70 lines
2.2 KiB
Python
70 lines
2.2 KiB
Python
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import os, sys, time, glob, random, argparse
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import numpy as np
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from copy import deepcopy
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import torch
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from pathlib import Path
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lib_dir = (Path(__file__).parent / '..' / 'lib').resolve()
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if str(lib_dir) not in sys.path: sys.path.insert(0, str(lib_dir))
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from graphviz import Digraph
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parser = argparse.ArgumentParser("Visualize the Networks")
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parser.add_argument('--checkpoint', type=str, help='The path to the checkpoint.')
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parser.add_argument('--save_dir', type=str, help='The directory to save the network plot.')
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args = parser.parse_args()
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def plot(genotype, filename):
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g = Digraph(
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format='pdf',
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edge_attr=dict(fontsize='20', fontname="times"),
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node_attr=dict(style='filled', shape='rect', align='center', fontsize='20', height='0.5', width='0.5', penwidth='2', fontname="times"),
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engine='dot')
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g.body.extend(['rankdir=LR'])
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g.node("c_{k-2}", fillcolor='darkseagreen2')
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g.node("c_{k-1}", fillcolor='darkseagreen2')
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assert len(genotype) % 2 == 0
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steps = len(genotype) // 2
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for i in range(steps):
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g.node(str(i), fillcolor='lightblue')
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for i in range(steps):
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for k in [2*i, 2*i + 1]:
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op, j, weight = genotype[k]
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if j == 0:
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u = "c_{k-2}"
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elif j == 1:
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u = "c_{k-1}"
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else:
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u = str(j-2)
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v = str(i)
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g.edge(u, v, label=op, fillcolor="gray")
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g.node("c_{k}", fillcolor='palegoldenrod')
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for i in range(steps):
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g.edge(str(i), "c_{k}", fillcolor="gray")
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g.render(filename, view=False)
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if __name__ == '__main__':
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checkpoint = args.checkpoint
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assert os.path.isfile(checkpoint), 'Invalid path for checkpoint : {:}'.format(checkpoint)
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checkpoint = torch.load( checkpoint, map_location='cpu' )
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genotypes = checkpoint['genotypes']
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save_dir = Path(args.save_dir)
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subs = ['normal', 'reduce']
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for sub in subs:
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if not (save_dir / sub).exists():
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(save_dir / sub).mkdir(parents=True, exist_ok=True)
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for key, network in genotypes.items():
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save_path = str(save_dir / 'normal' / 'epoch-{:03d}'.format( int(key) ))
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print('save into {:}'.format(save_path))
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plot(network.normal, save_path)
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save_path = str(save_dir / 'reduce' / 'epoch-{:03d}'.format( int(key) ))
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print('save into {:}'.format(save_path))
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plot(network.reduce, save_path)
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