Apply clang-format on repository
Code is formatted as per a revised clang format configuration
file(not part of this delivery). Version 14.0.6 is used.
Exclusion List:
- files with .cl extension
- files that are not strictly C/C++ (e.g. Android.bp, Sconscript ...)
And the following directories
- compute_kernel_writer/validation/
- tests/
- include/
- src/core/NEON/kernels/convolution/
- src/core/NEON/kernels/arm_gemm/
- src/core/NEON/kernels/arm_conv/
- data/
There will be a follow up for formatting of .cl files and the
files under tests/ and compute_kernel_writer/validation/.
Signed-off-by: Felix Thomasmathibalan <felixjohnny.thomasmathibalan@arm.com>
Change-Id: Ib7eb1fcf4e7537b9feaefcfc15098a804a3fde0a
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10391
Benchmark: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Gunes Bayir <gunes.bayir@arm.com>
diff --git a/examples/graph_edsr.h b/examples/graph_edsr.h
index 72012af..1161e4b 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 @@
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_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_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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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));
+ 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 });
+ 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;
}