Commit 79bfade7 authored by Mccaskey, Alex's avatar Mccaskey, Alex
Browse files

fix to rtd


Signed-off-by: Mccaskey, Alex's avatarAlex McCaskey <mccaskeyaj@ornl.gov>
parent ad3ce167
......@@ -315,7 +315,7 @@ EXTENSION_MAPPING =
# case of backward compatibilities issues.
# The default value is: YES.
MARKDOWN_SUPPORT = YES
MARKDOWN_SUPPORT = NO
# When the TOC_INCLUDE_HEADINGS tag is set to a non-zero value, all headings up
# to that level are automatically included in the table of contents, even if
......@@ -889,7 +889,7 @@ RECURSIVE = YES
# Note that relative paths are relative to the directory from which doxygen is
# run.
EXCLUDE = ../../quantum/plugins/ibm/accelerator/qiskit-terra/
#EXCLUDE = ../../quantum/plugins/ibm/accelerator/qiskit-terra/ ../../xacc/optimizers/nlopt-optimizer/nlopt/ ../../tpls/ ../../quantum/plugins/dwave/embedding/minorminer/
# The EXCLUDE_SYMLINKS tag can be used to select whether or not files or
# directories that are symbolic links (a Unix file system feature) are excluded
......@@ -906,6 +906,10 @@ EXCLUDE_SYMLINKS = NO
# exclude all test directories for example use the pattern */test/*
EXCLUDE_PATTERNS = */tests/*
EXCLUDE_PATTERNS += */qiskit-terra/*
EXCLUDE_PATTERNS += */nlopt/*
EXCLUDE_PATTERNS += */tpls/*
EXCLUDE_PATTERNS += */minorminer/*
# The EXCLUDE_SYMBOLS tag can be used to specify one or more symbol names
# (namespaces, classes, functions, etc.) that should be excluded from the
......@@ -1964,7 +1968,7 @@ MAN_LINKS = NO
# captures the structure of the code including all documentation.
# The default value is: NO.
GENERATE_XML = YES
GENERATE_XML = NO
# The XML_OUTPUT tag is used to specify where the XML pages will be put. If a
# relative path is entered the value of OUTPUT_DIRECTORY will be put in front of
......
......@@ -5,20 +5,20 @@ Here we demonstrate leveraging the XACC framework for various
quantum-classical programming tasks. We provide examples in both
C++ and Python.
`AcceleratorBuffer` Usage
``AcceleratorBuffer`` Usage
-------------------------
The `AcceleratorBuffer` represents a register of qubits. Programmers allocate
The ``AcceleratorBuffer`` represents a register of qubits. Programmers allocate
this register of a certain size, and pass it by reference to all execution tasks.
These execution tasks are carried out by concrete instances of the `Accelerator`
interface, and these instances are responsible for persisting information to the
provided buffer reference. This ensures programmers have access to all execution results
and metadata upon execution completion.
Programmers can allocate a buffer through the `xacc::qalloc(const int n)` (`xacc.qalloc(int)` in Python) call.
Programmers can allocate a buffer through the ``xacc::qalloc(const int n)`` (``xacc.qalloc(int)`` in Python) call.
After execution, measurement results can be queried as well as backend-specific
execution metadata. Below demonstrate some basic usage of the `AcceleratorBuffer`
execution metadata. Below demonstrate some basic usage of the ``AcceleratorBuffer``
.. code::
.. code:: cpp
#include "xacc.hpp"
...
......@@ -33,7 +33,7 @@ execution metadata. Below demonstrate some basic usage of the `AcceleratorBuffer
in Python
.. code::
.. code:: python
import xacc
...
......@@ -54,7 +54,7 @@ is represented in XACC as a `CompositeInstruction`. The creation of `Instruction
implementation of the `IRProvider`, specifically a 3 instruction circuit with one
parameterized `Ry` on a variable `theta`.
.. code::
.. code:: cpp
#include "xacc.hpp"
...
......@@ -67,7 +67,7 @@ parameterized `Ry` on a variable `theta`.
in Python
.. code::
.. code::python
import xacc
...
......@@ -84,7 +84,7 @@ a `Compiler` implementation for the language being used. `Compilers` take kernel
source strings and produce IR (one or many `CompositeInstruction`s). Here we demonstrate
the same circuit as above, but using a Quil kernel
.. code::
.. code:: cpp
#include "xacc.hpp"
...
......@@ -109,7 +109,7 @@ the same circuit as above, but using a Quil kernel
in Python
.. code::
.. code:: python
import xacc
...
......@@ -138,7 +138,7 @@ backend execution.
Next we demonstrate how one might leverate `IRTransformation` to perform general optimizations
on IR instances.
.. code::
.. code:: cpp
#include "xacc.hpp"
...
......@@ -161,7 +161,7 @@ on IR instances.
in Python
.. code::
.. code:: python
import xacc
...
......@@ -193,7 +193,7 @@ The `Observable` concept in XACC dictates measurements to be performed
on unmeasured an `CompositeInstruction`. XACC provides `pauli` and `fermion`
`Observable` implementations. Below we demonstrate how one might create these objects.
.. code::
.. code:: cpp
#include "xacc.hpp"
#include "xacc_observable.hpp"
......@@ -212,7 +212,7 @@ on unmeasured an `CompositeInstruction`. XACC provides `pauli` and `fermion`
in Python
.. code::
.. code:: python
import xacc
...
......@@ -235,7 +235,7 @@ Here we demonstrate getting reference to an `Accelerator` and using it to execut
Note this is a full example, that leverages the `xasm` compiler as well as requisite C++ framework
initialization and finalization.
.. code::
.. code:: cpp
#include "xacc.hpp"
int main(int argc, char **argv) {
......@@ -267,7 +267,7 @@ initialization and finalization.
in Python
.. code::
.. code:: python
import xacc
......@@ -295,7 +295,7 @@ a thin wrapper for functor-like objects exposing a specific argument structure (
arg a `vector<double>` representing current iterate's parameters, and another one representing the mutable
gradient vector). Below is a demonstration of how one might use this utility:
.. code::
.. code:: cpp
auto optimizer =
xacc::getOptimizer("nlopt");
......@@ -319,7 +319,7 @@ gradient vector). Below is a demonstration of how one might use this utility:
or in Python
.. code::
.. code:: python
def rosen_with_grad(x):
g = [-2*(1-x[0]) + 400.*(x[0]**3 - x[1]*x[0]), 200 * (x[1] - x[0]**2)]
......@@ -346,7 +346,7 @@ internal compilation database (standard map of CompositeInstruction names to Com
can get reference to the individual CompositeInstructions via an exposed `getCompiled()` XACC API call. The
code below demonstrates how one would use `qasm()` and its overall utility.
.. code::
.. code:: cpp
#include "xacc.hpp"
...
......@@ -385,7 +385,7 @@ code below demonstrates how one would use `qasm()` and its overall utility.
or in Python
.. code::
.. code:: python
import xacc
...
......
......@@ -14,7 +14,7 @@ install BLAS and LAPACK as well, which is required to build some optional simula
We install libunwind-dev which is also optional, but provides verbose stack-trace printing
upon execution error.
.. code::
.. code:: bash
$ sudo apt-get update && sudo apt-get install -y software-properties-common
$ sudo add-apt-repository ppa:ubuntu-toolchain-r/test && sudo apt-get update
......@@ -30,7 +30,7 @@ install BLAS and LAPACK as well, which is required to build some optional simula
We install libunwind-dev which is also optional, but provides verbose stack-trace printing
upon execution error.
.. code::
.. code:: bash
$ sudo apt-get update
$ sudo apt-get -y install gcc g++ git libcurl4-openssl-dev python3 libunwind-dev \
......@@ -41,7 +41,7 @@ Centos 7 Prerequisites
Here we will demonstrate installing from a bare Centos 7 install using GCC 8. We
install BLAS and LAPACK as well, which is required to build some optional simulators.
.. code::
.. code:: bash
$ sudo yum install libcurl-devel python3-devel git centos-release-scl make \
devtoolset-8-gcc devtoolset-8-gcc-c++ blas-devel lapack-devel
......@@ -52,7 +52,7 @@ Fedora 30 Prerequisites
Here we will demonstrate installing from a bare Fedora 30 install using GCC 9. We
install BLAS and LAPACK as well, which is required to build some optional simulators.
.. code::
.. code:: bash
$ sudo dnf install python3-devel libcurl-devel git g++ gcc make blas-devel lapack-devel
$ sudo python3 -m pip install cmake
......@@ -64,7 +64,7 @@ standard includes like `wchar.h` and others. See `here <https://stackoverflow.co
for proper XCode install and configuring to address these types of issues. Here we assume you
have Homebrew installed.
.. code::
.. code:: bash
$ brew install python3 openssl curl
......@@ -72,13 +72,13 @@ Build XACC
----------
The best way to install a recent version of CMake is through Python Pip.
.. code::
.. code:: bash
$ sudo python3 -m pip install cmake
Now clone and build XACC
.. code::
.. code:: bash
$ git clone https://github.com/eclipse/xacc
$ cd xacc && mkdir build && cd build
......@@ -92,7 +92,7 @@ Now clone and build XACC
You can run Python examples as well
.. code::
.. code:: bash
[ you may also want to add this to your .bashrc ]
$ export PYTHONPATH:$PYTHONPATH:$HOME/.xacc
......@@ -100,7 +100,7 @@ You can run Python examples as well
Most users build and install the TNQVM Accelerator
.. code::
.. code:: bash
$ git clone https://github.com/ornl-qci/tnqvm
$ cd tnqvm && mkdir build && cd build
......
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