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Pruning Bugfix: 1 out ch conv layer being treated as depthwise conv layer #5751

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Pruning Bugfix: 1 out ch conv layer being treated as depthwise conv layer #5751

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8 changes: 6 additions & 2 deletions nni/compression/speedup/dependency.py
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Original file line number Diff line number Diff line change
Expand Up @@ -316,8 +316,12 @@ def build_channel_dependency(graph_module: torch.fx.GraphModule,
if node.op == 'call_module':
submodule = graph_module.get_submodule(node.target)
# additional denpendency for (group number == output channel number) depth-wise conv:
if (isinstance(submodule, (torch.nn.Conv2d, torch.nn.ConvTranspose2d)) and submodule.groups == submodule.out_channels) \
or (isinstance(submodule, torch.nn.GroupNorm) and submodule.num_groups == submodule.num_channels):
if (
# check for conv layers with groups > 1, for depthwise convolutions
isinstance(submodule, (torch.nn.Conv2d, torch.nn.ConvTranspose2d))
and submodule.groups == submodule.out_channels
and submodule.out_channels != 1
) or (isinstance(submodule, torch.nn.GroupNorm) and submodule.num_groups == submodule.num_channels):
d_set = set([node] + find_adjacent_layers(node, graph_module, target_types, 'parent'))

elif node.op == 'call_function':
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