73 lines
2.6 KiB
Python
73 lines
2.6 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_dimensons=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensons=2, output_dimensions=10)
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trunk_net = FeedForward(input_dimensons=1, output_dimensions=10)
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networks = {branch_net1 : ['x'],
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branch_net2 : ['x', 'y'],
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trunk_net : ['z']}
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MIONet(networks=networks,
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reduction='+',
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aggregator='*')
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def test_constructor_fails_when_invalid_inner_layer_size():
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branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensons=2, output_dimensions=10)
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trunk_net = FeedForward(input_dimensons=1, output_dimensions=12)
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networks = {branch_net1 : ['x'],
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branch_net2 : ['x', 'y'],
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trunk_net : ['z']}
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with pytest.raises(ValueError):
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MIONet(networks=networks,
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reduction='+',
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aggregator='*')
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def test_forward_extract_str():
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branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensons=1, output_dimensions=10)
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trunk_net = FeedForward(input_dimensons=1, output_dimensions=10)
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networks = {branch_net1 : ['a'],
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branch_net2 : ['b'],
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trunk_net : ['c']}
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model = MIONet(networks=networks,
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reduction='+',
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aggregator='*')
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model(input_)
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def test_forward_extract_int():
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branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensons=1, output_dimensions=10)
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trunk_net = FeedForward(input_dimensons=1, output_dimensions=10)
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networks = {branch_net1 : [0],
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branch_net2 : [1],
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trunk_net : [2]}
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model = MIONet(networks=networks,
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reduction='+',
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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_dimensons=1, output_dimensions=10)
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branch_net2 = FeedForward(input_dimensons=1, output_dimensions=10)
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trunk_net = FeedForward(input_dimensons=1, output_dimensions=10)
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networks = {branch_net1 : ['a'],
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branch_net2 : ['b'],
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trunk_net : ['c']}
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model = MIONet(networks=networks,
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reduction='+',
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aggregator='*')
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with pytest.raises(RuntimeError):
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model(data)
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