components rai_vision_insights - Azure/azureml-assets GitHub Wiki
Version: 0.0.19
Preview
View in Studio: https://ml.azure.com/registries/azureml/components/rai_vision_insights/version/0.0.19
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
task_type | The type of task to perform | string | ['image_classification', 'multilabel_image_classification', 'object_detection'] | ||
model_input | The model name to be used for computing insights | mlflow_model | False | ||
model_info | The model name to be used for computing insights | string | False | ||
test_dataset | The test dataset to be used for computing insights | mltable | |||
target_column_name | The target column name | string | |||
maximum_rows_for_test_dataset | The maximum number of rows to use from the test dataset | integer | 5000 | ||
classes | The list of class names for the target column | string | [] | ||
categorical_metadata_features | The list of categorical metadata feature names | string | [] | ||
dropped_metadata_features | The list of dropped metadata feature names | string | [] | ||
precompute_explanation | Whether to precompute explanations | boolean | True | ||
enable_error_analysis | Whether to enable computation of error analysis | boolean | True | ||
use_model_dependency | Whether to install the MLFlow model's dependencies in the RAI environment | boolean | False | ||
use_conda | Whether to use conda to install dependencies | boolean | False | ||
model_type | The type of MLFlow model to deserialize | string | ['pyfunc', 'fastai', 'pytorch'] |
guided_gradcam doesn't work with transformer vision models and shap isn't supported for automl images models for more details on XAI parameters, refer to following link https://learn.microsoft.com/en-us/azure/machine-learning/how-to-auto-train-image-models?tabs=cligenerate-explanations-for-predictions
Name | Description | Type | Default | Optional | Enum |
---|---|---|---|---|---|
xai_algorithm | The explanation algorithm to use for AutoML vision models, always set to shap for others | string | guided_backprop | True | ['guided_backprop', 'guided_gradcam', 'integrated_gradients', 'xrai', 'shap'] |
n_steps | The number of steps for the integrated gradients and XRAI algorithms | integer | True | ||
xrai_fast | Whether to use the faster version of the XRAI algorithm | boolean | True | ||
approximation_method | The approximation method to use for the integrated gradients algorithm | string | True | ['gausslegendre', 'riemann_middle'] | |
confidence_score_threshold_multilabel | The confidence score threshold for multilabel classification explanations, above which the labels are selected for generating explanations | number | True | ||
image_width_in_inches | The width to resize the image to in inches | number | True | ||
max_evals | The maximum number of evaluations to run in shap's hierarchical image explainer. | integer | True | ||
num_masks | The number of masks to use for the DRISE image explainer for object detection. | integer | True | ||
mask_res | The resolution of the masks to use for the DRISE image explainer for object detection. | integer | True | ||
dataset_type | The type of image dataset to use, whether the images are on private azure blob storage or public urls | string | public | ['private', 'public'] |
Name | Description | Type |
---|---|---|
dashboard | Path to which RAIVisionInsights is serialized to for connecting to compute instance | path |
ux_json | Json file to which UX is serialized to for viewing in static AzureML Studio UI | path |
azureml://registries/azureml/environments/responsibleai-vision/versions/7