Update notebook

1 files changed, 111 insertions, 70 deletions

diff --git a/notebooks/04-convnext.ipynb b/notebooks/04-convnext.ipynb
index 6d70884..1779d13 100644
--- a/notebooks/04-convnext.ipynb
+++ b/notebooks/04-convnext.ipynb
@@ -2,19 +2,10 @@
  "cells": [
   {
    "cell_type": "code",
-   "execution_count": 61,
+   "execution_count": 1,
    "id": "7c02ae76-b540-4b16-9492-e9210b3b9249",
    "metadata": {},
-   "outputs": [
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "The autoreload extension is already loaded. To reload it, use:\n",
-      "  %reload_ext autoreload\n"
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "import os\n",
     "os.environ['CUDA_VISIBLE_DEVICE'] = ''\n",
@@ -37,7 +28,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 62,
+   "execution_count": 2,
    "id": "ccdb6dde-47e5-429a-88f2-0764fb7e259a",
    "metadata": {},
    "outputs": [],
@@ -49,7 +40,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 63,
+   "execution_count": 3,
    "id": "3cf50475-39f2-4642-a7d1-5bcbc0a036f7",
    "metadata": {},
    "outputs": [],
@@ -59,7 +50,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 64,
+   "execution_count": 4,
    "id": "e52ecb01-c975-4e55-925d-1182c7aea473",
    "metadata": {},
    "outputs": [],
@@ -70,17 +61,17 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 65,
+   "execution_count": 5,
    "id": "f939aa37-7b1d-45cc-885c-323c4540bda1",
    "metadata": {},
    "outputs": [
     {
      "data": {
       "text/plain": [
-       "{'_target_': 'text_recognizer.networks.convnext.ConvNext', 'dim': 16, 'dim_mults': [2, 4, 8], 'depths': [3, 3, 6], 'downsampling_factors': [[2, 2], [2, 2], [2, 2]]}"
+       "{'_target_': 'text_recognizer.networks.convnext.ConvNext', 'dim': 16, 'dim_mults': [2, 4, 8], 'depths': [3, 3, 6], 'downsampling_factors': [[2, 2], [2, 2], [2, 2]], 'attn': {'_target_': 'text_recognizer.networks.convnext.TransformerBlock', 'attn': {'_target_': 'text_recognizer.networks.convnext.Attention', 'dim': 128, 'heads': 4, 'dim_head': 64, 'scale': 8}, 'ff': {'_target_': 'text_recognizer.networks.convnext.FeedForward', 'dim': 128, 'mult': 4}}}"
       ]
      },
-     "execution_count": 65,
+     "execution_count": 5,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -91,8 +82,20 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 66,
-   "id": "aaeab329-aeb0-4a1b-aa35-5a2aab81b1d0",
+   "execution_count": 10,
+   "id": "a2b420c1",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "cfg.dim_mults = [2, 4, 8, 8, 8]\n",
+    "cfg.depths = [3, 3, 3, 3, 6]\n",
+    "cfg.downsampling_factors = [[2, 2], [2, 2], [2, 2], [2, 1], [2, 1]]"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "c9589350",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -101,7 +104,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 67,
+   "execution_count": 12,
    "id": "618b997c-e6a6-4487-b70c-9d260cb556d3",
    "metadata": {},
    "outputs": [],
@@ -111,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 68,
+   "execution_count": 13,
    "id": "25759b7b-8deb-4163-b75d-a1357c9fe88f",
    "metadata": {
     "scrolled": false
@@ -123,67 +126,105 @@
        "====================================================================================================\n",
        "Layer (type:depth-idx)                             Output Shape              Param #\n",
        "====================================================================================================\n",
-       "ConvNext                                           [2, 128, 7, 128]          --\n",
-       "├─Conv2d: 1-1                                      [2, 16, 56, 1024]         800\n",
-       "├─ModuleList: 1-2                                  --                        --\n",
-       "│    └─ModuleList: 2-1                             --                        --\n",
-       "│    │    └─ConvNextBlock: 3-1                     [2, 16, 56, 1024]         --\n",
-       "│    │    │    └─Conv2d: 4-1                       [2, 16, 56, 1024]         800\n",
-       "│    │    │    └─Sequential: 4-2                   [2, 16, 56, 1024]         9,280\n",
-       "│    │    │    └─Identity: 4-3                     [2, 16, 56, 1024]         --\n",
-       "│    │    └─ModuleList: 3-2                        --                        --\n",
-       "│    │    │    └─ConvNextBlock: 4-4                [2, 16, 56, 1024]         10,080\n",
-       "│    │    │    └─ConvNextBlock: 4-5                [2, 16, 56, 1024]         10,080\n",
-       "│    │    │    └─ConvNextBlock: 4-6                [2, 16, 56, 1024]         10,080\n",
-       "│    │    └─Downsample: 3-3                        [2, 32, 28, 512]          --\n",
-       "│    │    │    └─Sequential: 4-7                   [2, 32, 28, 512]          2,080\n",
-       "│    └─ModuleList: 2-2                             --                        --\n",
-       "│    │    └─ConvNextBlock: 3-4                     [2, 32, 28, 512]          --\n",
-       "│    │    │    └─Conv2d: 4-8                       [2, 32, 28, 512]          1,600\n",
-       "│    │    │    └─Sequential: 4-9                   [2, 32, 28, 512]          36,992\n",
-       "│    │    │    └─Identity: 4-10                    [2, 32, 28, 512]          --\n",
-       "│    │    └─ModuleList: 3-5                        --                        --\n",
-       "│    │    │    └─ConvNextBlock: 4-11               [2, 32, 28, 512]          38,592\n",
-       "│    │    │    └─ConvNextBlock: 4-12               [2, 32, 28, 512]          38,592\n",
-       "│    │    │    └─ConvNextBlock: 4-13               [2, 32, 28, 512]          38,592\n",
-       "│    │    └─Downsample: 3-6                        [2, 64, 14, 256]          --\n",
-       "│    │    │    └─Sequential: 4-14                  [2, 64, 14, 256]          8,256\n",
-       "│    └─ModuleList: 2-3                             --                        --\n",
-       "│    │    └─ConvNextBlock: 3-7                     [2, 64, 14, 256]          --\n",
-       "│    │    │    └─Conv2d: 4-15                      [2, 64, 14, 256]          3,200\n",
-       "│    │    │    └─Sequential: 4-16                  [2, 64, 14, 256]          147,712\n",
-       "│    │    │    └─Identity: 4-17                    [2, 64, 14, 256]          --\n",
-       "│    │    └─ModuleList: 3-8                        --                        --\n",
-       "│    │    │    └─ConvNextBlock: 4-18               [2, 64, 14, 256]          150,912\n",
-       "│    │    │    └─ConvNextBlock: 4-19               [2, 64, 14, 256]          150,912\n",
-       "│    │    │    └─ConvNextBlock: 4-20               [2, 64, 14, 256]          150,912\n",
-       "│    │    │    └─ConvNextBlock: 4-21               [2, 64, 14, 256]          150,912\n",
-       "│    │    │    └─ConvNextBlock: 4-22               [2, 64, 14, 256]          150,912\n",
-       "│    │    │    └─ConvNextBlock: 4-23               [2, 64, 14, 256]          150,912\n",
-       "│    │    └─Downsample: 3-9                        [2, 128, 7, 128]          --\n",
-       "│    │    │    └─Sequential: 4-24                  [2, 128, 7, 128]          32,896\n",
-       "├─LayerNorm: 1-3                                   [2, 128, 7, 128]          128\n",
+       "ConvNext                                           [2, 128, 18, 80]          5,969,376\n",
+       "├─Conv2d: 1-1                                      [2, 16, 576, 640]         800\n",
+       "├─ModuleList: 1                                    --                        --\n",
+       "│    └─ModuleList: 2                               --                        --\n",
+       "│    │    └─ConvNextBlock: 3-1                     [2, 16, 576, 640]         --\n",
+       "│    │    │    └─Conv2d: 4-1                       [2, 16, 576, 640]         800\n",
+       "│    │    │    └─Sequential: 4-2                   [2, 16, 576, 640]         9,280\n",
+       "│    │    │    └─Identity: 4-3                     [2, 16, 576, 640]         --\n",
+       "│    │    └─ModuleList: 3                          --                        --\n",
+       "│    │    │    └─ConvNextBlock: 4-4                [2, 16, 576, 640]         10,080\n",
+       "│    │    │    └─ConvNextBlock: 4-5                [2, 16, 576, 640]         10,080\n",
+       "│    │    │    └─ConvNextBlock: 4-6                [2, 16, 576, 640]         10,080\n",
+       "│    │    └─Downsample: 3-2                        [2, 32, 288, 320]         --\n",
+       "│    │    │    └─Sequential: 4-7                   [2, 32, 288, 320]         2,080\n",
+       "│    └─ModuleList: 2                               --                        --\n",
+       "│    │    └─ConvNextBlock: 3-3                     [2, 32, 288, 320]         --\n",
+       "│    │    │    └─Conv2d: 4-8                       [2, 32, 288, 320]         1,600\n",
+       "│    │    │    └─Sequential: 4-9                   [2, 32, 288, 320]         36,992\n",
+       "│    │    │    └─Identity: 4-10                    [2, 32, 288, 320]         --\n",
+       "│    │    └─ModuleList: 3                          --                        --\n",
+       "│    │    │    └─ConvNextBlock: 4-11               [2, 32, 288, 320]         38,592\n",
+       "│    │    │    └─ConvNextBlock: 4-12               [2, 32, 288, 320]         38,592\n",
+       "│    │    │    └─ConvNextBlock: 4-13               [2, 32, 288, 320]         38,592\n",
+       "│    │    └─Downsample: 3-4                        [2, 64, 144, 160]         --\n",
+       "│    │    │    └─Sequential: 4-14                  [2, 64, 144, 160]         8,256\n",
+       "│    └─ModuleList: 2                               --                        --\n",
+       "│    │    └─ConvNextBlock: 3-5                     [2, 64, 144, 160]         --\n",
+       "│    │    │    └─Conv2d: 4-15                      [2, 64, 144, 160]         3,200\n",
+       "│    │    │    └─Sequential: 4-16                  [2, 64, 144, 160]         147,712\n",
+       "│    │    │    └─Identity: 4-17                    [2, 64, 144, 160]         --\n",
+       "│    │    └─ModuleList: 3                          --                        --\n",
+       "│    │    │    └─ConvNextBlock: 4-18               [2, 64, 144, 160]         150,912\n",
+       "│    │    │    └─ConvNextBlock: 4-19               [2, 64, 144, 160]         150,912\n",
+       "│    │    │    └─ConvNextBlock: 4-20               [2, 64, 144, 160]         150,912\n",
+       "│    │    └─Downsample: 3-6                        [2, 128, 72, 80]          --\n",
+       "│    │    │    └─Sequential: 4-21                  [2, 128, 72, 80]          32,896\n",
+       "│    └─ModuleList: 2                               --                        --\n",
+       "│    │    └─ConvNextBlock: 3-7                     [2, 128, 72, 80]          --\n",
+       "│    │    │    └─Conv2d: 4-22                      [2, 128, 72, 80]          6,400\n",
+       "│    │    │    └─Sequential: 4-23                  [2, 128, 72, 80]          590,336\n",
+       "│    │    │    └─Identity: 4-24                    [2, 128, 72, 80]          --\n",
+       "│    │    └─ModuleList: 3                          --                        --\n",
+       "│    │    │    └─ConvNextBlock: 4-25               [2, 128, 72, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-26               [2, 128, 72, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-27               [2, 128, 72, 80]          596,736\n",
+       "│    │    └─Downsample: 3-8                        [2, 128, 36, 80]          --\n",
+       "│    │    │    └─Sequential: 4-28                  [2, 128, 36, 80]          32,896\n",
+       "│    └─ModuleList: 2                               --                        --\n",
+       "│    │    └─ConvNextBlock: 3-9                     [2, 128, 36, 80]          --\n",
+       "│    │    │    └─Conv2d: 4-29                      [2, 128, 36, 80]          6,400\n",
+       "│    │    │    └─Sequential: 4-30                  [2, 128, 36, 80]          590,336\n",
+       "│    │    │    └─Identity: 4-31                    [2, 128, 36, 80]          --\n",
+       "│    │    └─ModuleList: 3                          --                        --\n",
+       "│    │    │    └─ConvNextBlock: 4-32               [2, 128, 36, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-33               [2, 128, 36, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-34               [2, 128, 36, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-35               [2, 128, 36, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-36               [2, 128, 36, 80]          596,736\n",
+       "│    │    │    └─ConvNextBlock: 4-37               [2, 128, 36, 80]          596,736\n",
+       "│    │    └─Downsample: 3-10                       [2, 128, 18, 80]          --\n",
+       "│    │    │    └─Sequential: 4-38                  [2, 128, 18, 80]          32,896\n",
+       "├─TransformerBlock: 1-2                            [2, 128, 18, 80]          --\n",
+       "│    └─Attention: 2-1                              [2, 128, 18, 80]          --\n",
+       "│    │    └─LayerNorm: 3-11                        [2, 128, 18, 80]          128\n",
+       "│    │    └─Conv2d: 3-12                           [2, 768, 18, 80]          98,304\n",
+       "│    │    └─Conv2d: 3-13                           [2, 128, 18, 80]          32,768\n",
+       "│    └─FeedForward: 2-2                            [2, 128, 18, 80]          --\n",
+       "│    │    └─Residual: 3-14                         [2, 128, 18, 80]          --\n",
+       "│    │    │    └─Sequential: 4-39                  [2, 128, 18, 80]          131,712\n",
+       "├─LayerNorm: 1-3                                   [2, 128, 18, 80]          128\n",
        "====================================================================================================\n",
-       "Total params: 1,295,232\n",
-       "Trainable params: 1,295,232\n",
+       "Total params: 7,735,296\n",
+       "Trainable params: 7,735,296\n",
        "Non-trainable params: 0\n",
-       "Total mult-adds (G): 16.88\n",
+       "Total mult-adds (G): 140.23\n",
        "====================================================================================================\n",
-       "Input size (MB): 0.46\n",
-       "Forward/backward pass size (MB): 598.21\n",
-       "Params size (MB): 5.18\n",
-       "Estimated Total Size (MB): 603.85\n",
+       "Input size (MB): 2.95\n",
+       "Forward/backward pass size (MB): 3987.21\n",
+       "Params size (MB): 30.94\n",
+       "Estimated Total Size (MB): 4021.10\n",
        "===================================================================================================="
       ]
      },
-     "execution_count": 68,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
-    "summary(net, (2, 1, 56, 1024), device=\"cpu\", depth=4)"
+    "summary(net, (2, 1, 576, 640), device=\"cpu\", depth=4)"
    ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "7a7e27f4",
+   "metadata": {},
+   "outputs": [],
+   "source": []
   }
  ],
  "metadata": {