Spell Check 🥲

AidinHamedi · Oct 10, 2024 · f3ba6fe · f3ba6fe
1 parent 714c122
commit f3ba6fe
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Showing 2 changed files with 33 additions and 10 deletions.
diff --git a/.vscode/settings.json b/.vscode/settings.json
@@ -1,3 +1,24 @@
 {
-    "sarif-viewer.connectToGithubCodeScanning": "off"
+    "sarif-viewer.connectToGithubCodeScanning": "off",
+    "cSpell.words": [
+        "amsbound",
+        "annot",
+        "cmap",
+        "Efficientnet",
+        "ISCAM",
+        "nesterov",
+        "nrow",
+        "Onecycle",
+        "optim",
+        "SSCAM",
+        "subkey",
+        "subvalue",
+        "tablefmt",
+        "unscale",
+        "vutils",
+        "xlabel",
+        "xticklabels",
+        "ylabel",
+        "yticklabels"
+    ],
 }
diff --git a/Main.ipynb b/Main.ipynb
@@ -33,6 +33,7 @@
     }
    ],
    "source": [
+    "# /* spell-checker: disable */\n",
     "# Error Suppressing >>>\n",
     "import warnings\n",
     "\n",
@@ -80,6 +81,7 @@
     "    LayerCAM,\n",
     ")\n",
     "\n",
+    "\n",
     "# Utils >>>\n",
     "from Utils.Record_Var import Record_var\n",
     "from Utils.print_color import print_colored as cprint\n",
@@ -250,8 +252,8 @@
     "    img_size=img_res,\n",
     "    color_mode=img_format,\n",
     ")\n",
-    "# Peprocessing data >>>\n",
-    "cprint(\"<Fore.YELLOW>Peprocessing the data...\")\n",
+    "# Preprocessing data >>>\n",
+    "cprint(\"<Fore.YELLOW>Preprocessing the data...\")\n",
     "# One hot encode the labels\n",
     "cprint(\n",
     "    f\" │ <Fore.CYAN>One hot encoding the labels... <Fore.GREEN>[num_classes: {num_classes}]\"\n",
@@ -5833,11 +5835,11 @@
     "dynamic_agmentation_scaling = True  # if True, the magnitude will be scaled with the epoch\n",
     "dynamic_agmentation_scaling_fn = lambda epoch: min(epoch / (98 / 1), 8)  # output: magnitude (1-30) | input: epoch\n",
     "early_stop_patience = 86  # After n epochs without improvement, stop training and load the best model\n",
-    "train_eval_portion = 0.14  # The proportion of the training data that it used to messure the model's performance on train data\n",
-    "gradient_clipping = True  # If True, the gradient will be clipped to a maximum value/norm (Pervent exploding gradients)\n",
+    "train_eval_portion = 0.14  # The proportion of the training data that it used to measure the model's performance on train data\n",
+    "gradient_clipping = True  # If True, the gradient will be clipped to a maximum value/norm (Prevent exploding gradients)\n",
     "gradient_clipping_max = 1.2  # The maximum of the gradient\n",
     "gradient_clipping_method = \"Norm\"  # \"Norm\" or \"Value\"\n",
-    "agmentation_method = \"runtime\"  # \"runtime\" (Stable-LowRamUsage) Recomended or \"Pre_epoch\" (Unstable-HighRamUsage) Deparicated!\n",
+    "agmentation_method = \"runtime\"  # \"runtime\" (Stable-LowRamUsage) Recommended or \"Pre_epoch\" (Unstable-HighRamUsage) Deprecated!\n",
     "gradient_accumulation = False # If True, the gradient will be accumulated over multiple batches before being applied to the model. (To save memory if you need to use a large batch size)\n",
     "gradient_accumulation_steps = 2  # The number of batches to accumulate the gradient over\n",
     "exponential_moving_average = True  # If True, the model will be averaged over the last n epochs\n",
@@ -5935,7 +5937,7 @@
     "# Prep\n",
     "torch.cuda.empty_cache()\n",
     "gc.collect()\n",
-    "cprint(\"<Fore.YELLOW>Starting the traning engine...\")\n",
+    "cprint(\"<Fore.YELLOW>Starting the training engine...\")\n",
     "History = {\"Train\": [], \"Val\": []}\n",
     "Cache_dict = {}\n",
     "if not Is_tensor:\n",
@@ -6006,7 +6008,7 @@
     "cprint(\" │ <Fore.CYAN>Adding tensorboard model graph...\")\n",
     "TB_Data_writer.add_graph(model, torch.rand(1, x_test.shape[1], *img_res).to(device))\n",
     "train_reporter.Add_Prams(Train_Confs)\n",
-    "# Traing start msg\n",
+    "# Training start msg\n",
     "cprint(\"<Fore.YELLOW>Starting the training...\")\n",
     "# Main training loop\n",
     "try:\n",
@@ -6114,7 +6116,7 @@
     "        model.train()\n",
     "        # Moving loss to `device`\n",
     "        loss_fn = loss_fn.to(device)\n",
-    "        # Tarin Verbose Prep\n",
+    "        # Train Verbose Prep\n",
     "        cprint(\n",
     "            f\" │ <Fore.CYAN>Train Eval History len: <Fore.GREEN>{TrainEval_Data_len}/{Train_total_batches}\"\n",
     "        )\n",
@@ -6200,7 +6202,7 @@
     "                progress_bar.update()\n",
     "        # Close progress bar\n",
     "        progress_bar.close()\n",
-    "        # Lerning rate scheduler step + moving the loss to cpu + Weight Averaging bn update\n",
+    "        # Learning rate scheduler step + moving the loss to cpu + Weight Averaging bn update\n",
     "        loss_fn = loss_fn.cpu()\n",
     "        if lr_scheduler_update_method == \"Epoch\":\n",
     "            lr_scheduler.step()\n",