[ Test/App ] App to test subgraph function-related functions

- This commit writes an app to test functionality to enable subgraph feature. - This commit only test `shared_from` property. Self evaluation: Build test: [X]Passed [ ]Failed [ ]Skipped Run test: [X]Passed [ ]Failed [ ]Skipped Signed-off-by: Eunju Yang <[email protected]>
nnstreamer · Dec 26, 2024 · ba7e166 · ba7e166
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diff --git a/Applications/Subgraph/jni/main.cpp b/Applications/Subgraph/jni/main.cpp
@@ -0,0 +1,105 @@
+// SPDX-License-Identifier: Apache-2.0
+/**
+ * Copyright (C) 2024 Eunju Yang <[email protected]>
+ *
+ * @file   main.cpp
+ * @date   27 Dec 2024
+ * @brief  Test Application for shared_from
+ * @see    https://github.com/nnstreamer/nntrainer
+ * @author Eunju Yang <[email protected]>
+ * @bug    No known bugs except for NYI items
+ */
+
+#include <cifar_dataloader.h>
+#include <layer.h>
+#include <model.h>
+#include <optimizer.h>
+
+#include <array>
+#include <iostream>
+#include <sstream>
+#include <string>
+#include <vector>
+
+#include <model_util.h>
+
+using LayerHandle = std::shared_ptr<ml::train::Layer>;
+using ModelHandle = std::unique_ptr<ml::train::Model>;
+using UserDataType = std::unique_ptr<nntrainer::util::DataLoader>;
+
+/**
+ * @brief tain data callback
+ */
+int trainData_cb(float **input, float **label, bool *last, void *user_data) {
+  auto data = reinterpret_cast<nntrainer::util::DataLoader *>(user_data);
+
+  data->next(input, label, last);
+  return 0;
+}
+
+/**
+ * @brief Create subgraph
+ * @return vector of layers that contain subgraph
+ */
+std::vector<LayerHandle> createSubGraph(const std::string &scope,
+                                        int subgraph_idx) {
+
+  using ml::train::createLayer;
+
+  std::vector<LayerHandle> layers;
+
+  layers.push_back(createLayer(
+    "fully_connected",
+    {withKey("name", scope + "/fc_in" + std::to_string(subgraph_idx)),
+     withKey("unit", 320),
+     withKey("input_layers", "input/" + std::to_string(subgraph_idx)),
+     withKey("shared_from", scope + "/fc_in0")}));
+  layers.push_back(createLayer(
+    "fully_connected",
+    {
+      withKey("name", scope + "/fc_out" + std::to_string(subgraph_idx)),
+      withKey("unit", 320),
+      withKey("input_layers", scope + "/fc_in" + std::to_string(subgraph_idx)),
+      withKey("shared_from", scope + "/fc_out0"),
+    }));
+  layers.push_back(createLayer(
+    "identity",
+    {withKey("name", "input/" + std::to_string(subgraph_idx + 1))}));
+
+  return layers;
+}
+
+int main(int argc, char *argv[]) {
+
+  /** model */
+  ModelHandle model = ml::train::createModel(ml::train::ModelType::NEURAL_NET);
+
+  /** number of subgraphs */
+  const int n_sg = 3;
+
+  /** add input layer */
+  model->addLayer(
+    ml::train::createLayer("input", {"name=input/0", "input_shape=1:1:320"}));
+
+  /** add subgraphs with shared_from */
+  for (auto idx_sg = 0; idx_sg < n_sg; ++idx_sg) {
+    for (auto &layer : createSubGraph(std::string("subgraph"), idx_sg))
+      model->addLayer(layer);
+  }
+
+  auto optimizer = ml::train::createOptimizer("sgd", {"learning_rate=0.001"});
+  model->setOptimizer(std::move(optimizer));
+
+  /** model compilation */
+  if (model->compile(ml::train::ExecutionMode::INFERENCE)) {
+    throw std::invalid_argument("model compilation failed!");
+  }
+
+  /** model initialization */
+  if (model->initialize(ml::train::ExecutionMode::INFERENCE)) {
+    throw std::invalid_argument("model initialization failed!");
+  }
+
+  /** check weight sharing from summary */
+  model->summarize(std::cout, ML_TRAIN_SUMMARY_TENSOR);
+}
diff --git a/Applications/Subgraph/jni/meson.build b/Applications/Subgraph/jni/meson.build
@@ -0,0 +1,11 @@
+subgraph_source = ['main.cpp', cifar_path / 'cifar_dataloader.cpp']
+subgraph_dependencies = [app_utils_dep, nntrainer_dep, nntrainer_ccapi_dep]
+
+e = executable(
+    'nntrainer_subgraph',
+    subgraph_source,
+    include_directories: [include_directories('.'), cifar_include_dir],
+    dependencies: subgraph_dependencies,
+    install: get_option('install-app'),
+    install_dir: application_install_dir,
+)
diff --git a/Applications/Subgraph/jni/model_util.h b/Applications/Subgraph/jni/model_util.h
@@ -0,0 +1,35 @@
+#include <string>
+
+/**
+ * @brief make "key=value" from key and value
+ *
+ * @tparam T type of a value
+ * @param key key
+ * @param value value
+ * @return std::string with "key=value"
+ */
+template <typename T>
+static std::string withKey(const std::string &key, const T &value) {
+  std::stringstream ss;
+  ss << key << "=" << value;
+  return ss.str();
+}
+
+template <typename T>
+static std::string withKey(const std::string &key,
+                           std::initializer_list<T> value) {
+  if (std::empty(value)) {
+    throw std::invalid_argument("empty data cannot be converted");
+  }
+
+  std::stringstream ss;
+  ss << key << "=";
+
+  auto iter = value.begin();
+  for (; iter != value.end() - 1; ++iter) {
+    ss << *iter << ',';
+  }
+  ss << *iter;
+
+  return ss.str();
+}
diff --git a/Applications/Subgraph/jni/out_summary.txt b/Applications/Subgraph/jni/out_summary.txt
@@ -0,0 +1,241 @@
+reorg created
+reorg deleted
+================================================================================
+          Layer name          Layer type    Output dimension         Input layer
+================================================================================
+             input/0               input           1:1:1:320                    
+--------------------------------------------------------------------------------
+     subgraph/fc_in0     fully_connected           1:1:1:320             input/0
+--------------------------------------------------------------------------------
+    subgraph/fc_out0     fully_connected           1:1:1:320     subgraph/fc_in0
+--------------------------------------------------------------------------------
+             input/1            identity           1:1:1:320    subgraph/fc_out0
+--------------------------------------------------------------------------------
+     subgraph/fc_in1     fully_connected           1:1:1:320             input/1
+--------------------------------------------------------------------------------
+    subgraph/fc_out1     fully_connected           1:1:1:320     subgraph/fc_in1
+--------------------------------------------------------------------------------
+             input/2            identity           1:1:1:320    subgraph/fc_out1
+--------------------------------------------------------------------------------
+     subgraph/fc_in2     fully_connected           1:1:1:320             input/2
+--------------------------------------------------------------------------------
+    subgraph/fc_out2     fully_connected           1:1:1:320     subgraph/fc_in2
+--------------------------------------------------------------------------------
+             input/3            identity           1:1:1:320    subgraph/fc_out2
+================================================================================
+===================<input/0>
+Layer Type: input
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+normalization: false
+standardization: false
+======properties: 
+======weights: 
+======metrics: 
+Layer loss value: 0
+===================<subgraph/fc_in0>
+Layer Type: fully_connected
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+weight Shape: 1:1:320:320 [ FP32 : NCHW ]
+weight Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+weight_regularizer: none
+weight_regularizer_constant: 1.000000
+weight_initializer: xavier_uniform
+weight_decay: 0.000000
+bias_decay: 0.000000
+bias_initializer: zeros
+disable_bias: false
+print: false
+unit: 320
+======properties: 
+======weights: 
+<N9nntrainer6TensorE at 0x5cfcfe77df70>
+data addr: 0x7808e3ebd010
+Shape: 1:1:320:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+<N9nntrainer6TensorE at 0x5cfcfe77e340>
+data addr: 0x7808e3f21010
+Shape: 1:1:1:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+======metrics: 
+Layer loss value: 0
+===================<subgraph/fc_out0>
+Layer Type: fully_connected
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+weight Shape: 1:1:320:320 [ FP32 : NCHW ]
+weight Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+weight_regularizer: none
+weight_regularizer_constant: 1.000000
+weight_initializer: xavier_uniform
+weight_decay: 0.000000
+bias_decay: 0.000000
+bias_initializer: zeros
+disable_bias: false
+print: false
+unit: 320
+======properties: 
+======weights: 
+<N9nntrainer6TensorE at 0x5cfcfe77fb40>
+data addr: 0x7808e3f21510
+Shape: 1:1:320:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+<N9nntrainer6TensorE at 0x5cfcfe77fcf0>
+data addr: 0x7808e3f85510
+Shape: 1:1:1:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+======metrics: 
+Layer loss value: 0
+===================<input/1>
+Layer Type: identity
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+======properties: 
+======weights: 
+======metrics: 
+Layer loss value: 0
+===================<subgraph/fc_in1>
+Layer Type: fully_connected
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+weight Shape: 1:1:320:320 [ FP32 : NCHW ]
+weight Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+weight_regularizer: none
+weight_regularizer_constant: 1.000000
+weight_initializer: xavier_uniform
+weight_decay: 0.000000
+bias_decay: 0.000000
+bias_initializer: zeros
+disable_bias: false
+print: false
+unit: 320
+======properties: 
+======weights: 
+<N9nntrainer6TensorE at 0x5cfcfe77df70>
+data addr: 0x7808e3ebd010
+Shape: 1:1:320:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+<N9nntrainer6TensorE at 0x5cfcfe77e340>
+data addr: 0x7808e3f21010
+Shape: 1:1:1:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+======metrics: 
+Layer loss value: 0
+===================<subgraph/fc_out1>
+Layer Type: fully_connected
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+weight Shape: 1:1:320:320 [ FP32 : NCHW ]
+weight Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+weight_regularizer: none
+weight_regularizer_constant: 1.000000
+weight_initializer: xavier_uniform
+weight_decay: 0.000000
+bias_decay: 0.000000
+bias_initializer: zeros
+disable_bias: false
+print: false
+unit: 320
+======properties: 
+======weights: 
+<N9nntrainer6TensorE at 0x5cfcfe77fb40>
+data addr: 0x7808e3f21510
+Shape: 1:1:320:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+<N9nntrainer6TensorE at 0x5cfcfe77fcf0>
+data addr: 0x7808e3f85510
+Shape: 1:1:1:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+======metrics: 
+Layer loss value: 0
+===================<input/2>
+Layer Type: identity
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+======properties: 
+======weights: 
+======metrics: 
+Layer loss value: 0
+===================<subgraph/fc_in2>
+Layer Type: fully_connected
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+weight Shape: 1:1:320:320 [ FP32 : NCHW ]
+weight Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+weight_regularizer: none
+weight_regularizer_constant: 1.000000
+weight_initializer: xavier_uniform
+weight_decay: 0.000000
+bias_decay: 0.000000
+bias_initializer: zeros
+disable_bias: false
+print: false
+unit: 320
+======properties: 
+======weights: 
+<N9nntrainer6TensorE at 0x5cfcfe77df70>
+data addr: 0x7808e3ebd010
+Shape: 1:1:320:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+<N9nntrainer6TensorE at 0x5cfcfe77e340>
+data addr: 0x7808e3f21010
+Shape: 1:1:1:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+======metrics: 
+Layer loss value: 0
+===================<subgraph/fc_out2>
+Layer Type: fully_connected
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+weight Shape: 1:1:320:320 [ FP32 : NCHW ]
+weight Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+weight_regularizer: none
+weight_regularizer_constant: 1.000000
+weight_initializer: xavier_uniform
+weight_decay: 0.000000
+bias_decay: 0.000000
+bias_initializer: zeros
+disable_bias: false
+print: false
+unit: 320
+======properties: 
+======weights: 
+<N9nntrainer6TensorE at 0x5cfcfe77fb40>
+data addr: 0x7808e3f21510
+Shape: 1:1:320:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+<N9nntrainer6TensorE at 0x5cfcfe77fcf0>
+data addr: 0x7808e3f85510
+Shape: 1:1:1:320 [ FP32 : NCHW ]
+[0 0 0 ... 0 0 0]
+======metrics: 
+Layer loss value: 0
+===================<input/3>
+Layer Type: identity
+======shape information: 
+input Shape: 1:1:1:320 [ FP32 : NCHW ]
+output Shape: 1:1:1:320 [ FP32 : NCHW ]
+======meta properties: 
+======properties: 
+======weights: 
+======metrics: 
+Layer loss value: 0