Allow float_array.cpp to build without other dependencies (#3127)

Author: nickjong

src/ml/neural_net/float_array.cpp

@@ -10,8 +10,6 @@
 #include <cassert>
 #include <numeric>
 
-#include <core/logging/assertions.hpp>
-
 namespace turi {
 namespace neural_net {
 
@@ -74,9 +72,8 @@ shared_float_array::shared_float_array(
 }
 
 shared_float_array shared_float_array::operator[](size_t idx) const {
-
-  ASSERT_GT(dim_, 0);
-  ASSERT_LT(idx, shape_[0]);
+  assert(dim_ > 0);
+  assert(idx < shape_[0]);
 
   size_t stride = size_ / shape_[0];
   size_t offset = stride * idx;
@@ -99,27 +96,6 @@ std::ostream &operator<<(std::ostream &os, const float_array &arr) {
   return os;
 }
 
-void shared_float_array::save(oarchive& oarc) const {
-  // Write shape.
-  serialize_iterator(oarc, shape(), shape() + dim(), dim());
-
-  // Write data.
-  serialize_iterator(oarc, data(), data() + size(), size());
-}
-
-void shared_float_array::load(iarchive& iarc) {
-  // Read shape.
-  std::vector<size_t> shape;
-  iarc >> shape;
-
-  // Read data.
-  std::vector<float> data;
-  iarc >> data;
-
-  // Overwrite self with a new float_array wrapping the deserialized data.
-  *this = wrap(std::move(data), std::move(shape));
-}
-
 // static
 std::shared_ptr<float_array> shared_float_array::default_value() {
   // n.b. static variables should have trivial destructors

src/ml/neural_net/float_array.hpp

@@ -4,18 +4,16 @@
  * be found in the LICENSE.txt file or at https://opensource.org/licenses/BSD-3-Clause
  */
 
-#ifndef UNITY_TOOLKITS_NEURAL_NET_FLOAT_ARRAY_HPP_
-#define UNITY_TOOLKITS_NEURAL_NET_FLOAT_ARRAY_HPP_
+#pragma once
 
 #include <cstddef>
 #include <future>
 #include <map>
 #include <memory>
+#include <ostream>
 #include <string>
 #include <vector>
 
-#include <core/storage/serialization/serialization_includes.hpp>
-
 namespace turi {
 namespace neural_net {
 
@@ -160,10 +158,6 @@ class shared_float_array: public float_array {
 
   // TODO: Operations such as reshape, slice, etc.?
 
-  // Serialization.
-  void save(oarchive& oarc) const;
-  void load(iarchive& iarc);
-
 protected:
   shared_float_array(std::shared_ptr<float_array> impl, size_t offset,
                      const size_t* shape, size_t dim);
@@ -211,5 +205,3 @@ std::ostream &operator<<(std::ostream &out, const float_array &arr);
 
 }  // namespace neural_net
 }  // namespace turi
-
-#endif  // UNITY_TOOLKITS_NEURAL_NET_FLOAT_ARRAY_HPP_

src/ml/neural_net/style_transfer/mps_style_transfer_backend.hpp

@@ -5,13 +5,13 @@
  * https://opensource.org/licenses/BSD-3-Clause
  */
 
-#ifndef TURI_STYLE_TRANSFER_MPS_STYLE_TRANSFER_BACKEND_H_
-#define TURI_STYLE_TRANSFER_MPS_STYLE_TRANSFER_BACKEND_H_
+#pragma once
 
 #include <functional>
 #include <map>
 #include <memory>
 
+#include <core/export.hpp>
 #include <ml/neural_net/float_array.hpp>
 #include <ml/neural_net/model_backend.hpp>
 #include <ml/neural_net/mps_command_queue.hpp>
@@ -49,5 +49,3 @@ class EXPORT mps_style_transfer : public turi::neural_net::model_backend {
 } // namespace turi
 
 #endif // #ifdef HAS_MACOS_10_15
-
-#endif

src/ml/neural_net/style_transfer/mps_style_transfer_backend.mm

@@ -6,17 +6,18 @@
 
 #ifdef HAS_MACOS_10_15
 
-#import <ml/neural_net/style_transfer/mps_style_transfer_backend.hpp>
-#import <ml/neural_net/style_transfer/mps_style_transfer.h>
+#include <ml/neural_net/style_transfer/mps_style_transfer_backend.hpp>
+
+#include <numeric>
+
+#include <core/logging/logger_includes.hpp>
+#include <ml/neural_net/model_spec.hpp>
 
-#import <ml/neural_net/model_spec.hpp>
 #import <ml/neural_net/mps_device_manager.h>
 #import <ml/neural_net/mps_utils.h>
-
+#import <ml/neural_net/style_transfer/mps_style_transfer.h>
 #import <ml/neural_net/style_transfer/mps_style_transfer_weights.h>
 
-#include <numeric>
-
 using namespace turi::neural_net;
 
 @interface TCMPSStyleTransferHelpers:NSObject
@@ -283,4 +284,4 @@ float_array_map convert_weights_mps_coreml(const float_array_map &mps_weights) {
 } // namespace style_transfer
 } // namespace turi
 
-#endif // #ifdef HAS_MACOS_10_15
+#endif  // #ifdef HAS_MACOS_10_15

src/toolkits/activity_classification/activity_classifier.cpp

@@ -19,6 +19,7 @@
 #include <timer/timer.hpp>
 #include <toolkits/coreml_export/neural_net_models_exporter.hpp>
 #include <toolkits/evaluation/metrics.hpp>
+#include <toolkits/util/float_array_serialization.hpp>
 #include <toolkits/util/training_utils.hpp>
 
 namespace turi {
@@ -109,16 +110,16 @@ void activity_classifier::save_impl(oarchive& oarc) const {
   variant_deep_save(state, oarc);
 
   // Save neural net weights.
-  oarc << read_model_spec()->export_params_view();
+  save_float_array_map(read_model_spec()->export_params_view(), oarc);
 }
 
 void activity_classifier::load_version(iarchive& iarc, size_t version) {
   // Load model attributes.
   variant_deep_load(state, iarc);
 
   // Load neural net weights.
-  float_array_map nn_params;
-  iarc >> nn_params;
+  float_array_map nn_params = load_float_array_map(iarc);
+
   bool use_random_init = false;
   nn_spec_ = init_model(use_random_init);
   nn_spec_->update_params(nn_params);

src/toolkits/drawing_classifier/drawing_classifier.cpp

@@ -20,6 +20,7 @@
 #include <toolkits/coreml_export/neural_net_models_exporter.hpp>
 #include <toolkits/evaluation/metrics.hpp>
 #include <toolkits/supervised_learning/automatic_model_creation.hpp>
+#include <toolkits/util/float_array_serialization.hpp>
 #include <toolkits/util/training_utils.hpp>
 
 #include <toolkits/drawing_classifier/data_preparation.hpp>
@@ -87,7 +88,7 @@ void drawing_classifier::save_impl(oarchive& oarc) const {
   variant_deep_save(state, oarc);
 
   // Save neural net weights.
-  oarc << nn_spec_->export_params_view();
+  save_float_array_map(nn_spec_->export_params_view(), oarc);
 }
 
 void drawing_classifier::load_version(iarchive& iarc, size_t version) {
@@ -96,8 +97,7 @@ void drawing_classifier::load_version(iarchive& iarc, size_t version) {
   variant_deep_load(state, iarc);
 
   // Load neural net weights.
-  float_array_map nn_params;
-  iarc >> nn_params;
+  float_array_map nn_params = load_float_array_map(iarc);
 
   nn_spec_ = init_model(false);
   nn_spec_->update_params(nn_params);

src/toolkits/object_detection/od_serialization.cpp

@@ -11,6 +11,7 @@
 #include <cstdio>
 
 #include <toolkits/object_detection/od_yolo.hpp>
+#include <toolkits/util/float_array_serialization.hpp>
 
 #include <toolkits/coreml_export/mlmodel_include.hpp>
 
@@ -48,7 +49,7 @@ void _save_impl(oarchive& oarc,
   variant_deep_save(state, oarc);
 
   // Save neural net weights.
-  oarc << weights;
+  save_float_array_map(weights, oarc);
 }
 
 void _load_version(iarchive& iarc, size_t version,
@@ -58,7 +59,7 @@ void _load_version(iarchive& iarc, size_t version,
   variant_deep_load(*state, iarc);
 
   // Load neural net weights.
-  iarc >> *weights;
+  *weights = load_float_array_map(iarc);
 }
 
 void init_darknet_yolo(model_spec& nn_spec, size_t num_classes,

src/toolkits/style_transfer/style_transfer.cpp

@@ -18,6 +18,7 @@
 #include <model_server/lib/variant_deep_serialize.hpp>
 #include <toolkits/style_transfer/st_resnet16_model_trainer.hpp>
 #include <toolkits/style_transfer/style_transfer_model_definition.hpp>
+#include <toolkits/util/float_array_serialization.hpp>
 #include <toolkits/util/training_utils.hpp>
 
 #ifdef HAS_MPS
@@ -328,14 +329,13 @@ size_t style_transfer::get_version() const { return STYLE_TRANSFER_VERSION; }
 
 void style_transfer::save_impl(oarchive& oarc) const {
   variant_deep_save(state, oarc);
-  oarc << read_checkpoint().weights();
+  save_float_array_map(read_checkpoint().weights(), oarc);
 }
 
 void style_transfer::load_version(iarchive& iarc, size_t version) {
   variant_deep_load(state, iarc);
 
-  float_array_map nn_params;
-  iarc >> nn_params;
+  float_array_map nn_params = load_float_array_map(iarc);
   checkpoint_ = load_checkpoint(nn_params);
 }
 

src/toolkits/util/CMakeLists.txt

@@ -2,12 +2,14 @@ project(Turi)
 
 make_library(unity_util OBJECT
   SOURCES
-    precision_recall.cpp
+    class_registrations.cpp
     data_generators.cpp
+    float_array_serialization.cpp
     indexed_sframe_tools.cpp
-    sframe_utils.cpp
-    class_registrations.cpp
+    precision_recall.cpp
     random_sframe_generation.cpp
+    sframe_utils.cpp
   REQUIRES
     unity_core
+    unity_neural_net
 )

src/toolkits/util/float_array_serialization.cpp

@@ -0,0 +1,75 @@
+/* Copyright © 2020 Apple Inc. All rights reserved.
+ *
+ * Use of this source code is governed by a BSD-3-clause license that can
+ * be found in the LICENSE.txt file or at
+ * https://opensource.org/licenses/BSD-3-Clause
+ */
+#include <toolkits/util/float_array_serialization.hpp>
+
+namespace turi {
+
+using neural_net::float_array_map;
+using neural_net::shared_float_array;
+
+class float_array_serialization_wrapper {
+ public:
+  float_array_serialization_wrapper() = default;
+  explicit float_array_serialization_wrapper(shared_float_array array)
+      : impl_(std::move(array)) {}
+
+  const shared_float_array& get() const { return impl_; }
+
+  void save(oarchive& oarc) const {
+    // Write shape.
+    serialize_iterator(oarc, impl_.shape(), impl_.shape() + impl_.dim(),
+                       impl_.dim());
+
+    // Write data.
+    serialize_iterator(oarc, impl_.data(), impl_.data() + impl_.size(),
+                       impl_.size());
+  }
+
+  void load(iarchive& iarc) {
+    // Read shape.
+    std::vector<size_t> shape;
+    iarc >> shape;
+
+    // Read data.
+    std::vector<float> data;
+    iarc >> data;
+
+    // Overwrite self with a new float_array wrapping the deserialized data.
+    impl_ = shared_float_array::wrap(std::move(data), std::move(shape));
+  }
+
+ private:
+  shared_float_array impl_;
+};
+
+void save_float_array_map(const float_array_map& weights, oarchive& oarc) {
+  // Wrap each shared_float_array in weights in a wrapper that knows how to
+  // write itself to the oarchive.
+  std::map<std::string, float_array_serialization_wrapper> wrapped_weights;
+  for (const auto& key_value : weights) {
+    wrapped_weights[key_value.first] =
+        float_array_serialization_wrapper(key_value.second);
+  }
+
+  oarc << wrapped_weights;
+}
+
+float_array_map load_float_array_map(iarchive& iarc) {
+  // Read the iarchive into wrappers around the underlying weights.
+  std::map<std::string, float_array_serialization_wrapper> wrapped_weights;
+  iarc >> wrapped_weights;
+
+  // Obtain direct references to the underlying weights.
+  float_array_map weights;
+  for (const auto& key_value : wrapped_weights) {
+    weights[key_value.first] = key_value.second.get();
+  }
+
+  return weights;
+}
+
+}  // namespace turi