update core

nbs/00_core.ipynb

@@ -450,6 +450,57 @@
     "                print('Inferred learning rate: ', lr)\n"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class visionTrainer(Learner):\n",
+    "    \"\"\"\n",
+    "    A custom implementation of the FastAI Learner class for training models in bioinformatics applications.\n",
+    "\n",
+    "    \"\"\"\n",
+    "    \n",
+    "    def __init__(self, \n",
+    "                 dataloaders: DataLoaders, # The DataLoader objects containing training and validation datasets.\n",
+    "                 model: callable, # A callable model that will be trained on the dataset.\n",
+    "                 loss_fn: Any | None = None, # The loss function to optimize during training. If None, defaults to a suitable default.\n",
+    "                 optimizer: Optimizer | OptimWrapper = Adam, # The optimizer function to use. Defaults to Adam if not specified.\n",
+    "                 lr: float | slice = 1e-3, # Learning rate for the optimizer. Can be a float or a slice object for learning rate scheduling.\n",
+    "                 splitter: callable = trainable_params, # \n",
+    "                 callbacks: Callback | MutableSequence | None = None, # A callable that determines which parameters of the model should be updated during training.\n",
+    "                 metrics: Any | MutableSequence | None = None, # Optional list of callback functions to customize training behavior.\n",
+    "                 csv_log: bool = False, # Metrics to evaluate the performance of the model during training.\n",
+    "                 show_graph: bool = True, # Whether to log training history to a CSV file. If True, logs will be appended to 'history.csv'.\n",
+    "                 show_summary: bool = False, # The base directory where models are saved or loaded from. Defaults to None.\n",
+    "                 find_lr: bool = False, # Subdirectory within the base path where trained models are stored. Default is 'models'.\n",
+    "                 find_lr_fn = valley, # Weight decay factor for optimization. Defaults to None.\n",
+    "                 path: str | Path | None = None, # Whether to apply weight decay to batch normalization and bias parameters.\n",
+    "                 model_dir: str | Path = 'models', # Whether to update the batch normalization statistics during training.\n",
+    "                 wd: float | int | None = None, \n",
+    "                 wd_bn_bias: bool = False, \n",
+    "                 train_bn: bool = True, \n",
+    "                 moms: tuple = ..., # Tuple of tuples representing the momentum values for different layers in the model. Defaults to FastAI's default settings if not specified.\n",
+    "                 default_cbs: bool = True, # Automatically include default callbacks such as ShowGraphCallback and CSVLogger.\n",
+    "                 ):\n",
+    "        cbs = callbacks if callbacks is not None else []  # Ensure cbs is a list\n",
+    "        if default_cbs:\n",
+    "            if show_graph:\n",
+    "                cbs.append(ShowGraphCallback())\n",
+    "            if csv_log:\n",
+    "                cbs.append(CSVLogger(fname='history.csv', append=False))\n",
+    "        \n",
+    "        super().__init__(dataloaders, model, loss_fn, optimizer, lr, splitter, cbs, metrics, path, model_dir, wd, wd_bn_bias, train_bn, moms)\n",
+    "        \n",
+    "        if show_summary:\n",
+    "                print(self.summary())\n",
+    "        if find_lr:\n",
+    "                self.lr_find(suggest_funcs=find_lr_fn)\n",
+    "                lr = float('%.1g'%(lr))\n",
+    "                print('Inferred learning rate: ', lr)"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},

nbs/07_callbacks.ipynb

@@ -85,7 +85,7 @@
     }
    ],
    "source": [
-    "show_doc(ShortEpochCallback)\n"
+    "show_doc(ShortEpochCallback)"
    ]
   },
   {
@@ -124,7 +124,6 @@
     }
    ],
    "source": [
-    "\n",
     "show_doc(GradientAccumulation)"
    ]
   },
@@ -535,9 +534,13 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "python3",
+   "display_name": "bioMONAI-env",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,

nbs/901_demo_RI2FL_2d.ipynb

@@ -281,9 +281,13 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "python3",
+   "display_name": "bioMONAI-env",
    "language": "python",
    "name": "python3"
+  },
+  "language_info": {
+   "name": "python",
+   "version": "3.11.5"
   }
  },
  "nbformat": 4,