change dynameic shape
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@ -168,45 +168,45 @@ def create_predictor(args, mode, logger):
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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, 96, 20, 20],
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"conv2d_91.tmp_0": [1, 96, 10, 10],
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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, 96, 10, 10],
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"nearest_interp_v2_2.tmp_0": [1, 96, 20, 20],
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"conv2d_124.tmp_0": [1, 96, 20, 20],
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"nearest_interp_v2_3.tmp_0": [1, 24, 20, 20],
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"nearest_interp_v2_4.tmp_0": [1, 24, 20, 20],
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"nearest_interp_v2_5.tmp_0": [1, 24, 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, 96, 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, 2000, 2000],
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"conv2d_92.tmp_0": [1, 96, 400, 400],
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"conv2d_91.tmp_0": [1, 96, 200, 200],
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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, 96, 200, 200],
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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, 96, 400, 400],
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"nearest_interp_v2_3.tmp_0": [1, 24, 400, 400],
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"nearest_interp_v2_4.tmp_0": [1, 24, 400, 400],
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"nearest_interp_v2_5.tmp_0": [1, 24, 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, 96, 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, 96, 160, 160],
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"conv2d_91.tmp_0": [1, 96, 80, 80],
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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, 96, 80, 80],
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"nearest_interp_v2_2.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, 24, 160, 160],
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"nearest_interp_v2_4.tmp_0": [1, 24, 160, 160],
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"nearest_interp_v2_5.tmp_0": [1, 24, 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, 96, 40, 40]
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"nearest_interp_v2_0.tmp_0": [1, 256, 40, 40]
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}
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elif mode == "rec":
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min_input_shape = {"x": [args.rec_batch_num, 3, 32, 10]}
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