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@@ -121,6 +121,9 @@ def run_model(args, graph, inputs, outputs, data): |
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# must use level0 to avoid unintended opr modification |
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graph.options.graph_opt_level = 0 |
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if args.weight_preprocess: |
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graph.enable_weight_preprocess() |
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logger.info("input tensors: ") |
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for k, v in data.items(): |
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logger.info(" {}: {}".format(k, v.shape)) |
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@@ -161,8 +164,8 @@ def run_model(args, graph, inputs, outputs, data): |
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func.wait() |
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return [oup_node.get_value().numpy() for oup_node in output_dict.values()] |
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if args.warm_up: |
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logger.info("warming up") |
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for i in range(args.warm_up): |
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logger.info("warming up {}".format(i)) |
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run() |
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total_time = 0 |
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@@ -276,8 +279,9 @@ def main(): |
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) |
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parser.add_argument( |
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"--warm-up", |
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action="store_true", |
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help="warm up model before do timing " " for better estimation", |
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type=int, |
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default=0, |
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help="times of warm up model before do timing " " for better estimation", |
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) |
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parser.add_argument( |
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"--verbose", |
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@@ -394,6 +398,13 @@ def main(): |
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parser.add_argument( |
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"--custom-op-lib", type=str, help="path of the custom op", |
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) |
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parser.add_argument( |
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"--weight-preprocess", |
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action="store_true", |
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help="Execute operators with weight preprocess, which can" |
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"optimize the operator execution time with algo of winograd," |
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"im2col ,etc.,but it may consume more memory.", |
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) |
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args = parser.parse_args() |
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