Syncing various fixes

.vscode/settings.json

@@ -1,6 +1,5 @@
 {   "editor.autoIndent": true,
     "python.linting.pylintEnabled": false,
-    "python.linting.flake8Enabled": true,
     "python.linting.enabled": true,
     "python.linting.banditEnabled": false,
     "python.linting.mypyEnabled": false,
@@ -19,4 +18,13 @@
         "MD034": false
     },
     "restructuredtext.confPath": "${workspaceFolder}/docs",
+    "spellright.language": [
+        "en"
+    ],
+    "spellright.documentTypes": [
+        "markdown",
+        "latex",
+        "plaintext"
+    ],
+    "python.linting.flake8Enabled": true,
 }

CHANGES.md

@@ -6,13 +6,15 @@
 
 ## Additions
 
+- `__del__` method to `FowardHook` class
+
 ## Removals
 
 ## Fixes
 
 - Potential bug in convolutional models where checking the out size of the head would affect the batchnorm averaging
 - Potential bug in `plot_sample_pred` to do with bin ranges
-
+- `ForwardHook` not working with passed hook functions
 
 ## Changes
 

lumin/nn/models/model.py

@@ -204,6 +204,8 @@ def evaluate_from_by(self, by:BatchYielder, callbacks:Optional[List[AbsCallback]
             (weighted) loss of model predictions on provided data
         '''
 
+        # TODO: Fix this to work for incomplete batch
+
         loss = 0
         for x, y, w in by: loss += self.evaluate(x, y, w, callbacks)*by.bs
         return loss/(len(by)*by.bs)

lumin/utils/misc.py

@@ -2,6 +2,7 @@
 from typing import Union, List, Tuple, Optional
 import pandas as pd
 import sympy
+from functools import partial
 
 from sklearn.utils import resample
 
@@ -128,8 +129,10 @@ class FowardHook():
     '''
     def __init__(self, module:nn.Module, hook_fn:Optional=None):
         self.input,self.output = None,None
-        if hook_fn is not None: self.hook_fn = hook_fn
+        if hook_fn is not None: self.hook_fn = partial(hook_fn, self)
         self.hook = module.register_forward_hook(self.hook_fn)
+
+    def __del__(self): self.remove()
 
     def hook_fn(self, module:nn.Module, input:Union[Tensor,Tuple[Tensor]], output:Union[Tensor,Tuple[Tensor]]) -> None:
         r'''