folivo/PINA
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Fix Codacy Warnings (#477)

Browse Source 
---------

Co-authored-by: Dario Coscia <dariocos99@gmail.com>
This commit is contained in:
Filippo Olivo
2025-03-10 15:38:45 +01:00
committed by Nicola Demo
parent e3790e049a
commit 4177bfbb50
157 changed files with 3473 additions and 3839 deletions
Download Patch File Download Diff File Expand all files Collapse all files

38
tests/test_model/test_mionet.py
View File

@@ -6,7 +6,7 @@ from pina.model import MIONet
from pina.model import FeedForward
data = torch.rand((20, 3))
input_vars = ['a', 'b', 'c']
input_vars = ["a", "b", "c"]
input_ = LabelTensor(data, input_vars)
@@ -14,42 +14,42 @@ def test_constructor():
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']}
MIONet(networks=networks, reduction='+', aggregator='*')
networks = {branch_net1: ["x"], branch_net2: ["x", "y"], trunk_net: ["z"]}
MIONet(networks=networks, reduction="+", aggregator="*")
def test_constructor_fails_when_invalid_inner_layer_size():
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']}
networks = {branch_net1: ["x"], branch_net2: ["x", "y"], trunk_net: ["z"]}
with pytest.raises(ValueError):
MIONet(networks=networks, reduction='+', aggregator='*')
MIONet(networks=networks, reduction="+", aggregator="*")
def test_forward_extract_str():
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']}
model = MIONet(networks=networks, reduction='+', aggregator='*')
networks = {branch_net1: ["a"], branch_net2: ["b"], trunk_net: ["c"]}
model = MIONet(networks=networks, reduction="+", aggregator="*")
model(input_)
def test_backward_extract_str():
data = torch.rand((20, 3))
data.requires_grad = True
input_vars = ['a', 'b', 'c']
input_vars = ["a", "b", "c"]
input_ = LabelTensor(data, input_vars)
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']}
model = MIONet(networks=networks, reduction='+', aggregator='*')
networks = {branch_net1: ["a"], branch_net2: ["b"], trunk_net: ["c"]}
model = MIONet(networks=networks, reduction="+", aggregator="*")
model(input_)
l = torch.mean(model(input_))
l.backward()
assert data._grad.shape == torch.Size([20,3])
assert data._grad.shape == torch.Size([20, 3])
def test_forward_extract_int():
@@ -57,7 +57,7 @@ def test_forward_extract_int():
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]}
model = MIONet(networks=networks, reduction='+', aggregator='*')
model = MIONet(networks=networks, reduction="+", aggregator="*")
model(data)
@@ -68,19 +68,19 @@ def test_backward_extract_int():
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]}
model = MIONet(networks=networks, reduction='+', aggregator='*')
model = MIONet(networks=networks, reduction="+", aggregator="*")
model(data)
l = torch.mean(model(data))
l.backward()
assert data._grad.shape == torch.Size([20,3])
assert data._grad.shape == torch.Size([20, 3])
def test_forward_extract_str_wrong():
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']}
model = MIONet(networks=networks, reduction='+', aggregator='*')
networks = {branch_net1: ["a"], branch_net2: ["b"], trunk_net: ["c"]}
model = MIONet(networks=networks, reduction="+", aggregator="*")
with pytest.raises(RuntimeError):
model(data)
@@ -91,10 +91,10 @@ def test_backward_extract_str_wrong():
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']}
model = MIONet(networks=networks, reduction='+', aggregator='*')
networks = {branch_net1: ["a"], branch_net2: ["b"], trunk_net: ["c"]}
model = MIONet(networks=networks, reduction="+", aggregator="*")
with pytest.raises(RuntimeError):
model(data)
l = torch.mean(model(data))
l.backward()
assert data._grad.shape == torch.Size([20,3])
assert data._grad.shape == torch.Size([20, 3])