From e7f5f53f92fa78a6f7c206dca8f593c89ded039c Mon Sep 17 00:00:00 2001 From: Evgenya Stepyreva Date: Mon, 8 Jun 2020 13:00:54 +0300 Subject: [PATCH] [ MO ] Groupped conv fusion (#797) Fixed the group convolution fusion pass to properly get the feature dim in NCHW layout case. --- model-optimizer/mo/middle/passes/fusing/fuse_grouped_conv.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/model-optimizer/mo/middle/passes/fusing/fuse_grouped_conv.py b/model-optimizer/mo/middle/passes/fusing/fuse_grouped_conv.py index 80e3ce5..97d7abf 100644 --- a/model-optimizer/mo/middle/passes/fusing/fuse_grouped_conv.py +++ b/model-optimizer/mo/middle/passes/fusing/fuse_grouped_conv.py @@ -100,7 +100,7 @@ def concat_convolutions(graph: Graph, start_node: Node, last_node: Node): weights_value = np.array(weights_node.value) bias_value = np.array(bias_node.value) if has_biases else None - feature_dim = 3 if graph.graph['layout'] == 'NHWC' else 1 + feature_dim = 3 if graph.graph['layout'] == 'NHWC' else 0 for conv in conv_nodes[1:]: weights_value = np.concatenate((weights_value, conv.in_node(1).value), axis=feature_dim) -- 2.7.4