@@ -199,7 +199,7 @@ def export_program(
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return expo_program
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- def lower_ep_to_edge (
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+ def _lower_ep_to_edge (
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expo_program : ExportedProgram ,
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dump_graphs : bool = False ,
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constant_methods : Optional [dict [str , object ]] = None ,
@@ -250,7 +250,7 @@ def export_to_edge(
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expo_program = export_program (model , inputs )
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# Lower the model to edge IR.
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- edge_prog_manager = lower_ep_to_edge (expo_program , dump_graphs , constant_methods )
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+ edge_prog_manager = _lower_ep_to_edge (expo_program , dump_graphs , constant_methods )
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return edge_prog_manager
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@@ -272,22 +272,22 @@ def quantize_and_export_to_edge(
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dump_graphs = dump_graphs ,
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)
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- return lower_ep_to_edge (
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+ return _lower_ep_to_edge (
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quantized_model ,
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dump_graphs = dump_graphs ,
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constant_methods = constant_methods ,
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)
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- def lower_ep_to_cadence (
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+ def _lower_ep_to_cadence (
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program : ExportedProgram ,
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dump_graphs : bool = False ,
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opt_level : int = 1 ,
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) -> EdgeProgramManager :
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"""
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Lower an existing ExportedProgram to edge IR and apply frontend optimization passes.
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"""
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- edge_prog_manager = lower_ep_to_edge (program , dump_graphs = dump_graphs )
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+ edge_prog_manager = _lower_ep_to_edge (program , dump_graphs = dump_graphs )
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cadence_passes = get_cadence_passes (opt_level )
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# Run a couple required passes for quant/dequant ops
@@ -329,7 +329,7 @@ def quantize_and_export_to_cadence(
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"""
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quantized_model = quantize_pt2 (model , inputs )
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- return lower_ep_to_cadence (
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+ return _lower_ep_to_cadence (
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quantized_model ,
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opt_level = opt_level ,
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dump_graphs = dump_graphs ,
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