8b7b61b3bd
* Adding Equations, solving typos * improve _code.rst * the team rst and restuctore index.rst * fixing errors --------- Co-authored-by: Dario Coscia <dariocoscia@dhcp-015.eduroam.sissa.it>
56 lines
2.3 KiB
Python
56 lines
2.3 KiB
Python
import pytest
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import torch
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from pina import LabelTensor
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from pina.model import MIONet
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from pina.model import FeedForward
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data = torch.rand((20, 3))
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input_vars = ['a', 'b', 'c']
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input_ = LabelTensor(data, input_vars)
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def test_constructor():
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branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensions=2, output_dimensions=10)
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trunk_net = FeedForward(input_dimensions=1, output_dimensions=10)
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networks = {branch_net1: ['x'], branch_net2: ['x', 'y'], trunk_net: ['z']}
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MIONet(networks=networks, reduction='+', aggregator='*')
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def test_constructor_fails_when_invalid_inner_layer_size():
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branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensions=2, output_dimensions=10)
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trunk_net = FeedForward(input_dimensions=1, output_dimensions=12)
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networks = {branch_net1: ['x'], branch_net2: ['x', 'y'], trunk_net: ['z']}
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with pytest.raises(ValueError):
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MIONet(networks=networks, reduction='+', aggregator='*')
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def test_forward_extract_str():
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branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensions=1, output_dimensions=10)
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trunk_net = FeedForward(input_dimensions=1, output_dimensions=10)
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networks = {branch_net1: ['a'], branch_net2: ['b'], trunk_net: ['c']}
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model = MIONet(networks=networks, reduction='+', aggregator='*')
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model(input_)
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def test_forward_extract_int():
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branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensions=1, output_dimensions=10)
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trunk_net = FeedForward(input_dimensions=1, output_dimensions=10)
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networks = {branch_net1: [0], branch_net2: [1], trunk_net: [2]}
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model = MIONet(networks=networks, reduction='+', aggregator='*')
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model(data)
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def test_forward_extract_str_wrong():
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branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensions=1, output_dimensions=10)
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trunk_net = FeedForward(input_dimensions=1, output_dimensions=10)
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networks = {branch_net1: ['a'], branch_net2: ['b'], trunk_net: ['c']}
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model = MIONet(networks=networks, reduction='+', aggregator='*')
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with pytest.raises(RuntimeError):
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model(data)
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