rm dyg shape for trt (#7221)
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13f7b1c8b3
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f68571b2f6
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@ -231,89 +231,10 @@ def create_predictor(args, mode, logger):
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)
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config.enable_tuned_tensorrt_dynamic_shape(
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args.shape_info_filename, True)
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use_dynamic_shape = True
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if mode == "det":
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min_input_shape = {
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"x": [1, 3, 50, 50],
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"conv2d_92.tmp_0": [1, 120, 20, 20],
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"conv2d_91.tmp_0": [1, 24, 10, 10],
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"conv2d_59.tmp_0": [1, 96, 20, 20],
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"nearest_interp_v2_1.tmp_0": [1, 256, 10, 10],
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"nearest_interp_v2_2.tmp_0": [1, 256, 20, 20],
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"conv2d_124.tmp_0": [1, 256, 20, 20],
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"nearest_interp_v2_3.tmp_0": [1, 64, 20, 20],
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"nearest_interp_v2_4.tmp_0": [1, 64, 20, 20],
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"nearest_interp_v2_5.tmp_0": [1, 64, 20, 20],
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"elementwise_add_7": [1, 56, 2, 2],
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"nearest_interp_v2_0.tmp_0": [1, 256, 2, 2]
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}
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max_input_shape = {
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"x": [1, 3, 1536, 1536],
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"conv2d_92.tmp_0": [1, 120, 400, 400],
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"conv2d_91.tmp_0": [1, 24, 200, 200],
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"conv2d_59.tmp_0": [1, 96, 400, 400],
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"nearest_interp_v2_1.tmp_0": [1, 256, 200, 200],
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"conv2d_124.tmp_0": [1, 256, 400, 400],
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"nearest_interp_v2_2.tmp_0": [1, 256, 400, 400],
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"nearest_interp_v2_3.tmp_0": [1, 64, 400, 400],
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"nearest_interp_v2_4.tmp_0": [1, 64, 400, 400],
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"nearest_interp_v2_5.tmp_0": [1, 64, 400, 400],
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"elementwise_add_7": [1, 56, 400, 400],
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"nearest_interp_v2_0.tmp_0": [1, 256, 400, 400]
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}
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opt_input_shape = {
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"x": [1, 3, 640, 640],
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"conv2d_92.tmp_0": [1, 120, 160, 160],
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"conv2d_91.tmp_0": [1, 24, 80, 80],
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"conv2d_59.tmp_0": [1, 96, 160, 160],
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"nearest_interp_v2_1.tmp_0": [1, 256, 80, 80],
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"nearest_interp_v2_2.tmp_0": [1, 256, 160, 160],
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"conv2d_124.tmp_0": [1, 256, 160, 160],
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"nearest_interp_v2_3.tmp_0": [1, 64, 160, 160],
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"nearest_interp_v2_4.tmp_0": [1, 64, 160, 160],
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"nearest_interp_v2_5.tmp_0": [1, 64, 160, 160],
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"elementwise_add_7": [1, 56, 40, 40],
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"nearest_interp_v2_0.tmp_0": [1, 256, 40, 40]
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}
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min_pact_shape = {
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"nearest_interp_v2_26.tmp_0": [1, 256, 20, 20],
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"nearest_interp_v2_27.tmp_0": [1, 64, 20, 20],
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"nearest_interp_v2_28.tmp_0": [1, 64, 20, 20],
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"nearest_interp_v2_29.tmp_0": [1, 64, 20, 20]
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}
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max_pact_shape = {
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"nearest_interp_v2_26.tmp_0": [1, 256, 400, 400],
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"nearest_interp_v2_27.tmp_0": [1, 64, 400, 400],
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"nearest_interp_v2_28.tmp_0": [1, 64, 400, 400],
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"nearest_interp_v2_29.tmp_0": [1, 64, 400, 400]
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}
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opt_pact_shape = {
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"nearest_interp_v2_26.tmp_0": [1, 256, 160, 160],
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"nearest_interp_v2_27.tmp_0": [1, 64, 160, 160],
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"nearest_interp_v2_28.tmp_0": [1, 64, 160, 160],
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"nearest_interp_v2_29.tmp_0": [1, 64, 160, 160]
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}
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min_input_shape.update(min_pact_shape)
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max_input_shape.update(max_pact_shape)
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opt_input_shape.update(opt_pact_shape)
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elif mode == "rec":
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if args.rec_algorithm not in ["CRNN", "SVTR_LCNet"]:
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use_dynamic_shape = False
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imgH = int(args.rec_image_shape.split(',')[-2])
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min_input_shape = {"x": [1, 3, imgH, 10]}
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max_input_shape = {"x": [args.rec_batch_num, 3, imgH, 2304]}
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opt_input_shape = {"x": [args.rec_batch_num, 3, imgH, 320]}
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config.exp_disable_tensorrt_ops(["transpose2"])
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elif mode == "cls":
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min_input_shape = {"x": [1, 3, 48, 10]}
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max_input_shape = {"x": [args.rec_batch_num, 3, 48, 1024]}
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opt_input_shape = {"x": [args.rec_batch_num, 3, 48, 320]}
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else:
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use_dynamic_shape = False
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if use_dynamic_shape:
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config.set_trt_dynamic_shape_info(
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min_input_shape, max_input_shape, opt_input_shape)
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logger.info(
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f"when using tensorrt, dynamic shape is a suggested option, you can use '--shape_info_filename=shape.txt' for offline dygnamic shape tuning"
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)
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elif args.use_xpu:
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config.enable_xpu(10 * 1024 * 1024)
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