Trying out CME free energy

flatironinstitute · Aug 3, 2023 · fd80fc3 · fd80fc3
1 parent 9823753
commit fd80fc3
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diff --git a/Lukes_folder/Lars_hsp90.zip b/Lukes_folder/Lars_hsp90.zip
diff --git a/Lukes_folder/Lars_hsp90/hsp90_posterior b/Lukes_folder/Lars_hsp90/hsp90_posterior
diff --git a/Lukes_folder/MMD_testing.ipynb b/Lukes_folder/MMD_testing.ipynb
@@ -89,7 +89,7 @@
    "source": [
     "train_config = json.load(open(\"Lars_hsp90/resnet18_encoder.json\"))\n",
     "estimator = build_models.build_npe_flow_model(train_config)\n",
-    "estimator.load_state_dict(torch.load(\"Lars_hsp90/hsp90_posterior_alt.estimator\"))\n",
+    "estimator.load_state_dict(torch.load(\"Lars_hsp90/hsp90_posterior.estimator\"))\n",
     "estimator.cuda()\n",
     "estimator.eval();\n"
    ]

diff --git a/Lukes_folder/cryoBIFE_test.ipynb b/Lukes_folder/cryoBIFE_test.ipynb
diff --git a/Lukes_folder/train_BIFE_prior.ipynb b/Lukes_folder/train_BIFE_prior.ipynb
@@ -0,0 +1,149 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/Data/Packages/Utilities/miniconda3/envs/cryosbi_env/lib/python3.9/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "  from .autonotebook import tqdm as notebook_tqdm\n"
+     ]
+    }
+   ],
+   "source": [
+    "import torch\n",
+    "import matplotlib.pyplot as plt\n",
+    "\n",
+    "from cryo_sbi import CryoEmSimulator\n",
+    "from cryo_sbi import gen_training_set\n",
+    "from cryo_sbi.inference.NPE_train_from_disk import npe_train_from_disk\n",
+    "from cryo_sbi.inference.NPE_train_without_saving import npe_train_no_saving"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Creating particles and then training with them"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "hsp90_models.npy\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 10000/10000 [01:13<00:00, 136.60pair/s]\n",
+      "100%|██████████| 100/100 [00:00<00:00, 4779.94pair/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "gen_training_set(\n",
+    "    config_file=\"config_file.json\",\n",
+    "    num_train_samples=10000,\n",
+    "    num_val_samples=100,\n",
+    "    file_name=\"tut_imgs\",\n",
+    "    save_as_tensor=False,\n",
+    "    n_workers=2,\n",
+    "    batch_size=100,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training neural netowrk:\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 30/30 [04:44<00:00,  9.48s/epoch, train_loss=-.981, val_loss=0.108]  \n"
+     ]
+    }
+   ],
+   "source": [
+    "npe_train_from_disk(\n",
+    "    train_config=\"resnet18_encoder.json\",\n",
+    "    epochs=30,\n",
+    "    train_data_dir=\"tut_imgs_train.h5\",\n",
+    "    val_data_dir=\"tut_imgs_valid.h5\",\n",
+    "    estimator_file=\"tut_estimator\",\n",
+    "    loss_file=\"tut_loss\",\n",
+    "    train_from_checkpoint=False,\n",
+    "    model_state_dict=None,\n",
+    "    n_workers=2,\n",
+    ")"
+   ]
+  },
+  {
+   "attachments": {},
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Training without saving images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "npe_train_no_saving(\n",
+    "    image_config=\"image_params_snr01_128.json\",\n",
+    "    train_config=\"resnet18_encoder.json\",\n",
+    "    epochs=350,\n",
+    "    estimator_file=\"resnet18_encoder.estimator\",\n",
+    "    loss_file=\"resnet18_encoder.estimator\",\n",
+    "    n_workers=2,  # CHANGE\n",
+    ")"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "cryosbi_env",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.9.16"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/Lukes_folder/trying_it_out.ipynb b/Lukes_folder/trying_it_out.ipynb
@@ -162,7 +162,7 @@
    "source": [
     "train_config = json.load(open(\"Lars_hsp90/resnet18_encoder.json\"))\n",
     "estimator = build_models.build_npe_flow_model(train_config)\n",
-    "estimator.load_state_dict(torch.load(\"Lars_hsp90/hsp90_posterior_alt.estimator\"))\n",
+    "estimator.load_state_dict(torch.load(\"Lars_hsp90/hsp90_posterior.estimator\"))\n",
     "estimator.cuda()\n",
     "estimator.eval();\n"
    ]