components mmdetection_image_objectdetection_instancesegmentation_model_import - Azure/azureml-assets GitHub Wiki
Import PyTorch / MLflow model
Version: 0.0.19
View in Studio: https://ml.azure.com/registries/azureml/components/mmdetection_image_objectdetection_instancesegmentation_model_import/version/0.0.19
Model family
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
model_family | Which framework the model belongs to. | string | MmDetectionImage | True | ['MmDetectionImage'] |
Model name
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
model_name | Please select models from AzureML Model Assets for all supported models. For MMDetection, provide the model's config name here, same as its specified in MMDetection Model Zoo, To find the correct model name, go to https://github.com/open-mmlab/mmdetection/tree/v3.1.0/configs click on the model type and you will find the model name in the metafile.yml file which is present at configs/<MODEL_TYPE>/metafile.yml location. It is the user responsibility to comply with the model's license terms. | string | True |
Continual-Finetuning model path
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
pytorch_model | Pytorch Model registered in AzureML Asset. | custom_model | True | ||
mlflow_model | Mlflow Model registered in AzureML Asset. | mlflow_model | True | ||
validation_output | Validation status. | uri_file | True | ||
download_from_source | Download model directly from MMDetection instead of system registry | boolean | False | True |
Name | Description | Type |
---|---|---|
output_dir | Folder to store model metadata. | uri_folder |
azureml://registries/azureml/environments/acft-mmdetection-image-gpu/versions/46