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""" |
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A simple wrapper to show parameter of the model |
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Usage: |
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# go to the model directory, then |
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$: python script_model_para.py |
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We assume model.py and config.py are available in the project directory. |
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""" |
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from __future__ import print_function |
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import os |
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import sys |
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import numpy as np |
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import torch |
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import torch.nn as nn |
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import torch.nn.functional as F |
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import importlib |
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__author__ = "Xin Wang" |
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__email__ = "wangxin@nii.ac.jp" |
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__copyright__ = "Copyright 2020, Xin Wang" |
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def f_model_show(pt_model): |
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""" |
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f_model_show(pt_model) |
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Args: pt_model, a Pytorch model |
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Print the informaiton of the model |
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""" |
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print(pt_model) |
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num = sum(p.numel() for p in pt_model.parameters() if p.requires_grad) |
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print("Parameter number: {:d}".format(num)) |
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for name, p in pt_model.named_parameters(): |
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if p.requires_grad: |
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print("Layer: {:s}\tPara. num: {:<10d} ({:02.1f}%)\tShape: {:s}"\ |
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.format(name, p.numel(), p.numel()*100.0/num, str(p.shape))) |
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return |
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if __name__ == "__main__": |
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sys.path.insert(0, os.getcwd()) |
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if len(sys.argv) == 3: |
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prj_model = importlib.import_module(sys.argv[1]) |
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prj_conf = importlib.import_module(sys.argv[2]) |
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else: |
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print("By default, load model.py and config.py") |
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prj_model = importlib.import_module("model") |
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prj_conf = importlib.import_module("config") |
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input_dims = sum(prj_conf.input_dims) |
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output_dims = sum(prj_conf.output_dims) |
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model = prj_model.Model(input_dims, output_dims, None) |
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f_model_show(model) |
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