change timestamp type from long to string for 32-bit ARM architecture

Mochi/README.md

@@ -87,7 +87,7 @@ train 0 0.11 0.22 0.33 0.44 0.55 0.43 1615255010842
 1. Start the Online ML server: `./OrbitAI_Mochi`
 2. Send telnet commands to the server:
 ```
-eval 'input="test_data/camera_tiny.txt"; echo "reset"; while IFS= read -r line; do sleep 0.02; echo "train ${line/+/''} $(date +%s%3N)"; done < "$input";' | telnet localhost 9999
+eval 'input="test_data/camera_tiny.txt"; echo "reset"; while IFS= read -r line; do sleep 0.02; echo "train ${line/+/''} $(date +%s000)"; done < "$input";' | telnet localhost 9999
 ```
 3. Monitor a model file being updated: `watch -n 0.1 cat models/arow_2D`
 
@@ -103,15 +103,15 @@ eval 'input="test_data/camera_tiny.txt"; echo "reset"; while IFS= read -r line;
 1. Start the Online ML server: `./OrbitAI_Mochi`
 2. Send telnet commands to the server: 
 ```
-eval 'echo "load"; sleep 1; input="test_data/camera_tiny.txt"; while IFS= read -r line; do sleep 0.02; echo "infer ${line/+/''} $(date +%s%3N)"; done < "$input";' | telnet localhost 9999
+eval 'echo "load"; sleep 1; input="test_data/camera_tiny.txt"; while IFS= read -r line; do sleep 0.02; echo "infer ${line/+/''} $(date +%s000)"; done < "$input";' | telnet localhost 9999
 ```
 
 ### Validation
 As a pre-requisite, make sure that `src/OrbitAI_Mochi.cpp` is compiled with the `LOG_TIMES` define set to 0. This validation procedure is to check that the models save and load as expected. First, train and infer data without loading the the saved model files:
 1. Start the Online ML server: `./OrbitAI_Mochi`
 2. Delete any previously saved models and log files followed by training and infering test data: 
 ```
-eval 'echo "reset"; sleep 1; input="test_data/camera_train_and_infer_small.txt"; while IFS= read -r line; do sleep 0.02; echo "${line/+/''} $(date +%s%3N)"; done < "$input";' | telnet localhost 9999
+eval 'echo "reset"; sleep 1; input="test_data/camera_train_and_infer_small.txt"; while IFS= read -r line; do sleep 0.02; echo "${line/+/''} $(date +%s000)"; done < "$input";' | telnet localhost 9999
 ```
 3. Rename the `logs/training.csv` file to `logs/training1.csv` so the logged trianing data is not lost the next time that the `reset` command is invoked: `mv logs/training.csv logs/training1.csv`
 4. Rename the `logs/inference.csv` file to `logs/inference1.csv` so the logged inference results are not lost the next time that the `reset` command is invoked: `mv logs/inference.csv logs/inference1.csv`
@@ -120,15 +120,15 @@ Retrain the models from scratch but this time skip the inference:
 1. Start the Online ML server: `./OrbitAI_Mochi`
 2. Train and save the models:
 ```
-eval 'echo "reset"; sleep 1; input="test_data/camera_small.txt"; while IFS= read -r line; do sleep 0.02; echo "train ${line/+/''} $(date +%s%3N)"; done < "$input";' | telnet localhost 9999
+eval 'echo "reset"; sleep 1; input="test_data/camera_small.txt"; while IFS= read -r line; do sleep 0.02; echo "train ${line/+/''} $(date +%s000)"; done < "$input";' | telnet localhost 9999
 ```
 3. Diff `logs/training1.csv` and `logs/training.csv`. Both files should be exactly the same: `diff logs/training1.csv logs/training.csv`
 
 Load the saved models and infer given validation inputs. The inference results will be compared against those obtained in step 3:
 1. Start the Online ML server: `./OrbitAI_Mochi`
 2. Load saved models and infer:
 ```
-eval 'echo "load"; sleep 1; input="test_data/camera_validation_small.txt"; while IFS= read -r line; do sleep 0.02; echo "infer ${line/+/''} $(date +%s%3N)"; done < "$input";' | telnet localhost 9999
+eval 'echo "load"; sleep 1; input="test_data/camera_validation_small.txt"; while IFS= read -r line; do sleep 0.02; echo "infer ${line/+/''} $(date +%s000)"; done < "$input";' | telnet localhost 9999
 ```
 3. Diff `logs/inference1.csv` and `logs/inference.csv`. Both files should be exactly the same: `diff logs/inference1.csv logs/inference.csv`
 

Mochi/src/OrbitAI_Mochi.cpp

@@ -582,7 +582,7 @@ int main(int argc, char *argv[])
             {
                 /**
                  * Expected command string format:
-                 *      train <label:int> <pd1:float> <pd2:float> <pd3:float> <pd4:float> <pd5:float> <pd6:float> <timestamp:long>
+                 *      train <label:int> <pd1:float> <pd2:float> <pd3:float> <pd4:float> <pd5:float> <pd6:float> <timestamp:string>
                  * 
                  * e.g.: 
                  *  train 1 0.11 0.22 0.33 0.44 0.55 1.23 1615253200322
@@ -611,7 +611,9 @@ int main(int argc, char *argv[])
                     float pd6 = std::stof(cmdTokens[7]);
 
                     // PD acquisition timestamp.
-                    long timestamp = std::stol(cmdTokens[8]);
+                    // A long in SEPP's ARM architecture is 32 bit so it can't fit the timestamp in ms.
+                    // Use a string instead (we only use this value for logging).
+                    std::string timestamp = cmdTokens[8];
 
                     // Training input error.
                     if(!(label == 0 || label == -1 || label == 1))
@@ -953,7 +955,7 @@ int main(int argc, char *argv[])
                         // Creating the training row string to append to the log file.
                         std::string trainingLogFileRow = 
 #if LOG_TIMES
-                            std::to_string(timestamp) + "," + 
+                            timestamp + "," + 
 #endif 
                             std::to_string(pd1) + "," + std::to_string(pd2) + "," + std::to_string(pd3) + "," + std::to_string(pd4) + "," + std::to_string(pd5) + "," + std::to_string(pd6) + "," + std::to_string(label) 
 #if LOG_TIMES
@@ -995,7 +997,7 @@ int main(int argc, char *argv[])
             {
                 /**
                  * Expected command string format:
-                 *      infer <expected_label:int> <pd1:float> <pd2:float> <pd3:float> <pd4:float> <pd5:float> <pd6:float> <timestamp:long>
+                 *      infer <expected_label:int> <pd1:float> <pd2:float> <pd3:float> <pd4:float> <pd5:float> <pd6:float> <timestamp:string>
                  * 
                  * e.g.: 
                  *  infer +1 0.11 0.22 0.33 0.44 0.55 1.23 1615253200322
@@ -1025,7 +1027,9 @@ int main(int argc, char *argv[])
                     float pd6 = std::stof(cmdTokens[7]);
 
                     // PD acquisition timestamp.
-                    long timestamp = std::stol(cmdTokens[8]);
+                    // A long in SEPP's ARM architecture is 32 bit so it can't fit the timestamp in ms.
+                    // Use a string instead (we only use this value for logging).
+                    std::string timestamp = cmdTokens[8];
 
                     // inference input error.
                     if(!(label == 0 || label == -1 || label == 1))
@@ -1280,7 +1284,7 @@ int main(int argc, char *argv[])
                         // Creating the inference results row string to append to the log file.
                         std::string inferenceLogFileRow =
     #if LOG_TIMES
-                            std::to_string(timestamp) + "," + 
+                            timestamp + "," +
     #endif                     
                             std::to_string(pd1) + "," + std::to_string(pd2) + "," + std::to_string(pd3) + "," + std::to_string(pd4) + "," + std::to_string(pd5) + "," + std::to_string(pd6) + "," + std::to_string(label) + ","
                             + predictions