phiflow version updates, preparing for 2.2

diffphys-code-sol.ipynb

@@ -168,7 +168,7 @@
       },
       "outputs": [],
       "source": [
-        "!pip install --upgrade --quiet phiflow\n",
+        "!pip install --upgrade --quiet phiflow==2.1\n",
         "#!pip install --upgrade --quiet git+https://github.com/tum-pbs/PhiFlow@develop\n",
         "\n",
         "from phi.tf.flow import *\n",
@@ -1424,4 +1424,4 @@
   },
   "nbformat": 4,
   "nbformat_minor": 0
-}
+}

overview-optconv.md

@@ -51,11 +51,11 @@ We'll need a few tools for the derivations below, which are summarized here for
 
 Not surprisingly, we'll need some Taylor-series expansions. With the notation above it reads: 
 
-$$L(x+\Delta) = L + J^T \Delta + \frac{1}{2} H \Delta^2 + \cdots$$
+$$L(x+\Delta) = L + J \Delta + \frac{1}{2} H \Delta^2 + \cdots$$
 
 Then we also need the _Lagrange form_, which yields an exact solution for a $\xi$ from the interval $[x, x+\Delta]$:
 
-$$L(x+\Delta) = L + J^T \Delta + \frac{1}{2} H(\xi) \Delta^2$$
+$$L(x+\Delta) = L + J \Delta + \frac{1}{2} H(\xi) \Delta^2$$
 
 In several instances we'll make use of the fundamental theorem of calculus, repeated here for completeness:   
 
@@ -134,27 +134,27 @@ with lower loss values.
 First, we apply the fundamental theorem to L
 
 $$
-    L(x + \lambda \Delta) = L + \int_0^1 \text{ds}~ J^T(x + s \lambda \Delta) \lambda \Delta \ ,
+    L(x + \lambda \Delta) = L + \int_0^1 \text{ds}~ J(x + s \lambda \Delta) \lambda \Delta \ ,
 $$
 
 and likewise express $J$ around this location with it:
 
 $$\begin{aligned}
-    J^T(x + s \lambda \Delta) &= J^T + \int_0^1 \text{dt}~ H(x + s t \lambda \Delta) s \lambda \Delta
+    J(x + s \lambda \Delta) = J + s \lambda \Delta^T \int_0^1 \text{dt}~ H(x + s t \lambda \Delta) 
 \end{aligned}$$
 
 Inserting this $J^T$ into $L$ yields:
 
 $$\begin{aligned}
     L(x + \lambda \Delta) - L(x) 
-        &=  \int_0^1 \text{d}s \Big[    J^T + \int_0^1 \text{d}t~ H(x + s t \lambda \Delta) ~ s \lambda \Delta  \Big]^T  \lambda \Delta   \\
+        &=  \int_0^1 \text{d}s \Big[    J + s \lambda \Delta^T  \int_0^1 \text{d}t~ H(x + s t \lambda \Delta)   \Big]^T  \lambda \Delta   \\
         &=  \int_0^1 \text{d}s \Big[   -H \Delta + \int_0^1 \text{d}t H(x + s t \lambda \Delta) ~ s \lambda \Delta  \Big]^T  \lambda \Delta    \\
         &=  \int_0^1 \text{d}s  \int_0^1 \text{d}t \big[  -H \Delta + H(x + s t \lambda \Delta) ~ s \lambda \Delta  \big]^T  \lambda \Delta    \\
         &=  \int_0^1 \text{d}s  \int_0^1 \text{d}t \big[  -H \Delta (1+\lambda s) + [ H(x + s t \lambda \Delta) - H ] ~ s \lambda \Delta  \big]^T  \lambda \Delta    \\
         &=  -(H\Delta)^T \big( 1+\frac{\lambda}{2} \big) \lambda \Delta  +  \lambda^2  \int_0^1 \text{d}s ~ s  \int_0^1 \text{d}t \big[ [ H(x + s t \lambda \Delta) - H ] ~ \Delta  \big]^T  \Delta    \\
 \end{aligned}$$ (newton-step-size-conv1)
 
-Here we've first used $\Delta = - J^T/H$, and moved it into the integral in the third line.
+Here we've first used $\Delta = - J^T/H$, and moved it into the integral in the third line, alongside the $s \lambda \Delta$ term.
 Line four factors out $H \Delta$. This allows us to evaluate the integral for the first term
 $ -H \Delta (1+\lambda s)$ in the last line of equation {eq}`newton-step-size-conv1` above.
 

physgrad-code.ipynb

@@ -67,7 +67,8 @@
    },
    "outputs": [],
    "source": [
-    "!pip install --upgrade --quiet git+https://github.com/tum-pbs/PhiFlow\n",
+    "!pip install --upgrade --quiet phiflow==2.2\n",
+    "#!pip install --upgrade --quiet git+https://github.com/tum-pbs/PhiFlow\n",
     "from phi.torch.flow import *    # switch to TF with \"phi.tf.flow\""
    ]
   },

physgrad-hig-code.ipynb

@@ -785,12 +785,9 @@
   "metadata": {
     "colab": {
       "collapsed_sections": [],
-      "name": "LinearChain_GD_PG_HIG-fromSlack-colab.ipynb",
+      "name": "physgrad-hig-code.ipynb",
       "provenance": []
     },
-    "interpreter": {
-      "hash": "60a46218545510a486eb79ffac0761a327b44b02462576ac242e6c15f2abc4b7"
-    },
     "kernelspec": {
       "display_name": "Python 3.8.10 64-bit ('tf250': conda)",
       "name": "python3"

physicalloss-code.ipynb

@@ -74,23 +74,6 @@
      "name": "stderr",
      "output_type": "stream",
      "text": []
-    },
-    {
-     "name": "stdout",
-     "output_type": "stream",
-     "text": [
-      "Could not load resample cuda libraries: CUDA binaries not found at /Users/thuerey/Dropbox/mbaDevelSelected/phiflow-v1.5/phi/tf/cuda/build/resample.so. Run \"python setup.py cuda\" to compile them\n"
-     ]
-    },
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "  for key in self._mapping:\n",
-      "  yield (key, self._mapping[key])\n",
-      "$ python setup.py tf_cuda\n",
-      "before reinstalling phiflow.\n"
-     ]
     }
    ],
    "source": [
@@ -210,10 +193,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Instructions for updating:\n",
-      "Use keras.layers.Dense instead.\n",
-      "Instructions for updating:\n",
-      "Please use `layer.__call__` method instead.\n"
+      "\n"
      ]
     }
    ],