Files
PINA/tests/test_model/test_fnn.py
Dario Coscia 8b7b61b3bd Documentation for v0.1 version (#199)
* Adding Equations, solving typos
* improve _code.rst
* the team rst and restuctore index.rst
* fixing errors

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Co-authored-by: Dario Coscia <dariocoscia@dhcp-015.eduroam.sissa.it>
2023-11-17 09:51:29 +01:00

38 lines
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Python

import torch
import pytest
from pina.model import FeedForward
data = torch.rand((20, 3))
input_vars = 3
output_vars = 4
def test_constructor():
FeedForward(input_vars, output_vars)
FeedForward(input_vars, output_vars, inner_size=10, n_layers=20)
FeedForward(input_vars, output_vars, layers=[10, 20, 5, 2])
FeedForward(input_vars,
output_vars,
layers=[10, 20, 5, 2],
func=torch.nn.ReLU)
FeedForward(input_vars,
output_vars,
layers=[10, 20, 5, 2],
func=[torch.nn.ReLU, torch.nn.ReLU, None, torch.nn.Tanh])
def test_constructor_wrong():
with pytest.raises(RuntimeError):
FeedForward(input_vars,
output_vars,
layers=[10, 20, 5, 2],
func=[torch.nn.ReLU, torch.nn.ReLU])
def test_forward():
dim_in, dim_out = 3, 2
fnn = FeedForward(dim_in, dim_out)
output_ = fnn(data)
assert output_.shape == (data.shape[0], dim_out)