Created tybalt playground notebook. Minor TybaltVAE fixes

TybaltPlayground.ipynb

@@ -0,0 +1,72 @@
+{
+ "cells": [
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Train Tybalt VAE"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Set hyperparameters"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from models.Tybalt.TybaltVAE import TybaltVAE\n",
+    "\n",
+    "batchsize = 128\n",
+    "input_size = 5000\n",
+    "output_size = 5000\n",
+    "\n",
+    "model = TybaltVAE(input_size=input_size, output_size=output_size)"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Load data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from models.Tybalt.TybaltData import getTybaltDatasets\n",
+    "from torch.utils.data import DataLoader\n",
+    "\n",
+    "data_path = './tybaltdata/pancan_scaled_zeroone_rnaseq.tsv.gz'\n",
+    "dataset_train, dataset_val = getTybaltDatasets()\n",
+    "\n",
+    "dataloader_train = DataLoader(dataset_train,\n",
+    "                           batch_size = batchsize,\n",
+    "                           shuffle = True)\n",
+    "\n",
+    "dataloader_val = DataLoader(dataset_val,\n",
+    "                           batch_size = batchsize,\n",
+    "                           shuffle = False)"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

models/Tybalt/TybaltVAE.py

@@ -16,7 +16,7 @@ def __init__(self, output_size, zsize):
         self.decode = nn.Sequential(
             nn.Linear(zsize, 1000),
             nn.Sigmoid(),
-            nn.Linear(output_size),
+            nn.Linear(1000, output_size),
             nn.Sigmoid()
         )