ALL CNN EXPERIMENTS

CNN_DEMO/README.md

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+# Step 0: Get going
+To get going right away, train a LeNet-5 model on MNIST using Alt-Min by executing:
+```
+python train_cnn_14jan.py 
+```
+# Step 1: HYPERPARAMETER TESTING
+Write a hyperparameter grid search in `experiments` sub-folder.
+e.g.:
+* `./all_lenetFashionMnist_18jan.sh`    does both alt-min (am) and SGD for fashion-mnist
+* `./am_lenetMnist_18jan.sh`            does am on mnist
+* `./sgd_lenetMnist_18jan.sh`           does sgd on mnist
+
+These files call `../train_cnn_14jan.py` in a loop, which trains LeNet architectures on training sets and record error on validation set. Make sure to set "savePath" etc. within that file to an appropriate sub-directory.
+
+
+# Step 2: ANALYSIS
+1. Still from the experiments folder, use `cnnMnistViz19jan.py` to determine the hyperparameters which performed the best, on average. E.g.:
+```
+python -i ../cnnMnistViz19jan.py --loadPath='./lenetMnist_18jan/'
+```
+
+This will automatically save the results in `bestHypers` and `ims` subfolders within the folder specific via argument `--loadPath`.
+
+2. Copy the values saved in `bestHypers` subfolder (in `.pt` format) to the corresponding subfolder of `am2-paper-results/postHPexps/`. `postHPexps` stands for "POST-HYPER-PARAMETER-EXPERIMENTS", e.g. testing and visualization.
+
+3. To print the selected hyperparameters to terminal, execute from `am2-paper-results` e.g.:
+```
+python -i printHPOrez_cnn.py --loadPath='postHPexps/lenet/lenet_mnist/'
+```
+
+# Step 3: TESTING
+In the `postHPexps` subfolders, run the executables to initiate testing. Each one executes:
+1. Load the best hyperparameters determined in Step (2a) and copied in Step (2b).
+2. Train corresponding network using entire training set.
+3. Evaluate on the test.
+4. Repeat for many random intializations.
+
+# Step 4: VISUALIZATION
+From the `postHPexps` subfolder, use `testRezViz_19jan.py` to generate figures displaying testing results, e.g.
+```
+python ../../../testRezViz_19jan.py --loadPath='./testResults/'
+```
+