2.6.8

2.6.8

Issue

Conv.make_node() reads input_tensor_shape before the workaround that transposes
an NCHW input to NHWC, and never refreshes it.

The depthwise test compares group against input_tensor_shape[-1]. For a transposed
input this compares the channel count against a spatial dimension, the test fails, and
the node falls through to the grouped-conv path — producing a filter of shape
[C, K, K, 1] instead of a DepthwiseConv2D.

Symptom: in a MobileNet/ConvNeXt-style network only the first depthwise conv of each
stage converts correctly (it consumes a conv output directly), while the following ones
are silently degraded (they consume a residual Add whose input required the transpose).

The ONNX model is valid — depthwise is Conv with group=C and weight [C, 1, K, K].

Fix

Refresh input_tensor_shape from input_tensor right before the depthwise test.

What's Changed

• Fix depthwise Conv detection after NCHW->NHWC input transpose (Legacy converter) by @AL3708 in #959

Full Changelog: 2.6.7...2.6.8