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Cortex-M: Fix activation tests for conv2d #16379

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rascani merged 2 commits into from
Dec 24, 2025
Merged

Cortex-M: Fix activation tests for conv2d #16379

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ba3437b
Cortex-M: Fix activation tests for conv2d
Dec 23, 2025
7f444f8
Merge branch 'main' into fix_cortex_m
rascani Dec 23, 2025
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22 changes: 11 additions & 11 deletions backends/cortex_m/test/ops/test_activation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -268,11 +268,11 @@ class CortexMConv2DHardswish(torch.nn.Module):
"executorch_exir_dialects_edge__ops_cortex_m_dequantize_per_tensor_default": 1,
}

def __init__(self, in_channels=1, out_channels=1):
def __init__(self):
super().__init__()
self.conv = torch.nn.Conv2d(1, 1, 1, padding=0, bias=False)
self.conv = torch.nn.Conv2d(2, 1, 1, padding=0, bias=False)
self.act = torch.nn.Hardswish()
self.conv.weight.data.fill_(1)
self.conv.weight.data.fill_(0.5)

def forward(self, x):
return self.act(self.conv(x))
Expand Down Expand Up @@ -344,9 +344,9 @@ class CortexMConv2DHardsigmoid(torch.nn.Module):

def __init__(self):
super().__init__()
self.conv = torch.nn.Conv2d(1, 1, 1, bias=False)
self.conv = torch.nn.Conv2d(2, 1, 1, bias=False)
self.act = torch.nn.Hardsigmoid(inplace=True)
self.conv.weight.data.fill_(1)
self.conv.weight.data.fill_(0.5)

def forward(self, x):
return self.act(self.conv(x))
Expand All @@ -369,8 +369,8 @@ class CortexMConv2DClampInplace(torch.nn.Module):

def __init__(self):
super().__init__()
self.conv = torch.nn.Conv2d(1, 1, 1, bias=False)
self.conv.weight.data.fill_(1)
self.conv = torch.nn.Conv2d(2, 1, 1, bias=False)
self.conv.weight.data.fill_(0.5)

def forward(self, x):
return torch.clamp_(self.conv(x), min=0.0, max=None)
Expand Down Expand Up @@ -490,19 +490,19 @@ def forward(self, x):
"conv2d_hardsigmoid_inplace": McuTestCase(
model=CortexMConv2DHardsigmoid(),
example_inputs=(
ramp_tensor(-4, 4, (1, 1, 6, 6)).to(memory_format=torch.channels_last),
ramp_tensor(-4, 4, (1, 2, 6, 6)).to(memory_format=torch.channels_last),
),
),
"conv2d_hardswish": McuTestCase(
model=CortexMConv2DHardswish(in_channels=1, out_channels=1),
model=CortexMConv2DHardswish(),
example_inputs=(
ramp_tensor(-3, 0, (1, 1, 1, 100)).to(memory_format=torch.channels_last),
ramp_tensor(-3, 0, (1, 2, 1, 100)).to(memory_format=torch.channels_last),
),
),
"conv2d_clamp_inplace": McuTestCase(
model=CortexMConv2DClampInplace(),
example_inputs=(
ramp_tensor(-4, 4, (1, 1, 1, 10)).to(memory_format=torch.channels_last),
ramp_tensor(-4, 4, (1, 2, 1, 10)).to(memory_format=torch.channels_last),
),
),
"linear_clamp": McuTestCase(
Expand Down
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