47 const auto &data_path = common_params.
data_path;
48 const auto &target = common_params.
target;
50 NodeID id_upscale_net_FakeQuantWithMinMaxVars_transposed = _graph.add_node<
ConstNode>(
57 INode *node_upscale_net_FakeQuantWithMinMaxVars_transposed = _graph.node(id_upscale_net_FakeQuantWithMinMaxVars_transposed);
59 node_upscale_net_FakeQuantWithMinMaxVars_transposed->output(0)->set_accessor(
get_weights_accessor(data_path,
60 "/cnn_data/edsr_model/upscale_net_FakeQuantWithMinMaxVars_transposed.npy", DataLayout::NHWC));
69 INode *node_pre_upscale_Conv2D_bias = _graph.node(id_pre_upscale_Conv2D_bias);
71 node_pre_upscale_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/pre_upscale_Conv2D_bias.npy", DataLayout::NHWC));
73 NodeID id_pre_upscale_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
80 INode *node_pre_upscale_FakeQuantWithMinMaxVars = _graph.node(id_pre_upscale_FakeQuantWithMinMaxVars);
82 node_pre_upscale_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/pre_upscale_FakeQuantWithMinMaxVars.npy",
92 INode *node_post_residual_Conv2D_bias = _graph.node(id_post_residual_Conv2D_bias);
94 node_post_residual_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/post_residual_Conv2D_bias.npy", DataLayout::NHWC));
96 NodeID id_post_residual_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
103 INode *node_post_residual_FakeQuantWithMinMaxVars = _graph.node(id_post_residual_FakeQuantWithMinMaxVars);
105 node_post_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/post_residual_FakeQuantWithMinMaxVars.npy",
115 INode *node_mul_15_y = _graph.node(id_mul_15_y);
117 node_mul_15_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_15_y.npy", DataLayout::NHWC));
126 INode *node_block_15_1_Conv2D_bias = _graph.node(id_block_15_1_Conv2D_bias);
128 node_block_15_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_15_1_Conv2D_bias.npy", DataLayout::NHWC));
130 NodeID id_block_15_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
137 INode *node_block_15_1_FakeQuantWithMinMaxVars = _graph.node(id_block_15_1_FakeQuantWithMinMaxVars);
139 node_block_15_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_15_1_FakeQuantWithMinMaxVars.npy",
149 INode *node_mul_14_y = _graph.node(id_mul_14_y);
151 node_mul_14_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_14_y.npy", DataLayout::NHWC));
160 INode *node_block_14_1_Conv2D_bias = _graph.node(id_block_14_1_Conv2D_bias);
162 node_block_14_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_14_1_Conv2D_bias.npy", DataLayout::NHWC));
164 NodeID id_block_14_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
171 INode *node_block_14_1_FakeQuantWithMinMaxVars = _graph.node(id_block_14_1_FakeQuantWithMinMaxVars);
173 node_block_14_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_14_1_FakeQuantWithMinMaxVars.npy",
183 INode *node_mul_13_y = _graph.node(id_mul_13_y);
185 node_mul_13_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_13_y.npy", DataLayout::NHWC));
194 INode *node_block_13_1_Conv2D_bias = _graph.node(id_block_13_1_Conv2D_bias);
196 node_block_13_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_13_1_Conv2D_bias.npy", DataLayout::NHWC));
198 NodeID id_block_13_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
205 INode *node_block_13_1_FakeQuantWithMinMaxVars = _graph.node(id_block_13_1_FakeQuantWithMinMaxVars);
207 node_block_13_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_13_1_FakeQuantWithMinMaxVars.npy",
217 INode *node_mul_12_y = _graph.node(id_mul_12_y);
219 node_mul_12_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_12_y.npy", DataLayout::NHWC));
228 INode *node_block_12_1_Conv2D_bias = _graph.node(id_block_12_1_Conv2D_bias);
230 node_block_12_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_12_1_Conv2D_bias.npy", DataLayout::NHWC));
232 NodeID id_block_12_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
239 INode *node_block_12_1_FakeQuantWithMinMaxVars = _graph.node(id_block_12_1_FakeQuantWithMinMaxVars);
241 node_block_12_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_12_1_FakeQuantWithMinMaxVars.npy",
251 INode *node_mul_11_y = _graph.node(id_mul_11_y);
253 node_mul_11_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_11_y.npy", DataLayout::NHWC));
262 INode *node_block_11_1_Conv2D_bias = _graph.node(id_block_11_1_Conv2D_bias);
264 node_block_11_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_11_1_Conv2D_bias.npy", DataLayout::NHWC));
266 NodeID id_block_11_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
273 INode *node_block_11_1_FakeQuantWithMinMaxVars = _graph.node(id_block_11_1_FakeQuantWithMinMaxVars);
275 node_block_11_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_11_1_FakeQuantWithMinMaxVars.npy",
285 INode *node_mul_10_y = _graph.node(id_mul_10_y);
287 node_mul_10_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_10_y.npy", DataLayout::NHWC));
296 INode *node_block_10_1_Conv2D_bias = _graph.node(id_block_10_1_Conv2D_bias);
298 node_block_10_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_10_1_Conv2D_bias.npy", DataLayout::NHWC));
300 NodeID id_block_10_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
307 INode *node_block_10_1_FakeQuantWithMinMaxVars = _graph.node(id_block_10_1_FakeQuantWithMinMaxVars);
309 node_block_10_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_10_1_FakeQuantWithMinMaxVars.npy",
319 INode *node_mul_9_y = _graph.node(id_mul_9_y);
321 node_mul_9_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_9_y.npy", DataLayout::NHWC));
330 INode *node_block_9_1_Conv2D_bias = _graph.node(id_block_9_1_Conv2D_bias);
332 node_block_9_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_9_1_Conv2D_bias.npy", DataLayout::NHWC));
334 NodeID id_block_9_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
341 INode *node_block_9_1_FakeQuantWithMinMaxVars = _graph.node(id_block_9_1_FakeQuantWithMinMaxVars);
343 node_block_9_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_9_1_FakeQuantWithMinMaxVars.npy",
353 INode *node_mul_8_y = _graph.node(id_mul_8_y);
355 node_mul_8_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_8_y.npy", DataLayout::NHWC));
364 INode *node_block_8_1_Conv2D_bias = _graph.node(id_block_8_1_Conv2D_bias);
366 node_block_8_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_8_1_Conv2D_bias.npy", DataLayout::NHWC));
368 NodeID id_block_8_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
375 INode *node_block_8_1_FakeQuantWithMinMaxVars = _graph.node(id_block_8_1_FakeQuantWithMinMaxVars);
377 node_block_8_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_8_1_FakeQuantWithMinMaxVars.npy",
387 INode *node_mul_7_y = _graph.node(id_mul_7_y);
389 node_mul_7_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_7_y.npy", DataLayout::NHWC));
398 INode *node_block_7_1_Conv2D_bias = _graph.node(id_block_7_1_Conv2D_bias);
400 node_block_7_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_7_1_Conv2D_bias.npy", DataLayout::NHWC));
402 NodeID id_block_7_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
409 INode *node_block_7_1_FakeQuantWithMinMaxVars = _graph.node(id_block_7_1_FakeQuantWithMinMaxVars);
411 node_block_7_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_7_1_FakeQuantWithMinMaxVars.npy",
421 INode *node_mul_6_y = _graph.node(id_mul_6_y);
423 node_mul_6_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_6_y.npy", DataLayout::NHWC));
432 INode *node_block_6_1_Conv2D_bias = _graph.node(id_block_6_1_Conv2D_bias);
434 node_block_6_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_6_1_Conv2D_bias.npy", DataLayout::NHWC));
436 NodeID id_block_6_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
443 INode *node_block_6_1_FakeQuantWithMinMaxVars = _graph.node(id_block_6_1_FakeQuantWithMinMaxVars);
445 node_block_6_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_6_1_FakeQuantWithMinMaxVars.npy",
455 INode *node_mul_5_y = _graph.node(id_mul_5_y);
457 node_mul_5_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_5_y.npy", DataLayout::NHWC));
466 INode *node_block_5_1_Conv2D_bias = _graph.node(id_block_5_1_Conv2D_bias);
468 node_block_5_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_5_1_Conv2D_bias.npy", DataLayout::NHWC));
470 NodeID id_block_5_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
477 INode *node_block_5_1_FakeQuantWithMinMaxVars = _graph.node(id_block_5_1_FakeQuantWithMinMaxVars);
479 node_block_5_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_5_1_FakeQuantWithMinMaxVars.npy",
489 INode *node_mul_4_y = _graph.node(id_mul_4_y);
491 node_mul_4_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_4_y.npy", DataLayout::NHWC));
500 INode *node_block_4_1_Conv2D_bias = _graph.node(id_block_4_1_Conv2D_bias);
502 node_block_4_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_4_1_Conv2D_bias.npy", DataLayout::NHWC));
504 NodeID id_block_4_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
511 INode *node_block_4_1_FakeQuantWithMinMaxVars = _graph.node(id_block_4_1_FakeQuantWithMinMaxVars);
513 node_block_4_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_4_1_FakeQuantWithMinMaxVars.npy",
523 INode *node_mul_3_y = _graph.node(id_mul_3_y);
525 node_mul_3_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_3_y.npy", DataLayout::NHWC));
534 INode *node_block_3_1_Conv2D_bias = _graph.node(id_block_3_1_Conv2D_bias);
536 node_block_3_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_3_1_Conv2D_bias.npy", DataLayout::NHWC));
538 NodeID id_block_3_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
545 INode *node_block_3_1_FakeQuantWithMinMaxVars = _graph.node(id_block_3_1_FakeQuantWithMinMaxVars);
547 node_block_3_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_3_1_FakeQuantWithMinMaxVars.npy",
557 INode *node_mul_2_y = _graph.node(id_mul_2_y);
559 node_mul_2_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_2_y.npy", DataLayout::NHWC));
568 INode *node_block_2_1_Conv2D_bias = _graph.node(id_block_2_1_Conv2D_bias);
570 node_block_2_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_2_1_Conv2D_bias.npy", DataLayout::NHWC));
572 NodeID id_block_2_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
579 INode *node_block_2_1_FakeQuantWithMinMaxVars = _graph.node(id_block_2_1_FakeQuantWithMinMaxVars);
581 node_block_2_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_2_1_FakeQuantWithMinMaxVars.npy",
591 INode *node_mul_1_y = _graph.node(id_mul_1_y);
593 node_mul_1_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_1_y.npy", DataLayout::NHWC));
602 INode *node_block_1_1_Conv2D_bias = _graph.node(id_block_1_1_Conv2D_bias);
604 node_block_1_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_1_1_Conv2D_bias.npy", DataLayout::NHWC));
606 NodeID id_block_1_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
613 INode *node_block_1_1_FakeQuantWithMinMaxVars = _graph.node(id_block_1_1_FakeQuantWithMinMaxVars);
615 node_block_1_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_1_1_FakeQuantWithMinMaxVars.npy",
625 INode *node_mul_y = _graph.node(id_mul_y);
627 node_mul_y->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/mul_y.npy", DataLayout::NHWC));
636 INode *node_block_0_1_Conv2D_bias = _graph.node(id_block_0_1_Conv2D_bias);
638 node_block_0_1_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_0_1_Conv2D_bias.npy", DataLayout::NHWC));
640 NodeID id_block_0_1_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
647 INode *node_block_0_1_FakeQuantWithMinMaxVars = _graph.node(id_block_0_1_FakeQuantWithMinMaxVars);
649 node_block_0_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/block_0_1_FakeQuantWithMinMaxVars.npy",
659 INode *node_pre_residual_Conv2D_bias = _graph.node(id_pre_residual_Conv2D_bias);
661 node_pre_residual_Conv2D_bias->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/pre_residual_Conv2D_bias.npy", DataLayout::NHWC));
663 NodeID id_pre_residual_FakeQuantWithMinMaxVars = _graph.add_node<
ConstNode>(
670 INode *node_pre_residual_FakeQuantWithMinMaxVars = _graph.node(id_pre_residual_FakeQuantWithMinMaxVars);
672 node_pre_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(
get_weights_accessor(data_path,
"/cnn_data/edsr_model/pre_residual_FakeQuantWithMinMaxVars.npy",
685 INode *node_input = _graph.node(id_input);
695 DimensionRoundingType::FLOOR },
698 FastMathHint::Disabled,
700 INode *node_pre_residual_BiasAdd = _graph.node(id_pre_residual_BiasAdd);
702 _graph.add_connection(id_input, 0, id_pre_residual_BiasAdd, 0);
703 _graph.add_connection(id_pre_residual_FakeQuantWithMinMaxVars, 0, id_pre_residual_BiasAdd, 1);
704 _graph.add_connection(id_pre_residual_Conv2D_bias, 0, id_pre_residual_BiasAdd, 2);
712 DimensionRoundingType::FLOOR },
715 FastMathHint::Disabled,
717 INode *node_block_0_1_BiasAdd = _graph.node(id_block_0_1_BiasAdd);
719 _graph.add_connection(id_pre_residual_BiasAdd, 0, id_block_0_1_BiasAdd, 0);
720 _graph.add_connection(id_block_0_1_FakeQuantWithMinMaxVars, 0, id_block_0_1_BiasAdd, 1);
721 _graph.add_connection(id_block_0_1_Conv2D_bias, 0, id_block_0_1_BiasAdd, 2);
725 INode *node_mul = _graph.node(id_mul);
727 _graph.add_connection(id_block_0_1_BiasAdd, 0, id_mul, 0);
728 _graph.add_connection(id_mul_y, 0, id_mul, 1);
732 INode *node_add = _graph.node(id_add);
734 _graph.add_connection(id_pre_residual_BiasAdd, 0, id_add, 0);
735 _graph.add_connection(id_mul, 0, id_add, 1);
743 DimensionRoundingType::FLOOR },
746 FastMathHint::Disabled,
748 INode *node_block_1_1_BiasAdd = _graph.node(id_block_1_1_BiasAdd);
750 _graph.add_connection(id_add, 0, id_block_1_1_BiasAdd, 0);
751 _graph.add_connection(id_block_1_1_FakeQuantWithMinMaxVars, 0, id_block_1_1_BiasAdd, 1);
752 _graph.add_connection(id_block_1_1_Conv2D_bias, 0, id_block_1_1_BiasAdd, 2);
756 INode *node_mul_1 = _graph.node(id_mul_1);
758 _graph.add_connection(id_block_1_1_BiasAdd, 0, id_mul_1, 0);
759 _graph.add_connection(id_mul_1_y, 0, id_mul_1, 1);
763 INode *node_add_1 = _graph.node(id_add_1);
765 _graph.add_connection(id_add, 0, id_add_1, 0);
766 _graph.add_connection(id_mul_1, 0, id_add_1, 1);
774 DimensionRoundingType::FLOOR },
777 FastMathHint::Disabled,
779 INode *node_block_2_1_BiasAdd = _graph.node(id_block_2_1_BiasAdd);
781 _graph.add_connection(id_add_1, 0, id_block_2_1_BiasAdd, 0);
782 _graph.add_connection(id_block_2_1_FakeQuantWithMinMaxVars, 0, id_block_2_1_BiasAdd, 1);
783 _graph.add_connection(id_block_2_1_Conv2D_bias, 0, id_block_2_1_BiasAdd, 2);
787 INode *node_mul_2 = _graph.node(id_mul_2);
789 _graph.add_connection(id_block_2_1_BiasAdd, 0, id_mul_2, 0);
790 _graph.add_connection(id_mul_2_y, 0, id_mul_2, 1);
794 INode *node_add_2 = _graph.node(id_add_2);
796 _graph.add_connection(id_add_1, 0, id_add_2, 0);
797 _graph.add_connection(id_mul_2, 0, id_add_2, 1);
805 DimensionRoundingType::FLOOR },
808 FastMathHint::Disabled,
810 INode *node_block_3_1_BiasAdd = _graph.node(id_block_3_1_BiasAdd);
812 _graph.add_connection(id_add_2, 0, id_block_3_1_BiasAdd, 0);
813 _graph.add_connection(id_block_3_1_FakeQuantWithMinMaxVars, 0, id_block_3_1_BiasAdd, 1);
814 _graph.add_connection(id_block_3_1_Conv2D_bias, 0, id_block_3_1_BiasAdd, 2);
818 INode *node_mul_3 = _graph.node(id_mul_3);
820 _graph.add_connection(id_block_3_1_BiasAdd, 0, id_mul_3, 0);
821 _graph.add_connection(id_mul_3_y, 0, id_mul_3, 1);
825 INode *node_add_3 = _graph.node(id_add_3);
827 _graph.add_connection(id_add_2, 0, id_add_3, 0);
828 _graph.add_connection(id_mul_3, 0, id_add_3, 1);
836 DimensionRoundingType::FLOOR },
839 FastMathHint::Disabled,
841 INode *node_block_4_1_BiasAdd = _graph.node(id_block_4_1_BiasAdd);
843 _graph.add_connection(id_add_3, 0, id_block_4_1_BiasAdd, 0);
844 _graph.add_connection(id_block_4_1_FakeQuantWithMinMaxVars, 0, id_block_4_1_BiasAdd, 1);
845 _graph.add_connection(id_block_4_1_Conv2D_bias, 0, id_block_4_1_BiasAdd, 2);
849 INode *node_mul_4 = _graph.node(id_mul_4);
851 _graph.add_connection(id_block_4_1_BiasAdd, 0, id_mul_4, 0);
852 _graph.add_connection(id_mul_4_y, 0, id_mul_4, 1);
856 INode *node_add_4 = _graph.node(id_add_4);
858 _graph.add_connection(id_add_3, 0, id_add_4, 0);
859 _graph.add_connection(id_mul_4, 0, id_add_4, 1);
867 DimensionRoundingType::FLOOR },
870 FastMathHint::Disabled,
872 INode *node_block_5_1_BiasAdd = _graph.node(id_block_5_1_BiasAdd);
874 _graph.add_connection(id_add_4, 0, id_block_5_1_BiasAdd, 0);
875 _graph.add_connection(id_block_5_1_FakeQuantWithMinMaxVars, 0, id_block_5_1_BiasAdd, 1);
876 _graph.add_connection(id_block_5_1_Conv2D_bias, 0, id_block_5_1_BiasAdd, 2);
880 INode *node_mul_5 = _graph.node(id_mul_5);
882 _graph.add_connection(id_block_5_1_BiasAdd, 0, id_mul_5, 0);
883 _graph.add_connection(id_mul_5_y, 0, id_mul_5, 1);
887 INode *node_add_5 = _graph.node(id_add_5);
889 _graph.add_connection(id_add_4, 0, id_add_5, 0);
890 _graph.add_connection(id_mul_5, 0, id_add_5, 1);
898 DimensionRoundingType::FLOOR },
901 FastMathHint::Disabled,
903 INode *node_block_6_1_BiasAdd = _graph.node(id_block_6_1_BiasAdd);
905 _graph.add_connection(id_add_5, 0, id_block_6_1_BiasAdd, 0);
906 _graph.add_connection(id_block_6_1_FakeQuantWithMinMaxVars, 0, id_block_6_1_BiasAdd, 1);
907 _graph.add_connection(id_block_6_1_Conv2D_bias, 0, id_block_6_1_BiasAdd, 2);
911 INode *node_mul_6 = _graph.node(id_mul_6);
913 _graph.add_connection(id_block_6_1_BiasAdd, 0, id_mul_6, 0);
914 _graph.add_connection(id_mul_6_y, 0, id_mul_6, 1);
918 INode *node_add_6 = _graph.node(id_add_6);
920 _graph.add_connection(id_add_5, 0, id_add_6, 0);
921 _graph.add_connection(id_mul_6, 0, id_add_6, 1);
929 DimensionRoundingType::FLOOR },
932 FastMathHint::Disabled,
934 INode *node_block_7_1_BiasAdd = _graph.node(id_block_7_1_BiasAdd);
936 _graph.add_connection(id_add_6, 0, id_block_7_1_BiasAdd, 0);
937 _graph.add_connection(id_block_7_1_FakeQuantWithMinMaxVars, 0, id_block_7_1_BiasAdd, 1);
938 _graph.add_connection(id_block_7_1_Conv2D_bias, 0, id_block_7_1_BiasAdd, 2);
942 INode *node_mul_7 = _graph.node(id_mul_7);
944 _graph.add_connection(id_block_7_1_BiasAdd, 0, id_mul_7, 0);
945 _graph.add_connection(id_mul_7_y, 0, id_mul_7, 1);
949 INode *node_add_7 = _graph.node(id_add_7);
951 _graph.add_connection(id_add_6, 0, id_add_7, 0);
952 _graph.add_connection(id_mul_7, 0, id_add_7, 1);
960 DimensionRoundingType::FLOOR },
963 FastMathHint::Disabled,
965 INode *node_block_8_1_BiasAdd = _graph.node(id_block_8_1_BiasAdd);
967 _graph.add_connection(id_add_7, 0, id_block_8_1_BiasAdd, 0);
968 _graph.add_connection(id_block_8_1_FakeQuantWithMinMaxVars, 0, id_block_8_1_BiasAdd, 1);
969 _graph.add_connection(id_block_8_1_Conv2D_bias, 0, id_block_8_1_BiasAdd, 2);
973 INode *node_mul_8 = _graph.node(id_mul_8);
975 _graph.add_connection(id_block_8_1_BiasAdd, 0, id_mul_8, 0);
976 _graph.add_connection(id_mul_8_y, 0, id_mul_8, 1);
980 INode *node_add_8 = _graph.node(id_add_8);
982 _graph.add_connection(id_add_7, 0, id_add_8, 0);
983 _graph.add_connection(id_mul_8, 0, id_add_8, 1);
991 DimensionRoundingType::FLOOR },
994 FastMathHint::Disabled,
996 INode *node_block_9_1_BiasAdd = _graph.node(id_block_9_1_BiasAdd);
998 _graph.add_connection(id_add_8, 0, id_block_9_1_BiasAdd, 0);
999 _graph.add_connection(id_block_9_1_FakeQuantWithMinMaxVars, 0, id_block_9_1_BiasAdd, 1);
1000 _graph.add_connection(id_block_9_1_Conv2D_bias, 0, id_block_9_1_BiasAdd, 2);
1004 INode *node_mul_9 = _graph.node(id_mul_9);
1006 _graph.add_connection(id_block_9_1_BiasAdd, 0, id_mul_9, 0);
1007 _graph.add_connection(id_mul_9_y, 0, id_mul_9, 1);
1011 INode *node_add_9 = _graph.node(id_add_9);
1013 _graph.add_connection(id_add_8, 0, id_add_9, 0);
1014 _graph.add_connection(id_mul_9, 0, id_add_9, 1);
1022 DimensionRoundingType::FLOOR },
1025 FastMathHint::Disabled,
1027 INode *node_block_10_1_BiasAdd = _graph.node(id_block_10_1_BiasAdd);
1029 _graph.add_connection(id_add_9, 0, id_block_10_1_BiasAdd, 0);
1030 _graph.add_connection(id_block_10_1_FakeQuantWithMinMaxVars, 0, id_block_10_1_BiasAdd, 1);
1031 _graph.add_connection(id_block_10_1_Conv2D_bias, 0, id_block_10_1_BiasAdd, 2);
1035 INode *node_mul_10 = _graph.node(id_mul_10);
1037 _graph.add_connection(id_block_10_1_BiasAdd, 0, id_mul_10, 0);
1038 _graph.add_connection(id_mul_10_y, 0, id_mul_10, 1);
1042 INode *node_add_10 = _graph.node(id_add_10);
1044 _graph.add_connection(id_add_9, 0, id_add_10, 0);
1045 _graph.add_connection(id_mul_10, 0, id_add_10, 1);
1053 DimensionRoundingType::FLOOR },
1056 FastMathHint::Disabled,
1058 INode *node_block_11_1_BiasAdd = _graph.node(id_block_11_1_BiasAdd);
1060 _graph.add_connection(id_add_10, 0, id_block_11_1_BiasAdd, 0);
1061 _graph.add_connection(id_block_11_1_FakeQuantWithMinMaxVars, 0, id_block_11_1_BiasAdd, 1);
1062 _graph.add_connection(id_block_11_1_Conv2D_bias, 0, id_block_11_1_BiasAdd, 2);
1066 INode *node_mul_11 = _graph.node(id_mul_11);
1068 _graph.add_connection(id_block_11_1_BiasAdd, 0, id_mul_11, 0);
1069 _graph.add_connection(id_mul_11_y, 0, id_mul_11, 1);
1073 INode *node_add_11 = _graph.node(id_add_11);
1075 _graph.add_connection(id_add_10, 0, id_add_11, 0);
1076 _graph.add_connection(id_mul_11, 0, id_add_11, 1);
1084 DimensionRoundingType::FLOOR },
1087 FastMathHint::Disabled,
1089 INode *node_block_12_1_BiasAdd = _graph.node(id_block_12_1_BiasAdd);
1091 _graph.add_connection(id_add_11, 0, id_block_12_1_BiasAdd, 0);
1092 _graph.add_connection(id_block_12_1_FakeQuantWithMinMaxVars, 0, id_block_12_1_BiasAdd, 1);
1093 _graph.add_connection(id_block_12_1_Conv2D_bias, 0, id_block_12_1_BiasAdd, 2);
1097 INode *node_mul_12 = _graph.node(id_mul_12);
1099 _graph.add_connection(id_block_12_1_BiasAdd, 0, id_mul_12, 0);
1100 _graph.add_connection(id_mul_12_y, 0, id_mul_12, 1);
1104 INode *node_add_12 = _graph.node(id_add_12);
1106 _graph.add_connection(id_add_11, 0, id_add_12, 0);
1107 _graph.add_connection(id_mul_12, 0, id_add_12, 1);
1115 DimensionRoundingType::FLOOR },
1118 FastMathHint::Disabled,
1120 INode *node_block_13_1_BiasAdd = _graph.node(id_block_13_1_BiasAdd);
1122 _graph.add_connection(id_add_12, 0, id_block_13_1_BiasAdd, 0);
1123 _graph.add_connection(id_block_13_1_FakeQuantWithMinMaxVars, 0, id_block_13_1_BiasAdd, 1);
1124 _graph.add_connection(id_block_13_1_Conv2D_bias, 0, id_block_13_1_BiasAdd, 2);
1128 INode *node_mul_13 = _graph.node(id_mul_13);
1130 _graph.add_connection(id_block_13_1_BiasAdd, 0, id_mul_13, 0);
1131 _graph.add_connection(id_mul_13_y, 0, id_mul_13, 1);
1135 INode *node_add_13 = _graph.node(id_add_13);
1137 _graph.add_connection(id_add_12, 0, id_add_13, 0);
1138 _graph.add_connection(id_mul_13, 0, id_add_13, 1);
1146 DimensionRoundingType::FLOOR },
1149 FastMathHint::Disabled,
1151 INode *node_block_14_1_BiasAdd = _graph.node(id_block_14_1_BiasAdd);
1153 _graph.add_connection(id_add_13, 0, id_block_14_1_BiasAdd, 0);
1154 _graph.add_connection(id_block_14_1_FakeQuantWithMinMaxVars, 0, id_block_14_1_BiasAdd, 1);
1155 _graph.add_connection(id_block_14_1_Conv2D_bias, 0, id_block_14_1_BiasAdd, 2);
1159 INode *node_mul_14 = _graph.node(id_mul_14);
1161 _graph.add_connection(id_block_14_1_BiasAdd, 0, id_mul_14, 0);
1162 _graph.add_connection(id_mul_14_y, 0, id_mul_14, 1);
1166 INode *node_add_14 = _graph.node(id_add_14);
1168 _graph.add_connection(id_add_13, 0, id_add_14, 0);
1169 _graph.add_connection(id_mul_14, 0, id_add_14, 1);
1177 DimensionRoundingType::FLOOR },
1180 FastMathHint::Disabled,
1182 INode *node_block_15_1_BiasAdd = _graph.node(id_block_15_1_BiasAdd);
1184 _graph.add_connection(id_add_14, 0, id_block_15_1_BiasAdd, 0);
1185 _graph.add_connection(id_block_15_1_FakeQuantWithMinMaxVars, 0, id_block_15_1_BiasAdd, 1);
1186 _graph.add_connection(id_block_15_1_Conv2D_bias, 0, id_block_15_1_BiasAdd, 2);
1190 INode *node_mul_15 = _graph.node(id_mul_15);
1192 _graph.add_connection(id_block_15_1_BiasAdd, 0, id_mul_15, 0);
1193 _graph.add_connection(id_mul_15_y, 0, id_mul_15, 1);
1197 INode *node_add_15 = _graph.node(id_add_15);
1199 _graph.add_connection(id_add_14, 0, id_add_15, 0);
1200 _graph.add_connection(id_mul_15, 0, id_add_15, 1);
1208 DimensionRoundingType::FLOOR },
1211 FastMathHint::Disabled,
1213 INode *node_post_residual_BiasAdd = _graph.node(id_post_residual_BiasAdd);
1215 _graph.add_connection(id_add_15, 0, id_post_residual_BiasAdd, 0);
1216 _graph.add_connection(id_post_residual_FakeQuantWithMinMaxVars, 0, id_post_residual_BiasAdd, 1);
1217 _graph.add_connection(id_post_residual_Conv2D_bias, 0, id_post_residual_BiasAdd, 2);
1221 INode *node_add_16 = _graph.node(id_add_16);
1223 _graph.add_connection(id_post_residual_BiasAdd, 0, id_add_16, 0);
1224 _graph.add_connection(id_pre_residual_BiasAdd, 0, id_add_16, 1);
1232 DimensionRoundingType::FLOOR },
1235 FastMathHint::Disabled,
1237 INode *node_pre_upscale_BiasAdd = _graph.node(id_pre_upscale_BiasAdd);
1239 _graph.add_connection(id_add_16, 0, id_pre_upscale_BiasAdd, 0);
1240 _graph.add_connection(id_pre_upscale_FakeQuantWithMinMaxVars, 0, id_pre_upscale_BiasAdd, 1);
1241 _graph.add_connection(id_pre_upscale_Conv2D_bias, 0, id_pre_upscale_BiasAdd, 2);
1250 DimensionRoundingType::FLOOR },
1252 INode *node_upscale_net_FakeQuantWithMinMaxVars_1 = _graph.node(id_upscale_net_FakeQuantWithMinMaxVars_1);
1254 _graph.add_connection(id_pre_upscale_BiasAdd, 0, id_upscale_net_FakeQuantWithMinMaxVars_1, 0);
1255 _graph.add_connection(id_upscale_net_FakeQuantWithMinMaxVars_transposed, 0, id_upscale_net_FakeQuantWithMinMaxVars_1, 1);
1257 output_shape.
set(0, 3,
false).
set(1, 720,
false).
set(2, 1280,
false).
set(3, 1,
false);
1260 INode *node_output_140211982446376 = _graph.node(id_output_140211982446376);
1262 _graph.add_connection(id_upscale_net_FakeQuantWithMinMaxVars_1, 0, id_output_140211982446376, 0);
Deconvolution layer descriptor.
std::unique_ptr< graph::ITensorAccessor > get_input_accessor(const arm_compute::utils::CommonGraphParams &graph_parameters, std::unique_ptr< IPreprocessor > preprocessor=nullptr, bool bgr=true)
Generates appropriate input accessor according to the specified graph parameters. ...
arm_compute::graph::Target target
std::unique_ptr< graph::ITensorAccessor > get_npy_output_accessor(const std::string &npy_path, TensorShape shape, DataType data_type, DataLayout data_layout=DataLayout::NCHW, std::ostream &output_stream=std::cout)
Generates appropriate npy output accessor according to the specified npy_path.
arm_compute::DataLayout data_layout
Copyright (c) 2017-2021 Arm Limited.
Quantization information.
TensorShape input_shape
Validate test suite is to test ARM_COMPUTE_RETURN_ON_* macros we use to check the validity of given a...
Elementwise layer descriptor.
Padding and stride information class.
const T & value() const
Get the option value.
void set_common_node_parameters(NodeParams common_params)
Sets common node parameters.
std::unique_ptr< graph::ITensorAccessor > get_weights_accessor(const std::string &path, const std::string &data_file, DataLayout file_layout=DataLayout::NCHW)
Generates appropriate weights accessor according to the specified path.
Deconvolution Layer node.
Default approach using internal heuristics.
arm_compute::DataType data_type
TensorShape & set(size_t dimension, size_t value, bool apply_dim_correction=true, bool increase_dim_unit=true)
Accessor to set the value of one of the dimensions.