Add documentation from 5.1

doc/html/_sources/overview.rst.txt

+Overview
+========
+
+MIGraphX provides an optimized execution engine for deep learning neural networks.
+
+Building a program
+------------------
+
+A program consists of a set of instructions to be executed when calling `eval <migraphx::program::eval>`. Each instruction has an associated `operation <migraphx::operation>` which represents the computation to be performed by the instruction.
+
+We can start by building a simple program to add two numbers together::
+
+    program p;
+    instruction_ref one = p.add_literal(1);
+    instruction_ref two = p.add_literal(2);
+    p.add_instruction(add{}, one, two);
+
+The `add_literal <migraphx::program::add_literal>` function will add an instruction to the program to store a literal number. The `instruction_ref <migraphx::instruction_ref>` is a reference to the instruction in the program, which can be used to compose the output of the instruction with another instruction.
+
+After creating the literals, we then create the instruction to add the numbers together. This is done by using the `add{} <migraphx::add>` operation class along with the `instruction_ref <migraphx::instruction_ref>` for the input arguments of the instruction.
+
+Finally, we can run this `program <migraphx::program>` by compiling it for the cpu and then running it with `eval <migraphx::program::eval>`::
+
+    p.compile(cpu::target{});
+    argument result = p.eval({});
+
+The easiest way to see the result is to print it::
+
+    std::cout << result;
+
+Which will print ``3``.
+
+We can also compile the program for the gpu as well.
+
+Adding parameters
+-----------------
+
+Of course, this program will always produce the same value which is quite uninteresting. Instead, we want to pass an input to a program and compute a value based on the input. This can be done with a parameter. For example, we can modify the program to take an input ``x``::
+
+    program p;
+    instruction_ref x = p.add_parameter("x", {shape::int64_type});
+    instruction_ref two = p.add_literal(2);
+    p.add_instruction(add{}, x, two);
+    p.compile(cpu::target{});
+
+This adds a parameter of type ``int64``, and compiles it for the ``cpu``. To run the program, we need to pass the parameter to it when we call `eval <migraphx::program::eval>`::
+
+    argument result = p.eval({
+        {"x", literal{1}.get_argument()}
+    });
+    std::cout << result;
+
+This will print ``3``.
+
+A parameter is given as an `argument <migraphx::argument>`. In this case, the simplest way of creating an `argument <migraphx::argument>` is from a `literal <migraphx::literal>`.
+
+Tensor data
+-----------
+
+In this example we are just creating numbers, but the `shape <migraphx::shape>` class can describe multi-dimensional tensors. For example, we can build a simple network with convolution and relu::
+
+    program p;
+    instruction_ref input = p.add_parameter("x", shape{shape::float_type, {1, 3, 32, 32}});
+    instruction_ref weights = p.add_parameter("w", shape{shape::float_type, {1, 3, 5, 5}});
+    instruction_ref conv = p.add_instruction(convolution{}, input, weights);
+    p.add_instruction(activation{"relu"}, conv);
+
+Here we create two parameters for both the ``input`` and ``weights``. In the previous examples, we just created simple literals, however, most programs will take data from already allocated buffers(usually on the GPU). In this case, we can create `argument <migraphx::argument>` objects directly from the pointers to the buffers::
+
+    // Compile the program
+    p.compile(gpu::target{});
+    // Allocated buffers by the user
+    float* input = ...;
+    float* weights = ...;
+    // Create the arguments
+    argument input_arg{shape{shape::float_type, {1, 3, 32, 32}}, input};
+    argument weights_arg{shape{shape::float_type, {1, 3, 32, 32}}, weights};
+    p.eval({{"x", input_arg}, {"w", weights_arg}})
+
+An `argument <migraphx::argument>` can handle memory buffers from either the GPU or the CPU, but when running the `program <migraphx::program>`, buffers should be allocated for the corresponding target. That is, when compiling for the CPU, the buffers should be allocated on the CPU, and when compiling for the GPU the buffers should be allocated on the GPU.
+
+Importing from onnx
+-------------------
+
+A `program <migraphx::program>` can be built directly from an onnx file, which makes it easier to use neural networks directly from other frameworks. In this case, there is an ``parse_onnx`` function::
+
+    program p = parse_onnx("model.onnx");
+    p.compile(gpu::target{});
+

doc/html/_sources/py_user_guide.rst.txt

+Python User Guide
+=================
+
+.. toctree::
+   :maxdepth: 2
+   :caption: Contents:
+
+   reference/py

doc/html/_sources/reference/cpp.rst.txt

+
+C++ Reference
+=============
+
+shape
+-----
+
+.. doxygenenum:: migraphx_shape_datatype_t
+
+.. doxygenstruct:: migraphx::shape
+
+argument
+--------
+
+.. doxygenstruct:: migraphx::argument
+
+target
+------
+
+.. doxygenstruct:: migraphx::target
+
+program
+-------
+
+.. doxygenstruct:: migraphx::program_parameter_shapes
+
+.. doxygenstruct:: migraphx::program_parameters
+
+.. doxygenstruct:: migraphx_compile_options
+
+.. doxygenstruct:: migraphx::program
+
+quantize
+--------
+
+.. doxygenstruct:: migraphx::quantize_op_names
+
+.. doxygenfunction:: migraphx::quantize_fp16(const program&)
+
+.. doxygenfunction:: migraphx::quantize_fp16(const program&, const quantize_op_names&)
+
+.. doxygenstruct:: migraphx::quantize_int8_options
+
+.. doxygenfunction:: migraphx::quantize_int8
+
+parse_onnx
+----------
+
+.. doxygenstruct:: migraphx::onnx_options
+
+.. doxygenfunction:: migraphx::parse_onnx(const char *)
+
+.. doxygenfunction:: migraphx::parse_onnx(const char *, const migraphx::onnx_options&)
+
+.. doxygenfunction:: migraphx::parse_onnx_buffer(const std::string&)
+
+.. doxygenfunction:: migraphx::parse_onnx_buffer(const std::string&, const migraphx::onnx_options&)
+
+.. doxygenfunction:: migraphx::parse_onnx_buffer(const void *, size_t)
+
+.. doxygenfunction:: migraphx::parse_onnx_buffer(const void *, size_t, const migraphx::onnx_options&)
+
+load
+----
+
+.. doxygenstruct:: migraphx_file_options
+
+.. doxygenfunction:: migraphx::load(const char *)
+
+.. doxygenfunction:: migraphx::load(const char *, migraphx_file_options)
+
+save
+----
+
+.. doxygenfunction:: migraphx::save(const program&, const char *)
+
+.. doxygenfunction:: migraphx::save(const program&, const char *, migraphx_file_options)
+

doc/html/_sources/reference/py.rst.txt

+.. py:module:: migraphx
+
+Python Reference
+================
+
+shape
+-----
+
+.. py:class:: shape(type, lens, strides=None)
+
+    Describes the shape of a tensor. This includes size, layout, and data type/
+
+.. py:method:: type()
+
+    An integer that represents the type
+
+    :rtype: int
+
+.. py:method:: lens()
+
+    A list of the lengths of the shape
+
+    :rtype: list[int]
+
+.. py:method:: strides()
+
+    A list of the strides of the shape
+
+    :rtype: list[int]
+
+.. py:method:: elements()
+
+    The number of elements in the shape
+
+    :rtype: int
+
+.. py:method:: bytes()
+
+    The number of bytes the shape uses
+
+    :rtype: int
+
+.. py:method:: type_size()
+
+    The number of bytes one element uses
+
+    :rtype: int
+
+.. py:method:: packed()
+
+    Returns true if the shape is packed.
+
+    :rtype: bool
+
+.. py:method:: transposed()
+
+    Returns true if the shape is transposed.
+
+    :rtype: bool
+
+.. py:method:: broadcasted()
+
+    Returns true if the shape is broadcasted.
+
+    :rtype: bool
+
+.. py:method:: standard()
+
+    Returns true if the shape is a standard shape. That is, the shape is both packed and not transposed.
+
+    :rtype: bool
+
+.. py:method:: scalar()
+
+    Returns true if all strides are equal to 0 (scalar tensor).
+
+    :rtype: bool
+
+
+argument
+--------
+
+.. py:class:: argument(data)
+
+    Construct an argument from a python buffer. This can include numpy arrays.
+
+.. py:method:: get_shape()
+
+    Returns the shape of the argument.
+
+    :rtype: shape
+
+.. py:method:: tolist()
+
+    Convert the elements of the argument to a python list.
+
+    :rtype: list
+
+
+.. py:function:: generate_argument(s, seed=0)
+
+    Generate an argument with random data.
+
+    :param shape s: Shape of argument to generate.
+    :param int seed: The seed used for random number generation
+
+    :rtype: argument
+
+
+
+
+
+target
+------
+
+.. py:class:: target()
+
+    This represents the compiliation target.
+
+.. py:function:: get_target(name)
+
+    Constructs the target.
+
+    :param str name: The name of the target to construct. This can either be 'gpu' or 'ref'.
+
+    :rtype: target
+
+
+program
+-------
+
+.. py:class:: program()
+
+    Represents the computation graph to be compiled and run.
+
+.. py:method:: clone()
+
+    Make a copy of the program
+
+    :rtype: program
+
+.. py:method:: get_parameter_shapes()
+
+    Get the shapes of all the input parameters in the program.
+
+    :rtype: dict[str, shape]
+
+.. py:method:: get_shape()
+
+    Get the shape of the final output of the program.
+
+    :rtype: shape
+
+.. py:method:: compile(t, offload_copy=True, fast_math=True)
+
+    Compiles the program for the target and optimizes it.
+
+    :param target t: This is the target to compile the program for.
+    :param bool offload_copy: For targets with offloaded memory(such as the gpu), this will insert instructions during compilation to copy the input parameters to the offloaded memory and to copy the final result from the offloaded memory back to main memory.
+    :param bool fast_math: Optimize math functions to use faster approximate versions. There may be slight accuracy degredation when enabled.
+
+.. py:method:: run(params)
+
+    Run the program.
+
+    :param params: This is a map of the input parameters which will be used when running the program.
+    :type params: dict[str, argument]
+
+    :return: The result of the last instruction.
+    :rtype: argument
+
+.. py:function:: quantize_fp16(prog, ins_names=["all"])
+
+    Quantize the program to use fp16.
+
+    :param program prog: Program to quantize.
+    :param ins_names: List of instructions to quantize.
+    :type ins_names: list[str]
+
+
+.. py:function:: quantize_int8(prog, t, calibration=[], ins_names=["dot", "convolution"])
+
+    Quantize the program to use int8.
+
+    :param program prog: Program to quantize.
+    :param target t: Target that will be used to run the calibration data.
+    :param calibration: Calibration data used to decide the parameters to the int8 optimization.
+    :type calibration: list[dict[str, argument]]
+    :param ins_names: List of instructions to quantize.
+    :type ins_names: list[str]
+
+
+parse_onnx
+----------
+
+.. py:function:: parse_onnx(filename, default_dim_value=1, map_input_dims={}, skip_unknown_operators=false, print_program_on_error=false)
+
+    Load and parse an onnx file.
+
+    :param str filename: Path to file.
+    :param str default_dim_value: default batch size to use (if not specified in onnx file).
+    :param str map_input_dims: Explicitly specify the dims of an input.
+    :param str skip_unknown_operators: Continue parsing onnx file if an unknown operator is found.
+    :param str print_program_on_error: Print program if an error occurs.
+
+    :rtype: program
+
+parse_tf
+--------
+
+.. py:function:: parse_tf(filename, is_nhwc=True, batch_size=1)
+
+    Load and parse an tensorflow protobuf file file.
+
+    :param str filename: Path to file.
+    :param bool is_nhwc: Use nhwc as default format.
+    :param str batch_size: default batch size to use (if not specified in protobuf).
+
+    :rtype: program
+
+load
+----
+
+.. py:function:: load(filename, format='msgpack')
+
+    Load a MIGraphX program
+
+    :param str filename: Path to file.
+    :param str format: Format of file. Valid options are msgpack or json.
+
+    :rtype: program
+
+save
+----
+
+.. py:function:: save(p, filename, format='msgpack')
+
+    Save a MIGraphX program
+
+    :param program p: Program to save.
+    :param str filename: Path to file.
+    :param str format: Format of file. Valid options are msgpack or json.
+

doc/html/_static/basic.css

+/*
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+ * ~~~~~~~~~
+ *
+ * Sphinx stylesheet -- basic theme.
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+ * :license: BSD, see LICENSE for details.
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+    hyphens: manual;
+}
+
+/* -- hlist styles ---------------------------------------------------------- */
+
+table.hlist {
+    margin: 1em 0;
+}
+
+table.hlist td {
+    vertical-align: top;
+}
+
+/* -- object description styles --------------------------------------------- */
+
+.sig {
+	font-family: 'Consolas', 'Menlo', 'DejaVu Sans Mono', 'Bitstream Vera Sans Mono', monospace;
+}
+
+.sig-name, code.descname {
+    background-color: transparent;
+    font-weight: bold;
+}
+
+.sig-name {
+	font-size: 1.1em;
+}
+
+code.descname {
+    font-size: 1.2em;
+}
+
+.sig-prename, code.descclassname {
+    background-color: transparent;
+}
+
+.optional {
+    font-size: 1.3em;
+}
+
+.sig-paren {
+    font-size: larger;
+}
+
+.sig-param.n {
+	font-style: italic;
+}
+
+/* C++ specific styling */
+
+.sig-inline.c-texpr,
+.sig-inline.cpp-texpr {
+	font-family: unset;
+}
+
+.sig.c   .k, .sig.c   .kt,
+.sig.cpp .k, .sig.cpp .kt {
+	color: #0033B3;
+}
+
+.sig.c   .m,
+.sig.cpp .m {
+	color: #1750EB;
+}
+
+.sig.c   .s, .sig.c   .sc,
+.sig.cpp .s, .sig.cpp .sc {
+	color: #067D17;
+}
+
+
+/* -- other body styles ----------------------------------------------------- */
+
+ol.arabic {
+    list-style: decimal;
+}
+
+ol.loweralpha {
+    list-style: lower-alpha;
+}
+
+ol.upperalpha {
+    list-style: upper-alpha;
+}
+
+ol.lowerroman {
+    list-style: lower-roman;
+}
+
+ol.upperroman {
+    list-style: upper-roman;
+}
+
+:not(li) > ol > li:first-child > :first-child,
+:not(li) > ul > li:first-child > :first-child {
+    margin-top: 0px;
+}
+
+:not(li) > ol > li:last-child > :last-child,
+:not(li) > ul > li:last-child > :last-child {
+    margin-bottom: 0px;
+}
+
+ol.simple ol p,
+ol.simple ul p,
+ul.simple ol p,
+ul.simple ul p {
+    margin-top: 0;
+}
+
+ol.simple > li:not(:first-child) > p,
+ul.simple > li:not(:first-child) > p {
+    margin-top: 0;
+}
+
+ol.simple p,
+ul.simple p {
+    margin-bottom: 0;
+}
+
+dl.footnote > dt,
+dl.citation > dt {
+    float: left;
+    margin-right: 0.5em;
+}
+
+dl.footnote > dd,
+dl.citation > dd {
+    margin-bottom: 0em;
+}
+
+dl.footnote > dd:after,
+dl.citation > dd:after {
+    content: "";
+    clear: both;
+}
+
+dl.field-list {
+    display: grid;
+    grid-template-columns: fit-content(30%) auto;
+}
+
+dl.field-list > dt {
+    font-weight: bold;
+    word-break: break-word;
+    padding-left: 0.5em;
+    padding-right: 5px;
+}
+
+dl.field-list > dt:after {
+    content: ":";
+}
+
+dl.field-list > dd {
+    padding-left: 0.5em;
+    margin-top: 0em;
+    margin-left: 0em;
+    margin-bottom: 0em;
+}
+
+dl {
+    margin-bottom: 15px;
+}
+
+dd > :first-child {
+    margin-top: 0px;
+}
+
+dd ul, dd table {
+    margin-bottom: 10px;
+}
+
+dd {
+    margin-top: 3px;
+    margin-bottom: 10px;
+    margin-left: 30px;
+}
+
+dl > dd:last-child,
+dl > dd:last-child > :last-child {
+    margin-bottom: 0;
+}
+
+dt:target, span.highlighted {
+    background-color: #fbe54e;
+}
+
+rect.highlighted {
+    fill: #fbe54e;
+}
+
+dl.glossary dt {
+    font-weight: bold;
+    font-size: 1.1em;
+}
+
+.versionmodified {
+    font-style: italic;
+}
+
+.system-message {
+    background-color: #fda;
+    padding: 5px;
+    border: 3px solid red;
+}
+
+.footnote:target  {
+    background-color: #ffa;
+}
+
+.line-block {
+    display: block;
+    margin-top: 1em;
+    margin-bottom: 1em;
+}
+
+.line-block .line-block {
+    margin-top: 0;
+    margin-bottom: 0;
+    margin-left: 1.5em;
+}
+
+.guilabel, .menuselection {
+    font-family: sans-serif;
+}
+
+.accelerator {
+    text-decoration: underline;
+}
+
+.classifier {
+    font-style: oblique;
+}
+
+.classifier:before {
+    font-style: normal;
+    margin: 0.5em;
+    content: ":";
+}
+
+abbr, acronym {
+    border-bottom: dotted 1px;
+    cursor: help;
+}
+
+/* -- code displays --------------------------------------------------------- */
+
+pre {
+    overflow: auto;
+    overflow-y: hidden;  /* fixes display issues on Chrome browsers */
+}
+
+pre, div[class*="highlight-"] {
+    clear: both;
+}
+
+span.pre {
+    -moz-hyphens: none;
+    -ms-hyphens: none;
+    -webkit-hyphens: none;
+    hyphens: none;
+}
+
+div[class*="highlight-"] {
+    margin: 1em 0;
+}
+
+td.linenos pre {
+    border: 0;
+    background-color: transparent;
+    color: #aaa;
+}
+
+table.highlighttable {
+    display: block;
+}
+
+table.highlighttable tbody {
+    display: block;
+}
+
+table.highlighttable tr {
+    display: flex;
+}
+
+table.highlighttable td {
+    margin: 0;
+    padding: 0;
+}
+
+table.highlighttable td.linenos {
+    padding-right: 0.5em;
+}
+
+table.highlighttable td.code {
+    flex: 1;
+    overflow: hidden;
+}
+
+.highlight .hll {
+    display: block;
+}
+
+div.highlight pre,
+table.highlighttable pre {
+    margin: 0;
+}
+
+div.code-block-caption + div {
+    margin-top: 0;
+}
+
+div.code-block-caption {
+    margin-top: 1em;
+    padding: 2px 5px;
+    font-size: small;
+}
+
+div.code-block-caption code {
+    background-color: transparent;
+}
+
+table.highlighttable td.linenos,
+span.linenos,
+div.highlight span.gp {  /* gp: Generic.Prompt */
+  user-select: none;
+  -webkit-user-select: text; /* Safari fallback only */
+  -webkit-user-select: none; /* Chrome/Safari */
+  -moz-user-select: none; /* Firefox */
+  -ms-user-select: none; /* IE10+ */
+}
+
+div.code-block-caption span.caption-number {
+    padding: 0.1em 0.3em;
+    font-style: italic;
+}
+
+div.code-block-caption span.caption-text {
+}
+
+div.literal-block-wrapper {
+    margin: 1em 0;
+}
+
+code.xref, a code {
+    background-color: transparent;
+    font-weight: bold;
+}
+
+h1 code, h2 code, h3 code, h4 code, h5 code, h6 code {
+    background-color: transparent;
+}
+
+.viewcode-link {
+    float: right;
+}
+
+.viewcode-back {
+    float: right;
+    font-family: sans-serif;
+}
+
+div.viewcode-block:target {
+    margin: -1px -10px;
+    padding: 0 10px;
+}
+
+/* -- math display ---------------------------------------------------------- */
+
+img.math {
+    vertical-align: middle;
+}
+
+div.body div.math p {
+    text-align: center;
+}
+
+span.eqno {
+    float: right;
+}
+
+span.eqno a.headerlink {
+    position: absolute;
+    z-index: 1;
+}
+
+div.math:hover a.headerlink {
+    visibility: visible;
+}
+
+/* -- printout stylesheet --------------------------------------------------- */
+
+@media print {
+    div.document,
+    div.documentwrapper,
+    div.bodywrapper {
+        margin: 0 !important;
+        width: 100%;
+    }
+
+    div.sphinxsidebar,
+    div.related,
+    div.footer,
+    #top-link {
+        display: none;
+    }
+}
\ No newline at end of file

doc/html/_static/css/badge_only.css

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\ No newline at end of file