Model Summary and Visualization Toolkits

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get_model_size

Calculate model parameter size, return result in bytes.

get_model_size(model)

• model: model defined by Dandelion

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get_model_summary

Produce model parameter summary.

get_model_summary(model, size_unit='M')

• model: model defined by Dandelion
• size_unit: {'M'|'K'|'B'|int}, unit for calculating parameter size.
• return: OrderedDict instance. You can use json.dumps() to get a formatted json report file. For example:

    import json
    from dandelion.model import Alternate_2D_LSTM
    input_dim, hidden_dim, B, H, W = 8, 8, 2, 32, 32
    model = Alternate_2D_LSTM(input_dims=[input_dim],hidden_dim=hidden_dim, peephole=True, mode=2)
    model_summary = get_model_summary(model, size_unit=1)
    rpt = json.dumps(model_summary, ensure_ascii=False, indent=2)
    print(rpt)

The following is a snapshot of a complex model's summary, in which :

• the size attribute is in MB unit.
• the percent attribute is level-wise, and already in [0 ~ 100] range.

For example in the snapshot, it says model_6 (weights) is 21.36MB in total, and the first convolution layer stage1 accounts for 0.011% of all the weights.