:

Once you create the mount with above steps, you will have mounting path as:

/home/azureuser/cloudfiles/data/datastore/data/

Then you can use this as your parent directory DATA_DIR.

With the above setup I was to access the training data.

Update: To mount the datastores with python you can use the below code.

from  azureml.core  import  Workspace, Dataset, Datastore
workspace = Workspace.from_config()
datastore = Datastore.get(workspace, "workspaceblobstore")
dataset = Dataset.File.from_files(path=(datastore, 'Data'))
mounted_path = "/tmp/test"
mount_cont = dataset.mount(mounted_path)
mount_cont.start()

Then you can use the mounted_path as your parent directory.

Note: Please check your permissions and assigned role. That can be a reason why you are not able to see data actions and similar issue can also be for the above case.