Zindi_CGIAR_CNN.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### CNN for predicting crop yield using preprocessed arrays\n",
    "Author: Vivek Jayaswal \\\n",
    "Date: 20-Dec-2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import pandas as pd\n",
    "import torch\n",
    "from torch.utils.data import TensorDataset, DataLoader\n",
    "import torch.nn.functional as F"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Load custom functions\n",
    "%run Zindi_CGIAR_Functions.ipynb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "in_dir = 'C:/Work/Vivek_Work/Challenge_Data_Sets/Zindi/CGIAR/{}'\n",
    "trng_dir = 'C:/Work/Vivek_Work/Challenge_Data_Sets/Zindi/CGIAR/image_arrays_train/{}_Rev.npy'\n",
    "test_dir = 'C:/Work/Vivek_Work/Challenge_Data_Sets/Zindi/CGIAR/image_arrays_test/{}_Rev.npy'\n",
    "\n",
    "trng_data_annot = pd.read_csv(in_dir.format('Train.csv'))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
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       "    }\n",
       "\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Field_ID</th>\n",
       "      <th>Year</th>\n",
       "      <th>Quality</th>\n",
       "      <th>Yield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>MH2O0YH</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>3.686</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>O9TURWL</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>5.657</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>35AFSDD</td>\n",
       "      <td>2019</td>\n",
       "      <td>3</td>\n",
       "      <td>3.082</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>PM05EG9</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>2.707</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>V7PZBCG</td>\n",
       "      <td>2019</td>\n",
       "      <td>2</td>\n",
       "      <td>2.679</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Field_ID  Year  Quality  Yield\n",
       "0  MH2O0YH  2019        3  3.686\n",
       "1  O9TURWL  2019        2  5.657\n",
       "2  35AFSDD  2019        3  3.082\n",
       "3  PM05EG9  2019        2  2.707\n",
       "4  V7PZBCG  2019        2  2.679"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "trng_data_annot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(array([2, 3], dtype=int64), array([1231, 1321], dtype=int64))"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Remove poor quality images (quality = 1)\n",
    "trng_data_annot = trng_data_annot[trng_data_annot['Quality'] != 1]\n",
    "np.unique(trng_data_annot['Quality'], return_counts=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counter =  0\n",
      "Counter =  500\n",
      "Counter =  1000\n",
      "Counter =  1500\n",
      "Counter =  2000\n",
      "Counter =  2500\n"
     ]
    }
   ],
   "source": [
    "# Load all preprocessed 3-d arrays channels x bins x time into 4-d arrays\n",
    "field_names = trng_data_annot['Field_ID']\n",
    "num_fields = len(field_names)\n",
    "field_arrays = np.zeros((num_fields, 27, 20, 12))\n",
    "\n",
    "for current_idx in range(num_fields):\n",
    "    if current_idx%500 == 0:\n",
    "        print('Counter = ', current_idx)\n",
    "    temp_array = np.load(trng_dir.format(field_names.values[current_idx]))\n",
    "    field_arrays[current_idx] = temp_array"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "field_arrays[0, 0, :, :].sum()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Option 1: Dataset and DataLoader Generation\n",
    "Use of custom Dataset Class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Generate custom Dataset object for use with DataLoader for batch creation\n",
    "# Need to pass NumPy Arrays and not Pandas objects\n",
    "zindi_dataset = ZindiDataset(field_arrays, trng_data_annot['Yield'].values)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Array dimensions =  (27, 20, 12)\n",
      "Yield =  3.686\n"
     ]
    }
   ],
   "source": [
    "# Input array and its value\n",
    "print('Array dimensions = ', zindi_dataset[0][0].shape)\n",
    "print('Yield = ', zindi_dataset[0][1])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate batches of size 32\n",
    "zindi_dataloader = torch.utils.data.DataLoader(zindi_dataset, batch_size=32, shuffle=False)\n",
    "len(zindi_dataloader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "79.75"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of batches of size 32\n",
    "2552/32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Display the batch details\n",
    "temp = iter(zindi_dataloader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
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       "           [0.0000e+00, 3.6151e-03, 1.3474e-02,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 5.1487e-03],\n",
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       "           ...,\n",
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       " \n",
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       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
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       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
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       "           ...,\n",
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       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
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       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[6.2963e-02, 8.8906e-02, 8.8906e-02,  ..., 2.0968e-02,\n",
       "            9.9568e-02, 5.9764e-02],\n",
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       "           ...,\n",
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       " \n",
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       "           ...,\n",
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       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 1.0000e-01],\n",
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       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[9.1592e-02, 3.0457e-02, 4.8719e-02,  ..., 6.8374e-02,\n",
       "            7.9566e-02, 1.5033e-03],\n",
       "           [2.0045e-03, 6.3140e-02, 4.4878e-02,  ..., 0.0000e+00,\n",
       "            1.4031e-02, 8.0178e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 6.0134e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 6.6815e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
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       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 6.0134e-03]],\n",
       " \n",
       "          [[1.5521e-02, 5.7524e-03, 6.9463e-03,  ..., 6.4525e-02,\n",
       "            1.7800e-02, 2.5506e-03],\n",
       "           [6.5719e-02, 5.2477e-02, 5.5082e-02,  ..., 2.2304e-02,\n",
       "            6.4633e-02, 1.3241e-02],\n",
       "           [8.7914e-03, 3.0987e-02, 2.7297e-02,  ..., 2.7134e-03,\n",
       "            7.5975e-03, 9.6597e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 4.1244e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 3.2018e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 2.2250e-03]],\n",
       " \n",
       "          [[3.3584e-03, 1.0834e-03, 9.7503e-04,  ..., 3.4126e-03,\n",
       "            1.6792e-03, 3.7918e-04],\n",
       "           [2.3563e-02, 1.0400e-02, 9.9128e-03,  ..., 4.3822e-02,\n",
       "            1.5005e-02, 5.2543e-03],\n",
       "           [5.2760e-02, 4.9293e-02, 4.8372e-02,  ..., 3.9434e-02,\n",
       "            5.6931e-02, 8.3961e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 3.9001e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 3.7918e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 2.2209e-03]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 8.3333e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 2.0325e-02,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.3333e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            9.0909e-02, 9.0909e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         ...,\n",
       " \n",
       " \n",
       "         [[[5.4060e-02, 6.9065e-02, 1.2950e-02,  ..., 8.4224e-02,\n",
       "            0.0000e+00, 2.4666e-02],\n",
       "           [3.2323e-02, 1.7318e-02, 7.3124e-02,  ..., 2.1583e-03,\n",
       "            4.5735e-03, 3.9877e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 3.0832e-04,  ..., 0.0000e+00,\n",
       "            4.9332e-03, 2.1840e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            1.8499e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            8.0164e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            1.8499e-03, 0.0000e+00]],\n",
       " \n",
       "          [[2.7802e-02, 2.7243e-02, 7.0140e-03,  ..., 4.6150e-02,\n",
       "            0.0000e+00, 2.2313e-02],\n",
       "           [5.2757e-02, 5.2554e-02, 6.9022e-02,  ..., 3.5172e-02,\n",
       "            9.0978e-03, 3.8323e-02],\n",
       "           [3.4562e-03, 4.8285e-03, 7.2681e-03,  ..., 3.1004e-03,\n",
       "            5.5909e-03, 2.3990e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.6760e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.6760e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.8793e-03, 0.0000e+00]],\n",
       " \n",
       "          [[1.5799e-03, 1.6308e-03, 5.0963e-05,  ..., 1.2741e-03,\n",
       "            0.0000e+00, 1.4525e-02],\n",
       "           [5.2186e-02, 4.8007e-02, 2.6501e-02,  ..., 4.8976e-02,\n",
       "            5.6060e-04, 3.7815e-02],\n",
       "           [2.8132e-02, 3.0731e-02, 5.0250e-02,  ..., 3.0986e-02,\n",
       "            8.6128e-03, 3.1750e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            5.3002e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            5.0454e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.9944e-03, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 9.0909e-02,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 9.0909e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[7.1728e-02, 7.4086e-02, 3.7724e-03,  ..., 8.4303e-02,\n",
       "            4.4850e-02, 3.2851e-02],\n",
       "           [1.6347e-02, 1.3989e-02, 8.3360e-02,  ..., 3.7724e-03,\n",
       "            4.3225e-02, 5.5224e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 9.4310e-04,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[1.4222e-02, 1.1954e-02, 3.9161e-03,  ..., 2.0611e-02,\n",
       "            6.5956e-03, 1.8756e-02],\n",
       "           [7.0232e-02, 7.0490e-02, 6.9408e-02,  ..., 6.3894e-02,\n",
       "            7.7395e-02, 6.5749e-02],\n",
       "           [1.9581e-03, 3.9161e-03, 1.1903e-02,  ..., 1.8035e-03,\n",
       "            2.5249e-03, 1.7004e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[2.3719e-03, 2.1656e-03, 3.0937e-04,  ..., 2.1141e-03,\n",
       "            9.2812e-04, 3.1969e-03],\n",
       "           [3.4547e-02, 2.3976e-02, 8.4047e-03,  ..., 2.1759e-02,\n",
       "            2.0831e-02, 4.4962e-02],\n",
       "           [4.7076e-02, 5.3315e-02, 5.8884e-02,  ..., 5.7131e-02,\n",
       "            6.0689e-02, 3.6764e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 9.0909e-02,\n",
       "            6.4302e-02, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.5417e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[4.6259e-02, 6.2299e-02, 1.3039e-02,  ..., 7.8909e-02,\n",
       "            3.1978e-02, 3.7256e-03],\n",
       "           [4.0722e-02, 2.4682e-02, 7.3942e-02,  ..., 8.0720e-03,\n",
       "            5.5004e-02, 8.3256e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[1.7289e-02, 1.6877e-02, 5.6771e-03,  ..., 2.9882e-02,\n",
       "            1.1199e-02, 6.5545e-03],\n",
       "           [6.6268e-02, 6.6319e-02, 6.9571e-02,  ..., 5.1765e-02,\n",
       "            7.1480e-02, 7.4732e-02],\n",
       "           [2.4773e-03, 2.6321e-03, 1.0477e-02,  ..., 4.4901e-03,\n",
       "            3.0966e-03, 3.8192e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[1.7528e-03, 1.5466e-03, 0.0000e+00,  ..., 2.2167e-03,\n",
       "            3.6086e-04, 7.2172e-04],\n",
       "           [2.9848e-02, 2.7426e-02, 1.5878e-02,  ..., 2.4075e-02,\n",
       "            2.3353e-02, 2.0363e-02],\n",
       "           [5.1449e-02, 5.2119e-02, 4.9902e-02,  ..., 5.1242e-02,\n",
       "            5.5109e-02, 5.0263e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 9.0909e-02,\n",
       "            9.0909e-02, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.3333e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]]], dtype=torch.float64),\n",
       " tensor([3.6860, 5.6570, 3.0820, 2.7070, 2.6790, 4.3170, 2.9990, 4.1990, 3.5050,\n",
       "         5.0390, 3.1720, 2.3530, 2.9570, 3.2690, 3.1170, 2.7900, 4.8590, 2.5680,\n",
       "         0.9860, 3.4980, 2.6380, 4.4560, 4.1650, 4.0190, 3.5470, 2.4430, 4.3150,\n",
       "         2.2360, 3.4190, 3.4710, 4.0810, 0.4580], dtype=torch.float64)]"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(temp)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Option 2: Dataset and DataLoader Generation\n",
    "Use of TensorDataset"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [],
   "source": [
    "# An alternate approach to generating Dataset\n",
    "rev_zindi_dataset = TensorDataset(torch.FloatTensor(field_arrays),torch.FloatTensor(trng_data_annot['Yield']))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(tensor([[[0.0812, 0.0885, 0.0786,  ..., 0.0921, 0.0921, 0.0830],\n",
       "          [0.0000, 0.0036, 0.0135,  ..., 0.0000, 0.0000, 0.0051],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0020],\n",
       "          ...,\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000]],\n",
       " \n",
       "         [[0.0438, 0.0242, 0.0182,  ..., 0.0669, 0.0609, 0.0718],\n",
       "          [0.0466, 0.0610, 0.0673,  ..., 0.0236, 0.0296, 0.0180],\n",
       "          [0.0003, 0.0057, 0.0052,  ..., 0.0004, 0.0004, 0.0008],\n",
       "          ...,\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000]],\n",
       " \n",
       "         [[0.0070, 0.0027, 0.0012,  ..., 0.0014, 0.0012, 0.0486],\n",
       "          [0.0490, 0.0284, 0.0287,  ..., 0.0360, 0.0482, 0.0292],\n",
       "          [0.0346, 0.0545, 0.0557,  ..., 0.0516, 0.0404, 0.0104],\n",
       "          ...,\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000]],\n",
       " \n",
       "         ...,\n",
       " \n",
       "         [[0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          ...,\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000]],\n",
       " \n",
       "         [[0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.1250, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.1250, 0.0000],\n",
       "          ...,\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000]],\n",
       " \n",
       "         [[0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          ...,\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000],\n",
       "          [0.0000, 0.0000, 0.0000,  ..., 0.0000, 0.0000, 0.0000]]]),\n",
       " tensor(3.6860))"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "rev_zindi_dataset[0]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "80"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Generate batches of size 32\n",
    "zindi_dataloader = torch.utils.data.DataLoader(rev_zindi_dataset, batch_size=32, shuffle=False)\n",
    "len(zindi_dataloader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [],
   "source": [
    "temp = iter(zindi_dataloader)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[tensor([[[[8.1229e-02, 8.8459e-02, 7.8600e-02,  ..., 9.2074e-02,\n",
       "            9.2074e-02, 8.2982e-02],\n",
       "           [0.0000e+00, 3.6151e-03, 1.3474e-02,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 5.1487e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 1.9718e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[4.3817e-02, 2.4180e-02, 1.8230e-02,  ..., 6.6861e-02,\n",
       "            6.0857e-02, 7.1838e-02],\n",
       "           [4.6630e-02, 6.0965e-02, 6.7348e-02,  ..., 2.3585e-02,\n",
       "            2.9644e-02, 1.7960e-02],\n",
       "           [2.7047e-04, 5.6800e-03, 5.2472e-03,  ..., 3.7866e-04,\n",
       "            4.3276e-04, 8.1142e-04],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[7.0445e-03, 2.7094e-03, 1.1922e-03,  ..., 1.3547e-03,\n",
       "            1.2463e-03, 4.8553e-02],\n",
       "           [4.8987e-02, 2.8395e-02, 2.8666e-02,  ..., 3.5981e-02,\n",
       "            4.8174e-02, 2.9154e-02],\n",
       "           [3.4572e-02, 5.4514e-02, 5.5706e-02,  ..., 5.1642e-02,\n",
       "            4.0371e-02, 1.0404e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 1.2500e-01,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            1.2500e-01, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[6.2963e-02, 8.8906e-02, 8.8906e-02,  ..., 2.0968e-02,\n",
       "            9.9568e-02, 5.9764e-02],\n",
       "           [0.0000e+00, 6.3970e-03, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 7.1077e-04],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[5.0630e-02, 3.7477e-02, 4.4688e-02,  ..., 6.7946e-02,\n",
       "            5.8806e-02, 7.1196e-02],\n",
       "           [2.7524e-02, 4.2860e-02, 3.6208e-02,  ..., 5.3321e-03,\n",
       "            2.5036e-02, 7.8204e-03],\n",
       "           [9.1408e-04, 4.1641e-03, 1.6758e-03,  ..., 6.6017e-04,\n",
       "            7.6173e-04, 1.1172e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[2.2411e-02, 1.3675e-02, 1.6119e-02,  ..., 2.0955e-02,\n",
       "            1.0503e-02, 2.8026e-02],\n",
       "           [4.5029e-02, 4.1701e-02, 4.4717e-02,  ..., 5.2413e-02,\n",
       "            4.6849e-02, 6.4476e-03],\n",
       "           [1.6587e-02, 2.7038e-02, 2.3970e-02,  ..., 1.1959e-02,\n",
       "            2.7246e-02, 5.6156e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 8.3333e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.3333e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 1.0000e-01],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            1.0000e-01, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[9.1592e-02, 3.0457e-02, 4.8719e-02,  ..., 6.8374e-02,\n",
       "            7.9566e-02, 1.5033e-03],\n",
       "           [2.0045e-03, 6.3140e-02, 4.4878e-02,  ..., 0.0000e+00,\n",
       "            1.4031e-02, 8.0178e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 6.0134e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 6.6815e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 4.6771e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 6.0134e-03]],\n",
       " \n",
       "          [[1.5521e-02, 5.7524e-03, 6.9463e-03,  ..., 6.4525e-02,\n",
       "            1.7800e-02, 2.5506e-03],\n",
       "           [6.5719e-02, 5.2477e-02, 5.5082e-02,  ..., 2.2304e-02,\n",
       "            6.4633e-02, 1.3241e-02],\n",
       "           [8.7914e-03, 3.0987e-02, 2.7297e-02,  ..., 2.7134e-03,\n",
       "            7.5975e-03, 9.6597e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 4.1244e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 3.2018e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 2.2250e-03]],\n",
       " \n",
       "          [[3.3584e-03, 1.0834e-03, 9.7503e-04,  ..., 3.4126e-03,\n",
       "            1.6792e-03, 3.7918e-04],\n",
       "           [2.3563e-02, 1.0400e-02, 9.9128e-03,  ..., 4.3822e-02,\n",
       "            1.5005e-02, 5.2543e-03],\n",
       "           [5.2760e-02, 4.9293e-02, 4.8372e-02,  ..., 3.9434e-02,\n",
       "            5.6931e-02, 8.3961e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 3.9001e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 3.7918e-03],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 2.2209e-03]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 8.3333e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 2.0325e-02,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.3333e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            9.0909e-02, 9.0909e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         ...,\n",
       " \n",
       " \n",
       "         [[[5.4060e-02, 6.9065e-02, 1.2950e-02,  ..., 8.4224e-02,\n",
       "            0.0000e+00, 2.4666e-02],\n",
       "           [3.2323e-02, 1.7318e-02, 7.3124e-02,  ..., 2.1583e-03,\n",
       "            4.5735e-03, 3.9877e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 3.0832e-04,  ..., 0.0000e+00,\n",
       "            4.9332e-03, 2.1840e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            1.8499e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            8.0164e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            1.8499e-03, 0.0000e+00]],\n",
       " \n",
       "          [[2.7802e-02, 2.7243e-02, 7.0140e-03,  ..., 4.6150e-02,\n",
       "            0.0000e+00, 2.2313e-02],\n",
       "           [5.2757e-02, 5.2554e-02, 6.9022e-02,  ..., 3.5172e-02,\n",
       "            9.0978e-03, 3.8323e-02],\n",
       "           [3.4562e-03, 4.8285e-03, 7.2681e-03,  ..., 3.1004e-03,\n",
       "            5.5909e-03, 2.3990e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.6760e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.6760e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.8793e-03, 0.0000e+00]],\n",
       " \n",
       "          [[1.5799e-03, 1.6308e-03, 5.0963e-05,  ..., 1.2741e-03,\n",
       "            0.0000e+00, 1.4525e-02],\n",
       "           [5.2186e-02, 4.8007e-02, 2.6501e-02,  ..., 4.8976e-02,\n",
       "            5.6060e-04, 3.7815e-02],\n",
       "           [2.8132e-02, 3.0731e-02, 5.0250e-02,  ..., 3.0986e-02,\n",
       "            8.6128e-03, 3.1750e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            5.3002e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            5.0454e-03, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            4.9944e-03, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 9.0909e-02,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 9.0909e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[7.1728e-02, 7.4086e-02, 3.7724e-03,  ..., 8.4303e-02,\n",
       "            4.4850e-02, 3.2851e-02],\n",
       "           [1.6347e-02, 1.3989e-02, 8.3360e-02,  ..., 3.7724e-03,\n",
       "            4.3225e-02, 5.5224e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 9.4310e-04,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[1.4222e-02, 1.1954e-02, 3.9161e-03,  ..., 2.0611e-02,\n",
       "            6.5956e-03, 1.8756e-02],\n",
       "           [7.0232e-02, 7.0490e-02, 6.9408e-02,  ..., 6.3894e-02,\n",
       "            7.7395e-02, 6.5749e-02],\n",
       "           [1.9581e-03, 3.9161e-03, 1.1903e-02,  ..., 1.8035e-03,\n",
       "            2.5249e-03, 1.7004e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[2.3719e-03, 2.1656e-03, 3.0937e-04,  ..., 2.1141e-03,\n",
       "            9.2812e-04, 3.1969e-03],\n",
       "           [3.4547e-02, 2.3976e-02, 8.4047e-03,  ..., 2.1759e-02,\n",
       "            2.0831e-02, 4.4962e-02],\n",
       "           [4.7076e-02, 5.3315e-02, 5.8884e-02,  ..., 5.7131e-02,\n",
       "            6.0689e-02, 3.6764e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 9.0909e-02,\n",
       "            6.4302e-02, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.5417e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]],\n",
       " \n",
       " \n",
       "         [[[4.6259e-02, 6.2299e-02, 1.3039e-02,  ..., 7.8909e-02,\n",
       "            3.1978e-02, 3.7256e-03],\n",
       "           [4.0722e-02, 2.4682e-02, 7.3942e-02,  ..., 8.0720e-03,\n",
       "            5.5004e-02, 8.3256e-02],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[1.7289e-02, 1.6877e-02, 5.6771e-03,  ..., 2.9882e-02,\n",
       "            1.1199e-02, 6.5545e-03],\n",
       "           [6.6268e-02, 6.6319e-02, 6.9571e-02,  ..., 5.1765e-02,\n",
       "            7.1480e-02, 7.4732e-02],\n",
       "           [2.4773e-03, 2.6321e-03, 1.0477e-02,  ..., 4.4901e-03,\n",
       "            3.0966e-03, 3.8192e-03],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[1.7528e-03, 1.5466e-03, 0.0000e+00,  ..., 2.2167e-03,\n",
       "            3.6086e-04, 7.2172e-04],\n",
       "           [2.9848e-02, 2.7426e-02, 1.5878e-02,  ..., 2.4075e-02,\n",
       "            2.3353e-02, 2.0363e-02],\n",
       "           [5.1449e-02, 5.2119e-02, 4.9902e-02,  ..., 5.1242e-02,\n",
       "            5.5109e-02, 5.0263e-02],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          ...,\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 9.0909e-02,\n",
       "            9.0909e-02, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]],\n",
       " \n",
       "          [[0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           ...,\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 8.3333e-02, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00],\n",
       "           [0.0000e+00, 0.0000e+00, 0.0000e+00,  ..., 0.0000e+00,\n",
       "            0.0000e+00, 0.0000e+00]]]]),\n",
       " tensor([3.6860, 5.6570, 3.0820, 2.7070, 2.6790, 4.3170, 2.9990, 4.1990, 3.5050,\n",
       "         5.0390, 3.1720, 2.3530, 2.9570, 3.2690, 3.1170, 2.7900, 4.8590, 2.5680,\n",
       "         0.9860, 3.4980, 2.6380, 4.4560, 4.1650, 4.0190, 3.5470, 2.4430, 4.3150,\n",
       "         2.2360, 3.4190, 3.4710, 4.0810, 0.4580])]"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "next(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Data for first batch using 'Method 1'\n",
    "# tensor([3.6860, 5.6570, 3.0820, 2.7070, 2.6790, 4.3170, 2.9990, 4.1990, 3.5050,\n",
    "#          5.0390, 3.1720, 2.3530, 2.9570, 3.2690, 3.1170, 2.7900, 4.8590, 2.5680,\n",
    "#          0.9860, 3.4980, 2.6380, 4.4560, 4.1650, 4.0190, 3.5470, 2.4430, 4.3150,\n",
    "#          2.2360, 3.4190, 3.4710, 4.0810, 0.4580], dtype=torch.float64)]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Generate training and validation sets in batches of size 32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [],
   "source": [
    "rng = np.random.default_rng(100)\n",
    "\n",
    "num_obs = len(field_arrays)\n",
    "trng_set_idx = rng.choice(num_obs, (np.ceil(num_obs * 2/3)).astype(np.int16), replace=False)\n",
    "valid_set_idx = list(set(range(num_obs)) - set(trng_set_idx))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2552"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "union_set = set(valid_set_idx) | set(trng_set_idx)\n",
    "len(union_set)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "1702\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "53.1875"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(len(trng_set_idx))\n",
    "1702/32"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0    3.686\n",
      "1    5.657\n",
      "2    3.082\n",
      "3    2.707\n",
      "4    2.679\n",
      "5    4.317\n",
      "Name: Yield, dtype: float64\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0    3.686\n",
       "2    3.082\n",
       "5    4.317\n",
       "Name: Yield, dtype: float64"
      ]
     },
     "execution_count": 23,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zz = trng_data_annot['Yield']\n",
    "print(zz[0:6])\n",
    "zz.iloc[[0, 2, 5]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Dummy cell for executing all steps below it"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "54"
      ]
     },
     "execution_count": 25,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Randomize the generation of training and validation set\n",
    "num_obs = len(field_arrays)\n",
    "trng_set_idx = np.random.choice(num_obs, (np.ceil(num_obs * 2/3)).astype(np.int16), replace=False)\n",
    "valid_set_idx = list(set(range(num_obs)) - set(trng_set_idx))\n",
    "\n",
    "zindi_dataset_trng = TensorDataset(torch.FloatTensor(field_arrays[trng_set_idx])\n",
    "                                   ,torch.FloatTensor(trng_data_annot['Yield'].values[trng_set_idx]))\n",
    "\n",
    "# Use shuffle = True to change the order of observations across epochs\n",
    "zindi_dataloader_trng = torch.utils.data.DataLoader(zindi_dataset_trng, batch_size=32, shuffle=True)\n",
    "len(zindi_dataloader_trng)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "27"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zindi_dataset_valid = TensorDataset(torch.FloatTensor(field_arrays[valid_set_idx])\n",
    "                                   ,torch.FloatTensor(trng_data_annot['Yield'].values[valid_set_idx]))\n",
    "\n",
    "zindi_dataloader_valid = torch.utils.data.DataLoader(zindi_dataset_valid, batch_size=32, shuffle=True)\n",
    "len(zindi_dataloader_valid)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Create a CNN for predicting the yield per acre"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "252"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Number of variables to be flattened\n",
    "14*6*3"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<torch._C.Generator at 0x194ac54a600>"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Set seed for initialization of model parameters\n",
    "torch.manual_seed(10)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ZindiCnn(torch.nn.Module):\n",
    "    def __init__(self, num_channels):\n",
    "        super().__init__()\n",
    "        self.layer_1 = torch.nn.Conv2d(in_channels = num_channels, out_channels = 14, kernel_size = (1, 3))\n",
    "        self.pool_1 = torch.nn.AvgPool2d((3, 1), stride=1)\n",
    "#         self.layer_1 = torch.nn.Conv2d(in_channels = num_channels, out_channels = 14, kernel_size = (3, 3))\n",
    "        self.layer_2 = torch.nn.Conv2d(in_channels = 14, out_channels = 7, kernel_size = 3)\n",
    "        self.layer_3 = torch.nn.Conv2d(in_channels = 7, out_channels = 3, kernel_size = 3)\n",
    "        self.layer_4 = torch.nn.Linear(252, 3)\n",
    "        self.layer_5 = torch.nn.Linear(3, 1)\n",
    "        \n",
    "    def forward(self, x):\n",
    "        # define forward pass\n",
    "        x = self.layer_1(x)\n",
    "        x = F.relu(self.pool_1(x))\n",
    "        x = self.layer_2(x)\n",
    "        x = self.layer_3(x)\n",
    "#         print(x.size())\n",
    "        x = x.view(-1, 252)\n",
    "        x = F.relu(self.layer_4(x))\n",
    "        x = self.layer_5(x)\n",
    "        return x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [],
   "source": [
    "# temp = iter(zindi_dataloader_trng)\n",
    "# single_batch = next(temp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [],
   "source": [
    "# single_batch[0].size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [],
   "source": [
    "# single_batch[1].size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "# zindi_model = ZindiCnn(27)\n",
    "# zindi_optimizer = torch.optim.Adam(zindi_model.parameters(), lr=0.01)\n",
    "# zindi_loss_function = torch.nn.MSELoss()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0\n",
      "MSE on validation set =  14.30005896532977\n",
      "100\n",
      "MSE on validation set =  2.4483317092612937\n"
     ]
    }
   ],
   "source": [
    "# Train the model & evaluate generalization error\n",
    "num_epochs = 101\n",
    "# zindi_model.train()\n",
    "\n",
    "zindi_model = ZindiCnn(27)\n",
    "zindi_optimizer = torch.optim.Adam(zindi_model.parameters(), lr=0.001)\n",
    "zindi_loss_function = torch.nn.MSELoss()\n",
    "\n",
    "for epoch_idx in range(num_epochs):\n",
    "    \n",
    "    if epoch_idx%100 == 0:\n",
    "        print(epoch_idx)\n",
    "        test_loss = 0\n",
    "        \n",
    "        # Use model in evaluation mode\n",
    "        zindi_model.eval()\n",
    "        with torch.no_grad():\n",
    "            for valid_batch in zindi_dataloader_valid:\n",
    "                current_fit = zindi_model(valid_batch[0])\n",
    "                test_loss += zindi_loss_function(current_fit, torch.unsqueeze(valid_batch[1], 1)).item()\n",
    "\n",
    "        print('MSE on validation set = ', test_loss/len(zindi_dataloader_valid))\n",
    "    \n",
    "    zindi_model.train()\n",
    "    for single_batch in zindi_dataloader_trng:\n",
    "        current_fit = zindi_model(single_batch[0])  # 1\n",
    "        current_loss = zindi_loss_function(current_fit, torch.unsqueeze(single_batch[1], 1))  # 2\n",
    "        zindi_optimizer.zero_grad()  # 3\n",
    "        current_loss.backward()  # 4\n",
    "        zindi_optimizer.step()  # 5"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "# print(current_fit.size())\n",
    "# torch.unsqueeze(single_batch[1], 1).size()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "tensor([4.6000, 4.5012, 1.4020, 1.1000, 3.1688, 5.8630])"
      ]
     },
     "execution_count": 36,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "single_batch[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MSE on validation set =  2.527046706941393\n"
     ]
    }
   ],
   "source": [
    "zindi_model.eval()\n",
    "test_loss = 0\n",
    "\n",
    "with torch.no_grad():\n",
    "    for valid_batch in zindi_dataloader_valid:\n",
    "        current_fit = zindi_model(valid_batch[0])\n",
    "        test_loss += zindi_loss_function(current_fit, torch.unsqueeze(valid_batch[1], 1)).item()\n",
    "\n",
    "print('MSE on validation set = ', test_loss/len(zindi_dataloader_valid))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Parameter containing:\n",
       "tensor([-0.0650], requires_grad=True)"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zindi_model.layer_5.bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [],
   "source": [
    "# To be executed for second or later runs of the MSE estimation code\n",
    "\n",
    "# print(np.all(zindi_model.layer_1.weight.detach().numpy() == layer_1_weight))\n",
    "# print(np.all(zindi_model.layer_1.bias.detach().numpy() == layer_1_bias))\n",
    "\n",
    "# print(np.all(zindi_model.layer_2.weight.detach().numpy() == layer_2_weight))\n",
    "# print(np.all(zindi_model.layer_2.bias.detach().numpy() == layer_2_bias))\n",
    "\n",
    "# print(np.all(zindi_model.layer_3.weight.detach().numpy() == layer_3_weight))\n",
    "# print(np.all(zindi_model.layer_3.bias.detach().numpy() == layer_3_bias))\n",
    "\n",
    "# print(np.all(zindi_model.layer_4.weight.detach().numpy() == layer_4_weight))\n",
    "# print(np.all(zindi_model.layer_4.bias.detach().numpy() == layer_4_bias))\n",
    "\n",
    "# print(np.all(zindi_model.layer_5.weight.detach().numpy() == layer_5_weight))\n",
    "# print(np.all(zindi_model.layer_5.bias.detach().numpy() == layer_5_bias))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Results after first iteration on Validation Set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.5896687412607047"
      ]
     },
     "execution_count": 40,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Test the model using validation set\n",
    "np.sqrt(test_loss/len(zindi_dataloader_valid))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Parameter containing:\n",
       "tensor([[0.1473, 0.3081, 0.3614]], requires_grad=True)"
      ]
     },
     "execution_count": 41,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zindi_model.layer_5.weight"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Parameter containing:\n",
       "tensor([-0.0650], requires_grad=True)"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "zindi_model.layer_5.bias"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(14, 27, 1, 3)"
      ]
     },
     "execution_count": 43,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "layer_1_weight = zindi_model.layer_1.weight.detach().numpy()\n",
    "layer_1_bias = zindi_model.layer_1.bias.detach().numpy()\n",
    "layer_1_weight.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [],
   "source": [
    "layer_2_weight = zindi_model.layer_2.weight.detach().numpy()\n",
    "layer_2_bias = zindi_model.layer_2.bias.detach().numpy()\n",
    "\n",
    "layer_3_weight = zindi_model.layer_3.weight.detach().numpy()\n",
    "layer_3_bias = zindi_model.layer_3.bias.detach().numpy()\n",
    "\n",
    "layer_4_weight = zindi_model.layer_4.weight.detach().numpy()\n",
    "layer_4_bias = zindi_model.layer_4.bias.detach().numpy()\n",
    "\n",
    "layer_5_weight = zindi_model.layer_5.weight.detach().numpy()\n",
    "layer_5_bias = zindi_model.layer_5.bias.detach().numpy()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Predict the output for the test set"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Field_ID</th>\n",
       "      <th>Yield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>E9UZCEA</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1WGGS1Q</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EG2KXE2</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HC3GQXF</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7AK6GFK</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Field_ID  Yield\n",
       "0  E9UZCEA      0\n",
       "1  1WGGS1Q      0\n",
       "2  EG2KXE2      0\n",
       "3  HC3GQXF      0\n",
       "4  7AK6GFK      0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read the SampleSubmission.csv file\n",
    "test_annot = pd.read_csv(in_dir.format('SampleSubmission.csv'))\n",
    "test_annot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "torch.Size([2, 27, 20, 12])"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "test_sample_1 = torch.FloatTensor(np.load(test_dir.format(test_annot['Field_ID'].values[0])))\n",
    "test_sample_2 = torch.FloatTensor(np.load(test_dir.format(test_annot['Field_ID'].values[1])))\n",
    "test_batch = torch.stack((test_sample_1, test_sample_2), dim=0)\n",
    "test_batch.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "zindi_model.eval()\n",
    "\n",
    "with torch.no_grad():\n",
    "    current_fit = zindi_model(test_batch)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[3.3882675170898438, 3.4651482105255127]"
      ]
     },
     "execution_count": 48,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "current_fit.numpy().flatten().tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Counter =  0\n",
      "Counter =  500\n",
      "Counter =  1000\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "(1055, 27, 20, 12)"
      ]
     },
     "execution_count": 49,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Read all test images\n",
    "# Load all preprocessed 3-d arrays channels x bins x time into 4-d arrays\n",
    "field_names = test_annot['Field_ID']\n",
    "num_fields = len(field_names)\n",
    "test_field_arrays = np.zeros((num_fields, 27, 20, 12))\n",
    "\n",
    "for current_idx in range(num_fields):\n",
    "    if current_idx%500 == 0:\n",
    "        print('Counter = ', current_idx)\n",
    "    temp_array = np.load(test_dir.format(field_names.values[current_idx]))\n",
    "    test_field_arrays[current_idx] = temp_array\n",
    "    \n",
    "test_field_arrays.shape    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {},
   "outputs": [],
   "source": [
    "num_test_samples = test_field_arrays.shape[0]\n",
    "predicted_yield = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[0,\n",
       " 32,\n",
       " 64,\n",
       " 96,\n",
       " 128,\n",
       " 160,\n",
       " 192,\n",
       " 224,\n",
       " 256,\n",
       " 288,\n",
       " 320,\n",
       " 352,\n",
       " 384,\n",
       " 416,\n",
       " 448,\n",
       " 480,\n",
       " 512,\n",
       " 544,\n",
       " 576,\n",
       " 608,\n",
       " 640,\n",
       " 672,\n",
       " 704,\n",
       " 736,\n",
       " 768,\n",
       " 800,\n",
       " 832,\n",
       " 864,\n",
       " 896,\n",
       " 928,\n",
       " 960,\n",
       " 992,\n",
       " 1024]"
      ]
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "start_idx = list(range(0, num_test_samples, 32))\n",
    "start_idx"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index range from  0  to  32\n",
      "Index range from  32  to  64\n",
      "Index range from  64  to  96\n",
      "Index range from  96  to  128\n",
      "Index range from  128  to  160\n",
      "Index range from  160  to  192\n",
      "Index range from  192  to  224\n",
      "Index range from  224  to  256\n",
      "Index range from  256  to  288\n",
      "Index range from  288  to  320\n",
      "Index range from  320  to  352\n",
      "Index range from  352  to  384\n",
      "Index range from  384  to  416\n",
      "Index range from  416  to  448\n",
      "Index range from  448  to  480\n",
      "Index range from  480  to  512\n",
      "Index range from  512  to  544\n",
      "Index range from  544  to  576\n",
      "Index range from  576  to  608\n",
      "Index range from  608  to  640\n",
      "Index range from  640  to  672\n",
      "Index range from  672  to  704\n",
      "Index range from  704  to  736\n",
      "Index range from  736  to  768\n",
      "Index range from  768  to  800\n",
      "Index range from  800  to  832\n",
      "Index range from  832  to  864\n",
      "Index range from  864  to  896\n",
      "Index range from  896  to  928\n",
      "Index range from  928  to  960\n",
      "Index range from  960  to  992\n",
      "Index range from  992  to  1024\n",
      "Index range from  1024  to  1055\n"
     ]
    }
   ],
   "source": [
    "zindi_model.eval()\n",
    "\n",
    "with torch.no_grad():\n",
    "    for temp_idx in start_idx:\n",
    "        # Obtain the start and end indices\n",
    "        first_idx = 0 + temp_idx\n",
    "        last_idx = min(num_test_samples, 32 + temp_idx)\n",
    "        print('Index range from ', first_idx, ' to ', last_idx)\n",
    "        \n",
    "        current_indexes = list(range(first_idx, last_idx))\n",
    "        current_fit = zindi_model(torch.FloatTensor(test_field_arrays[current_indexes]))\n",
    "        predicted_yield = predicted_yield + current_fit.numpy().flatten().tolist()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1055"
      ]
     },
     "execution_count": 53,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "len(predicted_yield)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.8711638450622559"
      ]
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(predicted_yield).min()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "6.084647178649902"
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.array(predicted_yield).max()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "array([1.87116385, 2.56673074, 2.99811721, 3.84472454, 6.08464718])"
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.percentile(np.array(predicted_yield), [0, 25, 50, 75, 100])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Field_ID</th>\n",
       "      <th>Yield</th>\n",
       "      <th>Inferred_Yield</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>E9UZCEA</td>\n",
       "      <td>0</td>\n",
       "      <td>3.388268</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1WGGS1Q</td>\n",
       "      <td>0</td>\n",
       "      <td>3.465148</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>EG2KXE2</td>\n",
       "      <td>0</td>\n",
       "      <td>3.644513</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>HC3GQXF</td>\n",
       "      <td>0</td>\n",
       "      <td>3.547567</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>7AK6GFK</td>\n",
       "      <td>0</td>\n",
       "      <td>3.359572</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  Field_ID  Yield  Inferred_Yield\n",
       "0  E9UZCEA      0        3.388268\n",
       "1  1WGGS1Q      0        3.465148\n",
       "2  EG2KXE2      0        3.644513\n",
       "3  HC3GQXF      0        3.547567\n",
       "4  7AK6GFK      0        3.359572"
      ]
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Save the actuals yields in a new file\n",
    "test_annot['Inferred_Yield'] = predicted_yield\n",
    "test_annot.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "test_annot.to_csv('VJ_Submission.csv', columns = ['Field_ID', 'Inferred_Yield'], header = ['Field_ID', 'Yield']\n",
    "                 , index = False, )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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