diff --git "a/main-multisession.ipynb" "b/main-multisession.ipynb"
new file mode 100644--- /dev/null
+++ "b/main-multisession.ipynb"
@@ -0,0 +1,3222 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "b0f0f4f3",
+   "metadata": {},
+   "source": [
+    "# Import packages & functions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "id": "5bad764b-45c1-45ce-a716-8d055e09821a",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "importing modules\n",
+      "SLURM random seed indices not provided; using random seed = 0\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"importing modules\")\n",
+    "import os\n",
+    "import sys\n",
+    "import json\n",
+    "import argparse\n",
+    "import numpy as np\n",
+    "import time\n",
+    "import random\n",
+    "import string\n",
+    "import h5py\n",
+    "from tqdm import tqdm\n",
+    "import webdataset as wds\n",
+    "from PIL import Image\n",
+    "import pandas as pd\n",
+    "import nibabel as nib\n",
+    "\n",
+    "import matplotlib.pyplot as plt\n",
+    "import torch\n",
+    "import torch.nn as nn\n",
+    "from torchvision import transforms\n",
+    "\n",
+    "# tf32 data type is faster than standard float32\n",
+    "torch.backends.cuda.matmul.allow_tf32 = True\n",
+    "\n",
+    "import utils\n",
+    "\n",
+    "# Can run a SLURM job array to train many models with different random seed values\n",
+    "try:\n",
+    "    seed = int(os.environ[\"SLURM_ARRAY_TASK_ID\"])\n",
+    "    print(f\"using random seed {seed} in SLURM job {seed} of array\")\n",
+    "except:\n",
+    "    print(\"SLURM random seed indices not provided; using random seed = 0\")\n",
+    "    seed = 0\n",
+    "\n",
+    "\n",
+    "if utils.is_interactive():\n",
+    "    from IPython.display import clear_output # function to clear print outputs in cell\n",
+    "    %load_ext autoreload \n",
+    "    # this allows you to change functions in models.py or utils.py and have this notebook automatically update with your revisions\n",
+    "    %autoreload 2 "
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "bae2b2ad-e1ef-4262-8263-6ae9a0766caa",
+   "metadata": {},
+   "source": [
+    "# Princeton data prep"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "c6dbeabe-9e9c-4d8d-a8c3-414d79d14e63",
+   "metadata": {},
+   "source": [
+    "## Load Data & Design"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "0f2d14fc-bfe3-40dc-b14e-070812c43406",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "sub = \"sub-003\"\n",
+    "session = \"ses-01\"\n",
+    "if session == \"all\":\n",
+    "    ses_list = [\"ses-02\", \"ses-03\"]\n",
+    "n_runs = 16\n",
+    "train_test_split = 'MST' # 'orig'\n",
+    "remove_close_to_MST = False\n",
+    "remove_random_n = False\n",
+    "if remove_close_to_MST or remove_random_n:\n",
+    "    assert remove_close_to_MST != remove_random_n  # don't remove both sets of images\n",
+    "\n",
+    "if remove_random_n:\n",
+    "    assert train_test_split == 'MST'  # MST images are excluded from the n images removed, so only makes sense if they're not in the training set\n",
+    "    n_to_remove = 150"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "d5d98f76-1ae9-4880-93ec-cdc65e2b09a8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if utils.is_interactive():\n",
+    "    glmsingle_path = f'/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2/glmsingle_{sub}_{session}_nofithrf'\n",
+    "    # glmsingle_path = f'/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2/glmsingle_{session}'\n",
+    "else:\n",
+    "    glmsingle_path = os.environ[\"glmsingle_path\"]\n",
+    "    \n",
+    "assert os.path.exists(glmsingle_path)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
+   "id": "34c1e0c6-0641-4239-8201-f2c676532302",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "csv/sub-003_ses-01.csv\n",
+      "(1135, 106)\n",
+      "len_unique_images 851\n",
+      "n_runs 16\n",
+      "['all_stimuli/rtmindeye_stimuli/image_686_seed_1.png'\n",
+      " 'all_stimuli/rtmindeye_stimuli/image_262_seed_1.png'\n",
+      " 'all_stimuli/rtmindeye_stimuli/image_508_seed_1.png'\n",
+      " 'all_stimuli/rtmindeye_stimuli/image_671_seed_1.png']\n",
+      "[596.70813508 600.71900325 604.72332096 608.734187  ]\n",
+      "[0. 0. 0. 0.]\n",
+      "(1000,)\n"
+     ]
+    }
+   ],
+   "source": [
+    "if session == \"all\":\n",
+    "    filename = f\"csv/{sub}_{ses_list[0]}.csv\"\n",
+    "    data = pd.read_csv(filename)[14:]\n",
+    "    print(filename)\n",
+    "    print(data.shape)\n",
+    "    for s in ses_list[1:]:\n",
+    "        filename = f\"csv/{sub}_{s}.csv\"\n",
+    "        print(filename)\n",
+    "        data = pd.concat([data, pd.read_csv(filename)[14:]])\n",
+    "        print(data.shape)\n",
+    "else:\n",
+    "    filename = f\"csv/{sub}_{session}.csv\"\n",
+    "    if sub == 'sub-001' and session == 'ses-01':\n",
+    "        data = pd.read_csv(filename)[23:]\n",
+    "    else: \n",
+    "        data = pd.read_csv(filename)[14:]\n",
+    "    print(filename)\n",
+    "    print(data.shape)\n",
+    "\n",
+    "image_names = data['current_image'].values\n",
+    "starts = data['trial.started'].values\n",
+    "is_new_run = data['is_new_run'].values\n",
+    "\n",
+    "if sub == 'sub-001':\n",
+    "    if session == 'ses-01':\n",
+    "        assert image_names[0] == 'images/image_686_seed_1.png'\n",
+    "    elif session in ('ses-02', 'all'):\n",
+    "        assert image_names[0] == 'all_stimuli/special515/special_40840.jpg'\n",
+    "    elif session == 'ses-03':\n",
+    "        assert image_names[0] == 'all_stimuli/special515/special_69839.jpg'\n",
+    "    elif session == 'ses-04':\n",
+    "        assert image_names[0] == 'all_stimuli/rtmindeye_stimuli/image_686_seed_1.png'\n",
+    "elif sub == 'sub-003':\n",
+    "    assert image_names[0] == 'all_stimuli/rtmindeye_stimuli/image_686_seed_1.png'\n",
+    "\n",
+    "unique_images = np.unique(image_names.astype(str))\n",
+    "unique_images = unique_images[(unique_images!=\"nan\")]\n",
+    "# unique_images = unique_images[(unique_images!=\"blank.jpg\")]\n",
+    "len_unique_images = len(unique_images)\n",
+    "print(\"len_unique_images\",len_unique_images)\n",
+    "print(\"n_runs\",n_runs)\n",
+    "\n",
+    "if (sub == 'sub-001' and session == 'ses-04') or (sub == 'sub-003' and session == 'ses-01'):\n",
+    "    assert len(unique_images) == 851\n",
+    "\n",
+    "print(image_names[:4])\n",
+    "print(starts[:4])\n",
+    "print(is_new_run[:4])\n",
+    "\n",
+    "if remove_random_n:\n",
+    "    # want to remove 150 imgs\n",
+    "    # 100 special515 imgs are repeated 3x (300 total)\n",
+    "    # all other train imgs are only shown once (558 total)\n",
+    "    # of the 150, want to sample proportionally since we're cutting all repeats for special515\n",
+    "    # so take out 51 (17 unique) from special515 and 99 from rest = removing 150 total\n",
+    "    np.random.seed(seed)\n",
+    "    options_to_remove = [x for x in set(image_names) if str(x) != 'nan' and x != 'blank.jpg' and 'MST_pairs' not in x and 'special515' not in x and list(image_names).count(x)==1]  # all the imgs that only appear once (this is O(N^2) b/c of count() within list comprehension but image_names is a relatively small list)\n",
+    "    options_to_remove_special515 = [x for x in set(image_names) if str(x) != 'nan' and x != 'blank.jpg' and 'MST_pairs' not in x and 'special515' in x and list(image_names).count(x)>1]  # all the special515 images that are repeated (count()>1 necessary because there are special515 that are not repeated)\n",
+    "    imgs_to_remove = np.random.choice(options_to_remove, size=99, replace=False)\n",
+    "    imgs_to_remove = np.append(imgs_to_remove, np.random.choice(options_to_remove_special515, size=17, replace=False))\n",
+    "\n",
+    "image_idx = np.array([])  # contains the unique index of each presented image\n",
+    "vox_image_names = np.array([])  # contains the names of the images corresponding to image_idx\n",
+    "all_MST_images = dict()\n",
+    "for i, im in enumerate(image_names):\n",
+    "    # skip if blank, nan\n",
+    "    if im == \"blank.jpg\":\n",
+    "        i+=1\n",
+    "        continue\n",
+    "    if str(im) == \"nan\":\n",
+    "        i+=1\n",
+    "        continue\n",
+    "    vox_image_names = np.append(vox_image_names, im)\n",
+    "    if remove_close_to_MST:  # optionally skip close_to_MST images \n",
+    "        if \"closest_pairs\" in im:\n",
+    "            i+=1\n",
+    "            continue\n",
+    "    elif remove_random_n:\n",
+    "        if im in imgs_to_remove:\n",
+    "            i+=1\n",
+    "            continue\n",
+    "            \n",
+    "    image_idx_ = np.where(im==unique_images)[0].item()\n",
+    "    image_idx = np.append(image_idx, image_idx_)\n",
+    "    \n",
+    "    if (sub == 'sub-001' and session == 'ses-04') or (sub == 'sub-003' and session == 'ses-01'):  # MST images are ones that matched these image titles\n",
+    "        import re\n",
+    "        if ('w_' in im or 'paired_image_' in im or re.match(r'all_stimuli/rtmindeye_stimuli/\\d{1,2}_\\d{1,3}\\.png$', im) or re.match(r'images/\\d{1,2}_\\d{1,3}\\.png$', im)):  \n",
+    "        # the regexp here looks for **_***.png, allows 1-2 chars before underscore and 1-3 chars after it\n",
+    "            # print(im)\n",
+    "            all_MST_images[i] = im\n",
+    "            i+=1            \n",
+    "    elif 'MST' in im:\n",
+    "        all_MST_images[i] = im\n",
+    "        i+=1\n",
+    "    \n",
+    "image_idx = torch.Tensor(image_idx).long()\n",
+    "# for im in new_image_names[MST_images]:\n",
+    "#     assert 'MST_pairs' in im\n",
+    "# assert len(all_MST_images) == 300\n",
+    "\n",
+    "unique_MST_images = np.unique(list(all_MST_images.values())) \n",
+    "\n",
+    "MST_ID = np.array([], dtype=int)\n",
+    "if remove_close_to_MST:\n",
+    "    close_to_MST_idx = np.array([], dtype=int)\n",
+    "if remove_random_n:\n",
+    "    random_n_idx = np.array([], dtype=int)\n",
+    "\n",
+    "vox_idx = np.array([], dtype=int)\n",
+    "j=0  # this is a counter keeping track of the remove_random_n used later to index vox based on the removed images; unused otherwise\n",
+    "for i, im in enumerate(image_names):  # need unique_MST_images to be defined, so repeating the same loop structure\n",
+    "    # skip if blank, nan\n",
+    "    if im == \"blank.jpg\":\n",
+    "        i+=1\n",
+    "        continue\n",
+    "    if str(im) == \"nan\":\n",
+    "        i+=1\n",
+    "        continue\n",
+    "    if remove_close_to_MST:  # optionally skip close_to_MST images \n",
+    "        if \"closest_pairs\" in im:\n",
+    "            close_to_MST_idx = np.append(close_to_MST_idx, i)\n",
+    "            i+=1\n",
+    "            continue\n",
+    "    if remove_random_n:\n",
+    "        if im in imgs_to_remove:\n",
+    "            vox_idx = np.append(vox_idx, j)\n",
+    "            i+=1\n",
+    "            j+=1\n",
+    "            continue\n",
+    "    j+=1\n",
+    "    curr = np.where(im == unique_MST_images)\n",
+    "    # print(curr)\n",
+    "    if curr[0].size == 0:\n",
+    "        MST_ID = np.append(MST_ID, np.array(len(unique_MST_images)))  # add a value that should be out of range based on the for loop, will index it out later\n",
+    "    else:\n",
+    "        MST_ID = np.append(MST_ID, curr)\n",
+    "        \n",
+    "assert len(MST_ID) == len(image_idx)\n",
+    "# assert len(np.argwhere(pd.isna(data['current_image']))) + len(np.argwhere(data['current_image'] == 'blank.jpg')) + len(image_idx) == len(data)\n",
+    "# MST_ID = torch.tensor(MST_ID[MST_ID != len(unique_MST_images)], dtype=torch.uint8)  # torch.tensor (lowercase) allows dtype kwarg, Tensor (uppercase) is an alias for torch.FloatTensor\n",
+    "print(MST_ID.shape)\n",
+    "if (sub == 'sub-001' and session == 'ses-04') or (sub == 'sub-003' and session == 'ses-01'):\n",
+    "    assert len(all_MST_images) == 100"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e48ffe08-71ec-4a3f-9371-66fed2c21de4",
+   "metadata": {},
+   "source": [
+    "## Load images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 6,
+   "id": "2ceb404f-b04f-42b6-afc4-283bb2b40c08",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  0%|          | 0/1000 [00:00<?, ?it/s]/home/ri4541/.conda/envs/rt_mindEye2/lib/python3.11/site-packages/torchvision/transforms/functional.py:1603: UserWarning: The default value of the antialias parameter of all the resizing transforms (Resize(), RandomResizedCrop(), etc.) will change from None to True in v0.17, in order to be consistent across the PIL and Tensor backends. To suppress this warning, directly pass antialias=True (recommended, future default), antialias=None (current default, which means False for Tensors and True for PIL), or antialias=False (only works on Tensors - PIL will still use antialiasing). This also applies if you are using the inference transforms from the models weights: update the call to weights.transforms(antialias=True).\n",
+      "  warnings.warn(\n",
+      "100%|██████████| 1000/1000 [00:38<00:00, 26.12it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "images torch.Size([1000, 3, 224, 224])\n",
+      "MST_images 1000\n",
+      "MST_images==True 100\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "import imageio.v2 as imageio\n",
+    "resize_transform = transforms.Resize((224, 224))\n",
+    "MST_images = []\n",
+    "images = None\n",
+    "for im_name in tqdm(image_idx):\n",
+    "    if sub == 'sub-001' and session == 'ses-01':\n",
+    "        image_file = f\"all_stimuli/rtmindeye_stimuli/{unique_images[im_name]}\"\n",
+    "    else:\n",
+    "        image_file = f\"{unique_images[im_name]}\"\n",
+    "    im = imageio.imread(image_file)\n",
+    "    im = torch.Tensor(im / 255).permute(2,0,1)\n",
+    "    im = resize_transform(im.unsqueeze(0))\n",
+    "    if images is None:\n",
+    "        images = im\n",
+    "    else:\n",
+    "        images = torch.vstack((images, im))\n",
+    "    if (sub == 'sub-001' and session == 'ses-04') or (sub == 'sub-003' and session == 'ses-01'):\n",
+    "        if ('w_' in image_file or 'paired_image_' in image_file or re.match(r'all_stimuli/rtmindeye_stimuli/\\d{1,2}_\\d{1,3}\\.png$', image_file) or re.match(r'all_stimuli/rtmindeye_stimuli/images/\\d{1,2}_\\d{1,3}\\.png$', image_file)):  \n",
+    "            MST_images.append(True)\n",
+    "        else:\n",
+    "            MST_images.append(False)\n",
+    "    else:   \n",
+    "        if (\"MST_pairs\" in image_file): # (\"_seed_\" not in unique_images[im_name]) and (unique_images[im_name] != \"blank.jpg\") \n",
+    "            MST_images.append(True)\n",
+    "        else:\n",
+    "            MST_images.append(False)\n",
+    "\n",
+    "print(\"images\", images.shape)\n",
+    "MST_images = np.array(MST_images)\n",
+    "print(\"MST_images\", len(MST_images))\n",
+    "if (sub == 'sub-001' and session == 'ses-04') or (sub == 'sub-003' and session == 'ses-01'):\n",
+    "    assert len(MST_images[MST_images==True]) == 100\n",
+    "print(\"MST_images==True\", len(MST_images[MST_images==True]))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 7,
+   "id": "5202b735-4fce-4839-9b2e-b1d197834cdd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# unique_images_pairs = [\n",
+    "#     (1,2),(3,4),(5,6),(7,8),(9,10),(11,12),(13,14),(15,16),\n",
+    "#     (17,18),(19,20),(21,22),(23,24),(25,26),(27,28),(29,30),\n",
+    "#     (31,32),(33,34),(35,36),\n",
+    "#     (787, 788), (789, 790), (791, 792), (793, 794), (795, 796),\n",
+    "#     (797, 798), (799, 800), (801, 802), (803, 804), (805, 806),\n",
+    "#     (807, 808), (809, 810), (811, 812), (813, 814), (815, 816),\n",
+    "#     (817, 818), (819, 820), (821, 822), (823, 824), (825, 826),\n",
+    "#     (827, 828), (829, 830), (831, 832), (833, 834), (835, 836),\n",
+    "#     (837, 838), (839, 840), (841, 842), (843, 844), (845, 846),\n",
+    "#     (847, 848), (849, 850)\n",
+    "# ]\n",
+    "# len(unique_images_pairs), unique_images[unique_images_pairs]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 8,
+   "id": "19963e9d-9ec5-4f16-b376-2d2edbe0aedc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "# want IDs of pairmates based on MST_images\n",
+    "# create \"MST_pairmates\" which is a 25x2 array with indices of the 25 pairs based on MST_images == True\n",
+    "\n",
+    "assert unique_MST_images.shape[0] % 2 == 0  # make sure it's divisible by 2\n",
+    "MST_pairmate_names = unique_MST_images.reshape(int(unique_MST_images.shape[0]/2),2)\n",
+    "# print(MST_pairmate_names)\n",
+    "\n",
+    "MST_pairmate_indices = np.empty(shape=MST_pairmate_names.shape, dtype=int)\n",
+    "for p, pair in enumerate(MST_pairmate_names):\n",
+    "    for i, im in enumerate(pair):\n",
+    "        MST_pairmate_indices[p][i] = np.where(np.isin(list(all_MST_images.values()), im))[0][0]  # just take the first repeated instance of an image\n",
+    "        \n",
+    "# print(MST_pairmate_indices.shape, MST_pairmate_indices)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "04a3bf7e-2388-4c7b-82cf-7e5180e7f25b",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if (sub == 'sub-001' and session in ('ses-02', 'ses-03', 'all')):\n",
+    "    # MST_pairs contains the indices of repeats based on all_MST_images\n",
+    "    # all_MST_images contains the indices of images from image_names\n",
+    "    MST_pairs = utils.find_paired_indices(torch.tensor(MST_ID))\n",
+    "    MST_pairs = np.array(sorted(MST_pairs[:-1], key=lambda x: x[0]))  # we added a fake value as a placeholder so index out the last group of pairs\n",
+    "\n",
+    "    # assert images[MST_pairs]\n",
+    "\n",
+    "    fig, ax = plt.subplots(1, 3, figsize=(10,4))\n",
+    "    fig.suptitle('Sample MST pairs')\n",
+    "\n",
+    "    ax[0].imshow(images[MST_pairs[-1][0]].permute(1,2,0).numpy())\n",
+    "    ax[0].set_title(f\"Trial 0\")\n",
+    "\n",
+    "    ax[1].imshow(images[MST_pairs[-1][1]].permute(1,2,0).numpy())\n",
+    "    ax[1].set_title(f\"Trial 1\")\n",
+    "\n",
+    "    ax[2].imshow(images[MST_pairs[-1][2]].permute(1,2,0).numpy())\n",
+    "    ax[2].set_title(f\"Trial 2\")\n",
+    "\n",
+    "    plt.setp(ax, xticks=[], yticks=[])\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "dbb17afa-579e-40ee-9cd3-3083ad31b94c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 200x200 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 1000x800 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "# pairs has the indices of all repeated images\n",
+    "pairs = utils.find_paired_indices(image_idx)\n",
+    "pairs = np.array(sorted(pairs, key=lambda x: x[0]))\n",
+    "\n",
+    "plt.figure(figsize=(2,2))\n",
+    "plt.imshow(images[0].permute(1,2,0).numpy())\n",
+    "plt.title(f\"Trial 0\")\n",
+    "plt.show()\n",
+    "plt.figure(figsize=(2,2))\n",
+    "plt.imshow(images[1].permute(1,2,0).numpy())\n",
+    "plt.title(f\"Trial 1\")\n",
+    "plt.show()\n",
+    "plt.figure(figsize=(2,2))\n",
+    "plt.imshow(images[2].permute(1,2,0).numpy())\n",
+    "plt.title(f\"Trial 2\")\n",
+    "plt.show()\n",
+    "\n",
+    "p=100\n",
+    "if session in ('ses-02', 'ses-03', 'all'):\n",
+    "    fig, ax = plt.subplots(1, 3, figsize=(10,8))\n",
+    "\n",
+    "    ax[0].imshow(images[pairs[p][0]].permute(1,2,0).numpy())\n",
+    "    ax[0].set_title(f\"Repeat 1\")\n",
+    "\n",
+    "    ax[1].imshow(images[pairs[p][1]].permute(1,2,0).numpy())\n",
+    "    ax[1].set_title(f\"Repeat 2\")\n",
+    "\n",
+    "    ax[2].imshow(images[pairs[p][2]].permute(1,2,0).numpy())\n",
+    "    ax[2].set_title(f\"Repeat 3\")\n",
+    "\n",
+    "    plt.setp(ax, xticks=[], yticks=[])\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()\n",
+    "    \n",
+    "else:\n",
+    "    fig, ax = plt.subplots(1, 2, figsize=(10,8))\n",
+    "\n",
+    "    ax[0].imshow(images[pairs[p][0]].permute(1,2,0).numpy())\n",
+    "    ax[0].set_title(f\"Repeat 1\")\n",
+    "\n",
+    "    ax[1].imshow(images[pairs[p][1]].permute(1,2,0).numpy())\n",
+    "    ax[1].set_title(f\"Repeat 2\")\n",
+    "\n",
+    "    plt.setp(ax, xticks=[], yticks=[])\n",
+    "    plt.tight_layout()\n",
+    "    plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "b50dfcd3-9c49-4494-beda-69b5002809f7",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# np.array(list(all_MST_images.values()))[MST_pairmate_indices]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "7804edab-5dc2-4499-8a91-91d77f78bd77",
+   "metadata": {},
+   "source": [
+    "## Load GLMSingle voxel data"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 12,
+   "id": "3a5e1904-4944-4a5d-9b8d-d85f7cd161e4",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "vox (1000, 1, 1, 478003)\n",
+      "vox (1000, 478003)\n"
+     ]
+    }
+   ],
+   "source": [
+    "if session == \"all\":\n",
+    "    glmsingle = np.load(f\"{glmsingle_path}/glmsingle_{ses_list[0]}/TYPED_FITHRF_GLMDENOISE_RR.npz\",allow_pickle=True)\n",
+    "    vox = glmsingle['betasmd'].T\n",
+    "    print(\"vox\", vox.shape)\n",
+    "\n",
+    "    for s in ses_list[1:]:\n",
+    "        glmsingle = np.load(f\"{glmsingle_path}/glmsingle_{s}/TYPED_FITHRF_GLMDENOISE_RR.npz\",allow_pickle=True)\n",
+    "        vox = np.concatenate([vox, glmsingle['betasmd'].T])\n",
+    "        print(\"vox\", vox.shape)\n",
+    "\n",
+    "else:\n",
+    "    glmsingle = np.load(f\"{glmsingle_path}/TYPED_FITHRF_GLMDENOISE_RR.npz\",allow_pickle=True) \n",
+    "    vox = glmsingle['betasmd'].T\n",
+    "    \n",
+    "print(\"vox\", vox.shape)\n",
+    "\n",
+    "if vox.ndim==4:\n",
+    "    vox = vox[:,0,0]\n",
+    "    print(\"vox\", vox.shape)\n",
+    "    \n",
+    "if remove_close_to_MST:\n",
+    "    x = [x for x in image_names if (x!='blank.jpg') and (str(x)!='nan')]\n",
+    "    close_to_MST_idx = [y for y,z in enumerate(x) if 'closest_pairs' in z]\n",
+    "    # len(x), len(close_to_MST_idx)\n",
+    "    close_to_MST_mask = np.ones(len(vox), dtype=bool)\n",
+    "    close_to_MST_mask[close_to_MST_idx] = False\n",
+    "    vox = vox[close_to_MST_mask]\n",
+    "    print(\"vox after removing close_to_MST\", vox.shape)\n",
+    "elif remove_random_n:\n",
+    "    random_n_mask = np.ones(len(vox), dtype=bool)\n",
+    "    random_n_mask[vox_idx] = False\n",
+    "    vox = vox[random_n_mask]\n",
+    "    print(f\"vox after removing {n_to_remove}\", vox.shape)\n",
+    "\n",
+    "    \n",
+    "assert len(vox) == len(image_idx)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "e98f085f-d20d-4f9e-abc5-f823c90d7f49",
+   "metadata": {},
+   "source": [
+    "### Load nsdgeneral ROI"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 13,
+   "id": "e846060a-d9c0-43d3-824b-08fa2b4b354e",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "loading single session brain mask\n",
+      "Mask dimensions: (1.5, 1.5, 1.5)\n",
+      "\n",
+      "Affine:\n",
+      "[[  1.5          0.           0.         -72.61699677]\n",
+      " [  0.           1.5          0.         -79.29003143]\n",
+      " [  0.           0.           1.5        -59.4773941 ]\n",
+      " [  0.           0.           0.           1.        ]]\n",
+      "\n",
+      "There are 478003 voxels in the included brain mask\n",
+      "\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "<nilearn.plotting.displays._slicers.OrthoSlicer at 0x149e06e20510>"
+      ]
+     },
+     "execution_count": 13,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 660x350 with 4 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "from nilearn.plotting import plot_roi, plot_anat, plot_epi\n",
+    "\n",
+    "# avg_mask=nib.load(f'{sub}_ses-01_brain.nii.gz')\n",
+    "if session == \"all\":\n",
+    "    print('loading multisession brain mask')\n",
+    "    avg_mask=nib.load(f'{glmsingle_path}/{sub}_brain_multi.nii.gz')\n",
+    "else:\n",
+    "    print('loading single session brain mask')\n",
+    "    avg_mask=nib.load(f'{glmsingle_path}/{sub}_{session}_brain.nii.gz')\n",
+    "    # avg_mask=nib.load(f'masks/{sub}_{session}_brain.nii.gz')\n",
+    "\n",
+    "# mask info\n",
+    "dimsize=avg_mask.header.get_zooms()\n",
+    "affine_mat = avg_mask.affine\n",
+    "brain=avg_mask.get_fdata()\n",
+    "xyz=brain.shape #xyz dimensionality of brain mask and epi data\n",
+    "\n",
+    "print('Mask dimensions:', dimsize)\n",
+    "print('')\n",
+    "print('Affine:')\n",
+    "print(affine_mat)\n",
+    "print('')\n",
+    "print(f'There are {int(np.sum(brain))} voxels in the included brain mask\\n')\n",
+    "\n",
+    "roi = nib.load(f'{glmsingle_path}/{sub}_nsdgeneral.nii.gz')\n",
+    "# roi = nib.load(f\"masks/{sub}_nsdgeneral.nii.gz\")\n",
+    "\n",
+    "plot_roi(roi, bg_img=avg_mask)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 14,
+   "id": "f7f2e9dd-88af-4ca9-bd80-17cbe429b6ce",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "total voxels (whole brain) = 478003\n",
+      "nsdgeneral voxels = 52030\n"
+     ]
+    }
+   ],
+   "source": [
+    "avg_mask = avg_mask.get_fdata().flatten()\n",
+    "print(f\"total voxels (whole brain) = {int(avg_mask.sum())}\")\n",
+    "\n",
+    "roi = roi.get_fdata()\n",
+    "roi = roi.flatten()\n",
+    "roi = roi[avg_mask.astype(bool)]\n",
+    "roi[np.isnan(roi)] = 0\n",
+    "roi = roi.astype(bool)\n",
+    "print(f\"nsdgeneral voxels = {roi.sum()}\")"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "3bf38b1b-1270-4f65-bc01-07f90343963d",
+   "metadata": {},
+   "source": [
+    "### ROI voxel exclusion"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 15,
+   "id": "de856487-6f6b-4971-8e84-8b30c9a9e943",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "vox before ROI exclusion: (1000, 478003)\n",
+      "vox after ROI exclusion: (1000, 52030)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# ROI masking?\n",
+    "print(f\"vox before ROI exclusion: {vox.shape}\")\n",
+    "vox = vox[:,roi]\n",
+    "print(f\"vox after ROI exclusion: {vox.shape}\")\n",
+    "\n",
+    "if np.any(np.isnan(vox)):\n",
+    "    print(\"NaNs found! Removing voxels...\")\n",
+    "    x,y = np.where(np.isnan(vox))\n",
+    "    vox = vox[:,np.setdiff1d(np.arange(vox.shape[-1]), y)]"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "903c4f38-4f6e-44d7-8186-44c47c77507a",
+   "metadata": {},
+   "source": [
+    "## Reliability calculation"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "288e757f-fe51-4c3b-bb3c-e78b18c755c5",
+   "metadata": {},
+   "source": [
+    "### Calculate reliability (corr between first and second presentation of same image) for every voxel"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 16,
+   "id": "765ab07f-dbb3-4bdd-8de1-57fe85231d82",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 52030/52030 [00:02<00:00, 23062.78it/s]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "rels (52030,)\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "vox_pairs = utils.zscore(vox[pairs])\n",
+    "rels = np.full(vox.shape[-1],np.nan)\n",
+    "for v in tqdm(range(vox.shape[-1])):\n",
+    "    rels[v] = np.corrcoef(vox_pairs[:,0,v], vox_pairs[:,1,v])[1,0]\n",
+    "print(\"rels\", rels.shape)\n",
+    "assert np.sum(np.all(np.isnan(rels))) == 0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b646ecf4-dd03-4352-abcf-6c6ccb54d96b",
+   "metadata": {},
+   "source": [
+    "### Create representational similarity matrix"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 17,
+   "id": "81aebd28-a66b-43fd-8123-fbcd99851383",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 150/150 [00:00<00:00, 1572.71it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# creating img x vox x repetitions matrix | shape=(150, 18419, 2)\n",
+    "vox0 = np.zeros((len(pairs), vox.shape[-1], 2))\n",
+    "for ipair, pair in enumerate(tqdm(pairs)):\n",
+    "    pair = pair[:2] # to keep things consistent, just using the first two repeats\n",
+    "    i,j = pair\n",
+    "    vox0[ipair, :, :] = vox[pair].T\n",
+    "vox_avg = vox0.mean(-1) # average across the repetitions"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 18,
+   "id": "30fad9fc-5399-4820-8a8a-8b63fec5d371",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "reliability threshold = 0.0\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 150/150 [00:15<00:00,  9.52it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "reliability threshold = 0.1\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 150/150 [00:07<00:00, 21.12it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "reliability threshold = 0.2\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 150/150 [00:03<00:00, 38.64it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "reliability threshold = 0.3\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 150/150 [00:03<00:00, 42.50it/s]\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Masking RDM for each reliability threshold\n",
+    "r_thresholds = np.array([.0, .1, .2, .3])\n",
+    "rdm = np.zeros((len(r_thresholds), len(pairs), len(pairs))) \n",
+    "for ir_thresh, r_thresh in enumerate(r_thresholds):\n",
+    "    print(f\"reliability threshold = {r_thresh}\")\n",
+    "    for i in tqdm(range(len(pairs))):\n",
+    "        for j in range(len(pairs)):\n",
+    "            rdm[ir_thresh,i,j] = np.corrcoef(vox_avg[i,rels>r_thresh], \n",
+    "                                             vox_avg[j,rels>r_thresh])[0,1]\n",
+    "# rdm is shape (4, 150, 150)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 19,
+   "id": "feac20e6-d50f-466f-98c9-eab730db65e9",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 400x400 with 2 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "reliability_threshold_to_visualize = .1\n",
+    "plt.figure(figsize=(4,4))\n",
+    "plt.imshow(rdm[np.where(r_thresholds==reliability_threshold_to_visualize)[0].item()], clim=(-1,1))\n",
+    "plt.colorbar(shrink=0.8)\n",
+    "plt.title(f\"{sub}_{session}\\nreliability threshold={reliability_threshold_to_visualize}\\n\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 20,
+   "id": "4a4575dc-a6b1-449b-bcb8-31b3eef348ba",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "for thresh in range(rdm.shape[0]):\n",
+    "    for img in range(rdm.shape[1]):\n",
+    "        assert np.isclose(rdm[thresh, img, img], 1)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 21,
+   "id": "248ce3a0-f03b-4c97-aee1-920432664ae1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "vox before reliability thresholding: (1000, 52030)\n",
+      "\n",
+      "vox after reliability thresholding: (1000, 542)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# Reliability thresholding?\n",
+    "print(f\"\\nvox before reliability thresholding: {vox.shape}\")\n",
+    "vox = vox[:,rels>.2]\n",
+    "print(f\"\\nvox after reliability thresholding: {vox.shape}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 22,
+   "id": "b80aeb2d-6d53-431c-90ed-658dca7ecebd",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "torch.Size([1000, 3, 224, 224])\n",
+      "(1000, 542)\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(images.shape)\n",
+    "print(vox.shape)\n",
+    "assert len(images) == len(vox)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 23,
+   "id": "c087978f-b316-44f4-a2af-c17b5a00764b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "150 150\n"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "same_corrs = []\n",
+    "diff_corrs = []\n",
+    "for isamp, samp in enumerate(vox[pairs]):\n",
+    "    avg_same_img = []\n",
+    "    for i in range(samp.shape[0]):\n",
+    "        for j in range(i, samp.shape[0]):\n",
+    "            if i != j:\n",
+    "                avg_same_img.append(np.array([np.corrcoef(samp[i, :], samp[j, :])[0,1]]))\n",
+    "    \n",
+    "    same_corrs.append(np.mean(avg_same_img))\n",
+    "                       \n",
+    "    avg_diff_img = []\n",
+    "    for isamp_j, samp_j in enumerate(vox[pairs]):\n",
+    "        if isamp_j != isamp:\n",
+    "            for i in range(samp_j.shape[0]):\n",
+    "                for j in range(i, samp_j.shape[0]):\n",
+    "                    if i != j:\n",
+    "                        avg_diff_img.append(np.array([np.corrcoef(samp[i, :], samp_j[j, :])[0,1]]))\n",
+    "                                    \n",
+    "    # print(len(avg_diff_img))\n",
+    "    diff_corrs.append(np.mean(avg_diff_img))\n",
+    "\n",
+    "\n",
+    "print(len(same_corrs), len(diff_corrs))\n",
+    "same_corrs = np.array(same_corrs)\n",
+    "diff_corrs = np.array(diff_corrs)\n",
+    "\n",
+    "\n",
+    "plt.figure(figsize=(5,4))\n",
+    "plt.title(f\"{sub}_{session} same/diff Pearson corr.\")\n",
+    "plt.plot(np.sort(same_corrs),c='blue',label='same')\n",
+    "plt.plot(np.sort(diff_corrs),c='cyan',label='diff')\n",
+    "plt.axhline(0,c='k',ls='--')\n",
+    "plt.legend()\n",
+    "plt.xlabel(\"sample\")\n",
+    "plt.ylabel(\"Pearson R\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "31646431-10ac-4820-ba5d-c35f1e104557",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "<Figure size 500x400 with 1 Axes>"
+      ]
+     },
+     "metadata": {},
+     "output_type": "display_data"
+    }
+   ],
+   "source": [
+    "vox_pairs = utils.zscore(vox[pairs])\n",
+    "plt.figure(figsize=(5,4))\n",
+    "plt.title(f\"{sub}_{session} same minus diff difference Pearson corr.\")\n",
+    "plt.plot(np.sort(same_corrs) - np.sort(diff_corrs),c='cyan',label='difference')\n",
+    "plt.axhline(0,c='k',ls='--')\n",
+    "plt.legend()\n",
+    "plt.xlabel(\"sample\")\n",
+    "plt.ylabel(\"Pearson R\")\n",
+    "plt.show()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "a8866ce2-1cf2-459e-aa81-dec26a3dcd33",
+   "metadata": {},
+   "source": [
+    "# Training MindEye"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 24,
+   "id": "8f554db1-f7cd-40d2-ab62-5d1e282c2bc8",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "900 100\n"
+     ]
+    }
+   ],
+   "source": [
+    "utils.seed_everything(seed)\n",
+    "\n",
+    "if train_test_split == 'orig':\n",
+    "    # train = all images except images that were repeated\n",
+    "    # test = average of the same-image presentations\n",
+    "    imageTrain = np.arange(len(images))\n",
+    "    train_image_indices = np.array([item for item in imageTrain if item not in pairs.flatten()])\n",
+    "    test_image_indices = pairs\n",
+    "    print(len(train_image_indices), len(test_image_indices))\n",
+    "    assert len(train_image_indices) + len(test_image_indices.flatten()) == len(image_idx)\n",
+    "elif train_test_split == 'MST':\n",
+    "    # non-MST images are the train split\n",
+    "    # MST images are the test split\n",
+    "    train_image_indices = np.where(MST_images==False)[0]\n",
+    "    test_image_indices = np.where(MST_images==True)[0]\n",
+    "    print(len(train_image_indices), len(test_image_indices))\n",
+    "    assert len(train_image_indices) + len(test_image_indices) == len(image_idx)\n",
+    "else:\n",
+    "    raise Exception(\"invalid train_test_split\")\n",
+    "    \n",
+    "for i in train_image_indices:\n",
+    "    assert i not in test_image_indices"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 25,
+   "id": "590f2b4b-db7c-42a1-bfd0-cc578e6af988",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "voxels have been zscored\n",
+      "-0.020402974 0.99745756\n",
+      "vox (1000, 545)\n"
+     ]
+    }
+   ],
+   "source": [
+    "train_mean = np.mean(vox[train_image_indices],axis=0)\n",
+    "train_std = np.std(vox[train_image_indices],axis=0)\n",
+    "\n",
+    "vox = utils.zscore(vox,train_mean=train_mean,train_std=train_std)\n",
+    "print(\"voxels have been zscored\")\n",
+    "print(vox[:,0].mean(), vox[:,0].std())\n",
+    "print(\"vox\", vox.shape)\n",
+    "\n",
+    "images = torch.Tensor(images)\n",
+    "vox = torch.Tensor(vox)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 26,
+   "id": "cc5d2e32-6027-4a19-bef4-5ca068db35bb",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "Detected kernel version 4.18.0, which is below the recommended minimum of 5.5.0; this can cause the process to hang. It is recommended to upgrade the kernel to the minimum version or higher.\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "LOCAL RANK  0\n"
+     ]
+    }
+   ],
+   "source": [
+    "### Multi-GPU config ###\n",
+    "from accelerate import Accelerator, DeepSpeedPlugin\n",
+    "\n",
+    "local_rank = os.getenv('RANK')\n",
+    "if local_rank is None: \n",
+    "    local_rank = 0\n",
+    "else:\n",
+    "    local_rank = int(local_rank)\n",
+    "print(\"LOCAL RANK \", local_rank)  \n",
+    "\n",
+    "data_type = torch.float32 # change depending on your mixed_precision\n",
+    "\n",
+    "accelerator = Accelerator(split_batches=False)\n",
+    "batch_size = 8 "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 27,
+   "id": "b767ab6f-d4a9-47a5-b3bf-f56bf6760c0c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "PID of this process = 3556091\n",
+      "device: cuda\n",
+      "global_batch_size 8\n",
+      "Distributed environment: DistributedType.NO\n",
+      "Num processes: 1\n",
+      "Process index: 0\n",
+      "Local process index: 0\n",
+      "Device: cuda\n",
+      "\n",
+      "Mixed precision type: no\n",
+      "\n",
+      "distributed = False num_devices = 1 local rank = 0 world size = 1 data_type = torch.float32\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(\"PID of this process =\",os.getpid())\n",
+    "device = accelerator.device\n",
+    "print(\"device:\",device)\n",
+    "world_size = accelerator.state.num_processes\n",
+    "distributed = not accelerator.state.distributed_type == 'NO'\n",
+    "num_devices = torch.cuda.device_count()\n",
+    "global_batch_size = batch_size * num_devices\n",
+    "print(\"global_batch_size\", global_batch_size)\n",
+    "if num_devices==0 or not distributed: num_devices = 1\n",
+    "num_workers = num_devices\n",
+    "print(accelerator.state)\n",
+    "\n",
+    "# set data_type to match your mixed precision (automatically set based on deepspeed config)\n",
+    "if accelerator.mixed_precision == \"bf16\":\n",
+    "    data_type = torch.bfloat16\n",
+    "elif accelerator.mixed_precision == \"fp16\":\n",
+    "    data_type = torch.float16\n",
+    "else:\n",
+    "    data_type = torch.float32\n",
+    "\n",
+    "print(\"distributed =\",distributed, \"num_devices =\", num_devices, \"local rank =\", local_rank, \"world size =\", world_size, \"data_type =\", data_type)\n",
+    "print = accelerator.print # only print if local_rank=0"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "9018b82b-c054-4463-9527-4b0c2a75bda6",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Configurations"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 28,
+   "id": "2b61fec7-72a0-4b67-86da-1375f1d9fbd3",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "model_name: testing_MST\n",
+      "--data_path=/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2                     --model_name=testing_MST                     --no-multi_subject --subj=1 --batch_size=8                     --hidden_dim=1024 --clip_scale=1.                     --no-blurry_recon --blur_scale=.5                     --no-use_prior --prior_scale=30                     --n_blocks=4 --max_lr=3e-4 --mixup_pct=.33 --num_epochs=30 --no-use_image_aug                     --ckpt_interval=999 --no-ckpt_saving --new_test                     --multisubject_ckpt=/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2/train_logs/multisubject_subj01_1024hid_nolow_300ep\n"
+     ]
+    }
+   ],
+   "source": [
+    "# if running this interactively, can specify jupyter_args here for argparser to use\n",
+    "if utils.is_interactive():\n",
+    "    model_name = 'testing_MST' # 'sub-001_multi_bs24_MST_rishab_MSTsplit_remove_150_random_seed_0'\n",
+    "    print(\"model_name:\", model_name)\n",
+    "    \n",
+    "    # global_batch_size and batch_size should already be defined in the above cells\n",
+    "    # other variables can be specified in the following string:\n",
+    "    # jupyter_args = f\"--data_path=/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2 --model_name={model_name}\"\n",
+    "\n",
+    "    jupyter_args = f\"--data_path=/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2 \\\n",
+    "                    --model_name={model_name} \\\n",
+    "                    --no-multi_subject --subj=1 --batch_size={batch_size} \\\n",
+    "                    --hidden_dim=1024 --clip_scale=1. \\\n",
+    "                    --no-blurry_recon --blur_scale=.5 \\\n",
+    "                    --no-use_prior --prior_scale=30 \\\n",
+    "                    --n_blocks=4 --max_lr=3e-4 --mixup_pct=.33 --num_epochs=30 --no-use_image_aug \\\n",
+    "                    --ckpt_interval=999 --no-ckpt_saving --new_test \\\n",
+    "                    --multisubject_ckpt=/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2/train_logs/multisubject_subj01_1024hid_nolow_300ep\"\n",
+    "    print(jupyter_args)\n",
+    "    jupyter_args = jupyter_args.split()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 29,
+   "id": "2028bdf0-2f41-46d9-b6e7-86b870dbf16c",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "subj_list [1] num_sessions 0\n"
+     ]
+    }
+   ],
+   "source": [
+    "parser = argparse.ArgumentParser(description=\"Model Training Configuration\")\n",
+    "parser.add_argument(\n",
+    "    \"--model_name\", type=str, default=\"testing\",\n",
+    "    help=\"name of model, used for ckpt saving and wandb logging (if enabled)\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--data_path\", type=str, default=\"/weka/proj-fmri/shared/natural-scenes-dataset\",\n",
+    "    help=\"Path to where NSD data is stored / where to download it to\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--subj\",type=int, default=1, choices=[1,2,3,4,5,6,7,8],\n",
+    "    help=\"Validate on which subject?\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--multisubject_ckpt\", type=str, default=None,\n",
+    "    help=\"Path to pre-trained multisubject model to finetune a single subject from. multisubject must be False.\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--num_sessions\", type=int, default=0,\n",
+    "    help=\"Number of training sessions to include (if multi_subject, this variable doesnt matter)\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--use_prior\",action=argparse.BooleanOptionalAction,default=False,\n",
+    "    help=\"whether to train diffusion prior (True) or just rely on retrieval part of the pipeline (False)\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--batch_size\", type=int, default=32,\n",
+    "    help=\"Batch size can be increased by 10x if only training v2c and not diffusion diffuser\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--wandb_log\",action=argparse.BooleanOptionalAction,default=False,\n",
+    "    help=\"whether to log to wandb\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--resume_from_ckpt\",action=argparse.BooleanOptionalAction,default=False,\n",
+    "    help=\"if not using wandb and want to resume from a ckpt\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--wandb_project\",type=str,default=\"stability\",\n",
+    "    help=\"wandb project name\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--mixup_pct\",type=float,default=.33,\n",
+    "    help=\"proportion of way through training when to switch from BiMixCo to SoftCLIP\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--low_mem\",action=argparse.BooleanOptionalAction,default=False,\n",
+    "    help=\"whether to preload images to cpu to speed things up but consume more memory\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--blurry_recon\",action=argparse.BooleanOptionalAction,default=True,\n",
+    "    help=\"whether to output blurry reconstructions\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--blur_scale\",type=float,default=.5,\n",
+    "    help=\"multiply loss from blurry recons by this number\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--clip_scale\",type=float,default=1.,\n",
+    "    help=\"multiply contrastive loss by this number\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--prior_scale\",type=float,default=30,\n",
+    "    help=\"multiply diffusion prior loss by this\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--use_image_aug\",action=argparse.BooleanOptionalAction,default=True,\n",
+    "    help=\"whether to use image augmentation\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--num_epochs\",type=int,default=120,\n",
+    "    help=\"number of epochs of training\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--multi_subject\",action=argparse.BooleanOptionalAction,default=False,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--new_test\",action=argparse.BooleanOptionalAction,default=True,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--n_blocks\",type=int,default=2,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--hidden_dim\",type=int,default=1024,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--seq_past\",type=int,default=0,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--seq_future\",type=int,default=0,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--lr_scheduler_type\",type=str,default='cycle',choices=['cycle','linear'],\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--ckpt_saving\",action=argparse.BooleanOptionalAction,default=True,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--ckpt_interval\",type=int,default=5,\n",
+    "    help=\"save backup ckpt and reconstruct every x epochs\",\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--seed\",type=int,default=42,\n",
+    ")\n",
+    "parser.add_argument(\n",
+    "    \"--max_lr\",type=float,default=3e-4,\n",
+    ")\n",
+    "\n",
+    "if utils.is_interactive():\n",
+    "    args = parser.parse_args(jupyter_args)\n",
+    "else:\n",
+    "    args = parser.parse_args()\n",
+    "\n",
+    "# create global variables without the args prefix\n",
+    "for attribute_name in vars(args).keys():\n",
+    "    globals()[attribute_name] = getattr(args, attribute_name)\n",
+    "    \n",
+    "outdir = os.path.abspath(f'/scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2/train_logs/{model_name}')\n",
+    "if not os.path.exists(outdir) and ckpt_saving:\n",
+    "    os.makedirs(outdir,exist_ok=True)\n",
+    "    \n",
+    "if use_image_aug or blurry_recon:\n",
+    "    import kornia\n",
+    "    import kornia.augmentation as K\n",
+    "    from kornia.augmentation.container import AugmentationSequential\n",
+    "if use_image_aug:\n",
+    "    img_augment = AugmentationSequential(\n",
+    "        kornia.augmentation.ColorJitter(brightness=0.4, contrast=0.4, saturation=0.4, hue=0.1, p=0.3),\n",
+    "        same_on_batch=False,\n",
+    "        data_keys=[\"input\"],\n",
+    "    )\n",
+    "    # Define the blurring augmentations\n",
+    "    blur_augment = K.RandomGaussianBlur(kernel_size=(21, 21), sigma=(51.0, 51.0), p=1.)\n",
+    "    \n",
+    "if multi_subject:\n",
+    "    subj_list = np.arange(1,9)\n",
+    "    subj_list = subj_list[subj_list != subj]\n",
+    "else:\n",
+    "    subj_list = [subj]\n",
+    "\n",
+    "print(\"subj_list\", subj_list, \"num_sessions\", num_sessions)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "42d13c25-1369-4c49-81d4-83d713586096",
+   "metadata": {
+    "tags": []
+   },
+   "source": [
+    "## Prep data, models, and dataloaders"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 30,
+   "id": "a6660667-94bc-4829-8310-227042febd4c",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if ckpt_saving:\n",
+    "    # save MST_ID for 2-alternative forced-choice retrieval evaluation \n",
+    "    if 'MST' in model_name:\n",
+    "        eval_dir = os.environ[\"eval_dir\"]\n",
+    "        print('saving MST info in', eval_dir)\n",
+    "        # Saving ##\n",
+    "        if not os.path.exists(eval_dir):\n",
+    "            os.mkdir(eval_dir)\n",
+    "\n",
+    "        np.save(f\"{eval_dir}/MST_ID.npy\", MST_ID)\n",
+    "        np.save(f\"{eval_dir}/MST_pairmate_indices.npy\", MST_pairmate_indices)\n",
+    "\n",
+    "    if remove_random_n:\n",
+    "        np.save(f\"{eval_dir}/imgs_to_remove.npy\", imgs_to_remove)\n",
+    "\n",
+    "    np.save(f\"{eval_dir}/train_image_indices.npy\", train_image_indices)\n",
+    "    np.save(f\"{eval_dir}/test_image_indices.npy\", test_image_indices)\n",
+    "    np.save(f\"{eval_dir}/images.npy\", images)\n",
+    "    np.save(f\"{eval_dir}/vox.npy\", vox)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "1c023f24-5233-4a15-a2f5-78487b3a8546",
+   "metadata": {},
+   "source": [
+    "### Creating wds dataloader, preload betas and all 73k possible images"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 31,
+   "id": "aefe7c27-ab39-4b2c-90f4-480f4087b7ab",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "dividing batch size by subj_list, which will then be concatenated across subj during training...\n",
+      "batch_size = 8 num_iterations_per_epoch = 112 num_samples_per_epoch = 900\n"
+     ]
+    }
+   ],
+   "source": [
+    "def my_split_by_node(urls): return urls\n",
+    "num_voxels_list = []\n",
+    "\n",
+    "if multi_subject:\n",
+    "    nsessions_allsubj=np.array([40, 40, 32, 30, 40, 32, 40, 30])\n",
+    "    num_samples_per_epoch = (750*40) // num_devices \n",
+    "else:\n",
+    "    # num_samples_per_epoch = (750*num_sessions) // num_devices \n",
+    "    num_samples_per_epoch = len(train_image_indices)\n",
+    "\n",
+    "print(\"dividing batch size by subj_list, which will then be concatenated across subj during training...\") \n",
+    "batch_size = batch_size // len(subj_list)\n",
+    "\n",
+    "num_iterations_per_epoch = num_samples_per_epoch // (batch_size*len(subj_list))\n",
+    "\n",
+    "print(\"batch_size =\", batch_size, \"num_iterations_per_epoch =\",num_iterations_per_epoch, \"num_samples_per_epoch =\",num_samples_per_epoch)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 32,
+   "id": "e1942b0e-1223-40e6-b543-2f7ff2e8ebcd",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "train_data = {}\n",
+    "train_dl = {}\n",
+    "\n",
+    "train_data[f'subj0{subj}'] = torch.utils.data.TensorDataset(torch.tensor(train_image_indices))\n",
+    "test_data = torch.utils.data.TensorDataset(torch.tensor(test_image_indices))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 33,
+   "id": "81084834-035f-4465-ad59-59e6b806a2f5",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Training with 0 sessions\n",
+      "num_voxels for subj01: 545\n",
+      "Loaded all subj train dls and vox!\n",
+      "\n",
+      "Loaded test dl for subj1!\n",
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "num_voxels = {}\n",
+    "voxels = {}\n",
+    "for s in subj_list:\n",
+    "    print(f\"Training with {num_sessions} sessions\")\n",
+    "    train_dl = torch.utils.data.DataLoader(train_data[f'subj0{s}'], batch_size=batch_size, shuffle=True, drop_last=True, pin_memory=True)\n",
+    "\n",
+    "    num_voxels_list.append(vox[0].shape[-1])\n",
+    "    num_voxels[f'subj0{s}'] = vox[0].shape[-1]\n",
+    "    voxels[f'subj0{s}'] = vox\n",
+    "    print(f\"num_voxels for subj0{s}: {num_voxels[f'subj0{s}']}\")\n",
+    "\n",
+    "print(\"Loaded all subj train dls and vox!\\n\")\n",
+    "\n",
+    "# Validate only on one subject\n",
+    "if multi_subject: \n",
+    "    subj = subj_list[0] # cant validate on the actual held out person so picking first in subj_list\n",
+    "test_dl = torch.utils.data.DataLoader(test_data, batch_size=24, shuffle=False, drop_last=True, pin_memory=True)\n",
+    "\n",
+    "print(f\"Loaded test dl for subj{subj}!\\n\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 34,
+   "id": "bacb8ce2-58fe-4156-913c-7c2f1cf45197",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# paul_train_dl = torch.load('debug/paul_train_dl')\n",
+    "# paul_test_dl = torch.load('debug/paul_test_dl')\n",
+    "# # paul_train_dl.shape, train_dl.shape, paul_test_dl.shape, test_dl.shape"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 35,
+   "id": "5f5c5d62-ec5c-4155-b985-fd0aef45a0a0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# for i, b in enumerate(test_dl): \n",
+    "#     print(i,b)\n",
+    "    \n",
+    "# for i, b in enumerate(paul_test_dl): \n",
+    "#     print(i,b)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "10ec4517-dbdf-4ece-98f6-4714d5de4e15",
+   "metadata": {},
+   "source": [
+    "## Load models"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "48d6160e-1ee8-4da7-a755-9dbb452a6fa5",
+   "metadata": {},
+   "source": [
+    "### CLIP image embeddings  model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 36,
+   "id": "f3b09f1b-ed12-4e27-8206-3f12251d67bb",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import wandb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 37,
+   "id": "b0420dc0-199e-4c1a-857d-b1747058b467",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## USING OpenCLIP ViT-bigG ###\n",
+    "sys.path.append('generative_models/')\n",
+    "import sgm\n",
+    "from generative_models.sgm.modules.encoders.modules import FrozenOpenCLIPImageEmbedder\n",
+    "# from generative_models.sgm.models.diffusion import DiffusionEngine\n",
+    "# from omegaconf import OmegaConf\n",
+    "\n",
+    "try:\n",
+    "    print(clip_img_embedder)\n",
+    "except:\n",
+    "    clip_img_embedder = FrozenOpenCLIPImageEmbedder(\n",
+    "        arch=\"ViT-bigG-14\",\n",
+    "        version=\"laion2b_s39b_b160k\",\n",
+    "        output_tokens=True,\n",
+    "        only_tokens=True,\n",
+    "    )\n",
+    "    clip_img_embedder.to(device)\n",
+    "clip_seq_dim = 256\n",
+    "clip_emb_dim = 1664\n",
+    "\n",
+    "# ## USING OPEN AI CLIP ViT-L ###\n",
+    "# import clip\n",
+    "# try:\n",
+    "#     print(clip_model)\n",
+    "# except:\n",
+    "#     clip_model, preprocess = clip.load(\"ViT-L/14\", device=device)\n",
+    "#     preprocess = transforms.Compose([\n",
+    "#         transforms.Resize(224, interpolation=transforms.InterpolationMode.BILINEAR),\n",
+    "#         transforms.Normalize(mean=[0.48145466, 0.4578275, 0.40821073],\n",
+    "#                              std=[0.26862954, 0.26130258, 0.27577711]),\n",
+    "#     ])\n",
+    "# def clip_img_embedder(image):\n",
+    "#     preproc_img = preprocess(image)\n",
+    "#     return clip_model.encode_image(preproc_img)\n",
+    "# clip_seq_dim = 1\n",
+    "# clip_emb_dim = 768"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "260e5e4a-f697-4b2c-88fc-01f6a54886c0",
+   "metadata": {},
+   "source": [
+    "### MindEye modules"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 38,
+   "id": "c44c271b-173f-472e-b059-a2eda0f4c4c5",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "MindEyeModule()"
+      ]
+     },
+     "execution_count": 38,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "class MindEyeModule(nn.Module):\n",
+    "    def __init__(self):\n",
+    "        super(MindEyeModule, self).__init__()\n",
+    "    def forward(self, x):\n",
+    "        return x\n",
+    "        \n",
+    "model = MindEyeModule()\n",
+    "model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 39,
+   "id": "038a5d61-4769-40b9-a004-f4e7b5b38bb0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "param counts:\n",
+      "559,104 total\n",
+      "559,104 trainable\n",
+      "param counts:\n",
+      "559,104 total\n",
+      "559,104 trainable\n",
+      "torch.Size([2, 1, 545]) torch.Size([2, 1, 1024])\n"
+     ]
+    }
+   ],
+   "source": [
+    "class RidgeRegression(torch.nn.Module):\n",
+    "    # make sure to add weight_decay when initializing optimizer\n",
+    "    def __init__(self, input_sizes, out_features, seq_len=1): \n",
+    "        super(RidgeRegression, self).__init__()\n",
+    "        self.seq_len = seq_len\n",
+    "        self.out_features = out_features\n",
+    "        self.linears = torch.nn.ModuleList([\n",
+    "                torch.nn.Linear(input_size, out_features) for input_size in input_sizes\n",
+    "            ])\n",
+    "    def forward(self, x, subj_idx=0):\n",
+    "        out = torch.cat([self.linears[subj_idx](x[:,seq]).unsqueeze(1) for seq in range(self.seq_len)], dim=1)\n",
+    "        return out\n",
+    "        \n",
+    "model.ridge = RidgeRegression(num_voxels_list, out_features=hidden_dim)\n",
+    "utils.count_params(model.ridge)\n",
+    "utils.count_params(model)\n",
+    "\n",
+    "# test on subject 1 with fake data\n",
+    "b = torch.randn((2,1,num_voxels_list[0]))\n",
+    "print(b.shape, model.ridge(b,0).shape)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 40,
+   "id": "7b8de65a-6d3b-4248-bea9-9b6f4d562321",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "param counts:\n",
+      "453,360,280 total\n",
+      "453,360,280 trainable\n",
+      "param counts:\n",
+      "453,919,384 total\n",
+      "453,919,384 trainable\n",
+      "b.shape torch.Size([2, 1, 1024])\n",
+      "torch.Size([2, 256, 1664]) torch.Size([2, 256, 1664]) torch.Size([1]) torch.Size([1])\n"
+     ]
+    }
+   ],
+   "source": [
+    "from functools import partial\n",
+    "from diffusers.models.vae import Decoder\n",
+    "class BrainNetwork(nn.Module):\n",
+    "    def __init__(self, h=4096, in_dim=15724, out_dim=768, seq_len=1, n_blocks=n_blocks, drop=.15, \n",
+    "                 clip_size=768):\n",
+    "        super().__init__()\n",
+    "        self.seq_len = seq_len\n",
+    "        self.h = h\n",
+    "        self.clip_size = clip_size\n",
+    "        \n",
+    "        self.mixer_blocks1 = nn.ModuleList([\n",
+    "            self.mixer_block1(h, drop) for _ in range(n_blocks)\n",
+    "        ])\n",
+    "        self.mixer_blocks2 = nn.ModuleList([\n",
+    "            self.mixer_block2(seq_len, drop) for _ in range(n_blocks)\n",
+    "        ])\n",
+    "        \n",
+    "        # Output linear layer\n",
+    "        self.backbone_linear = nn.Linear(h * seq_len, out_dim, bias=True) \n",
+    "        if clip_scale>0:\n",
+    "            self.clip_proj = self.projector(clip_size, clip_size, h=clip_size)\n",
+    "            \n",
+    "    def projector(self, in_dim, out_dim, h=2048):\n",
+    "        return nn.Sequential(\n",
+    "            nn.LayerNorm(in_dim),\n",
+    "            nn.GELU(),\n",
+    "            nn.Linear(in_dim, h),\n",
+    "            nn.LayerNorm(h),\n",
+    "            nn.GELU(),\n",
+    "            nn.Linear(h, h),\n",
+    "            nn.LayerNorm(h),\n",
+    "            nn.GELU(),\n",
+    "            nn.Linear(h, out_dim)\n",
+    "        )\n",
+    "    \n",
+    "    def mlp(self, in_dim, out_dim, drop):\n",
+    "        return nn.Sequential(\n",
+    "            nn.Linear(in_dim, out_dim),\n",
+    "            nn.GELU(),\n",
+    "            nn.Dropout(drop),\n",
+    "            nn.Linear(out_dim, out_dim),\n",
+    "        )\n",
+    "    \n",
+    "    def mixer_block1(self, h, drop):\n",
+    "        return nn.Sequential(\n",
+    "            nn.LayerNorm(h),\n",
+    "            self.mlp(h, h, drop),  # Token mixing\n",
+    "        )\n",
+    "\n",
+    "    def mixer_block2(self, seq_len, drop):\n",
+    "        return nn.Sequential(\n",
+    "            nn.LayerNorm(seq_len),\n",
+    "            self.mlp(seq_len, seq_len, drop)  # Channel mixing\n",
+    "        )\n",
+    "        \n",
+    "    def forward(self, x):\n",
+    "        # make empty tensors\n",
+    "        c,b = torch.Tensor([0.]), torch.Tensor([[0.],[0.]])\n",
+    "        \n",
+    "        # Mixer blocks\n",
+    "        residual1 = x\n",
+    "        residual2 = x.permute(0,2,1)\n",
+    "        for block1, block2 in zip(self.mixer_blocks1,self.mixer_blocks2):\n",
+    "            x = block1(x) + residual1\n",
+    "            residual1 = x\n",
+    "            x = x.permute(0,2,1)\n",
+    "            \n",
+    "            x = block2(x) + residual2\n",
+    "            residual2 = x\n",
+    "            x = x.permute(0,2,1)\n",
+    "            \n",
+    "        x = x.reshape(x.size(0), -1)\n",
+    "        backbone = self.backbone_linear(x).reshape(len(x), -1, self.clip_size)\n",
+    "        if clip_scale>0:\n",
+    "            c = self.clip_proj(backbone)\n",
+    "        \n",
+    "        return backbone, c, b\n",
+    "\n",
+    "model.backbone = BrainNetwork(h=hidden_dim, in_dim=hidden_dim, seq_len=1, \n",
+    "                          clip_size=clip_emb_dim, out_dim=clip_emb_dim*clip_seq_dim)\n",
+    "utils.count_params(model.backbone)\n",
+    "utils.count_params(model)\n",
+    "\n",
+    "# test that the model works on some fake data\n",
+    "b = torch.randn((2,1,hidden_dim))\n",
+    "print(\"b.shape\",b.shape)\n",
+    "\n",
+    "backbone_, clip_, blur_ = model.backbone(b)\n",
+    "print(backbone_.shape, clip_.shape, blur_[0].shape, blur_[1].shape)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b397c0d7-52a3-4153-823b-c27d2eb3eeba",
+   "metadata": {},
+   "source": [
+    "### Adding diffusion prior + unCLIP if use_prior=True"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 41,
+   "id": "69965344-9346-4592-9cc5-e537e31d5fce",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [],
+   "source": [
+    "if use_prior:\n",
+    "    from models import *\n",
+    "\n",
+    "    # setup diffusion prior network\n",
+    "    out_dim = clip_emb_dim\n",
+    "    depth = 6\n",
+    "    dim_head = 52\n",
+    "    heads = clip_emb_dim//52 # heads * dim_head = clip_emb_dim\n",
+    "    timesteps = 100\n",
+    "\n",
+    "    prior_network = VersatileDiffusionPriorNetwork(\n",
+    "            dim=out_dim,\n",
+    "            depth=depth,\n",
+    "            dim_head=dim_head,\n",
+    "            heads=heads,\n",
+    "            causal=False,\n",
+    "            num_tokens = clip_seq_dim,\n",
+    "            learned_query_mode=\"pos_emb\"\n",
+    "        )\n",
+    "\n",
+    "    model.diffusion_prior = BrainDiffusionPrior(\n",
+    "        net=prior_network,\n",
+    "        image_embed_dim=out_dim,\n",
+    "        condition_on_text_encodings=False,\n",
+    "        timesteps=timesteps,\n",
+    "        cond_drop_prob=0.2,\n",
+    "        image_embed_scale=None,\n",
+    "    )\n",
+    "    \n",
+    "    utils.count_params(model.diffusion_prior)\n",
+    "    utils.count_params(model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "ec25271a-2209-400c-8026-df3b8ddc1eef",
+   "metadata": {},
+   "source": [
+    "### Setup optimizer / lr / ckpt saving"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 42,
+   "id": "e14d0482-dc42-43b9-9ce1-953c32f2c9c1",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "total_steps 3360\n",
+      "\n",
+      "Done with model preparations!\n",
+      "param counts:\n",
+      "453,919,384 total\n",
+      "453,919,384 trainable\n"
+     ]
+    }
+   ],
+   "source": [
+    "no_decay = ['bias', 'LayerNorm.bias', 'LayerNorm.weight']\n",
+    "\n",
+    "opt_grouped_parameters = [\n",
+    "    {'params': [p for n, p in model.ridge.named_parameters()], 'weight_decay': 1e-2},\n",
+    "    {'params': [p for n, p in model.backbone.named_parameters() if not any(nd in n for nd in no_decay)], 'weight_decay': 1e-2},\n",
+    "    {'params': [p for n, p in model.backbone.named_parameters() if any(nd in n for nd in no_decay)], 'weight_decay': 0.0},\n",
+    "]\n",
+    "# model.backbone.requires_grad_(False)\n",
+    "\n",
+    "if use_prior:\n",
+    "    opt_grouped_parameters.extend([\n",
+    "        {'params': [p for n, p in model.diffusion_prior.named_parameters() if not any(nd in n for nd in no_decay)], 'weight_decay': 1e-2},\n",
+    "        {'params': [p for n, p in model.diffusion_prior.named_parameters() if any(nd in n for nd in no_decay)], 'weight_decay': 0.0}\n",
+    "    ])\n",
+    "\n",
+    "optimizer = torch.optim.AdamW(opt_grouped_parameters, lr=max_lr)\n",
+    "\n",
+    "if lr_scheduler_type == 'linear':\n",
+    "    lr_scheduler = torch.optim.lr_scheduler.LinearLR(\n",
+    "        optimizer,\n",
+    "        total_iters=int(np.floor(num_epochs*num_iterations_per_epoch)),\n",
+    "        last_epoch=-1\n",
+    "    )\n",
+    "elif lr_scheduler_type == 'cycle':\n",
+    "    if num_iterations_per_epoch==0:\n",
+    "        num_iterations_per_epoch=1\n",
+    "    total_steps=int(np.floor(num_epochs*num_iterations_per_epoch))\n",
+    "    print(\"total_steps\", total_steps)\n",
+    "    lr_scheduler = torch.optim.lr_scheduler.OneCycleLR(\n",
+    "        optimizer, \n",
+    "        max_lr=max_lr,\n",
+    "        total_steps=total_steps,\n",
+    "        final_div_factor=1000,\n",
+    "        last_epoch=-1, pct_start=2/num_epochs\n",
+    "    )\n",
+    "    \n",
+    "def save_ckpt(tag):\n",
+    "    ckpt_path = outdir+f'/{tag}.pth'\n",
+    "    if accelerator.is_main_process:\n",
+    "        unwrapped_model = accelerator.unwrap_model(model)\n",
+    "        torch.save({\n",
+    "            'epoch': epoch,\n",
+    "            'model_state_dict': unwrapped_model.state_dict(),\n",
+    "            'optimizer_state_dict': optimizer.state_dict(),\n",
+    "            'lr_scheduler': lr_scheduler.state_dict(),\n",
+    "            'train_losses': losses,\n",
+    "            'test_losses': test_losses,\n",
+    "            'lrs': lrs,\n",
+    "            }, ckpt_path)\n",
+    "    print(f\"\\n---saved {outdir}/{tag} ckpt!---\\n\")\n",
+    "\n",
+    "def load_ckpt(tag,load_lr=True,load_optimizer=True,load_epoch=True,strict=True,outdir=outdir,multisubj_loading=False): \n",
+    "    print(f\"\\n---loading {outdir}/{tag}.pth ckpt---\\n\")\n",
+    "    checkpoint = torch.load(outdir+'/last.pth', map_location='cpu')\n",
+    "    state_dict = checkpoint['model_state_dict']\n",
+    "    if multisubj_loading: # remove incompatible ridge layer that will otherwise error\n",
+    "        state_dict.pop('ridge.linears.0.weight',None)\n",
+    "    model.load_state_dict(state_dict, strict=strict)\n",
+    "    if load_epoch:\n",
+    "        globals()[\"epoch\"] = checkpoint['epoch']\n",
+    "        print(\"Epoch\",epoch)\n",
+    "    if load_optimizer:\n",
+    "        optimizer.load_state_dict(checkpoint['optimizer_state_dict'])\n",
+    "    if load_lr:\n",
+    "        lr_scheduler.load_state_dict(checkpoint['lr_scheduler'])\n",
+    "    del checkpoint\n",
+    "\n",
+    "print(\"\\nDone with model preparations!\")\n",
+    "num_params = utils.count_params(model)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "b1e8dcc4-5ce2-4206-88dc-a68d1dd701cd",
+   "metadata": {},
+   "source": [
+    "# Wandb"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "990cce8c-df83-473a-93c8-c47ba355eccd",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "if local_rank==0 and wandb_log: # only use main process for wandb logging\n",
+    "    import wandb\n",
+    "    wandb_project = 'rtmindeye'\n",
+    "    print(f\"wandb {wandb_project} run {model_name}\")\n",
+    "    # need to configure wandb beforehand in terminal with \"wandb init\"!\n",
+    "    wandb_config = {\n",
+    "      \"model_name\": model_name,\n",
+    "      \"global_batch_size\": global_batch_size,\n",
+    "      \"batch_size\": batch_size,\n",
+    "      \"num_epochs\": num_epochs,\n",
+    "      \"num_sessions\": num_sessions,\n",
+    "      \"num_params\": num_params,\n",
+    "      \"clip_scale\": clip_scale,\n",
+    "      \"prior_scale\": prior_scale,\n",
+    "      \"blur_scale\": blur_scale,\n",
+    "      \"use_image_aug\": use_image_aug,\n",
+    "      \"max_lr\": max_lr,\n",
+    "      \"mixup_pct\": mixup_pct,\n",
+    "      \"num_samples_per_epoch\": num_samples_per_epoch,\n",
+    "      \"ckpt_interval\": ckpt_interval,\n",
+    "      \"ckpt_saving\": ckpt_saving,\n",
+    "      \"seed\": seed,\n",
+    "      \"distributed\": distributed,\n",
+    "      \"num_devices\": num_devices,\n",
+    "      \"world_size\": world_size,\n",
+    "    }\n",
+    "    print(\"wandb_config:\\n\",wandb_config)\n",
+    "    print(\"wandb_id:\",model_name)\n",
+    "    wandb.init(\n",
+    "        id=model_name,\n",
+    "        project=wandb_project,\n",
+    "        name=model_name,\n",
+    "        config=wandb_config,\n",
+    "        resume=\"allow\",\n",
+    "    )\n",
+    "else:\n",
+    "    wandb_log = False"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "d5690151-2131-4918-b750-e869cbd1a8a8",
+   "metadata": {},
+   "source": [
+    "# Train the model"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "12de6387-6e18-4e4b-b5ce-a847d625330a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "epoch = 0\n",
+    "losses, test_losses, lrs = [], [], []\n",
+    "best_test_loss = 1e9\n",
+    "torch.cuda.empty_cache()"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "607a7c7b-fe5e-41a4-80bf-d2814b3a57cc",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "---loading /scratch/gpfs/ri4541/MindEyeV2/src/mindeyev2/train_logs/multisubject_subj01_1024hid_nolow_300ep/last.pth ckpt---\n",
+      "\n",
+      "[2025-01-08 10:35:35,352] [INFO] [real_accelerator.py:191:get_accelerator] Setting ds_accelerator to cuda (auto detect)\n"
+     ]
+    }
+   ],
+   "source": [
+    "# load multisubject stage1 ckpt if set\n",
+    "if multisubject_ckpt is not None and not resume_from_ckpt:\n",
+    "    load_ckpt(\"last\",outdir=multisubject_ckpt,load_lr=False,load_optimizer=False,load_epoch=False,strict=False,multisubj_loading=True)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "00ea5ae0-5c92-4276-af5b-25a17ba4dc17",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# checkpoint = torch.load(multisubject_ckpt+'/last.pth', map_location='cpu')\n",
+    "# state_dict = checkpoint['model_state_dict']\n",
+    "# model.load_state_dict(state_dict, strict=False)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "99f09f76-4481-4133-b09a-a22b10dbc0c4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# train_dls = [train_dl[f'subj0{s}'] for s in subj_list]\n",
+    "\n",
+    "model, optimizer, train_dl, lr_scheduler = accelerator.prepare(model, optimizer, train_dl, lr_scheduler)\n",
+    "# leaving out test_dl since we will only have local_rank 0 device do evals"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "60be0d5f-3e94-4612-9373-61b53d836393",
+   "metadata": {
+    "tags": []
+   },
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "testing_MST starting with epoch 0 / 30\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  3%|██████████████████████▎                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                      | 1/30 [00:18<08:55, 18.48s/it, test/blurry_pixcorr=0, test/loss=3.5, test/loss_clip_total=3.5, test/loss_prior=0, test/num_steps=4, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0625, test/test_fwd_pct_correct=0.0417, train/blurry_pixcorr=0, train/bwd_pct_correct=0.135, train/fwd_pct_correct=0.161, train/loss=2.25, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=2.25, train/loss_prior=0, train/lr=0.000155, train/num_steps=112, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "  7%|████████████████████████████████████████████▋                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                 | 2/30 [00:35<08:16, 17.72s/it, test/blurry_pixcorr=0, test/loss=3.36, test/loss_clip_total=3.36, test/loss_prior=0, test/num_steps=8, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0938, test/test_fwd_pct_correct=0.104, train/blurry_pixcorr=0, train/bwd_pct_correct=0.251, train/fwd_pct_correct=0.477, train/loss=1.69, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=1.69, train/loss_prior=0, train/lr=0.0003, train/num_steps=224, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 10%|██████████████████████████████████████████████████████████████████▌                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                       | 3/30 [00:52<07:52, 17.50s/it, test/blurry_pixcorr=0, test/loss=3.32, test/loss_clip_total=3.32, test/loss_prior=0, test/num_steps=12, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.146, test/test_fwd_pct_correct=0.104, train/blurry_pixcorr=0, train/bwd_pct_correct=0.567, train/fwd_pct_correct=0.665, train/loss=0.804, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.804, train/loss_prior=0, train/lr=0.000299, train/num_steps=336, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 13%|████████████████████████████████████████████████████████████████████████████████████████▋                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                | 4/30 [01:10<07:32, 17.39s/it, test/blurry_pixcorr=0, test/loss=3.37, test/loss_clip_total=3.37, test/loss_prior=0, test/num_steps=16, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0625, test/test_fwd_pct_correct=0.135, train/blurry_pixcorr=0, train/bwd_pct_correct=0.695, train/fwd_pct_correct=0.699, train/loss=0.492, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.492, train/loss_prior=0, train/lr=0.000296, train/num_steps=448, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 17%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                          | 5/30 [01:27<07:13, 17.33s/it, test/blurry_pixcorr=0, test/loss=3.15, test/loss_clip_total=3.15, test/loss_prior=0, test/num_steps=20, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0521, test/test_fwd_pct_correct=0.125, train/blurry_pixcorr=0, train/bwd_pct_correct=0.741, train/fwd_pct_correct=0.703, train/loss=0.372, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.372, train/loss_prior=0, train/lr=0.000292, train/num_steps=560, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 20%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                        | 6/30 [01:44<06:55, 17.31s/it, test/blurry_pixcorr=0, test/loss=3.1, test/loss_clip_total=3.1, test/loss_prior=0, test/num_steps=24, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0625, test/test_fwd_pct_correct=0.0938, train/blurry_pixcorr=0, train/bwd_pct_correct=0.779, train/fwd_pct_correct=0.762, train/loss=0.3, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.3, train/loss_prior=0, train/lr=0.000285, train/num_steps=672, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 23%|██████████████████████████���████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                               | 7/30 [02:01<06:37, 17.29s/it, test/blurry_pixcorr=0, test/loss=3.09, test/loss_clip_total=3.09, test/loss_prior=0, test/num_steps=28, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.104, test/test_fwd_pct_correct=0.0938, train/blurry_pixcorr=0, train/bwd_pct_correct=0.814, train/fwd_pct_correct=0.797, train/loss=0.28, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.28, train/loss_prior=0, train/lr=0.000277, train/num_steps=784, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 27%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                                                                                                                                                                                                                                                                                                                                                                                                                                                                         | 8/30 [02:19<06:19, 17.27s/it, test/blurry_pixcorr=0, test/loss=3.1, test/loss_clip_total=3.1, test/loss_prior=0, test/num_steps=32, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0729, test/test_fwd_pct_correct=0.115, train/blurry_pixcorr=0, train/bwd_pct_correct=0.795, train/fwd_pct_correct=0.776, train/loss=0.304, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.304, train/loss_prior=0, train/lr=0.000267, train/num_steps=896, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 30%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                                                                                                                                                                                                                                                                                                                                                                                                                                                  | 9/30 [02:36<06:02, 17.25s/it, test/blurry_pixcorr=0, test/loss=3.1, test/loss_clip_total=3.1, test/loss_prior=0, test/num_steps=36, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.115, test/test_fwd_pct_correct=0.0938, train/blurry_pixcorr=0, train/bwd_pct_correct=0.786, train/fwd_pct_correct=0.765, train/loss=0.277, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.277, train/loss_prior=0, train/lr=0.000256, train/num_steps=1008, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 33%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                                                                                                                                                                                                                                                                                                                                                                                                                                        | 10/30 [02:53<05:44, 17.23s/it, test/blurry_pixcorr=0, test/loss=3.13, test/loss_clip_total=3.13, test/loss_prior=0, test/num_steps=40, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.104, test/test_fwd_pct_correct=0.125, train/blurry_pixcorr=0, train/bwd_pct_correct=0.999, train/fwd_pct_correct=0.999, train/loss=0.00648, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.00648, train/loss_prior=0, train/lr=0.000244, train/num_steps=1120, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 37%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                                                                                                                                                                                                                                                                                                                                                                                                                    | 11/30 [03:10<05:26, 17.21s/it, test/blurry_pixcorr=0, test/loss=3.14, test/loss_clip_total=3.14, test/loss_prior=0, test/num_steps=44, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.125, test/test_fwd_pct_correct=0.146, train/blurry_pixcorr=0, train/bwd_pct_correct=0.997, train/fwd_pct_correct=0.997, train/loss=0.0118, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.0118, train/loss_prior=0, train/lr=0.00023, train/num_steps=1232, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 40%|███████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▌                                                                                                                                                                                                                                                                                                                                                                                                           | 12/30 [03:27<05:09, 17.20s/it, test/blurry_pixcorr=0, test/loss=3.11, test/loss_clip_total=3.11, test/loss_prior=0, test/num_steps=48, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.0938, test/test_fwd_pct_correct=0.167, train/blurry_pixcorr=0, train/bwd_pct_correct=0.999, train/fwd_pct_correct=0.999, train/loss=0.00353, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.00353, train/loss_prior=0, train/lr=0.000215, train/num_steps=1344, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 43%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▎                                                                                                                                                                                                                                                                                                                                                                                           | 13/30 [03:44<04:52, 17.19s/it, test/blurry_pixcorr=0, test/loss=3.12, test/loss_clip_total=3.12, test/loss_prior=0, test/num_steps=52, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.115, test/test_fwd_pct_correct=0.156, train/blurry_pixcorr=0, train/bwd_pct_correct=1, train/fwd_pct_correct=1, train/loss=0.00101, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.00101, train/loss_prior=0, train/lr=0.0002, train/num_steps=1456, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 47%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▊                                                                                                                                                                                                                                                                                                                                                                   | 14/30 [04:02<04:35, 17.21s/it, test/blurry_pixcorr=0, test/loss=3.12, test/loss_clip_total=3.12, test/loss_prior=0, test/num_steps=56, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.104, test/test_fwd_pct_correct=0.156, train/blurry_pixcorr=0, train/bwd_pct_correct=1, train/fwd_pct_correct=1, train/loss=0.000909, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.000909, train/loss_prior=0, train/lr=0.000183, train/num_steps=1568, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 50%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████���██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████                                                                                                                                                                                                                                                                                                                                           | 15/30 [04:19<04:18, 17.22s/it, test/blurry_pixcorr=0, test/loss=3.13, test/loss_clip_total=3.13, test/loss_prior=0, test/num_steps=60, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.115, test/test_fwd_pct_correct=0.156, train/blurry_pixcorr=0, train/bwd_pct_correct=0.999, train/fwd_pct_correct=0.999, train/loss=0.0025, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.0025, train/loss_prior=0, train/lr=0.000167, train/num_steps=1680, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      " 53%|██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▋                                                                                                                                                                                                                                                                                                                      | 16/30 [04:36<04:01, 17.24s/it, test/blurry_pixcorr=0, test/loss=3.12, test/loss_clip_total=3.12, test/loss_prior=0, test/num_steps=64, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.125, test/test_fwd_pct_correct=0.146, train/blurry_pixcorr=0, train/bwd_pct_correct=1, train/fwd_pct_correct=0.999, train/loss=0.00187, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.00187, train/loss_prior=0, train/lr=0.00015, train/num_steps=1792, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
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+     "text": [
+      "---\n"
+     ]
+    },
+    {
+     "name": "stderr",
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+     "output_type": "stream",
+     "text": [
+      "100%|█████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 30/30 [08:38<00:00, 17.28s/it, test/blurry_pixcorr=0, test/loss=3.18, test/loss_clip_total=3.18, test/loss_prior=0, test/num_steps=120, test/recon_cossim=0, test/recon_mse=0, test/test_bwd_pct_correct=0.125, test/test_fwd_pct_correct=0.125, train/blurry_pixcorr=0, train/bwd_pct_correct=0.999, train/fwd_pct_correct=0.999, train/loss=0.00424, train/loss_blurry_cont_total=0, train/loss_blurry_total=0, train/loss_clip_total=0.00424, train/loss_prior=0, train/lr=1.2e-8, train/num_steps=3360, train/recon_cossim=0, train/recon_mse=0]"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "---\n",
+      "\n",
+      "===Finished!===\n",
+      "\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "\n"
+     ]
+    }
+   ],
+   "source": [
+    "print(f\"{model_name} starting with epoch {epoch} / {num_epochs}\")\n",
+    "progress_bar = tqdm(range(epoch,num_epochs), ncols=1200, disable=(local_rank!=0))\n",
+    "test_image, test_voxel = None, None\n",
+    "mse = nn.MSELoss()\n",
+    "l1 = nn.L1Loss()\n",
+    "soft_loss_temps = utils.cosine_anneal(0.004, 0.0075, num_epochs - int(mixup_pct * num_epochs))\n",
+    "skip_train = True if epoch>=(num_epochs-1) else False # skip training if you are resuming from a fully trained model\n",
+    "\n",
+    "for epoch in progress_bar:\n",
+    "    model.train()\n",
+    "\n",
+    "    fwd_percent_correct = 0.\n",
+    "    bwd_percent_correct = 0.\n",
+    "    test_fwd_percent_correct = 0.\n",
+    "    test_bwd_percent_correct = 0.\n",
+    "    \n",
+    "    recon_cossim = 0.\n",
+    "    test_recon_cossim = 0.\n",
+    "    recon_mse = 0.\n",
+    "    test_recon_mse = 0.\n",
+    "\n",
+    "    loss_clip_total = 0.\n",
+    "    loss_blurry_total = 0.\n",
+    "    loss_blurry_cont_total = 0.\n",
+    "    test_loss_clip_total = 0.\n",
+    "    \n",
+    "    loss_prior_total = 0.\n",
+    "    test_loss_prior_total = 0.\n",
+    "\n",
+    "    blurry_pixcorr = 0.\n",
+    "    test_blurry_pixcorr = 0. \n",
+    "\n",
+    "    # you now have voxel_iters and image_iters with num_iterations_per_epoch batches each\n",
+    "    for train_i, behav in enumerate(train_dl):  \n",
+    "        with torch.cuda.amp.autocast(dtype=data_type):\n",
+    "            optimizer.zero_grad()\n",
+    "            loss = 0.\n",
+    "            \n",
+    "            behav = behav[0]\n",
+    "\n",
+    "            image = images[behav.long().cpu()].to(device)\n",
+    "            voxel = vox[behav.long().cpu()]\n",
+    "            # voxel = (voxel - train_mean) / train_std\n",
+    "            voxel = torch.Tensor(voxel).unsqueeze(1).to(device)\n",
+    "\n",
+    "            if use_image_aug: \n",
+    "                image = img_augment(image)\n",
+    "\n",
+    "            clip_target = clip_img_embedder(image)\n",
+    "            assert not torch.any(torch.isnan(clip_target))\n",
+    "\n",
+    "            if epoch < int(mixup_pct * num_epochs):\n",
+    "                voxel, perm, betas, select = utils.mixco(voxel)\n",
+    "\n",
+    "            voxel_ridge = model.ridge(voxel,0) #[model.ridge(voxel_list[si],si) for si,s in enumerate(subj_list)]\n",
+    "            # voxel_ridge = torch.cat(voxel_ridge_list, dim=0)\n",
+    "\n",
+    "            backbone, clip_voxels, blurry_image_enc_ = model.backbone(voxel_ridge)\n",
+    "\n",
+    "            if clip_scale>0:\n",
+    "                clip_voxels_norm = nn.functional.normalize(clip_voxels.flatten(1), dim=-1)\n",
+    "                clip_target_norm = nn.functional.normalize(clip_target.flatten(1), dim=-1)\n",
+    "\n",
+    "            if use_prior:\n",
+    "                loss_prior, prior_out = model.diffusion_prior(text_embed=backbone, image_embed=clip_target)\n",
+    "                loss_prior_total += loss_prior.item()\n",
+    "                loss_prior *= prior_scale\n",
+    "                loss += loss_prior\n",
+    "\n",
+    "                recon_cossim += nn.functional.cosine_similarity(prior_out, clip_target).mean().item()\n",
+    "                recon_mse += mse(prior_out, clip_target).item()\n",
+    "\n",
+    "            if clip_scale>0:\n",
+    "                if epoch < int(mixup_pct * num_epochs):                \n",
+    "                    loss_clip = utils.mixco_nce(\n",
+    "                        clip_voxels_norm,\n",
+    "                        clip_target_norm,\n",
+    "                        temp=.006,\n",
+    "                        perm=perm, betas=betas, select=select)\n",
+    "                else:\n",
+    "                    epoch_temp = soft_loss_temps[epoch-int(mixup_pct*num_epochs)]\n",
+    "                    loss_clip = utils.soft_clip_loss(\n",
+    "                        clip_voxels_norm,\n",
+    "                        clip_target_norm,\n",
+    "                        temp=epoch_temp)\n",
+    "\n",
+    "                loss_clip_total += loss_clip.item()\n",
+    "                loss_clip *= clip_scale\n",
+    "                loss += loss_clip\n",
+    "\n",
+    "            if blurry_recon:     \n",
+    "                image_enc_pred, transformer_feats = blurry_image_enc_\n",
+    "\n",
+    "                image_enc = autoenc.encode(2*image-1).latent_dist.mode() * 0.18215\n",
+    "                loss_blurry = l1(image_enc_pred, image_enc)\n",
+    "                loss_blurry_total += loss_blurry.item()\n",
+    "\n",
+    "                if epoch < int(mixup_pct * num_epochs):\n",
+    "                    image_enc_shuf = image_enc[perm]\n",
+    "                    betas_shape = [-1] + [1]*(len(image_enc.shape)-1)\n",
+    "                    image_enc[select] = image_enc[select] * betas[select].reshape(*betas_shape) + \\\n",
+    "                        image_enc_shuf[select] * (1 - betas[select]).reshape(*betas_shape)\n",
+    "\n",
+    "                image_norm = (image - mean)/std\n",
+    "                image_aug = (blur_augs(image) - mean)/std\n",
+    "                _, cnx_embeds = cnx(image_norm)\n",
+    "                _, cnx_aug_embeds = cnx(image_aug)\n",
+    "\n",
+    "                cont_loss = utils.soft_cont_loss(\n",
+    "                    nn.functional.normalize(transformer_feats.reshape(-1, transformer_feats.shape[-1]), dim=-1),\n",
+    "                    nn.functional.normalize(cnx_embeds.reshape(-1, cnx_embeds.shape[-1]), dim=-1),\n",
+    "                    nn.functional.normalize(cnx_aug_embeds.reshape(-1, cnx_embeds.shape[-1]), dim=-1),\n",
+    "                    temp=0.2)\n",
+    "                loss_blurry_cont_total += cont_loss.item()\n",
+    "\n",
+    "                loss += (loss_blurry + 0.1*cont_loss) * blur_scale #/.18215\n",
+    "\n",
+    "            if clip_scale>0:\n",
+    "                # forward and backward top 1 accuracy        \n",
+    "                labels = torch.arange(len(clip_voxels_norm)).to(clip_voxels_norm.device) \n",
+    "                fwd_percent_correct += utils.topk(utils.batchwise_cosine_similarity(clip_voxels_norm, clip_target_norm), labels, k=1).item()\n",
+    "                bwd_percent_correct += utils.topk(utils.batchwise_cosine_similarity(clip_target_norm, clip_voxels_norm), labels, k=1).item()\n",
+    "\n",
+    "            if blurry_recon:\n",
+    "                with torch.no_grad():\n",
+    "                    # only doing pixcorr eval on a subset of the samples per batch because its costly & slow to compute autoenc.decode()\n",
+    "                    random_samps = np.random.choice(np.arange(len(image)), size=len(image)//5, replace=False)\n",
+    "                    blurry_recon_images = (autoenc.decode(image_enc_pred[random_samps]/0.18215).sample/ 2 + 0.5).clamp(0,1)\n",
+    "                    pixcorr = utils.pixcorr(image[random_samps], blurry_recon_images)\n",
+    "                    blurry_pixcorr += pixcorr.item()\n",
+    "            \n",
+    "            utils.check_loss(loss)\n",
+    "            accelerator.backward(loss)\n",
+    "            optimizer.step()\n",
+    "\n",
+    "            losses.append(loss.item())\n",
+    "            lrs.append(optimizer.param_groups[0]['lr'])\n",
+    "\n",
+    "            if lr_scheduler_type is not None:\n",
+    "                lr_scheduler.step()\n",
+    "                \n",
+    "            if train_i >= num_iterations_per_epoch-1:\n",
+    "                break\n",
+    "                \n",
+    "    model.eval()\n",
+    "    if local_rank==0:\n",
+    "        with torch.no_grad(), torch.cuda.amp.autocast(dtype=data_type): \n",
+    "            for test_i, behav in enumerate(test_dl):  \n",
+    "                behav = behav[0]\n",
+    "\n",
+    "                loss=0.\n",
+    "\n",
+    "                if behav.ndim>1:\n",
+    "                    image = images[behav[:,0].long().cpu()].to(device)\n",
+    "                    voxel = vox[behav.long().cpu()].mean(1)\n",
+    "                else:\n",
+    "                    image = images[behav.long().cpu()].to(device)\n",
+    "                    voxel = vox[behav.long().cpu()]\n",
+    "                    \n",
+    "                voxel = torch.Tensor(voxel).unsqueeze(1).to(device)\n",
+    "\n",
+    "                clip_img_embedder = clip_img_embedder.to(device)\n",
+    "                clip_target = clip_img_embedder(image.float())\n",
+    "                \n",
+    "                voxel_ridge = model.ridge(voxel,0)\n",
+    "\n",
+    "                backbone, clip_voxels, blurry_image_enc_ = model.backbone(voxel_ridge)\n",
+    "\n",
+    "                if clip_scale>0:\n",
+    "                    clip_voxels_norm = nn.functional.normalize(clip_voxels.flatten(1), dim=-1)\n",
+    "                    clip_target_norm = nn.functional.normalize(clip_target.flatten(1), dim=-1)\n",
+    "                \n",
+    "                # for some evals, only doing a subset of the samples per batch because of computational cost\n",
+    "                random_samps = np.random.choice(np.arange(len(image)), size=len(image)//5, replace=False)\n",
+    "                \n",
+    "                if use_prior:\n",
+    "                    loss_prior, contaminated_prior_out = model.diffusion_prior(text_embed=backbone[random_samps], image_embed=clip_target[random_samps])\n",
+    "                    test_loss_prior_total += loss_prior.item()\n",
+    "                    loss_prior *= prior_scale\n",
+    "                    loss += loss_prior\n",
+    "                        \n",
+    "                if clip_scale>0:\n",
+    "                    loss_clip = utils.soft_clip_loss(\n",
+    "                        clip_voxels_norm,\n",
+    "                        clip_target_norm,\n",
+    "                        temp=.006)\n",
+    "\n",
+    "                    test_loss_clip_total += loss_clip.item()\n",
+    "                    loss_clip = loss_clip * clip_scale\n",
+    "                    loss += loss_clip\n",
+    "\n",
+    "                if blurry_recon:\n",
+    "                    image_enc_pred, _ = blurry_image_enc_\n",
+    "                    blurry_recon_images = (autoenc.decode(image_enc_pred[random_samps]/0.18215).sample / 2 + 0.5).clamp(0,1)\n",
+    "                    pixcorr = utils.pixcorr(image[random_samps], blurry_recon_images)\n",
+    "                    test_blurry_pixcorr += pixcorr.item()\n",
+    "\n",
+    "                if clip_scale>0:\n",
+    "                    # forward and backward top 1 accuracy        \n",
+    "                    labels = torch.arange(len(clip_voxels_norm)).to(clip_voxels_norm.device) \n",
+    "                    test_fwd_percent_correct += utils.topk(utils.batchwise_cosine_similarity(clip_voxels_norm, clip_target_norm), labels, k=1).item()\n",
+    "                    test_bwd_percent_correct += utils.topk(utils.batchwise_cosine_similarity(clip_target_norm, clip_voxels_norm), labels, k=1).item()\n",
+    "                \n",
+    "                utils.check_loss(loss)                \n",
+    "                test_losses.append(loss.item())\n",
+    "\n",
+    "            # if utils.is_interactive(): clear_output(wait=True)\n",
+    "            if skip_train: break\n",
+    "            print(\"---\")\n",
+    "\n",
+    "            # assert (test_i+1) == 1\n",
+    "            logs = {\"train/loss\": np.mean(losses[-(train_i+1):]),\n",
+    "                \"test/loss\": np.mean(test_losses[-(test_i+1):]),\n",
+    "                \"train/lr\": lrs[-1],\n",
+    "                \"train/num_steps\": len(losses),\n",
+    "                \"test/num_steps\": len(test_losses),\n",
+    "                \"train/fwd_pct_correct\": fwd_percent_correct / (train_i + 1),\n",
+    "                \"train/bwd_pct_correct\": bwd_percent_correct / (train_i + 1),\n",
+    "                \"test/test_fwd_pct_correct\": test_fwd_percent_correct / (test_i + 1),\n",
+    "                \"test/test_bwd_pct_correct\": test_bwd_percent_correct / (test_i + 1),\n",
+    "                \"train/loss_clip_total\": loss_clip_total / (train_i + 1),\n",
+    "                \"train/loss_blurry_total\": loss_blurry_total / (train_i + 1),\n",
+    "                \"train/loss_blurry_cont_total\": loss_blurry_cont_total / (train_i + 1),\n",
+    "                \"test/loss_clip_total\": test_loss_clip_total / (test_i + 1),\n",
+    "                \"train/blurry_pixcorr\": blurry_pixcorr / (train_i + 1),\n",
+    "                \"test/blurry_pixcorr\": test_blurry_pixcorr / (test_i + 1),\n",
+    "                \"train/recon_cossim\": recon_cossim / (train_i + 1),\n",
+    "                \"test/recon_cossim\": test_recon_cossim / (test_i + 1),\n",
+    "                \"train/recon_mse\": recon_mse / (train_i + 1),\n",
+    "                \"test/recon_mse\": test_recon_mse / (test_i + 1),\n",
+    "                \"train/loss_prior\": loss_prior_total / (train_i + 1),\n",
+    "                \"test/loss_prior\": test_loss_prior_total / (test_i + 1),\n",
+    "                }\n",
+    "\n",
+    "            # if finished training, save jpg recons if they exist\n",
+    "            if (epoch == num_epochs-1) or (epoch % ckpt_interval == 0):\n",
+    "                if blurry_recon:    \n",
+    "                    image_enc = autoenc.encode(2*image[:4]-1).latent_dist.mode() * 0.18215\n",
+    "                    # transform blurry recon latents to images and plot it\n",
+    "                    fig, axes = plt.subplots(1, 8, figsize=(10, 4))\n",
+    "                    jj=-1\n",
+    "                    for j in [0,1,2,3]:\n",
+    "                        jj+=1\n",
+    "                        axes[jj].imshow(utils.torch_to_Image((autoenc.decode(image_enc[[j]]/0.18215).sample / 2 + 0.5).clamp(0,1)))\n",
+    "                        axes[jj].axis('off')\n",
+    "                        jj+=1\n",
+    "                        axes[jj].imshow(utils.torch_to_Image((autoenc.decode(image_enc_pred[[j]]/0.18215).sample / 2 + 0.5).clamp(0,1)))\n",
+    "                        axes[jj].axis('off')\n",
+    "                    plt.show()\n",
+    "\n",
+    "            progress_bar.set_postfix(**logs)\n",
+    "\n",
+    "            if wandb_log: wandb.log(logs)\n",
+    "            \n",
+    "    # Save model checkpoint and reconstruct\n",
+    "    if (ckpt_saving) and (epoch % ckpt_interval == 0):\n",
+    "        save_ckpt(f'last')\n",
+    "\n",
+    "    # wait for other GPUs to catch up if needed\n",
+    "    accelerator.wait_for_everyone()\n",
+    "    torch.cuda.empty_cache()\n",
+    "\n",
+    "print(\"\\n===Finished!===\\n\")\n",
+    "if ckpt_saving:\n",
+    "    save_ckpt(f'last')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "5702acf6-45fe-44f5-8842-c0e2d4d8e8ce",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# # Track metrics here:\n",
+    "# https://docs.google.com/spreadsheets/d/1-dbmr4ovl2-4-MFNAL1DqLS651KM_ihjDkkUeP1kHXs/edit?gid=1494588999#gid=1494588999"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "23a54acc-1dce-4de4-9d5f-d0582f5097c5",
+   "metadata": {},
+   "source": [
+    "**To tell if the model is working I'm looking at test_bwd/fwd_pct_correct and seeing if that is doing better than chance (1/batch_size)**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "3d1501cd-0473-4faa-8bfc-b2e2472559ae",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "array([['all_stimuli/rtmindeye_stimuli/10_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/12_0.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/12_56.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/13_44.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/13_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/14_33.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/14_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/15_44.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/15_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/16_22.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/16_78.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/17_56.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/17_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/18_22.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/18_78.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/19_0.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/19_56.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/1_22.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/1_78.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/20_0.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/20_56.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/21_0.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/21_33.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/3_56.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/3_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/4_22.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/4_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/5_100.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/5_33.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/6_44.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/6_89.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/8_0.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/8_78.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/9_11.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/9_56.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/image_0_seed_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_115_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_156_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_156_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_158_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_158_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_206_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_206_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_25_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_25_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_41_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_41_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_483_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_483_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_48_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_48_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_505_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_505_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_547_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_547_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_556_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_556_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_676_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_676_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_694_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_694_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_6_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_6_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_762_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_762_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_777_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_777_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_875_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_875_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_886_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_886_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/paired_image_949_1.png'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/paired_image_949_2.png',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_airplane_interior1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_airplane_interior2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_arch1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_arch2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_corridor1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_corridor2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_escalator1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_escalator2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_gym1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_gym2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_icerink1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_icerink2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_lighthouse1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_lighthouse2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_log_cabin1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_log_cabin2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_pagoda1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_pagoda2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_pool1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_pool2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_roller_coaster1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_roller_coaster2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_runway1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_runway2.jpg',\n",
+       "        'all_stimuli/rtmindeye_stimuli/w_yoga_studio1.jpg'],\n",
+       "       ['all_stimuli/rtmindeye_stimuli/w_yoga_studio2.jpg', 'blank.jpg']],\n",
+       "      dtype='<U54')"
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if sub==\"sub-002\":\n",
+    "    unique_images_pairs = [\n",
+    "        (2,3),(4,5),(7,8),(15,16),\n",
+    "        (483, 484), (485, 486), (487, 488), (491, 492), (495, 496), (499, 500), (501, 502),\n",
+    "        (503, 504), (512, 513), \n",
+    "    ]\n",
+    "else:\n",
+    "    unique_images_pairs = [\n",
+    "        (1,2),(3,4),(5,6),(7,8),(9,10),(11,12),(13,14),(15,16),\n",
+    "        (17,18),(19,20),(21,22),(23,24),(25,26),(27,28),(29,30),\n",
+    "        (31,32),(33,34),(35,36),\n",
+    "        (787, 788), (789, 790), (791, 792), (793, 794), (795, 796),\n",
+    "        (797, 798), (799, 800), (801, 802), (803, 804), (805, 806),\n",
+    "        (807, 808), (809, 810), (811, 812), (813, 814), (815, 816),\n",
+    "        (817, 818), (819, 820), (821, 822), (823, 824), (825, 826),\n",
+    "        (827, 828), (829, 830), (831, 832), (833, 834), (835, 836),\n",
+    "        (837, 838), (839, 840), (841, 842), (843, 844), (845, 846),\n",
+    "        (847, 848), (849, 850)\n",
+    "    ]\n",
+    "unique_images[unique_images_pairs]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "e97de7b2-2a32-4ce7-9533-aa8e06946cfe",
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "ValueError",
+     "evalue": "can only convert an array of size 1 to a Python scalar",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mValueError\u001b[0m                                Traceback (most recent call last)",
+      "Cell \u001b[0;32mIn[51], line 7\u001b[0m\n\u001b[1;32m      5\u001b[0m imageA_idx, imageB_idx \u001b[38;5;241m=\u001b[39m pair\n\u001b[1;32m      6\u001b[0m imageA_idx \u001b[38;5;241m=\u001b[39m np\u001b[38;5;241m.\u001b[39mwhere(image_idx \u001b[38;5;241m==\u001b[39m imageA_idx)[\u001b[38;5;241m0\u001b[39m]\u001b[38;5;241m.\u001b[39mitem()\n\u001b[0;32m----> 7\u001b[0m imageB_idx \u001b[38;5;241m=\u001b[39m \u001b[43mnp\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mwhere\u001b[49m\u001b[43m(\u001b[49m\u001b[43mimage_idx\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m==\u001b[39;49m\u001b[43m \u001b[49m\u001b[43mimageB_idx\u001b[49m\u001b[43m)\u001b[49m\u001b[43m[\u001b[49m\u001b[38;5;241;43m0\u001b[39;49m\u001b[43m]\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mitem\u001b[49m\u001b[43m(\u001b[49m\u001b[43m)\u001b[49m\n\u001b[1;32m      9\u001b[0m voxel \u001b[38;5;241m=\u001b[39m vox[imageA_idx]\u001b[38;5;241m.\u001b[39mto(device)[\u001b[38;5;28;01mNone\u001b[39;00m]\n\u001b[1;32m     10\u001b[0m voxel \u001b[38;5;241m=\u001b[39m torch\u001b[38;5;241m.\u001b[39mTensor(voxel)\u001b[38;5;241m.\u001b[39munsqueeze(\u001b[38;5;241m1\u001b[39m)\u001b[38;5;241m.\u001b[39mto(device)\n",
+      "\u001b[0;31mValueError\u001b[0m: can only convert an array of size 1 to a Python scalar"
+     ]
+    }
+   ],
+   "source": [
+    "score = 0\n",
+    "total = 0\n",
+    "with torch.no_grad(), torch.cuda.amp.autocast(dtype=data_type): \n",
+    "    for pair in unique_images_pairs:\n",
+    "        imageA_idx, imageB_idx = pair\n",
+    "        imageA_idx = np.where(image_idx == imageA_idx)[0].item()\n",
+    "        imageB_idx = np.where(image_idx == imageB_idx)[0].item()\n",
+    "        \n",
+    "        voxel = vox[imageA_idx].to(device)[None]\n",
+    "        voxel = torch.Tensor(voxel).unsqueeze(1).to(device)\n",
+    "        \n",
+    "        imageA = images[imageA_idx].to(device)[None]\n",
+    "        imageB = images[imageB_idx].to(device)[None]\n",
+    "\n",
+    "        clip_targetA = clip_img_embedder(imageA.float())\n",
+    "        clip_targetB = clip_img_embedder(imageB.float())\n",
+    "        \n",
+    "        voxel_ridge = model.ridge(voxel,0)\n",
+    "        backbone, clip_voxels, blurry_image_enc_ = model.backbone(voxel_ridge)\n",
+    "\n",
+    "        clip_voxels_norm = nn.functional.normalize(clip_voxels.flatten(1), dim=-1)\n",
+    "        clip_targetA_norm = nn.functional.normalize(clip_targetA.flatten(1), dim=-1)\n",
+    "        clip_targetB_norm = nn.functional.normalize(clip_targetB.flatten(1), dim=-1)\n",
+    "\n",
+    "        cossimA = utils.batchwise_cosine_similarity(clip_voxels_norm, clip_targetA_norm)\n",
+    "        cossimB = utils.batchwise_cosine_similarity(clip_voxels_norm, clip_targetB_norm)\n",
+    "        \n",
+    "        if cossimA > cossimB:\n",
+    "            score += 1\n",
+    "        total += 1\n",
+    "        \n",
+    "    for pair in unique_images_pairs:\n",
+    "        imageA_idx, imageB_idx = pair\n",
+    "        imageA_idx = np.where(image_idx == imageA_idx)[0].item()\n",
+    "        imageB_idx = np.where(image_idx == imageB_idx)[0].item()\n",
+    "        \n",
+    "        voxel = vox[imageB_idx].to(device)[None]\n",
+    "        voxel = torch.Tensor(voxel).unsqueeze(1).to(device)\n",
+    "        \n",
+    "        imageA = images[imageA_idx].to(device)[None]\n",
+    "        imageB = images[imageB_idx].to(device)[None]\n",
+    "\n",
+    "        clip_targetA = clip_img_embedder(imageA.float())\n",
+    "        clip_targetB = clip_img_embedder(imageB.float())\n",
+    "        \n",
+    "        voxel_ridge = model.ridge(voxel,0)\n",
+    "        backbone, clip_voxels, blurry_image_enc_ = model.backbone(voxel_ridge)\n",
+    "\n",
+    "        clip_voxels_norm = nn.functional.normalize(clip_voxels.flatten(1), dim=-1)\n",
+    "        clip_targetA_norm = nn.functional.normalize(clip_targetA.flatten(1), dim=-1)\n",
+    "        clip_targetB_norm = nn.functional.normalize(clip_targetB.flatten(1), dim=-1)\n",
+    "\n",
+    "        cossimA = utils.batchwise_cosine_similarity(clip_voxels_norm, clip_targetA_norm)\n",
+    "        cossimB = utils.batchwise_cosine_similarity(clip_voxels_norm, clip_targetB_norm)\n",
+    "        \n",
+    "        if cossimB > cossimA:\n",
+    "            score += 1\n",
+    "        total += 1\n",
+    "\n",
+    "print(score/total)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "ee4bd720-864a-480a-818e-e7e61c8ad429",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#display(utils.torch_to_Image(imageA))\n",
+    "#display(utils.torch_to_Image(imageB))"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "b0b54c3d-7544-4249-a0da-c4ae90b5172a",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from scipy.stats import binomtest\n",
+    "\n",
+    "total_samples = len(np.array(unique_images_pairs).flatten())\n",
+    "assert total_samples == 100\n",
+    "\n",
+    "correct_predictions = int((score/total) * total_samples)  # calculate the number of correct predictions\n",
+    "expected_accuracy = 0.5  # expected accuracy under the null hypothesis\n",
+    "\n",
+    "# Perform the binomial test\n",
+    "binom_stats = binomtest(correct_predictions, total_samples, expected_accuracy, alternative='greater')\n",
+    "p_value = binom_stats.pvalue\n",
+    "\n",
+    "# Output the result\n",
+    "print(f\"P-value: {p_value}\")\n",
+    "if p_value < 0.05:\n",
+    "    print(\"The decoder's accuracy is significantly better than chance.\")\n",
+    "else:\n",
+    "    print(\"The decoder's accuracy is not significantly better than chance.\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "68473420-d978-4d4d-ba51-90e02e62741b",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "rt_mindEye2 [~/.conda/envs/rt_mindEye2/]",
+   "language": "python",
+   "name": "conda_rt_mindeye2"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.7"
+  },
+  "toc": {
+   "base_numbering": 1,
+   "nav_menu": {},
+   "number_sections": true,
+   "sideBar": true,
+   "skip_h1_title": false,
+   "title_cell": "Table of Contents",
+   "title_sidebar": "Contents",
+   "toc_cell": false,
+   "toc_position": {
+    "height": "calc(100% - 180px)",
+    "left": "10px",
+    "top": "150px",
+    "width": "165px"
+   },
+   "toc_section_display": true,
+   "toc_window_display": true
+  },
+  "toc-autonumbering": true,
+  "vscode": {
+   "interpreter": {
+    "hash": "62aae01ef0cf7b6af841ab1c8ce59175c4332e693ab3d00bc32ceffb78a35376"
+   }
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}