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 https://github.com/PINTO0309/onnx2tf/pull/959 Full Changelog: https://github.com/PINTO0309/onnx2tf/compare/2.6.7...2.6.8