1 files changed, 43 insertions, 22 deletions

diff --git a/src/notebooks/02c-image-patches.ipynb b/src/notebooks/02c-image-patches.ipynb
index ee9a800..fedea91 100644
--- a/src/notebooks/02c-image-patches.ipynb
+++ b/src/notebooks/02c-image-patches.ipynb
@@ -48,8 +48,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2021-01-04 19:10:11.431 | DEBUG    | text_recognizer.datasets.emnist_lines_dataset:_generate_data:159 - Generating data...\n",
-      "2021-01-04 19:10:17.812 | DEBUG    | text_recognizer.datasets.emnist_lines_dataset:_load_data:152 - EmnistLinesDataset loading data from HDF5...\n"
+      "2021-01-10 17:44:25.666 | DEBUG    | text_recognizer.datasets.emnist_lines_dataset:_load_data:153 - EmnistLinesDataset loading data from HDF5...\n"
      ]
     }
    ],
@@ -210,7 +209,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 31,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -219,17 +218,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 23,
    "metadata": {},
    "outputs": [],
    "source": [
     "from einops.layers.torch import Rearrange\n",
-    "slide = nn.Sequential(nn.Unfold(kernel_size=(28, 64), stride=(1, 54)), Rearrange(\"b (c h w) t -> b t c h w\", h=28, w=64, c=1))"
+    "slide = nn.Sequential(nn.Unfold(kernel_size=(28, 46), stride=(1, 46)), Rearrange(\"b (c h w) t -> b t c h w\", h=28, w=46, c=1))"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 24,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -238,7 +237,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 32,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -247,17 +246,27 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 23,
+   "execution_count": 33,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "torch.Size([1, 1, 28, 952])"
+      ]
+     },
+     "execution_count": 33,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
-    "p=28\n",
-    "x = rearrange(data, 'b c (h p1) (w p2) -> b (h w) (p1 p2 c)', p1 = p, p2 = p)"
+    "data.shape"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 34,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -266,7 +275,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 25,
+   "execution_count": 35,
    "metadata": {},
    "outputs": [
     {
@@ -275,7 +284,7 @@
        "torch.Size([1, 34, 784])"
       ]
      },
-     "execution_count": 25,
+     "execution_count": 35,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -286,7 +295,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 31,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -296,7 +305,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 14,
+   "execution_count": 36,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -305,16 +314,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 15,
+   "execution_count": 37,
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "torch.Size([17, 1, 28, 64])"
+       "torch.Size([20, 1, 28, 46])"
       ]
      },
-     "execution_count": 15,
+     "execution_count": 37,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -325,14 +334,14 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 17,
+   "execution_count": 38,
    "metadata": {
     "scrolled": false
    },
    "outputs": [
     {
      "data": {
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       "text/plain": [
        "<Figure size 1440x1440 with 5 Axes>"
       ]
@@ -361,7 +370,19 @@
    "cell_type": "code",
    "execution_count": 18,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "ename": "ImportError",
+     "evalue": "cannot import name 'fetch_data_loaders' from 'text_recognizer.datasets.util' (/home/akternurra/Documents/projects/quest-for-general-artifical-intelligence/projects/text-recognizer/src/text_recognizer/datasets/util.py)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
+      "\u001b[0;31mImportError\u001b[0m                               Traceback (most recent call last)",
+      "\u001b[0;32m<ipython-input-18-5d40384147e9>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0;32mfrom\u001b[0m \u001b[0mtext_recognizer\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdatasets\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mutil\u001b[0m \u001b[0;32mimport\u001b[0m \u001b[0mfetch_data_loaders\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
+      "\u001b[0;31mImportError\u001b[0m: cannot import name 'fetch_data_loaders' from 'text_recognizer.datasets.util' (/home/akternurra/Documents/projects/quest-for-general-artifical-intelligence/projects/text-recognizer/src/text_recognizer/datasets/util.py)"
+     ]
+    }
+   ],
    "source": [
     "from text_recognizer.datasets.util import fetch_data_loaders"
    ]