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-rw-r--r--examples/graph_vgg_vdsr.cpp81
1 files changed, 41 insertions, 40 deletions
diff --git a/examples/graph_vgg_vdsr.cpp b/examples/graph_vgg_vdsr.cpp
index c308236f5b..a6cd337f82 100644
--- a/examples/graph_vgg_vdsr.cpp
+++ b/examples/graph_vgg_vdsr.cpp
@@ -1,5 +1,5 @@
/*
- * Copyright (c) 2018-2020 ARM Limited.
+ * Copyright (c) 2018-2021 Arm Limited.
*
* SPDX-License-Identifier: MIT
*
@@ -22,6 +22,7 @@
* SOFTWARE.
*/
#include "arm_compute/graph.h"
+
#include "support/ToolchainSupport.h"
#include "utils/CommonGraphOptions.h"
#include "utils/GraphUtils.h"
@@ -36,8 +37,7 @@ using namespace arm_compute::graph_utils;
class GraphVDSRExample : public Example
{
public:
- GraphVDSRExample()
- : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "VDSR")
+ GraphVDSRExample() : cmd_parser(), common_opts(cmd_parser), common_params(), graph(0, "VDSR")
{
model_input_width = cmd_parser.add_option<SimpleOption<unsigned int>>("image-width", 192);
model_input_height = cmd_parser.add_option<SimpleOption<unsigned int>>("image-height", 192);
@@ -46,7 +46,7 @@ public:
model_input_width->set_help("Input image width.");
model_input_height->set_help("Input image height.");
}
- GraphVDSRExample(const GraphVDSRExample &) = delete;
+ GraphVDSRExample(const GraphVDSRExample &) = delete;
GraphVDSRExample &operator=(const GraphVDSRExample &) = delete;
~GraphVDSRExample() override = default;
bool do_setup(int argc, char **argv) override
@@ -59,7 +59,7 @@ public:
common_params = consume_common_graph_parameters(common_opts);
// Return when help menu is requested
- if(common_params.help)
+ if (common_params.help)
{
cmd_parser.print_help(argv[0]);
return false;
@@ -79,18 +79,20 @@ public:
const std::string model_path = "/cnn_data/vdsr_model/";
// Create a preprocessor object
- std::unique_ptr<IPreprocessor> preprocessor = arm_compute::support::cpp14::make_unique<TFPreproccessor>();
+ std::unique_ptr<IPreprocessor> preprocessor = std::make_unique<TFPreproccessor>();
// Create input descriptor
- const TensorShape tensor_shape = permute_shape(TensorShape(image_width, image_height, 1U, 1U), DataLayout::NCHW, common_params.data_layout);
- TensorDescriptor input_descriptor = TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout);
+ const TensorShape tensor_shape =
+ permute_shape(TensorShape(image_width, image_height, 1U, common_params.batches), DataLayout::NCHW,
+ common_params.data_layout);
+ TensorDescriptor input_descriptor =
+ TensorDescriptor(tensor_shape, common_params.data_type).set_layout(common_params.data_layout);
// Set weights trained layout
const DataLayout weights_layout = DataLayout::NCHW;
// Note: Quantization info are random and used only for benchmarking purposes
- graph << common_params.target
- << common_params.fast_math_hint
+ graph << common_params.target << common_params.fast_math_hint
<< InputLayer(input_descriptor.set_quantization_info(QuantizationInfo(0.0078125f, 128)),
get_input_accessor(common_params, std::move(preprocessor), false));
@@ -98,49 +100,48 @@ public:
SubStream right(graph);
// Layer 1
- right << ConvolutionLayer(
- 3U, 3U, 64U,
- get_weights_accessor(data_path, "conv0_w.npy", weights_layout),
- get_weights_accessor(data_path, "conv0_b.npy"),
- PadStrideInfo(1, 1, 1, 1), 1, QuantizationInfo(0.031778190285f, 156), QuantizationInfo(0.0784313753247f, 128))
- .set_name("conv0")
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv0/Relu");
+ right << ConvolutionLayer(3U, 3U, 64U, get_weights_accessor(data_path, "conv0_w.npy", weights_layout),
+ get_weights_accessor(data_path, "conv0_b.npy"), PadStrideInfo(1, 1, 1, 1), 1,
+ QuantizationInfo(0.031778190285f, 156), QuantizationInfo(0.0784313753247f, 128))
+ .set_name("conv0")
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
+ .set_name("conv0/Relu");
// Rest 17 layers
- for(unsigned int i = 1; i < 19; ++i)
+ for (unsigned int i = 1; i < 19; ++i)
{
const std::string conv_w_path = "conv" + arm_compute::support::cpp11::to_string(i) + "_w.npy";
const std::string conv_b_path = "conv" + arm_compute::support::cpp11::to_string(i) + "_b.npy";
const std::string conv_name = "conv" + arm_compute::support::cpp11::to_string(i);
- right << ConvolutionLayer(
- 3U, 3U, 64U,
- get_weights_accessor(data_path, conv_w_path, weights_layout),
- get_weights_accessor(data_path, conv_b_path),
- PadStrideInfo(1, 1, 1, 1), 1, QuantizationInfo(0.015851572156f, 93))
- .set_name(conv_name)
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name(conv_name + "/Relu");
+ right << ConvolutionLayer(3U, 3U, 64U, get_weights_accessor(data_path, conv_w_path, weights_layout),
+ get_weights_accessor(data_path, conv_b_path), PadStrideInfo(1, 1, 1, 1), 1,
+ QuantizationInfo(0.015851572156f, 93))
+ .set_name(conv_name)
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
+ .set_name(conv_name + "/Relu");
}
// Final layer
- right << ConvolutionLayer(
- 3U, 3U, 1U,
- get_weights_accessor(data_path, "conv20_w.npy", weights_layout),
- get_weights_accessor(data_path, "conv20_b.npy"),
- PadStrideInfo(1, 1, 1, 1), 1, QuantizationInfo(0.015851572156f, 93))
- .set_name("conv20")
- << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU)).set_name("conv20/Relu");
+ right << ConvolutionLayer(3U, 3U, 1U, get_weights_accessor(data_path, "conv20_w.npy", weights_layout),
+ get_weights_accessor(data_path, "conv20_b.npy"), PadStrideInfo(1, 1, 1, 1), 1,
+ QuantizationInfo(0.015851572156f, 93))
+ .set_name("conv20")
+ << ActivationLayer(ActivationLayerInfo(ActivationLayerInfo::ActivationFunction::RELU))
+ .set_name("conv20/Relu");
// Add residual to input
graph << EltwiseLayer(std::move(left), std::move(right), EltwiseOperation::Add).set_name("add")
- << OutputLayer(arm_compute::support::cpp14::make_unique<DummyAccessor>(0));
+ << OutputLayer(std::make_unique<DummyAccessor>(0));
// Finalize graph
GraphConfig config;
- config.num_threads = common_params.threads;
- config.use_tuner = common_params.enable_tuner;
- config.tuner_mode = common_params.tuner_mode;
- config.tuner_file = common_params.tuner_file;
- config.convert_to_uint8 = (common_params.data_type == DataType::QASYMM8);
+ config.num_threads = common_params.threads;
+ config.use_tuner = common_params.enable_tuner;
+ config.tuner_mode = common_params.tuner_mode;
+ config.tuner_file = common_params.tuner_file;
+ config.mlgo_file = common_params.mlgo_file;
+ config.use_synthetic_type = arm_compute::is_data_type_quantized(common_params.data_type);
+ config.synthetic_type = common_params.data_type;
graph.finalize(common_params.target, config);
@@ -155,8 +156,8 @@ public:
private:
CommandLineParser cmd_parser;
CommonGraphOptions common_opts;
- SimpleOption<unsigned int> *model_input_width{ nullptr };
- SimpleOption<unsigned int> *model_input_height{ nullptr };
+ SimpleOption<unsigned int> *model_input_width{nullptr};
+ SimpleOption<unsigned int> *model_input_height{nullptr};
CommonGraphParams common_params;
Stream graph;
};
generated by cgit v1.2.1 (git 2.23.0) at 2024-05-05 10:49:47 +0000