4c5cb8f681
* add spline model * add tests for splines * rst files for splines --------- Co-authored-by: AleDinve <giuseppealessio.d@student.unisi.it> Co-authored-by: dario-coscia <dariocos99@gmail.com>
75 lines
2.0 KiB
Python
75 lines
2.0 KiB
Python
import torch
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import pytest
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from pina.model import Spline
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data = torch.rand((20, 3))
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input_vars = 3
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output_vars = 4
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valid_args = [
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{
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'knots': torch.tensor([0., 0., 0., 1., 2., 3., 3., 3.]),
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'control_points': torch.tensor([0., 0., 1., 0., 0.]),
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'order': 3
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},
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{
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'knots': torch.tensor([-2., -2., -2., -2., -1., 0., 1., 2., 2., 2., 2.]),
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'control_points': torch.tensor([0., 0., 0., 6., 0., 0., 0.]),
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'order': 4
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},
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# {'control_points': {'n': 5, 'dim': 1}, 'order': 2},
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# {'control_points': {'n': 7, 'dim': 1}, 'order': 3}
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]
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def scipy_check(model, x, y):
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from scipy.interpolate._bsplines import BSpline
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import numpy as np
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spline = BSpline(
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t=model.knots.detach().numpy(),
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c=model.control_points.detach().numpy(),
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k=model.order-1
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)
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y_scipy = spline(x).flatten()
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y = y.detach().numpy()
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np.testing.assert_allclose(y, y_scipy, atol=1e-5)
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@pytest.mark.parametrize("args", valid_args)
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def test_constructor(args):
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Spline(**args)
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def test_constructor_wrong():
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with pytest.raises(ValueError):
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Spline()
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@pytest.mark.parametrize("args", valid_args)
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def test_forward(args):
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min_x = args['knots'][0]
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max_x = args['knots'][-1]
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xi = torch.linspace(min_x, max_x, 1000)
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model = Spline(**args)
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yi = model(xi).squeeze()
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scipy_check(model, xi, yi)
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return
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@pytest.mark.parametrize("args", valid_args)
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def test_backward(args):
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min_x = args['knots'][0]
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max_x = args['knots'][-1]
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xi = torch.linspace(min_x, max_x, 100)
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model = Spline(**args)
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yi = model(xi)
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fake_loss = torch.sum(yi)
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assert model.control_points.grad is None
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fake_loss.backward()
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assert model.control_points.grad is not None
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# dim_in, dim_out = 3, 2
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# fnn = FeedForward(dim_in, dim_out)
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# data.requires_grad = True
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# output_ = fnn(data)
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# l=torch.mean(output_)
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# l.backward()
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# assert data._grad.shape == torch.Size([20,3])
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