c36bfefbf84ce280195e9589e44aac3ee688b11d,onnx_coreml/_operators_nd.py,,_convert_bn,#Any#Any#Any#Any#,294

Before Change

    var = node.input_tensors[node.inputs[4]] if node.inputs[4] in node.input_tensors else \
            np.ones(shape=channels, dtype=np.float32)

    if node.inputs[0] not in graph.shape_dict:
        return err.unsupported_op_configuration(builder, node, graph, "Shape of input unknown")

    rank = len(graph.shape_dict[node.inputs[0]])
    // ONNX converts B x C tensor into B x C x 1 hence
    // Rank 2 BN is mapped to Rank 3 BN
    if rank == 3:

After Change

    var = node.input_tensors[node.inputs[4]] if node.inputs[4] in node.input_tensors else \
            np.ones(shape=channels, dtype=np.float32)

    rank = builder._get_rank(node.inputs[0])
    // ONNX converts B x C tensor into B x C x 1 hence
    // Rank 2 BN is mapped to Rank 3 BN
    if rank == 3:
        // 1D Batch Norm

Instances