Model Asset Inspector
The Model Asset Inspector provides an overview of imported machine learning (ML) models. Use it to view and verify model properties after import, including structure, inputs, outputs, layers, and constants.
The Inspector supports all imported models. It reflects any changes made to the ONNX import settings or LiteRT import settings.
Imported object settings
After you configure the model's import settings, the Inspector displays the updated model properties in the Imported Object section.
Use the Imported Object settings section to do the following:
- Serialize the model to the
StreamingAssetsfolder. - Check the properties of an imported and optimized model.
The Imported Object section provides a structured view of an imported model, including inputs, outputs, layers, and constants.
Inputs
The Input section displays a list of model input tensors and their dimensions. The following table details the properties of each input.
| Property | Description |
|---|---|
| name | The name of the input, such as images or attention_mask. |
| index | The index of the input. |
| shape | The tensor shape of the input. A shape consisting only of numbers represents a static-shaped tensor, for example, (1, 1, 28, 28) indicates the model only accepts tensors of shape 1 × 1 × 28 × 28. If a dimension is a named string, such as batch_size or sequence_length, it's dynamic and can vary in size. For more information on dynamic inputs, refer to Model inputs. |
| dataType | The data type of the input. For example, Float or Int. |
Outputs
The Outputs section lists the model’s output tensors. The following table details the properties of each output.
| Property | Description |
|---|---|
| name | The name of the output. |
| index | The index of the output. |
| shape | The tensor shape of the output. Sentis tries to precalculate this shape from the model. If a dimension in the shape is a question mark (?), Sentis can't calculate the size of the dimension, or the size depends on the input (a dynamic output). If the entire tensor shape is Unknown, Sentis can't calculate the number of dimensions, or the number of dimensions is dynamic. |
| dataType | The data type of the output. |
Layers
The Layers section displays all layers in the model and the order in which Sentis executes them. The following table details the properties of each layer.
| Property | Description |
|---|---|
| type | The type of layer. For more information, refer to Supported ONNX operators. |
| index | The index of the layer. |
| inputs | The names of the inputs to the layer. Possible values are a model input from the Inputs section, another layer, or a constant. |
| properties | The properties of the layer. The properties will depend on the type of layer. For more information, refer to Supported ONNX operators. |
Constants
The Constants section lists fixed values used in the model. The following table shows the total number of constants and weights in the model, along with a detailed list of constants.
| Property | Description |
|---|---|
| type | The type is always Constant. |
| index | The index of the constant. |
| weights | The tensor shape of the constant. If the tensor shape is empty - () - the constant is a scalar (a zero-dimensional tensor). |
Model information
This section provides metadata about the imported model, including:
- Total weight size: Displays the total size of the model constants.
- Producer Name: Displays the source of the model. This might be the producer name and version from the ONNX model or
Scriptif Sentis generated the model.