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@@ -68,7 +67,7 @@ You can then obtain the corresponding backward assignments:
You can see the derivatives with respective to the two inputs multiplied by the gradient `diffz_C` of the output `z_C`.
.. testoutput::
.. code-block:: python
:options: -ELLIPSIS, +NORMALIZE_WHITESPACE
Subexpressions:
...
...
@@ -78,7 +77,7 @@ You can see the derivatives with respective to the two inputs multiplied by the
You can also use the class :class:`.AutoDiffOp` to obtain both the assignments (if you are curious) and auto-differentiable operations for Tensorflow...
.. testcode::
.. code-block:: python
op = AutoDiffOp(forward_assignments)
backward_assignments = op.backward_assignments
...
...
@@ -89,7 +88,7 @@ You can also use the class :class:`.AutoDiffOp` to obtain both the assignments (
You can see the derivatives with respective to the two inputs multiplied by the gradient `diffz_C` of the output `z_C`.
.. testoutput::
:options: -ELLIPSIS, +NORMALIZE_WHITESPACE
Subexpressions:
Main Assignments:
\hat{x}[0,0] ← diffz_C*y_C/x_C
\hat{y}[0,0] ← diffz_C*(log(x_C*y_C) + 1)
You can also use the class :class:`.AutoDiffOp` to obtain both the assignments (if you are curious) and auto-differentiable operations for Tensorflow...