Patch torch.nn.Paeameter

Closes #6

README.md

@@ -149,6 +149,9 @@ named_numbers = numbers.rename("C", "H","W")
 named_numbers
 ```
 
+    /home/xl0/mambaforge/envs/lovely-py31-torch25/lib/python3.10/site-packages/torch/_tensor.py:1420: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at ../c10/core/TensorImpl.h:1925.)
+      return super().rename(names)
+
     tensor[C=3, H=196, W=196] n=115248 (0.4Mb) x∈[-2.118, 2.640] μ=-0.388 σ=1.073
 
 ## Going `.deeper`
@@ -217,7 +220,7 @@ numbers.rgb
 *Maaaaybe?* Looks like someone normalized him.
 
 ``` python
-in_stats = ( (0.485, 0.456, 0.406),     # mean 
+in_stats = ( (0.485, 0.456, 0.406),     # mean
              (0.229, 0.224, 0.225) )    # std
 
 # numbers.rgb(in_stats, cl=True) # For channel-last input format
@@ -321,7 +324,6 @@ eight_images.rgb
 features[3].weight
 ```
 
-    Parameter containing:
     Parameter[128, 64, 3, 3] n=73728 (0.3Mb) x∈[-0.783, 0.776] μ=-0.004 σ=0.065 grad
 
 I want +/- 2σ to fall in the range \[-1..1\]

lovely_tensors/patch.py

@@ -17,7 +17,7 @@
 
 # %% ../nbs/10_patch.ipynb 4
 def monkey_patch(cls=torch.Tensor):
-    "Monkey-patch lovely features into `cls`" 
+    "Monkey-patch lovely features into `cls`"
 
     if not hasattr(cls, '_plain_repr'):
         if cls is torch.Tensor:
@@ -29,7 +29,7 @@ def monkey_patch(cls=torch.Tensor):
             cls._plain_str = cls.__str__
 
     @patch_to(cls)
-    def __repr__(self: torch.Tensor, *, tensor_contents=None):        
+    def __repr__(self: torch.Tensor, *, tensor_contents=None):
         return str(StrProxy(self))
 
     # Plain - the old behavior
@@ -51,7 +51,7 @@ def deeper(self: torch.Tensor):
     @patch_to(cls, as_prop=True)
     def rgb(t: torch.Tensor):
         return RGBProxy(t)
-    
+
     # .chans and .chans(...)
     @patch_to(cls, as_prop=True)
     def chans(t: torch.Tensor):
@@ -61,3 +61,7 @@ def chans(t: torch.Tensor):
     @patch_to(cls, as_prop=True)
     def plt(t: torch.Tensor):
         return PlotProxy(t)
+
+    # The base class repr handler nn.Parameter better.
+    if "__repr__" in torch.nn.Parameter.__dict__:
+        del torch.nn.Parameter.__repr__

nbs/index.ipynb

@@ -162,7 +162,7 @@
     }
    ],
    "source": [
-    "numbers "
+    "numbers"
    ]
   },
   {
@@ -363,6 +363,14 @@
    "execution_count": null,
    "metadata": {},
    "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "/home/xl0/mambaforge/envs/lovely-py31-torch25/lib/python3.10/site-packages/torch/_tensor.py:1420: UserWarning: Named tensors and all their associated APIs are an experimental feature and subject to change. Please do not use them for anything important until they are released as stable. (Triggered internally at ../c10/core/TensorImpl.h:1925.)\n",
+      "  return super().rename(names)\n"
+     ]
+    },
     {
      "data": {
       "text/plain": [
@@ -525,7 +533,7 @@
     }
    ],
    "source": [
-    "in_stats = ( (0.485, 0.456, 0.406),     # mean \n",
+    "in_stats = ( (0.485, 0.456, 0.406),     # mean\n",
     "             (0.229, 0.224, 0.225) )    # std\n",
     "\n",
     "# numbers.rgb(in_stats, cl=True) # For channel-last input format\n",
@@ -5846,7 +5854,6 @@
     {
      "data": {
       "text/plain": [
-       "Parameter containing:\n",
        "Parameter[128, 64, 3, 3] n=73728 (0.3Mb) x∈[-0.783, 0.776] μ=-0.004 σ=0.065 grad"
       ]
      },
@@ -10408,7 +10415,7 @@
     "rcParams[\"svg.hashsalt\"] = \"1\"\n",
     "\n",
     "# No date, don't include matplotlib version\n",
-    "kwargs = {'metadata': {\"Date\": None, \"Creator\": \"Matplotlib, https://matplotlib.org/\" }} \n",
+    "kwargs = {'metadata': {\"Date\": None, \"Creator\": \"Matplotlib, https://matplotlib.org/\" }}\n",
     "%config InlineBackend.print_figure_kwargs = kwargs"
    ]
   },