diff options
Diffstat (limited to 'examples/graph_edsr.h')
| -rw-r--r-- | examples/graph_edsr.h | 1360 |
1 files changed, 509 insertions, 851 deletions
diff --git a/examples/graph_edsr.h b/examples/graph_edsr.h index 72012afdcb..1161e4ba38 100644 --- a/examples/graph_edsr.h +++ b/examples/graph_edsr.h @@ -32,12 +32,12 @@ class GraphEdsr { public: - GraphEdsr() - : _graph(0, "EDSR") + GraphEdsr() : _graph(0, "EDSR") { } - bool setup(const arm_compute::utils::CommonGraphParams &common_params, const arm_compute::utils::SimpleOption<std::string> &expected_output_filename) + bool setup(const arm_compute::utils::CommonGraphParams &common_params, + const arm_compute::utils::SimpleOption<std::string> &expected_output_filename) { using namespace arm_compute; using namespace arm_compute::graph; @@ -47,1221 +47,879 @@ public: const auto &data_path = common_params.data_path; const auto &target = common_params.target; - NodeID id_upscale_net_FakeQuantWithMinMaxVars_transposed = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 12, 2, 2, 3 }, - DataType::QASYMM8, - QuantizationInfo(0.00393533194437623, 1), - DataLayout::NHWC }); - INode *node_upscale_net_FakeQuantWithMinMaxVars_transposed = _graph.node(id_upscale_net_FakeQuantWithMinMaxVars_transposed); - node_upscale_net_FakeQuantWithMinMaxVars_transposed->set_common_node_parameters(NodeParams{ "upscale_net_FakeQuantWithMinMaxVars_transposed", target }); - node_upscale_net_FakeQuantWithMinMaxVars_transposed->output(0)->set_accessor(get_weights_accessor(data_path, - "/cnn_data/edsr_model/upscale_net_FakeQuantWithMinMaxVars_transposed.npy", DataLayout::NHWC)); - - NodeID id_pre_upscale_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 12 }, - DataType::S32, - QuantizationInfo(2.9644968435604824e-06), - DataLayout::NHWC }); + NodeID id_upscale_net_FakeQuantWithMinMaxVars_transposed = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{12, 2, 2, 3}, DataType::QASYMM8, QuantizationInfo(0.00393533194437623, 1), DataLayout::NHWC}); + INode *node_upscale_net_FakeQuantWithMinMaxVars_transposed = + _graph.node(id_upscale_net_FakeQuantWithMinMaxVars_transposed); + node_upscale_net_FakeQuantWithMinMaxVars_transposed->set_common_node_parameters( + NodeParams{"upscale_net_FakeQuantWithMinMaxVars_transposed", target}); + node_upscale_net_FakeQuantWithMinMaxVars_transposed->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/upscale_net_FakeQuantWithMinMaxVars_transposed.npy", DataLayout::NHWC)); + + NodeID id_pre_upscale_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{12}, DataType::S32, QuantizationInfo(2.9644968435604824e-06), DataLayout::NHWC}); INode *node_pre_upscale_Conv2D_bias = _graph.node(id_pre_upscale_Conv2D_bias); - node_pre_upscale_Conv2D_bias->set_common_node_parameters(NodeParams{ "pre_upscale_Conv2D_bias", target }); - 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)); - - NodeID id_pre_upscale_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 12 }, - DataType::QASYMM8, - QuantizationInfo(0.000455576169770211, 128), - DataLayout::NHWC }); + node_pre_upscale_Conv2D_bias->set_common_node_parameters(NodeParams{"pre_upscale_Conv2D_bias", target}); + 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)); + + NodeID id_pre_upscale_FakeQuantWithMinMaxVars = + _graph.add_node<ConstNode>(TensorDescriptor{TensorShape{256, 3, 3, 12}, DataType::QASYMM8, + QuantizationInfo(0.000455576169770211, 128), DataLayout::NHWC}); INode *node_pre_upscale_FakeQuantWithMinMaxVars = _graph.node(id_pre_upscale_FakeQuantWithMinMaxVars); - node_pre_upscale_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "pre_upscale_FakeQuantWithMinMaxVars", target }); - node_pre_upscale_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/pre_upscale_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_post_residual_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.2760000345224398e-06), - DataLayout::NHWC }); + node_pre_upscale_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"pre_upscale_FakeQuantWithMinMaxVars", target}); + node_pre_upscale_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/pre_upscale_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_post_residual_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.2760000345224398e-06), DataLayout::NHWC}); INode *node_post_residual_Conv2D_bias = _graph.node(id_post_residual_Conv2D_bias); - node_post_residual_Conv2D_bias->set_common_node_parameters(NodeParams{ "post_residual_Conv2D_bias", target }); - 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)); + node_post_residual_Conv2D_bias->set_common_node_parameters(NodeParams{"post_residual_Conv2D_bias", target}); + 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)); NodeID id_post_residual_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00036424631252884865, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00036424631252884865, 129), DataLayout::NHWC}); INode *node_post_residual_FakeQuantWithMinMaxVars = _graph.node(id_post_residual_FakeQuantWithMinMaxVars); - node_post_residual_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "post_residual_FakeQuantWithMinMaxVars", target }); - node_post_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/post_residual_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_15_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_post_residual_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"post_residual_FakeQuantWithMinMaxVars", target}); + node_post_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/post_residual_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_15_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_15_y = _graph.node(id_mul_15_y); - node_mul_15_y->set_common_node_parameters(NodeParams{ "mul_15_y", target }); - node_mul_15_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_15_y.npy", DataLayout::NHWC)); - - NodeID id_block_15_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.2441644230420934e-06), - DataLayout::NHWC }); + node_mul_15_y->set_common_node_parameters(NodeParams{"mul_15_y", target}); + node_mul_15_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_15_y.npy", DataLayout::NHWC)); + + NodeID id_block_15_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.2441644230420934e-06), DataLayout::NHWC}); INode *node_block_15_1_Conv2D_bias = _graph.node(id_block_15_1_Conv2D_bias); - node_block_15_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_15_1_Conv2D_bias", target }); - 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)); + node_block_15_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_15_1_Conv2D_bias", target}); + 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)); NodeID id_block_15_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00037038681330159307, 125), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00037038681330159307, 125), DataLayout::NHWC}); INode *node_block_15_1_FakeQuantWithMinMaxVars = _graph.node(id_block_15_1_FakeQuantWithMinMaxVars); - node_block_15_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_15_1_FakeQuantWithMinMaxVars", target }); - node_block_15_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_15_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_14_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_15_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_15_1_FakeQuantWithMinMaxVars", target}); + node_block_15_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_15_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_14_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_14_y = _graph.node(id_mul_14_y); - node_mul_14_y->set_common_node_parameters(NodeParams{ "mul_14_y", target }); - node_mul_14_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_14_y.npy", DataLayout::NHWC)); - - NodeID id_block_14_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.3417260333881131e-06), - DataLayout::NHWC }); + node_mul_14_y->set_common_node_parameters(NodeParams{"mul_14_y", target}); + node_mul_14_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_14_y.npy", DataLayout::NHWC)); + + NodeID id_block_14_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.3417260333881131e-06), DataLayout::NHWC}); INode *node_block_14_1_Conv2D_bias = _graph.node(id_block_14_1_Conv2D_bias); - node_block_14_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_14_1_Conv2D_bias", target }); - 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)); + node_block_14_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_14_1_Conv2D_bias", target}); + 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)); NodeID id_block_14_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00040307495510205626, 127), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00040307495510205626, 127), DataLayout::NHWC}); INode *node_block_14_1_FakeQuantWithMinMaxVars = _graph.node(id_block_14_1_FakeQuantWithMinMaxVars); - node_block_14_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_14_1_FakeQuantWithMinMaxVars", target }); - node_block_14_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_14_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_13_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_14_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_14_1_FakeQuantWithMinMaxVars", target}); + node_block_14_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_14_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_13_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_13_y = _graph.node(id_mul_13_y); - node_mul_13_y->set_common_node_parameters(NodeParams{ "mul_13_y", target }); - node_mul_13_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_13_y.npy", DataLayout::NHWC)); - - NodeID id_block_13_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.2636977544389083e-06), - DataLayout::NHWC }); + node_mul_13_y->set_common_node_parameters(NodeParams{"mul_13_y", target}); + node_mul_13_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_13_y.npy", DataLayout::NHWC)); + + NodeID id_block_13_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.2636977544389083e-06), DataLayout::NHWC}); INode *node_block_13_1_Conv2D_bias = _graph.node(id_block_13_1_Conv2D_bias); - node_block_13_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_13_1_Conv2D_bias", target }); - 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)); + node_block_13_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_13_1_Conv2D_bias", target}); + 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)); NodeID id_block_13_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0003858553245663643, 131), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.0003858553245663643, 131), DataLayout::NHWC}); INode *node_block_13_1_FakeQuantWithMinMaxVars = _graph.node(id_block_13_1_FakeQuantWithMinMaxVars); - node_block_13_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_13_1_FakeQuantWithMinMaxVars", target }); - node_block_13_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_13_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_12_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_13_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_13_1_FakeQuantWithMinMaxVars", target}); + node_block_13_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_13_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_12_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_12_y = _graph.node(id_mul_12_y); - node_mul_12_y->set_common_node_parameters(NodeParams{ "mul_12_y", target }); - node_mul_12_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_12_y.npy", DataLayout::NHWC)); - - NodeID id_block_12_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.3479783547154511e-06), - DataLayout::NHWC }); + node_mul_12_y->set_common_node_parameters(NodeParams{"mul_12_y", target}); + node_mul_12_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_12_y.npy", DataLayout::NHWC)); + + NodeID id_block_12_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.3479783547154511e-06), DataLayout::NHWC}); INode *node_block_12_1_Conv2D_bias = _graph.node(id_block_12_1_Conv2D_bias); - node_block_12_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_12_1_Conv2D_bias", target }); - 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)); + node_block_12_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_12_1_Conv2D_bias", target}); + 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)); NodeID id_block_12_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00041212860378436744, 130), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00041212860378436744, 130), DataLayout::NHWC}); INode *node_block_12_1_FakeQuantWithMinMaxVars = _graph.node(id_block_12_1_FakeQuantWithMinMaxVars); - node_block_12_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_12_1_FakeQuantWithMinMaxVars", target }); - node_block_12_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_12_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_11_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_12_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_12_1_FakeQuantWithMinMaxVars", target}); + node_block_12_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_12_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_11_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_11_y = _graph.node(id_mul_11_y); - node_mul_11_y->set_common_node_parameters(NodeParams{ "mul_11_y", target }); - node_mul_11_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_11_y.npy", DataLayout::NHWC)); - - NodeID id_block_11_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.2847248171965475e-06), - DataLayout::NHWC }); + node_mul_11_y->set_common_node_parameters(NodeParams{"mul_11_y", target}); + node_mul_11_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_11_y.npy", DataLayout::NHWC)); + + NodeID id_block_11_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.2847248171965475e-06), DataLayout::NHWC}); INode *node_block_11_1_Conv2D_bias = _graph.node(id_block_11_1_Conv2D_bias); - node_block_11_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_11_1_Conv2D_bias", target }); - 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)); + node_block_11_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_11_1_Conv2D_bias", target}); + 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)); NodeID id_block_11_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00040296532097272575, 131), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00040296532097272575, 131), DataLayout::NHWC}); INode *node_block_11_1_FakeQuantWithMinMaxVars = _graph.node(id_block_11_1_FakeQuantWithMinMaxVars); - node_block_11_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_11_1_FakeQuantWithMinMaxVars", target }); - node_block_11_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_11_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_10_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_11_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_11_1_FakeQuantWithMinMaxVars", target}); + node_block_11_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_11_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_10_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_10_y = _graph.node(id_mul_10_y); - node_mul_10_y->set_common_node_parameters(NodeParams{ "mul_10_y", target }); - node_mul_10_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_10_y.npy", DataLayout::NHWC)); - - NodeID id_block_10_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.1997129831797793e-06), - DataLayout::NHWC }); + node_mul_10_y->set_common_node_parameters(NodeParams{"mul_10_y", target}); + node_mul_10_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_10_y.npy", DataLayout::NHWC)); + + NodeID id_block_10_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.1997129831797793e-06), DataLayout::NHWC}); INode *node_block_10_1_Conv2D_bias = _graph.node(id_block_10_1_Conv2D_bias); - node_block_10_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_10_1_Conv2D_bias", target }); - 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)); + node_block_10_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_10_1_Conv2D_bias", target}); + 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)); NodeID id_block_10_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00036640543839894235, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00036640543839894235, 129), DataLayout::NHWC}); INode *node_block_10_1_FakeQuantWithMinMaxVars = _graph.node(id_block_10_1_FakeQuantWithMinMaxVars); - node_block_10_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_10_1_FakeQuantWithMinMaxVars", target }); - node_block_10_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_10_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_9_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_10_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_10_1_FakeQuantWithMinMaxVars", target}); + node_block_10_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_10_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_9_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_9_y = _graph.node(id_mul_9_y); - node_mul_9_y->set_common_node_parameters(NodeParams{ "mul_9_y", target }); - node_mul_9_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_9_y.npy", DataLayout::NHWC)); - - NodeID id_block_9_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.1920226370421005e-06), - DataLayout::NHWC }); + node_mul_9_y->set_common_node_parameters(NodeParams{"mul_9_y", target}); + node_mul_9_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_9_y.npy", DataLayout::NHWC)); + + NodeID id_block_9_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.1920226370421005e-06), DataLayout::NHWC}); INode *node_block_9_1_Conv2D_bias = _graph.node(id_block_9_1_Conv2D_bias); - node_block_9_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_9_1_Conv2D_bias", target }); - 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)); + node_block_9_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_9_1_Conv2D_bias", target}); + 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)); NodeID id_block_9_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0003706997958943248, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.0003706997958943248, 129), DataLayout::NHWC}); INode *node_block_9_1_FakeQuantWithMinMaxVars = _graph.node(id_block_9_1_FakeQuantWithMinMaxVars); - node_block_9_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_9_1_FakeQuantWithMinMaxVars", target }); - node_block_9_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_9_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_8_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_9_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_9_1_FakeQuantWithMinMaxVars", target}); + node_block_9_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_9_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_8_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_8_y = _graph.node(id_mul_8_y); - node_mul_8_y->set_common_node_parameters(NodeParams{ "mul_8_y", target }); - node_mul_8_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_8_y.npy", DataLayout::NHWC)); - - NodeID id_block_8_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.218903321387188e-06), - DataLayout::NHWC }); + node_mul_8_y->set_common_node_parameters(NodeParams{"mul_8_y", target}); + node_mul_8_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_8_y.npy", DataLayout::NHWC)); + + NodeID id_block_8_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.218903321387188e-06), DataLayout::NHWC}); INode *node_block_8_1_Conv2D_bias = _graph.node(id_block_8_1_Conv2D_bias); - node_block_8_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_8_1_Conv2D_bias", target }); - 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)); + node_block_8_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_8_1_Conv2D_bias", target}); + 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)); NodeID id_block_8_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00038377835880964994, 127), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00038377835880964994, 127), DataLayout::NHWC}); INode *node_block_8_1_FakeQuantWithMinMaxVars = _graph.node(id_block_8_1_FakeQuantWithMinMaxVars); - node_block_8_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_8_1_FakeQuantWithMinMaxVars", target }); - node_block_8_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_8_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_7_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_8_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_8_1_FakeQuantWithMinMaxVars", target}); + node_block_8_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_8_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_7_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_7_y = _graph.node(id_mul_7_y); - node_mul_7_y->set_common_node_parameters(NodeParams{ "mul_7_y", target }); - node_mul_7_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_7_y.npy", DataLayout::NHWC)); - - NodeID id_block_7_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.257252392861119e-06), - DataLayout::NHWC }); + node_mul_7_y->set_common_node_parameters(NodeParams{"mul_7_y", target}); + node_mul_7_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_7_y.npy", DataLayout::NHWC)); + + NodeID id_block_7_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.257252392861119e-06), DataLayout::NHWC}); INode *node_block_7_1_Conv2D_bias = _graph.node(id_block_7_1_Conv2D_bias); - node_block_7_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_7_1_Conv2D_bias", target }); - 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)); + node_block_7_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_7_1_Conv2D_bias", target}); + 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)); NodeID id_block_7_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00039844686398282647, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00039844686398282647, 129), DataLayout::NHWC}); INode *node_block_7_1_FakeQuantWithMinMaxVars = _graph.node(id_block_7_1_FakeQuantWithMinMaxVars); - node_block_7_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_7_1_FakeQuantWithMinMaxVars", target }); - node_block_7_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_7_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_6_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_7_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_7_1_FakeQuantWithMinMaxVars", target}); + node_block_7_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_7_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_6_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_6_y = _graph.node(id_mul_6_y); - node_mul_6_y->set_common_node_parameters(NodeParams{ "mul_6_y", target }); - node_mul_6_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_6_y.npy", DataLayout::NHWC)); - - NodeID id_block_6_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.244850636794581e-06), - DataLayout::NHWC }); + node_mul_6_y->set_common_node_parameters(NodeParams{"mul_6_y", target}); + node_mul_6_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_6_y.npy", DataLayout::NHWC)); + + NodeID id_block_6_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.244850636794581e-06), DataLayout::NHWC}); INode *node_block_6_1_Conv2D_bias = _graph.node(id_block_6_1_Conv2D_bias); - node_block_6_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_6_1_Conv2D_bias", target }); - 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)); + node_block_6_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_6_1_Conv2D_bias", target}); + 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)); NodeID id_block_6_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00040187727427110076, 132), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00040187727427110076, 132), DataLayout::NHWC}); INode *node_block_6_1_FakeQuantWithMinMaxVars = _graph.node(id_block_6_1_FakeQuantWithMinMaxVars); - node_block_6_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_6_1_FakeQuantWithMinMaxVars", target }); - node_block_6_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_6_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_5_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_6_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_6_1_FakeQuantWithMinMaxVars", target}); + node_block_6_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_6_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_5_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_5_y = _graph.node(id_mul_5_y); - node_mul_5_y->set_common_node_parameters(NodeParams{ "mul_5_y", target }); - node_mul_5_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_5_y.npy", DataLayout::NHWC)); - - NodeID id_block_5_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.241092718373693e-06), - DataLayout::NHWC }); + node_mul_5_y->set_common_node_parameters(NodeParams{"mul_5_y", target}); + node_mul_5_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_5_y.npy", DataLayout::NHWC)); + + NodeID id_block_5_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.241092718373693e-06), DataLayout::NHWC}); INode *node_block_5_1_Conv2D_bias = _graph.node(id_block_5_1_Conv2D_bias); - node_block_5_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_5_1_Conv2D_bias", target }); - 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)); + node_block_5_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_5_1_Conv2D_bias", target}); + 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)); NodeID id_block_5_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0003938926674891263, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.0003938926674891263, 129), DataLayout::NHWC}); INode *node_block_5_1_FakeQuantWithMinMaxVars = _graph.node(id_block_5_1_FakeQuantWithMinMaxVars); - node_block_5_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_5_1_FakeQuantWithMinMaxVars", target }); - node_block_5_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_5_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_4_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_5_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_5_1_FakeQuantWithMinMaxVars", target}); + node_block_5_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_5_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_4_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_4_y = _graph.node(id_mul_4_y); - node_mul_4_y->set_common_node_parameters(NodeParams{ "mul_4_y", target }); - node_mul_4_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_4_y.npy", DataLayout::NHWC)); - - NodeID id_block_4_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.1748390988941537e-06), - DataLayout::NHWC }); + node_mul_4_y->set_common_node_parameters(NodeParams{"mul_4_y", target}); + node_mul_4_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_4_y.npy", DataLayout::NHWC)); + + NodeID id_block_4_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.1748390988941537e-06), DataLayout::NHWC}); INode *node_block_4_1_Conv2D_bias = _graph.node(id_block_4_1_Conv2D_bias); - node_block_4_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_4_1_Conv2D_bias", target }); - 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)); + node_block_4_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_4_1_Conv2D_bias", target}); + 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)); NodeID id_block_4_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0003788181929849088, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.0003788181929849088, 129), DataLayout::NHWC}); INode *node_block_4_1_FakeQuantWithMinMaxVars = _graph.node(id_block_4_1_FakeQuantWithMinMaxVars); - node_block_4_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_4_1_FakeQuantWithMinMaxVars", target }); - node_block_4_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_4_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_3_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_4_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_4_1_FakeQuantWithMinMaxVars", target}); + node_block_4_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_4_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_3_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_3_y = _graph.node(id_mul_3_y); - node_mul_3_y->set_common_node_parameters(NodeParams{ "mul_3_y", target }); - node_mul_3_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_3_y.npy", DataLayout::NHWC)); - - NodeID id_block_3_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.1937011095142225e-06), - DataLayout::NHWC }); + node_mul_3_y->set_common_node_parameters(NodeParams{"mul_3_y", target}); + node_mul_3_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_3_y.npy", DataLayout::NHWC)); + + NodeID id_block_3_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.1937011095142225e-06), DataLayout::NHWC}); INode *node_block_3_1_Conv2D_bias = _graph.node(id_block_3_1_Conv2D_bias); - node_block_3_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_3_1_Conv2D_bias", target }); - 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)); + node_block_3_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_3_1_Conv2D_bias", target}); + 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)); NodeID id_block_3_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0003944312920793891, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.0003944312920793891, 129), DataLayout::NHWC}); INode *node_block_3_1_FakeQuantWithMinMaxVars = _graph.node(id_block_3_1_FakeQuantWithMinMaxVars); - node_block_3_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_3_1_FakeQuantWithMinMaxVars", target }); - node_block_3_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_3_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_2_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_3_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_3_1_FakeQuantWithMinMaxVars", target}); + node_block_3_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_3_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_2_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_2_y = _graph.node(id_mul_2_y); - node_mul_2_y->set_common_node_parameters(NodeParams{ "mul_2_y", target }); - node_mul_2_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_2_y.npy", DataLayout::NHWC)); - - NodeID id_block_2_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.1634580232566805e-06), - DataLayout::NHWC }); + node_mul_2_y->set_common_node_parameters(NodeParams{"mul_2_y", target}); + node_mul_2_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_2_y.npy", DataLayout::NHWC)); + + NodeID id_block_2_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.1634580232566805e-06), DataLayout::NHWC}); INode *node_block_2_1_Conv2D_bias = _graph.node(id_block_2_1_Conv2D_bias); - node_block_2_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_2_1_Conv2D_bias", target }); - 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)); + node_block_2_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_2_1_Conv2D_bias", target}); + 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)); NodeID id_block_2_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0003789655165746808, 132), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.0003789655165746808, 132), DataLayout::NHWC}); INode *node_block_2_1_FakeQuantWithMinMaxVars = _graph.node(id_block_2_1_FakeQuantWithMinMaxVars); - node_block_2_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_2_1_FakeQuantWithMinMaxVars", target }); - node_block_2_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_2_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_1_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_2_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_2_1_FakeQuantWithMinMaxVars", target}); + node_block_2_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_2_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_1_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_1_y = _graph.node(id_mul_1_y); - node_mul_1_y->set_common_node_parameters(NodeParams{ "mul_1_y", target }); - node_mul_1_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_1_y.npy", DataLayout::NHWC)); - - NodeID id_block_1_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.197920255435747e-06), - DataLayout::NHWC }); + node_mul_1_y->set_common_node_parameters(NodeParams{"mul_1_y", target}); + node_mul_1_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_1_y.npy", DataLayout::NHWC)); + + NodeID id_block_1_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.197920255435747e-06), DataLayout::NHWC}); INode *node_block_1_1_Conv2D_bias = _graph.node(id_block_1_1_Conv2D_bias); - node_block_1_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_1_1_Conv2D_bias", target }); - 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)); + node_block_1_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_1_1_Conv2D_bias", target}); + 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)); NodeID id_block_1_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00038527738070115447, 132), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00038527738070115447, 132), DataLayout::NHWC}); INode *node_block_1_1_FakeQuantWithMinMaxVars = _graph.node(id_block_1_1_FakeQuantWithMinMaxVars); - node_block_1_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_1_1_FakeQuantWithMinMaxVars", target }); - node_block_1_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_1_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_mul_y = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 1 }, - DataType::QASYMM8, - QuantizationInfo(0.0003921568568330258), - DataLayout::NHWC }); + node_block_1_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_1_1_FakeQuantWithMinMaxVars", target}); + node_block_1_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_1_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_mul_y = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{1}, DataType::QASYMM8, QuantizationInfo(0.0003921568568330258), DataLayout::NHWC}); INode *node_mul_y = _graph.node(id_mul_y); - node_mul_y->set_common_node_parameters(NodeParams{ "mul_y", target }); - node_mul_y->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_y.npy", DataLayout::NHWC)); - - NodeID id_block_0_1_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.315485519626236e-06), - DataLayout::NHWC }); + node_mul_y->set_common_node_parameters(NodeParams{"mul_y", target}); + node_mul_y->output(0)->set_accessor( + get_weights_accessor(data_path, "/cnn_data/edsr_model/mul_y.npy", DataLayout::NHWC)); + + NodeID id_block_0_1_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.315485519626236e-06), DataLayout::NHWC}); INode *node_block_0_1_Conv2D_bias = _graph.node(id_block_0_1_Conv2D_bias); - node_block_0_1_Conv2D_bias->set_common_node_parameters(NodeParams{ "block_0_1_Conv2D_bias", target }); - 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)); + node_block_0_1_Conv2D_bias->set_common_node_parameters(NodeParams{"block_0_1_Conv2D_bias", target}); + 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)); NodeID id_block_0_1_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.00039420535904355347, 129), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{256, 3, 3, 256}, DataType::QASYMM8, + QuantizationInfo(0.00039420535904355347, 129), DataLayout::NHWC}); INode *node_block_0_1_FakeQuantWithMinMaxVars = _graph.node(id_block_0_1_FakeQuantWithMinMaxVars); - node_block_0_1_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "block_0_1_FakeQuantWithMinMaxVars", target }); - node_block_0_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/block_0_1_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); - - NodeID id_pre_residual_Conv2D_bias = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 256 }, - DataType::S32, - QuantizationInfo(1.7214160834555514e-06), - DataLayout::NHWC }); + node_block_0_1_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"block_0_1_FakeQuantWithMinMaxVars", target}); + node_block_0_1_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/block_0_1_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); + + NodeID id_pre_residual_Conv2D_bias = _graph.add_node<ConstNode>(TensorDescriptor{ + TensorShape{256}, DataType::S32, QuantizationInfo(1.7214160834555514e-06), DataLayout::NHWC}); INode *node_pre_residual_Conv2D_bias = _graph.node(id_pre_residual_Conv2D_bias); - node_pre_residual_Conv2D_bias->set_common_node_parameters(NodeParams{ "pre_residual_Conv2D_bias", target }); - 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)); + node_pre_residual_Conv2D_bias->set_common_node_parameters(NodeParams{"pre_residual_Conv2D_bias", target}); + 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)); NodeID id_pre_residual_FakeQuantWithMinMaxVars = _graph.add_node<ConstNode>( - TensorDescriptor - { - TensorShape{ 3, 3, 3, 256 }, - DataType::QASYMM8, - QuantizationInfo(0.0004389610840007663, 127), - DataLayout::NHWC }); + TensorDescriptor{TensorShape{3, 3, 3, 256}, DataType::QASYMM8, QuantizationInfo(0.0004389610840007663, 127), + DataLayout::NHWC}); INode *node_pre_residual_FakeQuantWithMinMaxVars = _graph.node(id_pre_residual_FakeQuantWithMinMaxVars); - node_pre_residual_FakeQuantWithMinMaxVars->set_common_node_parameters(NodeParams{ "pre_residual_FakeQuantWithMinMaxVars", target }); - node_pre_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor(data_path, "/cnn_data/edsr_model/pre_residual_FakeQuantWithMinMaxVars.npy", - DataLayout::NHWC)); + node_pre_residual_FakeQuantWithMinMaxVars->set_common_node_parameters( + NodeParams{"pre_residual_FakeQuantWithMinMaxVars", target}); + node_pre_residual_FakeQuantWithMinMaxVars->output(0)->set_accessor(get_weights_accessor( + data_path, "/cnn_data/edsr_model/pre_residual_FakeQuantWithMinMaxVars.npy", DataLayout::NHWC)); TensorShape input_shape{}; input_shape.set(0, 3, false).set(1, 360, false).set(2, 640, false).set(3, 1, false); NodeID id_input = _graph.add_node<InputNode>( - TensorDescriptor - { - input_shape, - DataType::QASYMM8, - QuantizationInfo(0.003921568859368563), - DataLayout::NHWC }); + TensorDescriptor{input_shape, DataType::QASYMM8, QuantizationInfo(0.003921568859368563), DataLayout::NHWC}); INode *node_input = _graph.node(id_input); - node_input->set_common_node_parameters(NodeParams{ "input", target }); + node_input->set_common_node_parameters(NodeParams{"input", target}); node_input->output(0)->set_accessor(get_input_accessor(common_params)); - NodeID id_pre_residual_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.0033370566088706255, 96)); + NodeID id_pre_residual_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.0033370566088706255, 96)); INode *node_pre_residual_BiasAdd = _graph.node(id_pre_residual_BiasAdd); - node_pre_residual_BiasAdd->set_common_node_parameters(NodeParams{ "pre_residual_BiasAdd", target }); + node_pre_residual_BiasAdd->set_common_node_parameters(NodeParams{"pre_residual_BiasAdd", target}); _graph.add_connection(id_input, 0, id_pre_residual_BiasAdd, 0); _graph.add_connection(id_pre_residual_FakeQuantWithMinMaxVars, 0, id_pre_residual_BiasAdd, 1); _graph.add_connection(id_pre_residual_Conv2D_bias, 0, id_pre_residual_BiasAdd, 2); - NodeID id_block_0_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.007344874087721109, 185)); + NodeID id_block_0_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.007344874087721109, 185)); INode *node_block_0_1_BiasAdd = _graph.node(id_block_0_1_BiasAdd); - node_block_0_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_0_1_BiasAdd", target }); + node_block_0_1_BiasAdd->set_common_node_parameters(NodeParams{"block_0_1_BiasAdd", target}); _graph.add_connection(id_pre_residual_BiasAdd, 0, id_block_0_1_BiasAdd, 0); _graph.add_connection(id_block_0_1_FakeQuantWithMinMaxVars, 0, id_block_0_1_BiasAdd, 1); _graph.add_connection(id_block_0_1_Conv2D_bias, 0, id_block_0_1_BiasAdd, 2); NodeID id_mul = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0006341293919831514, 174 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0006341293919831514, 174}}); INode *node_mul = _graph.node(id_mul); - node_mul->set_common_node_parameters(NodeParams{ "mul", target }); + node_mul->set_common_node_parameters(NodeParams{"mul", target}); _graph.add_connection(id_block_0_1_BiasAdd, 0, id_mul, 0); _graph.add_connection(id_mul_y, 0, id_mul, 1); NodeID id_add = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0031092411372810602, 95 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0031092411372810602, 95}}); INode *node_add = _graph.node(id_add); - node_add->set_common_node_parameters(NodeParams{ "add", target }); + node_add->set_common_node_parameters(NodeParams{"add", target}); _graph.add_connection(id_pre_residual_BiasAdd, 0, id_add, 0); _graph.add_connection(id_mul, 0, id_add, 1); - NodeID id_block_1_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.005333727691322565, 117)); + NodeID id_block_1_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.005333727691322565, 117)); INode *node_block_1_1_BiasAdd = _graph.node(id_block_1_1_BiasAdd); - node_block_1_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_1_1_BiasAdd", target }); + node_block_1_1_BiasAdd->set_common_node_parameters(NodeParams{"block_1_1_BiasAdd", target}); _graph.add_connection(id_add, 0, id_block_1_1_BiasAdd, 0); _graph.add_connection(id_block_1_1_FakeQuantWithMinMaxVars, 0, id_block_1_1_BiasAdd, 1); _graph.add_connection(id_block_1_1_Conv2D_bias, 0, id_block_1_1_BiasAdd, 2); NodeID id_mul_1 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004965941770933568, 122 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004965941770933568, 122}}); INode *node_mul_1 = _graph.node(id_mul_1); - node_mul_1->set_common_node_parameters(NodeParams{ "mul_1", target }); + node_mul_1->set_common_node_parameters(NodeParams{"mul_1", target}); _graph.add_connection(id_block_1_1_BiasAdd, 0, id_mul_1, 0); _graph.add_connection(id_mul_1_y, 0, id_mul_1, 1); NodeID id_add_1 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0030700892675668, 96 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0030700892675668, 96}}); INode *node_add_1 = _graph.node(id_add_1); - node_add_1->set_common_node_parameters(NodeParams{ "add_1", target }); + node_add_1->set_common_node_parameters(NodeParams{"add_1", target}); _graph.add_connection(id_add, 0, id_add_1, 0); _graph.add_connection(id_mul_1, 0, id_add_1, 1); - NodeID id_block_2_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.004199742339551449, 132)); + NodeID id_block_2_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.004199742339551449, 132)); INode *node_block_2_1_BiasAdd = _graph.node(id_block_2_1_BiasAdd); - node_block_2_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_2_1_BiasAdd", target }); + node_block_2_1_BiasAdd->set_common_node_parameters(NodeParams{"block_2_1_BiasAdd", target}); _graph.add_connection(id_add_1, 0, id_block_2_1_BiasAdd, 0); _graph.add_connection(id_block_2_1_FakeQuantWithMinMaxVars, 0, id_block_2_1_BiasAdd, 1); _graph.add_connection(id_block_2_1_Conv2D_bias, 0, id_block_2_1_BiasAdd, 2); NodeID id_mul_2 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004133903712499887, 130 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004133903712499887, 130}}); INode *node_mul_2 = _graph.node(id_mul_2); - node_mul_2->set_common_node_parameters(NodeParams{ "mul_2", target }); + node_mul_2->set_common_node_parameters(NodeParams{"mul_2", target}); _graph.add_connection(id_block_2_1_BiasAdd, 0, id_mul_2, 0); _graph.add_connection(id_mul_2_y, 0, id_mul_2, 1); NodeID id_add_2 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.003026385325938463, 94 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.003026385325938463, 94}}); INode *node_add_2 = _graph.node(id_add_2); - node_add_2->set_common_node_parameters(NodeParams{ "add_2", target }); + node_add_2->set_common_node_parameters(NodeParams{"add_2", target}); _graph.add_connection(id_add_1, 0, id_add_2, 0); _graph.add_connection(id_mul_2, 0, id_add_2, 1); - NodeID id_block_3_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.003977528307586908, 142)); + NodeID id_block_3_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.003977528307586908, 142)); INode *node_block_3_1_BiasAdd = _graph.node(id_block_3_1_BiasAdd); - node_block_3_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_3_1_BiasAdd", target }); + node_block_3_1_BiasAdd->set_common_node_parameters(NodeParams{"block_3_1_BiasAdd", target}); _graph.add_connection(id_add_2, 0, id_block_3_1_BiasAdd, 0); _graph.add_connection(id_block_3_1_FakeQuantWithMinMaxVars, 0, id_block_3_1_BiasAdd, 1); _graph.add_connection(id_block_3_1_Conv2D_bias, 0, id_block_3_1_BiasAdd, 2); NodeID id_mul_3 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0003943995980080217, 141 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0003943995980080217, 141}}); INode *node_mul_3 = _graph.node(id_mul_3); - node_mul_3->set_common_node_parameters(NodeParams{ "mul_3", target }); + node_mul_3->set_common_node_parameters(NodeParams{"mul_3", target}); _graph.add_connection(id_block_3_1_BiasAdd, 0, id_mul_3, 0); _graph.add_connection(id_mul_3_y, 0, id_mul_3, 1); NodeID id_add_3 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.003101327223703265, 98 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.003101327223703265, 98}}); INode *node_add_3 = _graph.node(id_add_3); - node_add_3->set_common_node_parameters(NodeParams{ "add_3", target }); + node_add_3->set_common_node_parameters(NodeParams{"add_3", target}); _graph.add_connection(id_add_2, 0, id_add_3, 0); _graph.add_connection(id_mul_3, 0, id_add_3, 1); - NodeID id_block_4_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.0045388080179691315, 146)); + NodeID id_block_4_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.0045388080179691315, 146)); INode *node_block_4_1_BiasAdd = _graph.node(id_block_4_1_BiasAdd); - node_block_4_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_4_1_BiasAdd", target }); + node_block_4_1_BiasAdd->set_common_node_parameters(NodeParams{"block_4_1_BiasAdd", target}); _graph.add_connection(id_add_3, 0, id_block_4_1_BiasAdd, 0); _graph.add_connection(id_block_4_1_FakeQuantWithMinMaxVars, 0, id_block_4_1_BiasAdd, 1); _graph.add_connection(id_block_4_1_Conv2D_bias, 0, id_block_4_1_BiasAdd, 2); NodeID id_mul_4 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.00044342130422592163, 143 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.00044342130422592163, 143}}); INode *node_mul_4 = _graph.node(id_mul_4); - node_mul_4->set_common_node_parameters(NodeParams{ "mul_4", target }); + node_mul_4->set_common_node_parameters(NodeParams{"mul_4", target}); _graph.add_connection(id_block_4_1_BiasAdd, 0, id_mul_4, 0); _graph.add_connection(id_mul_4_y, 0, id_mul_4, 1); NodeID id_add_4 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.003150839824229479, 98 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.003150839824229479, 98}}); INode *node_add_4 = _graph.node(id_add_4); - node_add_4->set_common_node_parameters(NodeParams{ "add_4", target }); + node_add_4->set_common_node_parameters(NodeParams{"add_4", target}); _graph.add_connection(id_add_3, 0, id_add_4, 0); _graph.add_connection(id_mul_4, 0, id_add_4, 1); - NodeID id_block_5_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.00402890844270587, 132)); + NodeID id_block_5_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.00402890844270587, 132)); INode *node_block_5_1_BiasAdd = _graph.node(id_block_5_1_BiasAdd); - node_block_5_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_5_1_BiasAdd", target }); + node_block_5_1_BiasAdd->set_common_node_parameters(NodeParams{"block_5_1_BiasAdd", target}); _graph.add_connection(id_add_4, 0, id_block_5_1_BiasAdd, 0); _graph.add_connection(id_block_5_1_FakeQuantWithMinMaxVars, 0, id_block_5_1_BiasAdd, 1); _graph.add_connection(id_block_5_1_Conv2D_bias, 0, id_block_5_1_BiasAdd, 2); NodeID id_mul_5 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004023382789455354, 132 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004023382789455354, 132}}); INode *node_mul_5 = _graph.node(id_mul_5); - node_mul_5->set_common_node_parameters(NodeParams{ "mul_5", target }); + node_mul_5->set_common_node_parameters(NodeParams{"mul_5", target}); _graph.add_connection(id_block_5_1_BiasAdd, 0, id_mul_5, 0); _graph.add_connection(id_mul_5_y, 0, id_mul_5, 1); NodeID id_add_5 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0030975888948887587, 94 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0030975888948887587, 94}}); INode *node_add_5 = _graph.node(id_add_5); - node_add_5->set_common_node_parameters(NodeParams{ "add_5", target }); + node_add_5->set_common_node_parameters(NodeParams{"add_5", target}); _graph.add_connection(id_add_4, 0, id_add_5, 0); _graph.add_connection(id_mul_5, 0, id_add_5, 1); - NodeID id_block_6_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.00421866774559021, 125)); + NodeID id_block_6_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.00421866774559021, 125)); INode *node_block_6_1_BiasAdd = _graph.node(id_block_6_1_BiasAdd); - node_block_6_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_6_1_BiasAdd", target }); + node_block_6_1_BiasAdd->set_common_node_parameters(NodeParams{"block_6_1_BiasAdd", target}); _graph.add_connection(id_add_5, 0, id_block_6_1_BiasAdd, 0); _graph.add_connection(id_block_6_1_FakeQuantWithMinMaxVars, 0, id_block_6_1_BiasAdd, 1); _graph.add_connection(id_block_6_1_Conv2D_bias, 0, id_block_6_1_BiasAdd, 2); NodeID id_mul_6 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.00041950203012675047, 125 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.00041950203012675047, 125}}); INode *node_mul_6 = _graph.node(id_mul_6); - node_mul_6->set_common_node_parameters(NodeParams{ "mul_6", target }); + node_mul_6->set_common_node_parameters(NodeParams{"mul_6", target}); _graph.add_connection(id_block_6_1_BiasAdd, 0, id_mul_6, 0); _graph.add_connection(id_mul_6_y, 0, id_mul_6, 1); NodeID id_add_6 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.003155382815748453, 92 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.003155382815748453, 92}}); INode *node_add_6 = _graph.node(id_add_6); - node_add_6->set_common_node_parameters(NodeParams{ "add_6", target }); + node_add_6->set_common_node_parameters(NodeParams{"add_6", target}); _graph.add_connection(id_add_5, 0, id_add_6, 0); _graph.add_connection(id_mul_6, 0, id_add_6, 1); - NodeID id_block_7_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.004250136204063892, 143)); + NodeID id_block_7_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.004250136204063892, 143)); INode *node_block_7_1_BiasAdd = _graph.node(id_block_7_1_BiasAdd); - node_block_7_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_7_1_BiasAdd", target }); + node_block_7_1_BiasAdd->set_common_node_parameters(NodeParams{"block_7_1_BiasAdd", target}); _graph.add_connection(id_add_6, 0, id_block_7_1_BiasAdd, 0); _graph.add_connection(id_block_7_1_FakeQuantWithMinMaxVars, 0, id_block_7_1_BiasAdd, 1); _graph.add_connection(id_block_7_1_Conv2D_bias, 0, id_block_7_1_BiasAdd, 2); NodeID id_mul_7 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.00042401350219734013, 142 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.00042401350219734013, 142}}); INode *node_mul_7 = _graph.node(id_mul_7); - node_mul_7->set_common_node_parameters(NodeParams{ "mul_7", target }); + node_mul_7->set_common_node_parameters(NodeParams{"mul_7", target}); _graph.add_connection(id_block_7_1_BiasAdd, 0, id_mul_7, 0); _graph.add_connection(id_mul_7_y, 0, id_mul_7, 1); NodeID id_add_7 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0031760605052113533, 86 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0031760605052113533, 86}}); INode *node_add_7 = _graph.node(id_add_7); - node_add_7->set_common_node_parameters(NodeParams{ "add_7", target }); + node_add_7->set_common_node_parameters(NodeParams{"add_7", target}); _graph.add_connection(id_add_6, 0, id_add_7, 0); _graph.add_connection(id_mul_7, 0, id_add_7, 1); - NodeID id_block_8_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.004277155734598637, 123)); + NodeID id_block_8_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.004277155734598637, 123)); INode *node_block_8_1_BiasAdd = _graph.node(id_block_8_1_BiasAdd); - node_block_8_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_8_1_BiasAdd", target }); + node_block_8_1_BiasAdd->set_common_node_parameters(NodeParams{"block_8_1_BiasAdd", target}); _graph.add_connection(id_add_7, 0, id_block_8_1_BiasAdd, 0); _graph.add_connection(id_block_8_1_FakeQuantWithMinMaxVars, 0, id_block_8_1_BiasAdd, 1); _graph.add_connection(id_block_8_1_Conv2D_bias, 0, id_block_8_1_BiasAdd, 2); NodeID id_mul_8 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.00042673019925132394, 123 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.00042673019925132394, 123}}); INode *node_mul_8 = _graph.node(id_mul_8); - node_mul_8->set_common_node_parameters(NodeParams{ "mul_8", target }); + node_mul_8->set_common_node_parameters(NodeParams{"mul_8", target}); _graph.add_connection(id_block_8_1_BiasAdd, 0, id_mul_8, 0); _graph.add_connection(id_mul_8_y, 0, id_mul_8, 1); NodeID id_add_8 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0032156009692698717, 86 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0032156009692698717, 86}}); INode *node_add_8 = _graph.node(id_add_8); - node_add_8->set_common_node_parameters(NodeParams{ "add_8", target }); + node_add_8->set_common_node_parameters(NodeParams{"add_8", target}); _graph.add_connection(id_add_7, 0, id_add_8, 0); _graph.add_connection(id_mul_8, 0, id_add_8, 1); - NodeID id_block_9_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.00445037754252553, 129)); + NodeID id_block_9_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.00445037754252553, 129)); INode *node_block_9_1_BiasAdd = _graph.node(id_block_9_1_BiasAdd); - node_block_9_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_9_1_BiasAdd", target }); + node_block_9_1_BiasAdd->set_common_node_parameters(NodeParams{"block_9_1_BiasAdd", target}); _graph.add_connection(id_add_8, 0, id_block_9_1_BiasAdd, 0); _graph.add_connection(id_block_9_1_FakeQuantWithMinMaxVars, 0, id_block_9_1_BiasAdd, 1); _graph.add_connection(id_block_9_1_Conv2D_bias, 0, id_block_9_1_BiasAdd, 2); NodeID id_mul_9 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004448975087143481, 129 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004448975087143481, 129}}); INode *node_mul_9 = _graph.node(id_mul_9); - node_mul_9->set_common_node_parameters(NodeParams{ "mul_9", target }); + node_mul_9->set_common_node_parameters(NodeParams{"mul_9", target}); _graph.add_connection(id_block_9_1_BiasAdd, 0, id_mul_9, 0); _graph.add_connection(id_mul_9_y, 0, id_mul_9, 1); NodeID id_add_9 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0032742770854383707, 80 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0032742770854383707, 80}}); INode *node_add_9 = _graph.node(id_add_9); - node_add_9->set_common_node_parameters(NodeParams{ "add_9", target }); + node_add_9->set_common_node_parameters(NodeParams{"add_9", target}); _graph.add_connection(id_add_8, 0, id_add_9, 0); _graph.add_connection(id_mul_9, 0, id_add_9, 1); - NodeID id_block_10_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.003614710411056876, 131)); + NodeID id_block_10_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.003614710411056876, 131)); INode *node_block_10_1_BiasAdd = _graph.node(id_block_10_1_BiasAdd); - node_block_10_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_10_1_BiasAdd", target }); + node_block_10_1_BiasAdd->set_common_node_parameters(NodeParams{"block_10_1_BiasAdd", target}); _graph.add_connection(id_add_9, 0, id_block_10_1_BiasAdd, 0); _graph.add_connection(id_block_10_1_FakeQuantWithMinMaxVars, 0, id_block_10_1_BiasAdd, 1); _graph.add_connection(id_block_10_1_Conv2D_bias, 0, id_block_10_1_BiasAdd, 2); NodeID id_mul_10 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.00036083892337046564, 130 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.00036083892337046564, 130}}); INode *node_mul_10 = _graph.node(id_mul_10); - node_mul_10->set_common_node_parameters(NodeParams{ "mul_10", target }); + node_mul_10->set_common_node_parameters(NodeParams{"mul_10", target}); _graph.add_connection(id_block_10_1_BiasAdd, 0, id_mul_10, 0); _graph.add_connection(id_mul_10_y, 0, id_mul_10, 1); NodeID id_add_10 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0031881770119071007, 81 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0031881770119071007, 81}}); INode *node_add_10 = _graph.node(id_add_10); - node_add_10->set_common_node_parameters(NodeParams{ "add_10", target }); + node_add_10->set_common_node_parameters(NodeParams{"add_10", target}); _graph.add_connection(id_add_9, 0, id_add_10, 0); _graph.add_connection(id_mul_10, 0, id_add_10, 1); - NodeID id_block_11_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.003969002980738878, 133)); + NodeID id_block_11_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.003969002980738878, 133)); INode *node_block_11_1_BiasAdd = _graph.node(id_block_11_1_BiasAdd); - node_block_11_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_11_1_BiasAdd", target }); + node_block_11_1_BiasAdd->set_common_node_parameters(NodeParams{"block_11_1_BiasAdd", target}); _graph.add_connection(id_add_10, 0, id_block_11_1_BiasAdd, 0); _graph.add_connection(id_block_11_1_FakeQuantWithMinMaxVars, 0, id_block_11_1_BiasAdd, 1); _graph.add_connection(id_block_11_1_Conv2D_bias, 0, id_block_11_1_BiasAdd, 2); NodeID id_mul_11 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0003968806122429669, 133 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0003968806122429669, 133}}); INode *node_mul_11 = _graph.node(id_mul_11); - node_mul_11->set_common_node_parameters(NodeParams{ "mul_11", target }); + node_mul_11->set_common_node_parameters(NodeParams{"mul_11", target}); _graph.add_connection(id_block_11_1_BiasAdd, 0, id_mul_11, 0); _graph.add_connection(id_mul_11_y, 0, id_mul_11, 1); NodeID id_add_11 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0032707711216062307, 80 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0032707711216062307, 80}}); INode *node_add_11 = _graph.node(id_add_11); - node_add_11->set_common_node_parameters(NodeParams{ "add_11", target }); + node_add_11->set_common_node_parameters(NodeParams{"add_11", target}); _graph.add_connection(id_add_10, 0, id_add_11, 0); _graph.add_connection(id_mul_11, 0, id_add_11, 1); - NodeID id_block_12_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.004366801120340824, 110)); + NodeID id_block_12_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.004366801120340824, 110)); INode *node_block_12_1_BiasAdd = _graph.node(id_block_12_1_BiasAdd); - node_block_12_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_12_1_BiasAdd", target }); + node_block_12_1_BiasAdd->set_common_node_parameters(NodeParams{"block_12_1_BiasAdd", target}); _graph.add_connection(id_add_11, 0, id_block_12_1_BiasAdd, 0); _graph.add_connection(id_block_12_1_FakeQuantWithMinMaxVars, 0, id_block_12_1_BiasAdd, 1); _graph.add_connection(id_block_12_1_Conv2D_bias, 0, id_block_12_1_BiasAdd, 2); NodeID id_mul_12 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004365936329122633, 110 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004365936329122633, 110}}); INode *node_mul_12 = _graph.node(id_mul_12); - node_mul_12->set_common_node_parameters(NodeParams{ "mul_12", target }); + node_mul_12->set_common_node_parameters(NodeParams{"mul_12", target}); _graph.add_connection(id_block_12_1_BiasAdd, 0, id_mul_12, 0); _graph.add_connection(id_mul_12_y, 0, id_mul_12, 1); NodeID id_add_12 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.003275055903941393, 79 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.003275055903941393, 79}}); INode *node_add_12 = _graph.node(id_add_12); - node_add_12->set_common_node_parameters(NodeParams{ "add_12", target }); + node_add_12->set_common_node_parameters(NodeParams{"add_12", target}); _graph.add_connection(id_add_11, 0, id_add_12, 0); _graph.add_connection(id_mul_12, 0, id_add_12, 1); - NodeID id_block_13_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.004386766813695431, 139)); + NodeID id_block_13_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.004386766813695431, 139)); INode *node_block_13_1_BiasAdd = _graph.node(id_block_13_1_BiasAdd); - node_block_13_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_13_1_BiasAdd", target }); + node_block_13_1_BiasAdd->set_common_node_parameters(NodeParams{"block_13_1_BiasAdd", target}); _graph.add_connection(id_add_12, 0, id_block_13_1_BiasAdd, 0); _graph.add_connection(id_block_13_1_FakeQuantWithMinMaxVars, 0, id_block_13_1_BiasAdd, 1); _graph.add_connection(id_block_13_1_Conv2D_bias, 0, id_block_13_1_BiasAdd, 2); NodeID id_mul_13 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004385628562886268, 139 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004385628562886268, 139}}); INode *node_mul_13 = _graph.node(id_mul_13); - node_mul_13->set_common_node_parameters(NodeParams{ "mul_13", target }); + node_mul_13->set_common_node_parameters(NodeParams{"mul_13", target}); _graph.add_connection(id_block_13_1_BiasAdd, 0, id_mul_13, 0); _graph.add_connection(id_mul_13_y, 0, id_mul_13, 1); NodeID id_add_13 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0033287261612713337, 78 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0033287261612713337, 78}}); INode *node_add_13 = _graph.node(id_add_13); - node_add_13->set_common_node_parameters(NodeParams{ "add_13", target }); + node_add_13->set_common_node_parameters(NodeParams{"add_13", target}); _graph.add_connection(id_add_12, 0, id_add_13, 0); _graph.add_connection(id_mul_13, 0, id_add_13, 1); - NodeID id_block_14_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.0038069337606430054, 130)); + NodeID id_block_14_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.0038069337606430054, 130)); INode *node_block_14_1_BiasAdd = _graph.node(id_block_14_1_BiasAdd); - node_block_14_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_14_1_BiasAdd", target }); + node_block_14_1_BiasAdd->set_common_node_parameters(NodeParams{"block_14_1_BiasAdd", target}); _graph.add_connection(id_add_13, 0, id_block_14_1_BiasAdd, 0); _graph.add_connection(id_block_14_1_FakeQuantWithMinMaxVars, 0, id_block_14_1_BiasAdd, 1); _graph.add_connection(id_block_14_1_Conv2D_bias, 0, id_block_14_1_BiasAdd, 2); NodeID id_mul_14 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.00037829321809113026, 130 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.00037829321809113026, 130}}); INode *node_mul_14 = _graph.node(id_mul_14); - node_mul_14->set_common_node_parameters(NodeParams{ "mul_14", target }); + node_mul_14->set_common_node_parameters(NodeParams{"mul_14", target}); _graph.add_connection(id_block_14_1_BiasAdd, 0, id_mul_14, 0); _graph.add_connection(id_mul_14_y, 0, id_mul_14, 1); NodeID id_add_14 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0033590947277843952, 77 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0033590947277843952, 77}}); INode *node_add_14 = _graph.node(id_add_14); - node_add_14->set_common_node_parameters(NodeParams{ "add_14", target }); + node_add_14->set_common_node_parameters(NodeParams{"add_14", target}); _graph.add_connection(id_add_13, 0, id_add_14, 0); _graph.add_connection(id_mul_14, 0, id_add_14, 1); - NodeID id_block_15_1_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.004009159281849861, 130)); + NodeID id_block_15_1_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.004009159281849861, 130)); INode *node_block_15_1_BiasAdd = _graph.node(id_block_15_1_BiasAdd); - node_block_15_1_BiasAdd->set_common_node_parameters(NodeParams{ "block_15_1_BiasAdd", target }); + node_block_15_1_BiasAdd->set_common_node_parameters(NodeParams{"block_15_1_BiasAdd", target}); _graph.add_connection(id_add_14, 0, id_block_15_1_BiasAdd, 0); _graph.add_connection(id_block_15_1_FakeQuantWithMinMaxVars, 0, id_block_15_1_BiasAdd, 1); _graph.add_connection(id_block_15_1_Conv2D_bias, 0, id_block_15_1_BiasAdd, 2); NodeID id_mul_15 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Mul, QuantizationInfo{ 0.0004008286341559142, 130 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Mul, QuantizationInfo{0.0004008286341559142, 130}}); INode *node_mul_15 = _graph.node(id_mul_15); - node_mul_15->set_common_node_parameters(NodeParams{ "mul_15", target }); + node_mul_15->set_common_node_parameters(NodeParams{"mul_15", target}); _graph.add_connection(id_block_15_1_BiasAdd, 0, id_mul_15, 0); _graph.add_connection(id_mul_15_y, 0, id_mul_15, 1); NodeID id_add_15 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0035031239967793226, 78 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0035031239967793226, 78}}); INode *node_add_15 = _graph.node(id_add_15); - node_add_15->set_common_node_parameters(NodeParams{ "add_15", target }); + node_add_15->set_common_node_parameters(NodeParams{"add_15", target}); _graph.add_connection(id_add_14, 0, id_add_15, 0); _graph.add_connection(id_mul_15, 0, id_add_15, 1); - NodeID id_post_residual_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.005167999770492315, 112)); + NodeID id_post_residual_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.005167999770492315, 112)); INode *node_post_residual_BiasAdd = _graph.node(id_post_residual_BiasAdd); - node_post_residual_BiasAdd->set_common_node_parameters(NodeParams{ "post_residual_BiasAdd", target }); + node_post_residual_BiasAdd->set_common_node_parameters(NodeParams{"post_residual_BiasAdd", target}); _graph.add_connection(id_add_15, 0, id_post_residual_BiasAdd, 0); _graph.add_connection(id_post_residual_FakeQuantWithMinMaxVars, 0, id_post_residual_BiasAdd, 1); _graph.add_connection(id_post_residual_Conv2D_bias, 0, id_post_residual_BiasAdd, 2); NodeID id_add_16 = _graph.add_node<EltwiseLayerNode>( - descriptors::EltwiseLayerDescriptor{ EltwiseOperation::Add, QuantizationInfo{ 0.0065071373246610165, 89 } }); + descriptors::EltwiseLayerDescriptor{EltwiseOperation::Add, QuantizationInfo{0.0065071373246610165, 89}}); INode *node_add_16 = _graph.node(id_add_16); - node_add_16->set_common_node_parameters(NodeParams{ "add_16", target }); + node_add_16->set_common_node_parameters(NodeParams{"add_16", target}); _graph.add_connection(id_post_residual_BiasAdd, 0, id_add_16, 0); _graph.add_connection(id_pre_residual_BiasAdd, 0, id_add_16, 1); - NodeID id_pre_upscale_BiasAdd = _graph.add_node<ConvolutionLayerNode>( - PadStrideInfo - { - 1, 1, - 1, 1, - 1, 1, - DimensionRoundingType::FLOOR }, - 1, - arm_compute::graph::ConvolutionMethod::Default, - FastMathHint::Disabled, - QuantizationInfo(0.005013593938201666, 26)); + NodeID id_pre_upscale_BiasAdd = + _graph.add_node<ConvolutionLayerNode>(PadStrideInfo{1, 1, 1, 1, 1, 1, DimensionRoundingType::FLOOR}, 1, + arm_compute::graph::ConvolutionMethod::Default, + FastMathHint::Disabled, QuantizationInfo(0.005013593938201666, 26)); INode *node_pre_upscale_BiasAdd = _graph.node(id_pre_upscale_BiasAdd); - node_pre_upscale_BiasAdd->set_common_node_parameters(NodeParams{ "pre_upscale_BiasAdd", target }); + node_pre_upscale_BiasAdd->set_common_node_parameters(NodeParams{"pre_upscale_BiasAdd", target}); _graph.add_connection(id_add_16, 0, id_pre_upscale_BiasAdd, 0); _graph.add_connection(id_pre_upscale_FakeQuantWithMinMaxVars, 0, id_pre_upscale_BiasAdd, 1); _graph.add_connection(id_pre_upscale_Conv2D_bias, 0, id_pre_upscale_BiasAdd, 2); NodeID id_upscale_net_FakeQuantWithMinMaxVars_1 = _graph.add_node<DeconvolutionLayerNode>( - descriptors::DeconvolutionLayerDescriptor - { - PadStrideInfo{ - 2, 2, - 0, 0, - 0, 0, - DimensionRoundingType::FLOOR }, - QuantizationInfo{ 0.004990961868315935, 26 } }); + descriptors::DeconvolutionLayerDescriptor{PadStrideInfo{2, 2, 0, 0, 0, 0, DimensionRoundingType::FLOOR}, + QuantizationInfo{0.004990961868315935, 26}}); INode *node_upscale_net_FakeQuantWithMinMaxVars_1 = _graph.node(id_upscale_net_FakeQuantWithMinMaxVars_1); - node_upscale_net_FakeQuantWithMinMaxVars_1->set_common_node_parameters(NodeParams{ "upscale_net_FakeQuantWithMinMaxVars_1", target }); + node_upscale_net_FakeQuantWithMinMaxVars_1->set_common_node_parameters( + NodeParams{"upscale_net_FakeQuantWithMinMaxVars_1", target}); _graph.add_connection(id_pre_upscale_BiasAdd, 0, id_upscale_net_FakeQuantWithMinMaxVars_1, 0); - _graph.add_connection(id_upscale_net_FakeQuantWithMinMaxVars_transposed, 0, id_upscale_net_FakeQuantWithMinMaxVars_1, 1); + _graph.add_connection(id_upscale_net_FakeQuantWithMinMaxVars_transposed, 0, + id_upscale_net_FakeQuantWithMinMaxVars_1, 1); TensorShape output_shape; output_shape.set(0, 3, false).set(1, 720, false).set(2, 1280, false).set(3, 1, false); NodeID id_output_140211982446376 = _graph.add_node<OutputNode>(); INode *node_output_140211982446376 = _graph.node(id_output_140211982446376); - node_output_140211982446376->set_common_node_parameters(NodeParams{ "output_140211982446376", target }); + node_output_140211982446376->set_common_node_parameters(NodeParams{"output_140211982446376", target}); _graph.add_connection(id_upscale_net_FakeQuantWithMinMaxVars_1, 0, id_output_140211982446376, 0); - node_output_140211982446376->input(0)->set_accessor(get_npy_output_accessor(expected_output_filename.value(), output_shape, common_params.data_type, - common_params.data_layout)); + node_output_140211982446376->input(0)->set_accessor(get_npy_output_accessor( + expected_output_filename.value(), output_shape, common_params.data_type, common_params.data_layout)); return true; } |