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Conv conversion: getting rank from weights if possible #524

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Conv conversion: getting rank from weights if possible #524

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9 changes: 8 additions & 1 deletion onnx_coreml/_operators_nd.py
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,14 @@ def load_input_constants(builder, node, graph, err):
def _add_conv_like_op(add_func, get_params_func, params_dict,
builder, node, graph, err):


# To do: Need to avoid dependence on rank for conversion since rank is not always available.

rank = builder._get_rank(node.inputs[0])

if rank < 0 and node.op_type == "Conv" and "w_shape" in params_dict:
rank = len(params_dict["w_shape"])

if rank == 4:
get_params_func(builder, node, graph, err, params_dict)
add_func(node.inputs, node.outputs, params_dict=params_dict, builder=builder, node=node, graph=graph, err=err)
Expand All @@ -67,7 +74,7 @@ def _add_conv_like_op(add_func, get_params_func, params_dict,
axes=axes
)
else:
return err.unsupported_op_configuration(builder, node, graph, "provided number axes {} not supported".format(rank))
return err.unsupported_op_configuration(builder, node, graph, "Unable to infer rank of the input. Invalid rank {} not supported".format(rank))


def add_broadcastable_op_chain(builder, node, err, add_op_function):
Expand Down