62 lines
1.8 KiB
Python
62 lines
1.8 KiB
Python
import argparse
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import torch
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from torch.nn import Softplus
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from pina import PINN, Plotter, LabelTensor
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from pina.model import FeedForward
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from burger2 import Burgers1D
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class myFeature(torch.nn.Module):
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"""
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Feature: sin(pi*x)
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"""
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def __init__(self, idx):
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super(myFeature, self).__init__()
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self.idx = idx
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def forward(self, x):
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return LabelTensor(torch.sin(torch.pi * x.extract(['x'])), ['sin(x)'])
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if __name__ == "__main__":
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parser = argparse.ArgumentParser(description="Run PINA")
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group = parser.add_mutually_exclusive_group(required=True)
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group.add_argument("-s", "-save", action="store_true")
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group.add_argument("-l", "-load", action="store_true")
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parser.add_argument("id_run", help="number of run", type=int)
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parser.add_argument("features", help="extra features", type=int)
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args = parser.parse_args()
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feat = [myFeature(0)] if args.features else []
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burgers_problem = Burgers1D()
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model = FeedForward(
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layers=[30, 20, 10, 5],
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output_variables=burgers_problem.output_variables,
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input_variables=burgers_problem.input_variables,
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func=Softplus,
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extra_features=feat,
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)
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pinn = PINN(
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burgers_problem,
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model,
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lr=0.006,
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error_norm='mse',
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regularizer=0)
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if args.s:
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pinn.span_pts(
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{'n': 200, 'mode': 'random', 'variables': 't'},
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{'n': 20, 'mode': 'random', 'variables': 'x'},
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locations=['D'])
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pinn.span_pts(150, 'random', location=['gamma1', 'gamma2', 't0'])
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pinn.train(5000, 100)
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pinn.save_state('pina.burger.{}.{}'.format(args.id_run, args.features))
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else:
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pinn.load_state('pina.burger.{}.{}'.format(args.id_run, args.features))
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plotter = Plotter()
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plotter.plot(pinn)
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