diff options
Diffstat (limited to 'src/notebooks/00-testing-stuff-out.ipynb')
| -rw-r--r-- | src/notebooks/00-testing-stuff-out.ipynb | 118 |
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" } |