Merge pull request #47 from KevinMusgrave/dev

v0.0.60

Author: KevinMusgrave

README.md

@@ -44,7 +44,7 @@ for data in tqdm(dataloader):
     data = batch_to_device(data, device)
     # Optimization is done inside the hook.
     # The returned loss is for logging.
-    loss, _ = hook({}, {**models, **data})
+    _, loss = hook({**models, **data})
 ```
 
 ### Build complex algorithms
@@ -62,7 +62,7 @@ misc = {"combined_model": torch.nn.Sequential(G, C)}
 hook = DANNHook(optimizers, post_g=[MCCHook(), VATHook()])
 for data in tqdm(dataloader):
     data = batch_to_device(data, device)
-    loss, _ = hook({}, {**models, **data, **misc})
+    _, loss = hook({**models, **data, **misc})
 ```
 
 ### Wrap with your favorite PyTorch framework

examples/getting_started/CustomizingAlgorithms.ipynb

@@ -108,7 +108,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def print_info(model_counts, losses, outputs, G, C, D=None):\n",
+    "def print_info(model_counts, outputs, losses, G, C, D=None):\n",
     "    def get_shape(v):\n",
     "        if isinstance(v, torch.Tensor):\n",
     "            return v.shape\n",
@@ -152,8 +152,8 @@
     "G.count, C.count = 0, 0\n",
     "hook = ClassifierHook(opts)\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C)"
+    "outputs, losses = hook({**models, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C)"
    ]
   },
   {
@@ -200,8 +200,8 @@
     "weighter = MeanWeighter(weights={\"bsp_loss\": 1e-5})\n",
     "hook = ClassifierHook(opts, post=[BSPHook(), BNMHook()], weighter=weighter)\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C)"
+    "outputs, losses = hook({**models, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C)"
    ]
   },
   {
@@ -237,8 +237,8 @@
     "G.count, C.count, D.count = 0, 0, 0\n",
     "hook = DANNHook(opts)\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C, D)"
+    "outputs, losses = hook({**models, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C, D)"
    ]
   },
   {
@@ -271,8 +271,8 @@
     "\n",
     "hook = DANNHook(opts, post_g=[mcc, atdoc])\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C, D)"
+    "outputs, losses = hook({**models, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C, D)"
    ]
   },
   {
@@ -310,8 +310,8 @@
     "\n",
     "hook = CDANHook(d_opts=d_opts, g_opts=g_opts)\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **misc, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C, D)"
+    "outputs, losses = hook({**models, **misc, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C, D)"
    ]
   },
   {
@@ -341,8 +341,8 @@
     "misc[\"combined_model\"] = torch.nn.Sequential(G, C)\n",
     "hook = CDANHook(d_opts=d_opts, g_opts=g_opts, post_g=[VATHook()])\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **misc, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C, D)"
+    "outputs, losses = hook({**models, **misc, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C, D)"
    ]
   },
   {
@@ -384,8 +384,8 @@
     "\n",
     "hook = MCDHook(g_opts=g_opts, c_opts=c_opts)\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C_multiple)"
+    "outputs, losses = hook({**models, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C_multiple)"
    ]
   },
   {
@@ -415,8 +415,8 @@
     "G.count, C_multiple.count = 0, 0\n",
     "hook = MCDHook(g_opts=g_opts, c_opts=c_opts, post_x=[AFNHook()], post_z=[AlignerHook()])\n",
     "model_counts = validate_hook(hook, list(data.keys()))\n",
-    "losses, outputs = hook({}, {**models, **data})\n",
-    "print_info(model_counts, losses, outputs, G, C_multiple)"
+    "outputs, losses = hook({**models, **data})\n",
+    "print_info(model_counts, outputs, losses, G, C_multiple)"
    ]
   },
   {
@@ -445,7 +445,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.9.7"
   }
  },
  "nbformat": 4,