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>
69 lines
2.2 KiB
Python
69 lines
2.2 KiB
Python
from pina.model.layers import ResidualBlock, EnhancedLinear
|
|
import torch
|
|
import torch.nn as nn
|
|
|
|
|
|
def test_constructor_residual_block():
|
|
|
|
res_block = ResidualBlock(input_dim=10, output_dim=3, hidden_dim=4)
|
|
|
|
res_block = ResidualBlock(input_dim=10,
|
|
output_dim=3,
|
|
hidden_dim=4,
|
|
spectral_norm=True)
|
|
|
|
|
|
def test_forward_residual_block():
|
|
|
|
res_block = ResidualBlock(input_dim=10, output_dim=3, hidden_dim=4)
|
|
|
|
x = torch.rand(size=(80, 10))
|
|
y = res_block(x)
|
|
assert y.shape[1] == 3
|
|
assert y.shape[0] == x.shape[0]
|
|
|
|
def test_constructor_no_activation_no_dropout():
|
|
linear_layer = nn.Linear(10, 20)
|
|
enhanced_linear = EnhancedLinear(linear_layer)
|
|
|
|
assert len(list(enhanced_linear.parameters())) == len(list(linear_layer.parameters()))
|
|
|
|
def test_constructor_with_activation_no_dropout():
|
|
linear_layer = nn.Linear(10, 20)
|
|
activation = nn.ReLU()
|
|
enhanced_linear = EnhancedLinear(linear_layer, activation)
|
|
|
|
assert len(list(enhanced_linear.parameters())) == len(list(linear_layer.parameters())) + len(list(activation.parameters()))
|
|
|
|
def test_constructor_no_activation_with_dropout():
|
|
linear_layer = nn.Linear(10, 20)
|
|
dropout_prob = 0.5
|
|
enhanced_linear = EnhancedLinear(linear_layer, dropout=dropout_prob)
|
|
|
|
assert len(list(enhanced_linear.parameters())) == len(list(linear_layer.parameters()))
|
|
|
|
def test_constructor_with_activation_with_dropout():
|
|
linear_layer = nn.Linear(10, 20)
|
|
activation = nn.ReLU()
|
|
dropout_prob = 0.5
|
|
enhanced_linear = EnhancedLinear(linear_layer, activation, dropout_prob)
|
|
|
|
assert len(list(enhanced_linear.parameters())) == len(list(linear_layer.parameters())) + len(list(activation.parameters()))
|
|
|
|
def test_forward_enhanced_linear_no_dropout():
|
|
|
|
enhanced_linear = EnhancedLinear(nn.Linear(10, 3))
|
|
|
|
x = torch.rand(size=(80, 10))
|
|
y = enhanced_linear(x)
|
|
assert y.shape[1] == 3
|
|
assert y.shape[0] == x.shape[0]
|
|
|
|
def test_forward_enhanced_linear_dropout():
|
|
|
|
enhanced_linear = EnhancedLinear(nn.Linear(10, 3), dropout=0.5)
|
|
|
|
x = torch.rand(size=(80, 10))
|
|
y = enhanced_linear(x)
|
|
assert y.shape[1] == 3
|
|
assert y.shape[0] == x.shape[0] |