From 5a4c114d486bc5104640ba793f3740d361c6e2a7 Mon Sep 17 00:00:00 2001 From: Dario Coscia Date: Wed, 13 Sep 2023 12:48:55 +0200 Subject: [PATCH] variable name fix FeedForward model --- pina/model/feed_forward.py | 8 ++++---- tests/test_model/test_deeponet.py | 20 ++++++++++---------- tests/test_model/test_mionet.py | 30 +++++++++++++++--------------- 3 files changed, 29 insertions(+), 29 deletions(-) diff --git a/pina/model/feed_forward.py b/pina/model/feed_forward.py index 259e3f5..3ad75d9 100644 --- a/pina/model/feed_forward.py +++ b/pina/model/feed_forward.py @@ -28,16 +28,16 @@ class FeedForward(torch.nn.Module): `inner_size` are not considered. :param bool bias: If `True` the MLP will consider some bias. """ - def __init__(self, input_dimensons, output_dimensions, inner_size=20, + def __init__(self, input_dimensions, output_dimensions, inner_size=20, n_layers=2, func=nn.Tanh, layers=None, bias=True): """ """ super().__init__() - if not isinstance(input_dimensons, int): - raise ValueError('input_dimensons expected to be int.') - self.input_dimension = input_dimensons + if not isinstance(input_dimensions, int): + raise ValueError('input_dimensions expected to be int.') + self.input_dimension = input_dimensions if not isinstance(output_dimensions, int): raise ValueError('output_dimensions expected to be int.') diff --git a/tests/test_model/test_deeponet.py b/tests/test_model/test_deeponet.py index fe21f06..348175b 100644 --- a/tests/test_model/test_deeponet.py +++ b/tests/test_model/test_deeponet.py @@ -11,8 +11,8 @@ input_ = LabelTensor(data, input_vars) def test_constructor(): - branch_net = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=2, output_dimensions=10) + branch_net = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=2, output_dimensions=10) DeepONet(branch_net=branch_net, trunk_net=trunk_net, input_indeces_branch_net=['a'], @@ -22,8 +22,8 @@ def test_constructor(): def test_constructor_fails_when_invalid_inner_layer_size(): - branch_net = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=2, output_dimensions=8) + branch_net = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=2, output_dimensions=8) with pytest.raises(ValueError): DeepONet(branch_net=branch_net, trunk_net=trunk_net, @@ -33,8 +33,8 @@ def test_constructor_fails_when_invalid_inner_layer_size(): aggregator='*') def test_forward_extract_str(): - branch_net = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=2, output_dimensions=10) + branch_net = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=2, output_dimensions=10) model = DeepONet(branch_net=branch_net, trunk_net=trunk_net, input_indeces_branch_net=['a'], @@ -44,8 +44,8 @@ def test_forward_extract_str(): model(input_) def test_forward_extract_int(): - branch_net = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=2, output_dimensions=10) + branch_net = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=2, output_dimensions=10) model = DeepONet(branch_net=branch_net, trunk_net=trunk_net, input_indeces_branch_net=[0], @@ -55,8 +55,8 @@ def test_forward_extract_int(): model(data) def test_forward_extract_str_wrong(): - branch_net = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=2, output_dimensions=10) + branch_net = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=2, output_dimensions=10) model = DeepONet(branch_net=branch_net, trunk_net=trunk_net, input_indeces_branch_net=['a'], diff --git a/tests/test_model/test_mionet.py b/tests/test_model/test_mionet.py index 5150485..1983429 100644 --- a/tests/test_model/test_mionet.py +++ b/tests/test_model/test_mionet.py @@ -11,9 +11,9 @@ input_ = LabelTensor(data, input_vars) def test_constructor(): - branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10) - branch_net2 = FeedForward(input_dimensons=2, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=1, output_dimensions=10) + branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10) + branch_net2 = FeedForward(input_dimensions=2, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=1, output_dimensions=10) networks = {branch_net1 : ['x'], branch_net2 : ['x', 'y'], trunk_net : ['z']} @@ -23,9 +23,9 @@ def test_constructor(): def test_constructor_fails_when_invalid_inner_layer_size(): - branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10) - branch_net2 = FeedForward(input_dimensons=2, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=1, output_dimensions=12) + branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10) + branch_net2 = FeedForward(input_dimensions=2, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=1, output_dimensions=12) networks = {branch_net1 : ['x'], branch_net2 : ['x', 'y'], trunk_net : ['z']} @@ -35,9 +35,9 @@ def test_constructor_fails_when_invalid_inner_layer_size(): aggregator='*') def test_forward_extract_str(): - branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10) - branch_net2 = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=1, output_dimensions=10) + branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10) + branch_net2 = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=1, output_dimensions=10) networks = {branch_net1 : ['a'], branch_net2 : ['b'], trunk_net : ['c']} @@ -47,9 +47,9 @@ def test_forward_extract_str(): model(input_) def test_forward_extract_int(): - branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10) - branch_net2 = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=1, output_dimensions=10) + branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10) + branch_net2 = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=1, output_dimensions=10) networks = {branch_net1 : [0], branch_net2 : [1], trunk_net : [2]} @@ -59,9 +59,9 @@ def test_forward_extract_int(): model(data) def test_forward_extract_str_wrong(): - branch_net1 = FeedForward(input_dimensons=1, output_dimensions=10) - branch_net2 = FeedForward(input_dimensons=1, output_dimensions=10) - trunk_net = FeedForward(input_dimensons=1, output_dimensions=10) + branch_net1 = FeedForward(input_dimensions=1, output_dimensions=10) + branch_net2 = FeedForward(input_dimensions=1, output_dimensions=10) + trunk_net = FeedForward(input_dimensions=1, output_dimensions=10) networks = {branch_net1 : ['a'], branch_net2 : ['b'], trunk_net : ['c']}