Minor bug fixes etc.

1 files changed, 103 insertions, 15 deletions

diff --git a/src/notebooks/00-testing-stuff-out.ipynb b/src/notebooks/00-testing-stuff-out.ipynb
index 9d265ba..0294394 100644
--- a/src/notebooks/00-testing-stuff-out.ipynb
+++ b/src/notebooks/00-testing-stuff-out.ipynb
@@ -22,36 +22,94 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 4,
    "metadata": {},
    "outputs": [],
    "source": [
-    "from text_recognizer.networks.residual_network import IdentityBlock, ResidualBlock, BasicBlock, BottleNeckBlock, ResidualLayer, Encoder, ResidualNetwork"
+    "from text_recognizer.networks.residual_network import IdentityBlock, ResidualBlock, BasicBlock, BottleNeckBlock, ResidualLayer, ResidualNetwork"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "IdentityBlock(\n",
+       "  (blocks): Identity()\n",
+       "  (activation_fn): ReLU(inplace=True)\n",
+       "  (shortcut): Identity()\n",
+       ")"
+      ]
+     },
+     "execution_count": 5,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "IdentityBlock(32, 64)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 6,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "ResidualBlock(\n",
+       "  (blocks): Identity()\n",
+       "  (activation_fn): ReLU(inplace=True)\n",
+       "  (shortcut): Sequential(\n",
+       "    (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+       "    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+       "  )\n",
+       ")"
+      ]
+     },
+     "execution_count": 6,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
    "source": [
     "ResidualBlock(32, 64)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 7,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "BasicBlock(\n",
+      "  (blocks): Sequential(\n",
+      "    (0): Sequential(\n",
+      "      (0): Conv2dAuto(32, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
+      "      (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "    )\n",
+      "    (1): ReLU(inplace=True)\n",
+      "    (2): Sequential(\n",
+      "      (0): Conv2dAuto(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
+      "      (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "    )\n",
+      "  )\n",
+      "  (activation_fn): ReLU(inplace=True)\n",
+      "  (shortcut): Sequential(\n",
+      "    (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+      "    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "  )\n",
+      ")\n"
+     ]
+    }
+   ],
    "source": [
     "dummy = torch.ones((1, 32, 224, 224))\n",
     "\n",
@@ -62,9 +120,39 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 8,
    "metadata": {},
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "BottleNeckBlock(\n",
+      "  (blocks): Sequential(\n",
+      "    (0): Sequential(\n",
+      "      (0): Conv2dAuto(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+      "      (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "    )\n",
+      "    (1): ReLU(inplace=True)\n",
+      "    (2): Sequential(\n",
+      "      (0): Conv2dAuto(64, 64, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)\n",
+      "      (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "    )\n",
+      "    (3): ReLU(inplace=True)\n",
+      "    (4): Sequential(\n",
+      "      (0): Conv2dAuto(64, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+      "      (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "    )\n",
+      "  )\n",
+      "  (activation_fn): ReLU(inplace=True)\n",
+      "  (shortcut): Sequential(\n",
+      "    (0): Conv2d(32, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)\n",
+      "    (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)\n",
+      "  )\n",
+      ")\n"
+     ]
+    }
+   ],
    "source": [
     "dummy = torch.ones((1, 32, 10, 10))\n",
     "\n",
@@ -191,7 +279,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -200,7 +288,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -218,7 +306,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -227,7 +315,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 14,
    "metadata": {},
    "outputs": [
     {
@@ -505,7 +593,7 @@
        "==============================================================================================="
       ]
      },
-     "execution_count": 8,
+     "execution_count": 14,
      "metadata": {},
      "output_type": "execute_result"
     }