2D Convolutional Autoencoder

.github/workflows/ci.yml

@@ -10,8 +10,33 @@ on:
       - main
 
 jobs:
-  # docker-image:
-  #   uses: ./.github/workflows/docker.yml
+  docker-image:
+    uses: ./.github/workflows/docker.yml
   api-doc:
-    # needs: [docker-image]
-    uses: ./.github/workflows/sphinx.yml
+    uses: ./.github/workflows/sphinx.yml
+  linux:
+    runs-on: ubuntu-latest
+    needs: [docker-image]
+    container:
+      image: ghcr.io/llnl/gplasdi/lasdi_env:latest
+      options: --user 1001 --privileged
+      volumes:
+        - /mnt:/mnt
+    steps:
+      - name: Cancel previous runs
+        uses: styfle/cancel-workflow-action@0.11.0
+        with:
+          access_token: ${{ github.token }}
+      # - name: Set Swap Space
+      #   uses: pierotofy/set-swap-space@master
+      #   with:
+      #     swap-size-gb: 10
+      - name: Check out LaSDI
+        uses: actions/checkout@v3
+      - name: Build LaSDI
+        run: |
+            cd ${GITHUB_WORKSPACE}
+            pip install .
+      - name: Test CNN2D
+        run: |
+            pytest -vrx tests/test_CNN2D.py

docker/Dockerfile

@@ -23,8 +23,8 @@ RUN sudo apt-get install -yq python3-dev
 RUN sudo apt-get install -yq python3-pip
 RUN sudo apt-get install python-is-python3
 RUN sudo python -m pip install --upgrade pip
-RUN sudo python -m pip install sphinx sphinx-autoapi sphinx_rtd_theme
-#RUN sudo pip3 install numpy scipy argparse tables PyYAML h5py pybind11 pytest mpi4py merlin
+# RUN sudo python -m pip install sphinx sphinx-autoapi sphinx_rtd_theme
+RUN sudo pip3 install torch==2.0.1 numpy==1.23.0 scikit-learn==1.3 scipy==1.10 pyyaml==6.0 matplotlib==3.8.0 argparse==1.1 h5py pytest pytest-cov
 #
 RUN sudo apt-get clean -q
 

docs/source/conf.py

@@ -25,6 +25,7 @@
 ]
 
 autoapi_dirs = ['../../src']
+autoapi_python_class_content = 'both'
 
 napoleon_google_docstring = False
 napoleon_use_param = False

examples/burgers1d.ipynb

@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 1,
+   "execution_count": null,
    "id": "d67dad03-9d76-4891-82ff-7e19d1369a24",
    "metadata": {},
    "outputs": [],
@@ -78,7 +78,7 @@
    "outputs": [],
    "source": [
     "# Specify the restart file you have.\n",
-    "filename = 'lasdi_10_01_2024_17_09.npy'\n",
+    "filename = 'restarts/burgers1d.restart.npy'\n",
     "\n",
     "import yaml\n",
     "from lasdi.workflow import initialize_trainer\n",
@@ -111,7 +111,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "id": "dcdac0c2",
    "metadata": {},
    "outputs": [],
@@ -179,6 +179,28 @@
     "n_coef = restart_file['latent_dynamics']['ncoefs']"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "03a96b35",
+   "metadata": {},
+   "source": [
+    "# Loss history"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "e0163864",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "plt.figure(1)\n",
+    "plt.loglog(trainer.training_loss)\n",
+    "plt.loglog(trainer.ae_loss)\n",
+    "plt.loglog(trainer.ld_loss)\n",
+    "plt.loglog(trainer.coef_loss)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "1262a0c3",
@@ -306,7 +328,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "11c629e4",
+   "id": "ba098b6d",
    "metadata": {},
    "outputs": [],
    "source": []

src/lasdi/gplasdi.py

@@ -145,6 +145,11 @@ def __init__(self, physics, autoencoder, latent_dynamics, param_space, config):
         self.X_train = torch.Tensor([])
         self.X_test = torch.Tensor([])
 
+        self.training_loss = []
+        self.ae_loss = []
+        self.ld_loss = []
+        self.coef_loss = []
+
         return
 
     def train(self):
@@ -163,11 +168,6 @@ def train(self):
         n_train = ps.n_train()
         ld = self.latent_dynamics
 
-        self.training_loss = []
-        self.ae_loss = []
-        self.ld_loss = []
-        self.coef_loss = []
-
         '''
             determine number of iterations.
             Perform n_iter iterations until overall iterations hit max_iter.
@@ -291,4 +291,9 @@ def load(self, dict_):
         self.optimizer.load_state_dict(dict_['optimizer'])
         if (self.device != 'cpu'):
             optimizer_to(self.optimizer, self.device)
+
+        self.training_loss = dict_['training_loss']
+        self.ae_loss = dict_['ae_loss']
+        self.ld_loss = dict_['ld_loss']
+        self.coef_loss = dict_['coeff_loss']
         return