Merge pull request #642 from ProGamerGov/optim-wip-model-tutorial

add model tutorial

Author: ProGamerGov

captum/optim/_core/loss.py

@@ -175,9 +175,14 @@ def loss_fn(module: ModuleOutputMapping) -> torch.Tensor:
             return math_op(torch.mean(self(module)), torch.mean(other(module)))
 
         name = f"Compose({', '.join([self.__name__, other.__name__])})"
+
+        # ToDo: Refine logic for self.target handling
         target = (self.target if isinstance(self.target, list) else [self.target]) + (
             other.target if isinstance(other.target, list) else [other.target]
         )
+
+        # Filter out duplicate targets
+        target = list(dict.fromkeys(target))
     else:
         raise TypeError(
             "Can only apply math operations with int, float or Loss. Received type "
@@ -1398,6 +1403,9 @@ def loss_fn(module: ModuleOutputMapping) -> torch.Tensor:
         ]
         for target in targets
     ]
+
+    # Filter out duplicate targets
+    target = list(dict.fromkeys(target))
     return CompositeLoss(loss_fn, name=name, target=target)
 
 

captum/optim/models/_common.py

@@ -255,6 +255,7 @@ def collect_activations(
     """
     if not isinstance(targets, list):
         targets = [targets]
+    targets = list(dict.fromkeys(targets))
     catch_activ = ActivationFetcher(model, targets)
     activ_dict = catch_activ(model_input)
     return activ_dict

captum/optim/models/_image/inception_v1.py

@@ -5,10 +5,7 @@
 import torch.nn as nn
 from captum.optim.models._common import Conv2dSame, RedirectedReluLayer, SkipLayer
 
-GS_SAVED_WEIGHTS_URL = (
-    "https://github.com/pytorch/captum/raw/"
-    + "optim-wip/captum/optim/models/_image/inception5h.pth"
-)
+GS_SAVED_WEIGHTS_URL = "https://pytorch.s3.amazonaws.com/models/captum/inception5h.pth"
 
 
 def googlenet(