Metrics support

There are multiple ways to add metrics and metadata for a model:

1. Built-in Format Support: Each format can include a built-in implementation to expose metadata and metrics. This data can be embedded in the model file, loaded from a known auxiliary file format, or computed by the format implementation itself. Each Model, Graph, Node, Value, and Tensor can expose this data via a metadata or metrics property.

2. Attachment File: Metadata and metrics can be extended by loading an attachment file — a JSON file containing additional metadata and metrics. First, load the model file, then drag the attachment file into the app.
   Examples: mnist.onnx.zip, model.tflite.zip

3. Automatic Tensor Metrics: Basic tensor metrics such as min, max, and std are automatically computed for all floating-point tensors with fewer than 8 million elements.

Note: Metrics and metadata are displayed in the sidebar for the currently selected model, graph, node, value, or tensor.