Warning

This feature is under heavy development and API changes may occur without notice in future versions.

Visualization Tools

aimet_torch.v2.visualization_tools.visualize_stats(sim, dummy_input, save_path=None)[source]

Produces an interactive html to view the stats collected by each quantizer during calibration

Note

The QuantizationSimModel input is expected to have been calibrated before using this function. Stats will only be plotted for activations/parameters with quantizers containing calibration statistics.

Currently, this tool is only compatible with quantizers containing MinMaxEncodingAnalyzer encoding analyzers (i.e., QuantScheme.post_training_tf and QuantScheme.training_range_learning_with_tf_init quant schemes).

Creates an interactive visualization of min and max activations/weights of all quantized modules in the input QuantSim object. The features include:

  • Adjustable threshold values to flag layers whose min or max activations/weights exceed the set thresholds

  • Tables containing names and ranges for layers exceeding threshold values

Saves the visualization as a .html at the given path.

Example

>>> sim = aimet_torch.v2.quantsim.QuantizationSimModel(model, dummy_input, quant_scheme=QuantScheme.post_training_tf)
>>> with aimet_torch.v2.nn.compute_encodings(sim.model):
...     for data, _ in data_loader:
...         sim.model(data)
...
>>> visualize_stats(sim, dummy_input, "./quant_stats_visualization.html")
Parameters:

  • sim (QuantizationSimModel) – Calibrated QuantizationSimModel

  • dummy_input – Sample input used to trace the model

  • save_path (Optional[str]) – Path for saving the visualization. Default is “./quant_stats_visualization.html”

Return type:

None