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Fixes #37 #38

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merged 15 commits into from
Apr 4, 2024
Merged

Fixes #37 #38

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7c3b19e
Update python-package.yml (#29)
xir4n Mar 19, 2024
140abd5
change default padding mode to 'symmetric'
xir4n Mar 20, 2024
c5dd559
VER dev branch 0.3.dev0 (#35)
lostanlen Mar 21, 2024
182b6f9
Merge branch 'main' into dev
xir4n Mar 25, 2024
eafb93d
add murenn_graph
xir4n Mar 25, 2024
bdd6f01
MURENNGraph output shape test
xir4n Mar 25, 2024
0bc8de4
change output shape
xir4n Mar 25, 2024
d5b024b
rename MURENNGraph ->MuReNNDirect; change output shape; differentiabi…
xir4n Mar 26, 2024
f1a3bea
add comments
xir4n Mar 26, 2024
add5770
rename graph.py to nn.py
xir4n Mar 26, 2024
e88e6f7
fix bug
xir4n Mar 26, 2024
bfe1596
'test_graph.py'-->'test_nn.py'
xir4n Mar 26, 2024
9dc02b9
Merge branch 'main' into dev
xir4n Mar 26, 2024
a3b60cf
fix bug: Conv1D first
xir4n Apr 2, 2024
8897343
Delete test_graph.py
xir4n Apr 2, 2024
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7 changes: 4 additions & 3 deletions murenn/dtcwt/nn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -59,9 +59,10 @@ def forward(self, x):
ys = []

for j in range(self.dtcwt.J):
x_j = torch.abs(bps[j])
x_j = self.conv1d[j](x_j)
y_j, _ = self.down[j](x_j)
Wx_r = self.conv1d[j](bps[j].real)
Wx_i = self.conv1d[j](bps[j].imag)
Ux = Wx_r ** 2 + Wx_i ** 2
y_j, _ = self.down[j](Ux)

B, _, N = y_j.shape
# reshape from (B, C*Q, N) to (B, C, Q, N)
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5 changes: 3 additions & 2 deletions tests/test_graph.py → tests/test_nn.py
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Original file line number Diff line number Diff line change
Expand Up @@ -7,7 +7,7 @@
@pytest.mark.parametrize("Q", [3, 4])
@pytest.mark.parametrize("T", [8, 16])
@pytest.mark.parametrize("padding_mode", ["symmetric", "zeros"])
def test_shape(J, Q, T, padding_mode):
def test_direct_shape(J, Q, T, padding_mode):
B, C, N = 2, 3, 2**(J+4)
x = torch.zeros(B, C, N)
graph = murenn.MuReNNDirect(
Expand All @@ -19,8 +19,9 @@ def test_shape(J, Q, T, padding_mode):
)
y = graph(x)
assert y.shape == (B, C, Q, J, 2**4)


def test_diff():
def test_direct_diff():
J, Q, T = 3, 4, 4
B, C, N = 2, 3, 2**(J+4)
x = torch.zeros(B, C, N)
Expand Down