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Commit cd4ab535 authored by Khalique Ahmed's avatar Khalique Ahmed
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manual merge

parents 3891ee58 a0fa3742
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Showing with 1144 additions and 183 deletions
src/api/include/migraphx/migraphx.hpp
View file @ cd4ab535
......@@ -571,10 +571,90 @@ using require_interface =
// NOLINTNEXTLINE
#define MIGRAPHX_CONST_HANDLE_BASE(name) MIGRAPHX_DETAIL_HANDLE_BASE(name, const)
/**
* Container to hold optimal dynamic dimension values.
*/
struct optimals : MIGRAPHX_HANDLE_BASE(optimals)
{
MIGRAPHX_HANDLE_CONSTRUCTOR(optimals)
optimals(std::initializer_list<size_t> init_list)
{
this->make_handle(&migraphx_optimals_create, init_list.begin(), init_list.size());
}
};
/**
* @brief Dynamic dimension object.
* @details minimum, maximum, and optimal dimensions
*/
struct dynamic_dimension : MIGRAPHX_CONST_HANDLE_BASE(dynamic_dimension)
{
MIGRAPHX_HANDLE_CONSTRUCTOR(dynamic_dimension)
dynamic_dimension(size_t min, size_t max)
{
this->make_handle(&migraphx_dynamic_dimension_create_min_max, min, max);
}
dynamic_dimension(size_t min, size_t max, const optimals& opts)
{
this->make_handle(
&migraphx_dynamic_dimension_create_min_max_optimals, min, max, opts.get_handle_ptr());
}
bool is_fixed() const
{
bool result = false;
call(&migraphx_dynamic_dimension_is_fixed, &result, this->get_handle_ptr());
return result;
}
friend bool operator==(const dynamic_dimension& x, const dynamic_dimension& y)
{
bool pout;
call(&migraphx_dynamic_dimension_equal, &pout, x.get_handle_ptr(), y.get_handle_ptr());
return pout;
}
friend bool operator!=(const dynamic_dimension& x, const dynamic_dimension& y)
{
return not(x == y);
}
};
/**
* Container to hold dynamic_dimension objects.
*/
struct dynamic_dimensions : MIGRAPHX_HANDLE_BASE(dynamic_dimensions)
{
MIGRAPHX_HANDLE_CONSTRUCTOR(dynamic_dimensions)
template <class... Ts>
dynamic_dimensions(Ts... xs)
{
std::array<const_migraphx_dynamic_dimension_t, sizeof...(Ts)> a{xs.get_handle_ptr()...};
this->make_handle(&migraphx_dynamic_dimensions_create, a.data(), a.size());
}
size_t size() const
{
size_t pout;
call(&migraphx_dynamic_dimensions_size, &pout, this->get_handle_ptr());
return pout;
}
dynamic_dimension operator[](size_t pidx) const
{
const_migraphx_dynamic_dimension_t pout;
call(&migraphx_dynamic_dimensions_get, &pout, this->get_handle_ptr(), pidx);
return {pout, this->share_handle()};
}
};
/**
* @brief Describe shape of tensor
* @details A shape consists of a data type, lengths of multi-dimension tensor, and strides
*
*/
struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
{
......@@ -598,6 +678,13 @@ struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
this->make_handle(&migraphx_shape_create, type, plengths.data(), plengths.size());
}
// Force all calls of the format `shape( type_t, { size_t compatibles } )` to map to
// shape(type_t, std::vector<std::size_t> l)
shape(migraphx_shape_datatype_t t, std::initializer_list<std::size_t> d)
: shape::shape(t, std::vector<std::size_t>{d.begin(), d.end()})
{
}
shape(migraphx_shape_datatype_t type,
std::vector<size_t> plengths,
std::vector<size_t> pstrides)
......@@ -610,6 +697,11 @@ struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
pstrides.size());
}
shape(migraphx_shape_datatype_t type, const dynamic_dimensions& dyn_dims)
{
this->make_handle(&migraphx_shape_create_dynamic, type, dyn_dims.get_handle_ptr());
}
std::vector<size_t> lengths() const
{
const size_t* pout;
......@@ -626,6 +718,14 @@ struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
return {pout, pout + pout_size};
}
/// Get the dynamic dimensions of the shape
dynamic_dimensions dyn_dims() const
{
migraphx_dynamic_dimensions_t pout;
call(&migraphx_shape_dyn_dims, &pout, this->get_handle_ptr());
return {pout, own{}};
}
migraphx_shape_datatype_t type() const
{
migraphx_shape_datatype_t pout;
......@@ -654,6 +754,14 @@ struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
return result;
}
/// Is the shape dynamic
bool dynamic() const
{
bool result = false;
call(&migraphx_shape_dynamic, &result, this->get_handle_ptr());
return result;
}
// map element index to space index
size_t index(size_t i) const
{
......@@ -687,6 +795,11 @@ struct argument : MIGRAPHX_CONST_HANDLE_BASE(argument)
MIGRAPHX_DEPRECATED("Contructor without lifetime annotation is deprecated.")
argument(const migraphx_argument* p) { this->set_handle(p, borrow{}); }
argument(shape pshape)
{
this->make_handle(&migraphx_argument_create_empty, pshape.get_handle_ptr());
}
argument(shape pshape, void* pbuffer)
{
this->make_handle(&migraphx_argument_create, pshape.get_handle_ptr(), pbuffer);
......@@ -1182,12 +1295,27 @@ struct onnx_options : MIGRAPHX_HANDLE_BASE(onnx_options)
dim.size());
}
void set_dyn_input_parameter_shape(const std::string& name, const dynamic_dimensions& dyn_dims)
{
call(&migraphx_onnx_options_set_dyn_input_parameter_shape,
this->get_handle_ptr(),
name.c_str(),
dyn_dims.get_handle_ptr());
}
/// When there is a dimension parameter, then use this default value
void set_default_dim_value(unsigned int value)
{
call(&migraphx_onnx_options_set_default_dim_value, this->get_handle_ptr(), value);
}
void set_default_dyn_dim_value(const dynamic_dimension& dd)
{
call(&migraphx_onnx_options_set_default_dyn_dim_value,
this->get_handle_ptr(),
dd.get_handle_ptr());
}
/// Set default max iteration number for the loop operator
void set_default_loop_iterations(int64_t value)
{
......
src/api/migraphx.py
View file @ cd4ab535
......@@ -45,56 +45,48 @@ def shape_type_wrap(p):
p.read = 'migraphx::to_shape_type(${name})'
@api.cwrap('migraphx::compile_options')
def compile_options_type_wrap(p):
if p.returns:
p.add_param('migraphx_compile_options *')
p.bad_param('${name} == nullptr', 'Null pointer')
p.write = ['*${name} = migraphx::to_compile_options(${result})']
else:
p.add_param('migraphx_compile_options *')
p.read = '${name} == nullptr ? migraphx::compile_options{} : migraphx::to_compile_options(*${name})'
@api.cwrap('migraphx::file_options')
def file_options_type_wrap(p):
if p.returns:
p.add_param('migraphx_file_options *')
p.bad_param('${name} == nullptr', 'Null pointer')
p.write = ['*${name} = migraphx::to_file_options(${result})']
else:
p.add_param('migraphx_file_options *')
p.read = '${name} == nullptr ? migraphx::file_options{} : migraphx::to_file_options(*${name})'
def auto_handle(*args, **kwargs):
def with_handle(f):
return api.handle('migraphx_' + f.__name__, 'migraphx::' + f.__name__,
*args, **kwargs)(f)
return with_handle
@api.cwrap('migraphx::onnx_options')
def onnx_options_type_wrap(p):
if p.returns:
p.add_param('migraphx_onnx_options *')
p.bad_param('${name} == nullptr', 'Null pointer')
p.write = ['*${name} = migraphx::to_onnx_options(${result})']
else:
p.add_param('migraphx_onnx_options *')
p.read = '${name} == nullptr ? migraphx::onnx_options{} : migraphx::to_onnx_options(*${name})'
@api.handle('migraphx_optimals', 'std::set<size_t>')
def optimals(h):
h.constructor('create',
api.params(ptr='const size_t*', size='size_t'),
fname='migraphx::make_set<size_t>')
@api.cwrap('migraphx::tf_options')
def tf_options_type_wrap(p):
if p.returns:
p.add_param('migraphx_tf_options *')
p.bad_param('${name} == nullptr', 'Null pointer')
p.write = ['*${name} = migraphx::to_tf_options(${result})']
else:
p.add_param('migraphx_tf_options *')
p.read = '${name} == nullptr ? migraphx::tf_options{} : migraphx::to_tf_options(*${name})'
@api.handle('migraphx_dynamic_dimension', 'migraphx::shape::dynamic_dimension')
def dynamic_dimension(h):
h.constructor('create_min_max', api.params(min='size_t', max='size_t'))
h.constructor(
'create_min_max_optimals',
api.params(min='size_t', max='size_t', optimals='std::set<size_t>'))
h.method('is_fixed', returns='bool', const=True)
h.method('equal',
api.params(x='const migraphx::shape::dynamic_dimension&'),
invoke='migraphx::equal($@)',
returns='bool',
const=True)
def auto_handle(*args, **kwargs):
def with_handle(f):
return api.handle('migraphx_' + f.__name__, 'migraphx::' + f.__name__,
*args, **kwargs)(f)
return with_handle
@api.handle('migraphx_dynamic_dimensions',
'std::vector<migraphx::shape::dynamic_dimension>')
def dynamic_dimensions(h):
h.constructor(
'create',
api.params(ptr='const_migraphx_dynamic_dimension_t*', size='size_t'),
fname='migraphx::to_obj_vector<const_migraphx_dynamic_dimension_t>')
h.method('size', returns='size_t')
h.method('get',
api.params(idx='size_t'),
fname='at',
cpp_name='operator[]',
returns='const migraphx::shape::dynamic_dimension&')
@auto_handle()
......@@ -109,20 +101,29 @@ def shape(h):
lengths='std::vector<size_t>',
strides='std::vector<size_t>'))
h.constructor('create_scalar', api.params(type='migraphx::shape::type_t'))
h.constructor(
'create_dynamic',
api.params(type='migraphx::shape::type_t',
dims='std::vector<migraphx::shape::dynamic_dimension>'))
h.method('lengths',
fname='lens',
returns='const std::vector<size_t>&',
const=True)
h.method('strides', returns='const std::vector<size_t>&', const=True)
h.method('dyn_dims',
returns='std::vector<migraphx::shape::dynamic_dimension>',
const=True)
h.method('type', returns='migraphx::shape::type_t', const=True)
h.method('elements', returns='size_t', const=True)
h.method('bytes', returns='size_t', const=True)
h.method('ndim', returns='size_t', const=True)
h.method('equal',
api.params(x='const migraphx::shape&'),
invoke='migraphx::equal($@)',
returns='bool',
const=True)
h.method('standard', returns='bool', const=True)
h.method('dynamic', returns='bool', const=True)
h.method('index', api.params(i='size_t'), returns='size_t', const=True)
......@@ -130,6 +131,7 @@ def shape(h):
def argument(h):
h.constructor('create',
api.params(shape='const migraphx::shape&', buffer='void*'))
h.constructor('create_empty', api.params(shape='const migraphx::shape&'))
h.method('shape',
fname='get_shape',
cpp_name='get_shape',
......@@ -325,11 +327,22 @@ def onnx_options(h):
api.params(name='const char*', dims='std::vector<size_t>'),
invoke='migraphx::set_input_parameter_shape($@)',
)
h.method(
'set_dyn_input_parameter_shape',
api.params(name='const char*',
dims='std::vector<migraphx::shape::dynamic_dimension>'),
invoke='migraphx::set_dyn_input_parameter_shape($@)',
)
h.method(
'set_default_dim_value',
api.params(value='size_t'),
invoke='migraphx::set_default_dim_value($@)',
)
h.method(
'set_default_dyn_dim_value',
api.params(dd='const migraphx::shape::dynamic_dimension&'),
invoke='migraphx::set_default_dyn_dim_value($@)',
)
h.method(
'set_default_loop_iterations',
api.params(value='int64_t'),
......
src/common.cpp
View file @ cd4ab535
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
* Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
......@@ -31,20 +31,6 @@
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
// Example:
// s0 = (3,2,4,5) and s1 = (2,1,1)
//
// In this case we need to broadcast (:,1,1) portion of
// s1 plus broadcast the 1st dimension of s1
// giving output_lens = (3,2,4,5)
//
// Another example:
// s0 = (3,2,1,5) and s1 = (2,7,5)
// In this case we need to broadcast the (:,:,1:,:) axis
// of s0 plus the 1st dimension of s1 giving
// output_lens = (3,2,7,5)
//
std::vector<std::size_t> compute_broadcasted_lens(std::vector<std::size_t> s0,
std::vector<std::size_t> s1)
{
......@@ -77,32 +63,38 @@ std::vector<shape::dynamic_dimension> compute_broadcasted_dyn_dims(shape s0, sha
}
auto offset = s1.ndim() - s0.ndim();
std::vector<shape::dynamic_dimension> out_dims(s1.dyn_dims());
std::transform(
s0.dyn_dims().cbegin(),
s0.dyn_dims().cend(),
s1.dyn_dims().cbegin() + offset,
out_dims.begin() + offset,
[&](auto a, auto b) {
if(a == b)
{
return a;
}
else if(a == 1 or b == 1)
{
// setting opt to 0, may need to be changed
return shape::dynamic_dimension{std::max(a.min, b.min), std::max(a.max, b.max), 0};
}
else
{
MIGRAPHX_THROW("COMPUTE_BROADCASTED_DYN_DIMS: dynamic shapes {" +
migraphx::to_string_range(s0.dyn_dims()) + "} and {" +
migraphx::to_string_range(s1.dyn_dims()) + "} mismatch!");
}
});
std::transform(s0.dyn_dims().cbegin(),
s0.dyn_dims().cend(),
s1.dyn_dims().cbegin() + offset,
out_dims.begin() + offset,
[&](auto a, auto b) {
if(a == b or b == 1)
{
return a;
}
else if(a == 1)
{
return b;
}
else
{
MIGRAPHX_THROW("COMPUTE_BROADCASTED_DYN_DIMS: dynamic shapes {" +
migraphx::to_string_range(s0.dyn_dims()) + "} and {" +
migraphx::to_string_range(s1.dyn_dims()) + "} mismatch!");
}
});
return out_dims;
}
// Compute the common (broadcasted) dimensions of a list of fixed shapes
std::vector<shape::dynamic_dimension> compute_common_dyn_dims(const std::vector<shape>& shapes)
{
auto ret_shape = shapes.at(0);
std::for_each(shapes.cbegin() + 1, shapes.cend(), [&](auto s) {
ret_shape = shape{ret_shape.type(), compute_broadcasted_dyn_dims(ret_shape, s)};
});
return ret_shape.dyn_dims();
}
std::vector<std::size_t> compute_common_lens(const std::vector<shape>& shapes)
{
assert(not shapes.empty());
......@@ -148,42 +140,35 @@ shape common_shape(const std::vector<shape>& shapes)
return {compute_common_types(shapes), compute_common_lens(shapes)};
}
instruction_ref insert_common_op(module& m,
instruction_ref ins,
const operation& op,
std::vector<instruction_ref> inputs)
std::vector<instruction_ref>
insert_common_args(module& m, instruction_ref ins, std::vector<instruction_ref> inputs)
{
if(std::any_of(
inputs.cbegin(), inputs.cend(), [](auto input) { return input->get_shape().dynamic(); }))
{
// currently only handles the binary case
if(inputs.size() != 2)
{
MIGRAPHX_THROW("INSERT_COMMON_OP: not handled; " + migraphx::to_string(inputs.size()) +
"inputs, only handle two inputs if any are dynamic shape");
}
auto c_type = compute_common_types(to_shapes(inputs));
auto c_dyn_dims =
compute_broadcasted_dyn_dims(inputs[0]->get_shape(), inputs[1]->get_shape());
auto input_shapes = to_shapes(inputs);
auto c_type = compute_common_types(input_shapes);
auto c_dyn_dims = compute_common_dyn_dims(input_shapes);
// following should work for a static or dynamic shape
if(inputs[0]->get_shape().dyn_dims() != c_dyn_dims)
{
inputs[0] = m.insert_instruction(
ins,
make_op("multibroadcast", {{"out_dyn_dims", to_value(c_dyn_dims)}}),
inputs[0],
inputs[1]);
}
if(inputs[1]->get_shape().dyn_dims() != c_dyn_dims)
{
inputs[1] = m.insert_instruction(
ins,
make_op("multibroadcast", {{"out_dyn_dims", to_value(c_dyn_dims)}}),
inputs[1],
inputs[0]);
ins, make_op("multibroadcast", {{"out_dyn_dims", to_value(c_dyn_dims)}}), inputs);
}
std::transform(inputs.begin() + 1, inputs.end(), inputs.begin() + 1, [&](auto input) {
// uses previous multibroadcast to avoid recalculating the common shape from the
// full set of input shapes at runtime
if(input->get_shape().dyn_dims() != c_dyn_dims)
{
return m.insert_instruction(
ins,
make_op("multibroadcast", {{"out_dyn_dims", to_value(c_dyn_dims)}}),
input,
inputs[0]);
}
return input;
});
std::transform(inputs.begin(), inputs.end(), inputs.begin(), [&](auto input) {
if(input->get_shape().type() != c_type)
{
......@@ -210,7 +195,20 @@ instruction_ref insert_common_op(module& m,
return input;
});
}
return m.insert_instruction(ins, op, inputs);
return inputs;
}
std::vector<instruction_ref> add_common_args(module& m, std::vector<instruction_ref> inputs)
{
return insert_common_args(m, m.end(), std::move(inputs));
}
instruction_ref insert_common_op(module& m,
instruction_ref ins,
const operation& op,
std::vector<instruction_ref> inputs)
{
return m.insert_instruction(ins, op, insert_common_args(m, ins, std::move(inputs)));
}
instruction_ref add_common_op(module& m, const operation& op, std::vector<instruction_ref> inputs)
......
src/cpp_generator.cpp
View file @ cd4ab535
......@@ -106,6 +106,18 @@ cpp_generator::function& cpp_generator::function::set_generic_types(const module
return *this;
}
cpp_generator::function& cpp_generator::function::unused_param(const std::string& pname)
{
body.insert(0, "(void)" + pname + ";\n");
return *this;
}
cpp_generator::function& cpp_generator::function::add_generic_param(const std::string& pname)
{
params.push_back({pname, "T" + pname});
tparams.push_back("class T" + pname);
return *this;
}
struct cpp_generator_impl
{
std::stringstream fs{};
......@@ -167,6 +179,8 @@ std::string cpp_generator::generate_point_op(const operation& op,
else if(with_char(::isdigit)(key[0]))
{
auto i = std::stoul(key);
if(i >= args.size())
MIGRAPHX_THROW("Invalid argument index: " + key);
return args.at(i);
}
else if(v.contains(key))
......@@ -182,7 +196,8 @@ std::string cpp_generator::generate_point_op(const operation& op,
std::string cpp_generator::str() const { return impl->fs.str(); }
cpp_generator::function cpp_generator::generate_module(const module& m)
cpp_generator::function cpp_generator::generate_module(const module& m,
const generate_module_callback& g)
{
function f;
auto name = transform_string(m.name(), [](char c) {
......@@ -193,15 +208,25 @@ cpp_generator::function cpp_generator::generate_module(const module& m)
f.set_name(name).set_types(m).set_body(
m, [&](instruction_ref ins, const auto& names) -> std::string {
if(ins->name() == "@literal")
return shape::cpp_type(ins->get_shape().type()) + "(" +
ins->get_literal().to_string() + ")";
std::vector<std::string> args;
std::transform(ins->inputs().begin(),
ins->inputs().end(),
std::back_inserter(args),
[&](auto i) { return names.at(i); });
auto s = this->generate_point_op(ins->get_operator(), args);
{
std::string string_literal;
ins->get_literal().visit([&](auto v) {
assert(v.size() == 1);
auto x = v.front();
if(std::isinf(x))
{
string_literal = "__builtin_huge_val()";
if(x < 0)
string_literal = "-__builtin_huge_val()";
}
else if(std::isnan(x))
string_literal = "__builtin_nan()";
else
string_literal = ins->get_literal().to_string();
});
return shape::cpp_type(ins->get_shape().type()) + "(" + string_literal + ")";
}
auto s = g(ins, names);
if(impl->fresult)
return impl->fresult(ins->get_shape()) + '(' + s + ')';
else
......@@ -210,6 +235,24 @@ cpp_generator::function cpp_generator::generate_module(const module& m)
return f;
}
std::vector<std::string>
cpp_generator::to_args(const std::vector<instruction_ref>& inputs,
const std::unordered_map<instruction_ref, std::string>& names)
{
std::vector<std::string> args;
std::transform(inputs.begin(), inputs.end(), std::back_inserter(args), [&](auto i) {
return names.at(i);
});
return args;
}
cpp_generator::function cpp_generator::generate_module(const module& m)
{
return this->generate_module(m, [&](auto ins, const auto& names) {
return this->generate_point_op(ins->get_operator(), to_args(ins->inputs(), names));
});
}
std::string cpp_generator::create_function(const cpp_generator::function& f)
{
impl->function_count++;
......@@ -218,6 +261,8 @@ std::string cpp_generator::create_function(const cpp_generator::function& f)
std::string name = f.name.empty() ? "f" + std::to_string(impl->function_count) : f.name;
impl->fs << join_strings(f.attributes, " ") << " " << f.return_type << " " << name;
char delim = '(';
if(f.params.empty())
impl->fs << delim;
for(auto&& p : f.params)
{
impl->fs << delim << p.type << " " << p.name;
......
src/driver/argument_parser.hpp
View file @ cd4ab535
......@@ -148,13 +148,21 @@ struct value_parser
template <MIGRAPHX_REQUIRES(not std::is_enum<T>{} and not is_multi_value<T>{})>
static T apply(const std::string& x)
{
T result;
std::stringstream ss;
ss.str(x);
ss >> result;
if(ss.fail())
throw std::runtime_error("Failed to parse '" + x + "' as " + type_name<T>::apply());
return result;
// handle whitespace in string
if constexpr(std::is_same<T, std::string>{})
{
return x;
}
else
{
T result;
std::stringstream ss;
ss.str(x);
ss >> result;
if(ss.fail())
throw std::runtime_error("Failed to parse '" + x + "' as " + type_name<T>::apply());
return result;
}
}
template <MIGRAPHX_REQUIRES(std::is_enum<T>{} and not is_multi_value<T>{})>
......
src/driver/main.cpp
View file @ cd4ab535
......@@ -33,6 +33,7 @@
#include <migraphx/tf.hpp>
#include <migraphx/onnx.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/convert_to_json.hpp>
#include <migraphx/load_save.hpp>
#include <migraphx/json.hpp>
#include <migraphx/version.h>
......@@ -68,7 +69,9 @@ struct loader
bool brief = false;
std::string output_type;
std::string output;
std::string default_dyn_dim;
std::vector<std::string> param_dims;
std::vector<std::string> dyn_param_dims;
std::vector<std::string> output_names;
void parse(argument_parser& ap)
......@@ -83,7 +86,11 @@ struct loader
ap(file_type, {"--tf"}, ap.help("Load as tensorflow"), ap.set_value("tf"));
ap(file_type, {"--migraphx"}, ap.help("Load as MIGraphX"), ap.set_value("migraphx"));
ap(file_type, {"--migraphx-json"}, ap.help("Load as MIGraphX JSON"), ap.set_value("json"));
ap(batch, {"--batch"}, ap.help("Set batch size for model"));
ap(batch,
{"--batch"},
ap.help("For a static model, sets default_dim_value size (commonly batch size). For a "
"dynamic batch model, sets the batch "
"size at runtime."));
ap(is_nhwc, {"--nhwc"}, ap.help("Treat tensorflow format as nhwc"), ap.set_value(true));
ap(skip_unknown_operators,
{"--skip-unknown-operators"},
......@@ -96,7 +103,16 @@ struct loader
ap.help("Dim of a parameter (format: \"@name d1 d2 dn\")"),
ap.append(),
ap.nargs(2));
ap(dyn_param_dims,
{"--dyn-input-dim"},
ap.help("Dynamic dimensions of a parameter (format: \"@name_1\" \"[{min:x, max:y, "
"optimals:[o1,o2,...]}, dim2,dim3, ...]\", \"@name_2\", ... You can supply a "
"single integer value for a dimension to specify it as fixed."),
ap.append(),
ap.nargs(2));
ap(default_dyn_dim,
{"--default-dyn-dim"},
ap.help("Default dynamic dimension (format: \"{min:x, max:y, optimals:[o1,o2]}\")."));
ap(output_names,
{"--output-names"},
ap.help("Names of node output (format: \"name_1 name_2 name_n\")"),
......@@ -147,6 +163,40 @@ struct loader
return map_input_dims;
}
static auto parse_dyn_dims_json(const std::string& dd_json)
{
// expecting a json string like "[{min:1,max:64,optimals:[1,2,4,8]},3,224,224]"
auto v = from_json_string(convert_to_json(dd_json));
std::vector<migraphx::shape::dynamic_dimension> dyn_dims;
std::transform(v.begin(), v.end(), std::back_inserter(dyn_dims), [&](auto x) {
if(x.is_object())
return from_value<migraphx::shape::dynamic_dimension>(x);
auto d = x.template to<std::size_t>();
return migraphx::shape::dynamic_dimension{d, d};
});
return dyn_dims;
}
static auto parse_dyn_dims_map(const std::vector<std::string>& param_dyn_dims)
{
// expecting vector of strings formatted like
// {"@param_name_0", "dd_json_0", "@param_name_1", "dd_json_1", ...}
std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims;
std::string name = "";
for(auto&& x : param_dyn_dims)
{
if(x[0] == '@')
{
name = x.substr(1);
}
else
{
map_dyn_input_dims[name] = parse_dyn_dims_json(x);
}
}
return map_dyn_input_dims;
}
static auto parse_output_names(const std::vector<std::string>& output_names_info)
{
std::vector<std::string> output_node_names;
......@@ -158,13 +208,44 @@ struct loader
return output_node_names;
}
tf_options get_tf_options() const
{
auto map_input_dims = parse_param_dims(param_dims);
auto output_node_names = parse_output_names(output_names);
tf_options options;
options.is_nhwc = is_nhwc;
options.batch_size = batch;
options.map_input_dims = map_input_dims;
options.output_node_names = output_node_names;
return options;
}
onnx_options get_onnx_options() const
{
auto map_input_dims = parse_param_dims(param_dims);
auto map_dyn_input_dims = parse_dyn_dims_map(dyn_param_dims);
onnx_options options;
if(default_dyn_dim.empty())
{
options.default_dim_value = batch;
}
else
{
auto v = from_json_string(convert_to_json(default_dyn_dim));
options.default_dyn_dim_value = from_value<migraphx::shape::dynamic_dimension>(v);
}
options.skip_unknown_operators = skip_unknown_operators;
options.print_program_on_error = true;
options.map_input_dims = map_input_dims;
options.map_dyn_input_dims = map_dyn_input_dims;
return options;
}
program load()
{
program p;
if(model.empty())
{
auto map_input_dims = parse_param_dims(param_dims);
auto output_node_names = parse_output_names(output_names);
if(file_type.empty())
{
if(ends_with(file, ".onnx"))
......@@ -179,16 +260,11 @@ struct loader
std::cout << "Reading: " << file << std::endl;
if(file_type == "onnx")
{
onnx_options options;
options.default_dim_value = batch;
options.skip_unknown_operators = skip_unknown_operators;
options.print_program_on_error = true;
options.map_input_dims = map_input_dims;
p = parse_onnx(file, options);
p = parse_onnx(file, get_onnx_options());
}
else if(file_type == "tf")
{
p = parse_tf(file, tf_options{is_nhwc, batch, map_input_dims, output_node_names});
p = parse_tf(file, get_tf_options());
}
else if(file_type == "json")
{
......@@ -289,14 +365,21 @@ struct program_params
ap(fill1, {"--fill1"}, ap.help("Fill parameter with 1s"), ap.append(), ap.nargs(2));
}
auto generate(const program& p, const target& t, bool offload)
auto generate(const program& p, const target& t, bool offload, unsigned batch)
{
parameter_map m;
auto param_shapes = p.get_parameter_shapes();
std::unordered_map<std::string, shape> static_param_shapes;
std::transform(
param_shapes.cbegin(),
param_shapes.cend(),
std::inserter(static_param_shapes, static_param_shapes.end()),
[&](const auto& x) { return std::make_pair(x.first, x.second.to_static(batch)); });
for(auto&& s : fill0)
m[s] = fill_argument(p.get_parameter_shape(s), 0);
m[s] = fill_argument(static_param_shapes.at(s), 0);
for(auto&& s : fill1)
m[s] = fill_argument(p.get_parameter_shape(s), 1);
fill_param_map(m, p, t, offload);
m[s] = fill_argument(static_param_shapes.at(s), 1);
fill_param_map(m, static_param_shapes, t, offload);
return m;
}
};
......@@ -305,12 +388,12 @@ struct compiler_target
{
#ifdef HAVE_GPU
std::string target_name = "gpu";
#elif HAVE_CPU
#elif defined(HAVE_CPU)
std::string target_name = "cpu";
#elif HAVE_FPGA
std::string target_name = "fpga"
#elif defined(HAVE_FPGA)
std::string target_name = "fpga";
#else
std::string target_name = "ref"
std::string target_name = "ref";
#endif
void parse(argument_parser& ap)
......@@ -332,7 +415,8 @@ struct compiler
program_params parameters;
compiler_target ct;
compile_options co;
precision quantize = precision::fp32;
bool to_fp16 = false;
bool to_int8 = false;
std::vector<std::string> fill0;
std::vector<std::string> fill1;
......@@ -353,29 +437,55 @@ struct compiler
{"--exhaustive-tune"},
ap.help("Exhastively search for best tuning parameters for kernels"),
ap.set_value(true));
ap(quantize, {"--fp16"}, ap.help("Quantize for fp16"), ap.set_value(precision::fp16));
ap(quantize, {"--int8"}, ap.help("Quantize for int8"), ap.set_value(precision::int8));
ap(to_fp16, {"--fp16"}, ap.help("Quantize for fp16"), ap.set_value(true));
ap(to_int8, {"--int8"}, ap.help("Quantize for int8"), ap.set_value(true));
}
auto params(const program& p)
{
return parameters.generate(p, ct.get_target(), co.offload_copy);
return parameters.generate(p, ct.get_target(), co.offload_copy, l.batch);
}
auto host_params(const program& p)
{
return parameters.generate(p, ct.get_target(), true, l.batch);
}
program compile()
{
auto p = l.load();
// Dont compile if its already been compiled
if(p.is_compiled())
{
if(ct.target_name == "gpu")
{
if(is_offload_copy_set(p) and not co.offload_copy)
{
std::cout << "MIGraphX program was likely compiled with offload_copy set, Try "
"passing "
"`--enable-offload-copy` if program run fails.\n";
}
else if(co.offload_copy)
{
std::cout << "MIGraphX program was likely compiled without "
"offload_copy set, Try "
"removing "
"`--enable-offload-copy` flag if passed to driver, if program run "
"fails.\n";
}
}
return p;
}
auto t = ct.get_target();
if(quantize == precision::fp16)
if(to_fp16)
{
quantize_fp16(p);
}
else if(quantize == precision::int8)
if(to_int8)
{
quantize_int8(p, t, {params(p)});
quantize_int8(p, t, {host_params(p)});
}
p.compile(t, co);
l.save(p);
......@@ -432,19 +542,25 @@ struct verify : command<verify>
std::cout << p << std::endl;
auto t = c.ct.get_target();
auto m = c.parameters.generate(p, t, true);
auto m = c.parameters.generate(p, t, true, c.l.batch);
auto quantize = precision::fp32;
if(c.to_fp16)
quantize = precision::fp16;
if(c.to_int8)
quantize = precision::int8;
if(per_instruction)
{
verify_instructions(p, t, c.co, c.quantize, tolerance);
verify_instructions(p, t, c.co, quantize, tolerance);
}
else if(reduce)
{
verify_reduced_program(p, t, c.co, c.quantize, m, tolerance);
verify_reduced_program(p, t, c.co, quantize, m, tolerance);
}
else
{
verify_program(c.l.file, p, t, c.co, c.quantize, m, tolerance);
verify_program(c.l.file, p, t, c.co, quantize, m, tolerance);
}
}
};
......@@ -574,6 +690,26 @@ struct onnx : command<onnx>
}
};
struct tf : command<tf>
{
bool show_ops = false;
void parse(argument_parser& ap)
{
ap(show_ops,
{"--list", "-l"},
ap.help("List all tf operators supported by MIGraphX"),
ap.set_value(true));
}
void run() const
{
if(show_ops)
{
for(const auto& name : get_tf_operators())
std::cout << name << std::endl;
}
}
};
struct main_command
{
static std::string get_command_help(const std::string& title = colorize(color::fg_yellow,
......
src/driver/perf.cpp
View file @ cd4ab535
......@@ -24,6 +24,8 @@
#include "perf.hpp"
#include <migraphx/generate.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/instruction_ref.hpp>
#include <migraphx/register_target.hpp>
#ifdef HAVE_GPU
#include <migraphx/gpu/hip.hpp>
......@@ -39,36 +41,25 @@ auto get_hash(const T& x)
return std::hash<T>{}(x);
}
parameter_map fill_param_map(parameter_map& m, const program& p, const target& t, bool offload)
parameter_map fill_param_map(parameter_map& m,
const std::unordered_map<std::string, shape>& param_shapes,
const target& t,
bool offload)
{
for(auto&& x : p.get_parameter_shapes())
for(auto&& x : param_shapes)
{
argument& arg = m[x.first];
if(arg.empty())
{
assert(not x.second.dynamic());
arg = generate_argument(x.second, get_hash(x.first));
}
if(not offload)
arg = t.copy_to(arg);
}
return m;
}
parameter_map fill_param_map(parameter_map& m, const program& p, bool gpu)
{
for(auto&& x : p.get_parameter_shapes())
{
argument& arg = m[x.first];
if(arg.empty())
arg = generate_argument(x.second, get_hash(x.first));
#ifdef HAVE_GPU
if(gpu)
arg = gpu::to_gpu(arg);
#else
(void)gpu;
#endif
}
return m;
}
parameter_map create_param_map(const program& p, const target& t, bool offload)
{
parameter_map m;
......@@ -108,6 +99,38 @@ target get_target(bool gpu)
return make_target("cpu");
}
bool is_offload_copy_set(const program& p)
{
assert(p.is_compiled());
const module* mm = p.get_main_module();
std::vector<std::string> param_names = mm->get_parameter_names();
std::unordered_set<instruction_ref> param_ins;
std::transform(param_names.begin(),
param_names.end(),
std::inserter(param_ins, param_ins.begin()),
[&](const auto& i) { return mm->get_parameter(i); });
for(const auto& i : *mm)
{
if(i.name() == "hip::copy_to_gpu")
{
auto copy_arg = instruction::get_output_alias(i.inputs().front(), true);
param_ins.erase(copy_arg);
}
else if(i.name() == "@return")
{
auto return_args = i.inputs();
for(const auto& j : return_args)
{
auto alias_ins = instruction::get_output_alias(j, true);
if((alias_ins->name() == "@param" && param_ins.erase(alias_ins) == 0) or
(alias_ins->name() != "hip::copy_from_gpu"))
return false;
}
}
}
return param_ins.empty();
}
} // namespace MIGRAPHX_INLINE_NS
} // namespace driver
} // namespace migraphx
src/driver/perf.hpp
View file @ cd4ab535
......@@ -30,13 +30,24 @@ namespace migraphx {
namespace driver {
inline namespace MIGRAPHX_INLINE_NS {
parameter_map
fill_param_map(parameter_map& m, const program& p, const target& t, bool offload = false);
parameter_map fill_param_map(parameter_map& m,
const std::unordered_map<std::string, shape>& param_shapes,
const target& t,
bool offload = false);
parameter_map create_param_map(const program& p, const target& t, bool offload = false);
parameter_map fill_param_map(parameter_map& m, const program& p, bool gpu);
parameter_map create_param_map(const program& p, bool gpu = true);
target get_target(bool gpu);
/**
* @brief Checks if MIGraphX program compiled for "GPU" has offload_copy set of not. This is
intended to print a HINT for the users and would not always correctly classify compiled program as
with or without offload_copy in all cases.
* @param p Compiled MIGraphX program for GPU backend
* @return true if program is classified as compiled with "offload_copy" set
*/
bool is_offload_copy_set(const program& p);
} // namespace MIGRAPHX_INLINE_NS
} // namespace driver
......
src/dynamic_loader.cpp
View file @ cd4ab535
......@@ -71,6 +71,16 @@ struct dynamic_loader_impl
std::shared_ptr<tmp_dir> temp = nullptr;
};
fs::path dynamic_loader::path(void* address)
{
fs::path p;
Dl_info info;
// Find the location of .so
if(dladdr(address, &info) != 0)
p = info.dli_fname;
return p;
}
dynamic_loader::dynamic_loader(const fs::path& p) : impl(std::make_shared<dynamic_loader_impl>(p))
{
}
......
src/fuse_pointwise.cpp
View file @ cd4ab535
......@@ -31,6 +31,8 @@
#include <migraphx/ranges.hpp>
#include <iterator>
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_DISABLE_POINTWISE_FUSION)
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -67,13 +69,13 @@ static void create_pointwise_modules(module_pass_manager& mpm)
continue;
if(ins->get_operator().name() == "layout")
continue;
assert(ins->get_operator().attributes().contains("point_op"));
auto* pm = mpm.create_module(mpm.get_module().name() + ":pointwise" + std::to_string(n++));
pm->set_bypass();
std::unordered_map<instruction_ref, instruction_ref> param_map;
std::vector<instruction_ref> pointwise_inputs;
std::size_t i = 0;
for(auto input : ins->inputs())
{
if(contains(param_map, input))
......@@ -92,6 +94,10 @@ static void create_pointwise_modules(module_pass_manager& mpm)
}
}
// Don't create pointwise module if no inputs are detected
if(pointwise_inputs.empty())
continue;
std::vector<instruction_ref> inputs;
std::transform(ins->inputs().begin(),
ins->inputs().end(),
......@@ -188,6 +194,10 @@ void fuse_pointwise::apply(module_pass_manager& mpm) const
{
create_pointwise_modules(mpm);
mpm.run_pass(dead_code_elimination{});
if(enabled(MIGRAPHX_DISABLE_POINTWISE_FUSION{}))
{
return;
}
for(int i = 0; i < 8; i++)
{
if(not find_pointwise_modules(mpm.get_module()))
......
src/fuse_reduce.cpp 0 → 100644
View file @ cd4ab535
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#include <migraphx/fuse_reduce.hpp>
#include <migraphx/pass_manager.hpp>
#include <migraphx/dead_code_elimination.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/program.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/ranges.hpp>
#include <migraphx/check_shapes.hpp>
#include <migraphx/matcher.hpp>
#include <migraphx/register_op.hpp>
#include <iterator>
#include <map>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
struct fused_reduce
{
std::vector<std::int64_t> axes{};
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.axes, "axes"));
}
shape compute_shape(const std::vector<shape>& inputs, std::vector<module_ref> mods) const
{
if(mods.size() != 1)
MIGRAPHX_THROW("should have one submodule.");
auto* sm = mods.front();
if(sm->get_output_shapes().size() != 1)
MIGRAPHX_THROW("Only one output supported");
auto names = sm->get_parameter_names();
check_shapes{inputs, *this}.has(names.size()).same_ndims();
std::sort(names.begin(), names.end());
auto shapes = sm->get_parameter_shapes();
// Check dimension matches for each input
if(not equal(names, inputs, [&](const auto& name, const auto& input) {
return shapes.at(name).lens() == input.lens();
}))
MIGRAPHX_THROW("Dimenstion does not match the submodule.");
const auto& s = inputs.at(0);
auto lens = s.lens();
if(lens != sm->get_output_shapes().front().lens())
{
for(const auto& axis : axes)
{
lens[axis] = 1;
}
}
return shape::from_permutation(
sm->get_output_shapes().front().type(), lens, find_permutation(inputs));
}
std::string name() const { return "fused_reduce"; }
};
MIGRAPHX_REGISTER_OP(fused_reduce);
static std::unordered_map<instruction_ref, instruction_ref>
get_ins_param_map(const std::vector<instruction_ref>& inputs, const_module_ref sm)
{
std::unordered_map<instruction_ref, instruction_ref> result;
auto names = sm->get_parameter_names();
std::sort(names.begin(), names.end());
assert(names.size() == inputs.size());
std::transform(names.begin(),
names.end(),
inputs.begin(),
std::inserter(result, result.end()),
[&](const auto& name, auto input) {
return std::make_pair(input, sm->get_parameter(name));
});
return result;
}
static void insert_params(module_ref sm,
instruction_ref ins,
std::unordered_map<instruction_ref, instruction_ref>& map_ins)
{
auto n = sm->get_parameter_shapes().size();
for(auto input : ins->inputs())
{
if(contains(map_ins, input))
continue;
auto s = shape{input->get_shape().type(), input->get_shape().lens()};
map_ins[input] = sm->add_parameter("x" + std::to_string(n++), s);
}
}
static auto insert_ins_in_submodule(module_ref sm,
instruction_ref ins,
std::unordered_map<instruction_ref, instruction_ref>& map_ins)
{
insert_params(sm, ins, map_ins);
return sm->add_instructions({ins}, map_ins);
}
static auto insert_ins_in_submodule(module_ref sm, instruction_ref ins)
{
std::unordered_map<instruction_ref, instruction_ref> map_ins;
return insert_ins_in_submodule(sm, ins, map_ins);
}
static auto
insert_module_in_submodule(module_ref sm,
instruction_ref ins,
std::unordered_map<instruction_ref, instruction_ref>& map_ins)
{
insert_params(sm, ins, map_ins);
auto* m = ins->module_inputs().front();
auto param_map = get_ins_param_map(ins->inputs(), m);
for(auto&& [input, param] : param_map)
{
map_ins[param] = map_ins.at(input);
}
return sm->add_instructions(m, map_ins);
}
static std::vector<instruction_ref>
find_inputs(module_ref sm,
const module& parent,
const std::unordered_map<instruction_ref, instruction_ref>& map_ins)
{
std::vector<instruction_ref> result;
std::map<std::string, instruction_ref> names;
for(auto&& [input, param] : map_ins)
{
if(not sm->has_instruction(param))
continue;
if(param->name() != "@param")
continue;
if(not parent.has_instruction(input))
continue;
auto v = param->get_operator().to_value();
auto name = v.at("parameter").to<std::string>();
names[name] = input;
}
std::transform(names.begin(), names.end(), std::back_inserter(result), [](const auto& p) {
return p.second;
});
assert(result.size() == sm->get_parameter_shapes().size());
return result;
}
static void create_reduce_modules(module_pass_manager& mpm)
{
std::size_t n = 0;
for(auto ins : iterator_for(mpm.get_module()))
{
if(not ins->get_operator().attributes().get("reduce", false))
continue;
if(ins->inputs().size() != 1)
continue;
auto* rm =
mpm.create_module(mpm.get_module().name() + ":" + ins->name() + std::to_string(n++));
rm->set_bypass();
rm->add_return(insert_ins_in_submodule(rm, ins));
auto v = ins->get_operator().to_value();
mpm.get_module().replace_instruction(
ins, make_op("fused_reduce", {{"axes", v["axes"]}}), ins->inputs(), {rm});
}
}
template <class... Ms>
static auto match_broadcast(Ms... ms)
{
return match::skip(match::name("contiguous"))(
match::name("multibroadcast")(match::arg(0)(ms...), match::used_once()).bind("broadcast"));
}
template <class... Ms>
static auto any_input(Ms... ms)
{
return match::any_of[match::inputs()](match::any(ms...).bind("input"));
}
static auto match_broadcastable_input(const std::string& op, const std::string& name)
{
auto match_op = match::name(op)(match::used_once()).bind(name);
auto match_op_input = any_input(match_op, match::used_once());
auto broadcast_match_op_input = any_input(match_broadcast(match_op), match::used_once());
return match::any_of(match_op_input, broadcast_match_op_input);
}
namespace {
struct find_pointwise_reduce
{
auto matcher() const
{
return match::name("fused_reduce")(match_broadcastable_input("pointwise", "pointwise"));
}
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
auto reduce = r.result;
auto input = r.instructions["pointwise"];
const auto* pm = input->module_inputs().front();
const auto* old_rm = reduce->module_inputs().front();
auto* rm = mpm.create_module(pm->name() + ":" + old_rm->name());
rm->set_bypass();
std::unordered_map<instruction_ref, instruction_ref> map_ins;
// Insert pointwise
auto rins = insert_ins_in_submodule(rm, input, map_ins).front();
map_ins[input] = rins;
if(contains(r.instructions, "broadcast"))
{
auto broadcast = r.instructions["broadcast"];
map_ins[broadcast] = insert_ins_in_submodule(rm, broadcast, map_ins).front();
}
// Insert fused_reduce
rm->add_return(insert_module_in_submodule(rm, reduce, map_ins));
auto new_inputs = find_inputs(rm, mpm.get_module(), map_ins);
mpm.get_module().replace_instruction(reduce, reduce->get_operator(), new_inputs, {rm});
}
};
struct find_reduce_pointwise
{
auto matcher() const
{
return match::name("pointwise")(match_broadcastable_input("fused_reduce", "reduce"));
}
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
auto pw = r.result;
auto reduce = r.instructions["reduce"];
auto input = r.instructions["input"];
const auto* pm = pw->module_inputs().front();
const auto* old_rm = reduce->module_inputs().front();
auto* rm = mpm.create_module(old_rm->name() + ":" + pm->name());
rm->set_bypass();
std::unordered_map<instruction_ref, instruction_ref> map_ins;
// Copy module instructions
insert_module_in_submodule(rm, reduce, map_ins);
if(contains(r.instructions, "broadcast"))
{
auto broadcast = r.instructions["broadcast"];
map_ins[broadcast->inputs().front()] = rm->get_returns().front();
auto bout = insert_ins_in_submodule(rm, broadcast, map_ins);
map_ins[input] = bout.front();
}
else
{
map_ins[input] = rm->get_returns().front();
}
auto out = insert_ins_in_submodule(rm, pw, map_ins);
rm->replace_return(out);
auto new_inputs = find_inputs(rm, mpm.get_module(), map_ins);
mpm.get_module().replace_instruction(pw, reduce->get_operator(), new_inputs, {rm});
}
};
struct find_reduce_reduce
{
auto matcher() const
{
return match::name("fused_reduce")(match_broadcastable_input("fused_reduce", "reduce"));
}
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
auto reduce1 = r.result;
auto reduce2 = r.instructions["reduce"];
auto input = r.instructions["input"];
if(reduce1->get_operator() != reduce2->get_operator())
return;
const auto* rm1 = reduce1->module_inputs().front();
const auto* rm2 = reduce2->module_inputs().front();
auto* rm = mpm.create_module(rm1->name() + ":" + rm2->name());
rm->set_bypass();
std::unordered_map<instruction_ref, instruction_ref> map_ins;
// Copy reduce1 instructions
insert_module_in_submodule(rm, reduce2, map_ins);
if(contains(r.instructions, "broadcast"))
{
auto broadcast = r.instructions["broadcast"];
map_ins[broadcast->inputs().front()] = rm->get_returns().front();
auto bout = insert_ins_in_submodule(rm, broadcast, map_ins);
map_ins[input] = bout.front();
}
else
{
map_ins[input] = rm->get_returns().front();
}
auto out = insert_module_in_submodule(rm, reduce1, map_ins);
rm->replace_return(out);
auto new_inputs = find_inputs(rm, mpm.get_module(), map_ins);
mpm.get_module().replace_instruction(reduce1, reduce1->get_operator(), new_inputs, {rm});
}
};
} // namespace
void fuse_reduce::apply(module_pass_manager& mpm) const
{
create_reduce_modules(mpm);
mpm.run_pass(dead_code_elimination{});
for(int i = 0; i < 4; i++)
{
match::find_matches(
mpm, find_reduce_pointwise{}, find_pointwise_reduce{}, find_reduce_reduce{});
mpm.run_pass(dead_code_elimination{});
}
}
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/include/migraphx/auto_any_cast.hpp
View file @ cd4ab535
......@@ -42,7 +42,7 @@ void any_cast()
template <class T>
struct auto_any_caster
{
T& x;
T& x; // NOLINT
template <class U>
operator U&()
......
src/include/migraphx/check_context.hpp
View file @ cd4ab535
......@@ -27,6 +27,8 @@
#include <migraphx/program.hpp>
#include <migraphx/config.hpp>
#include <migraphx/register_op.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/ranges.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -36,7 +38,27 @@ struct check_context
{
struct op : auto_register_op<op>
{
std::string name() const { return "check_context::" + get_type_name<T>(); }
static std::string compute_op_name()
{
const auto& op_type_name = get_type_name<T>();
const auto& split_name = split_string(op_type_name, ':');
std::vector<std::string> name_without_version = {"check_context"};
// op_type_name would contain internal namespace name with version_x_y_z
// remove version and construct op_name such as check_context::migraphx::gpu::context
std::copy_if(
split_name.begin(),
split_name.end(),
std::back_inserter(name_without_version),
[&](const auto& i) { return not i.empty() and not contains(i, "version"); });
return join_strings(name_without_version, "::");
}
std::string name() const
{
static auto op_name = compute_op_name();
return op_name;
}
shape compute_shape(const std::vector<shape>&) const { return {}; }
argument compute(context& ctx, const shape&, const std::vector<argument>&) const
{
......
src/include/migraphx/check_shapes.hpp
View file @ cd4ab535
......@@ -38,8 +38,8 @@ struct check_shapes
{
const shape* begin;
const shape* end;
const std::string name;
const bool dynamic_allowed;
std::string name;
bool dynamic_allowed;
check_shapes(const shape* b, const shape* e, const std::string& n, const bool d = false)
: begin(b), end(e), name(n), dynamic_allowed(d)
......
src/include/migraphx/common.hpp
View file @ cd4ab535
......@@ -34,6 +34,26 @@ inline namespace MIGRAPHX_INLINE_NS {
struct module;
struct operation;
/**
* Broadcasting works by comparing the shapes element-wise starting with
* the trailing (right-most) dimensions and working leftwards. This is equivalent
* to what is done in NumPy.
* example 1:
* s0 = (3,2,4,5) and s1 = (2,1,1)
* In this case we need to broadcast (:,1,1) portion of
* s1 plus broadcast the 1st dimension of s0
* giving output_lens = (3,2,4,5)
*
* example 2:
* s0 = (3,2,1,5) and s1 = (2,7,5)
* In this case we need to broadcast the (:,:,1:,:) axis
* of s0 plus the 1st dimension of s1 giving
* output_lens = (3,2,7,5)
*
* example 3:
* s0 = (4, 1, 1) and s1 = (3, 4)
* output_lens = (4, 3, 4)
*/
std::vector<std::size_t> compute_broadcasted_lens(std::vector<std::size_t> s0,
std::vector<std::size_t> s1);
......@@ -41,10 +61,41 @@ std::vector<shape::dynamic_dimension> compute_broadcasted_dyn_dims(shape s0, sha
shape common_shape(const std::vector<shape>& shapes);
/**
* @brief Compute the common (broadcasted) dimensions of a list of fixed shapes
*/
std::vector<std::size_t> compute_common_lens(const std::vector<shape>& shapes);
/**
* @ brief Compute the common (broadcasted) dynamic dimensions of a list of dynamic shapes
*/
std::vector<shape::dynamic_dimension> compute_common_dyn_dims(const std::vector<shape>& shapes);
/**
* @brief Creates and adds instructions to convert input arguments to common shapes and types
* by adding multi-broadcast and type convert operations. This is a utility function for creating
* operations where the shape and type of inputs need to match. It supports both dynamic and
* static-shaped arguments.
*
* @param m containing module for instruction
* @param ins insertion location in instruction list
* @param inputs instructions to use as argument list; also, the shapes
* attached to each instruction_ref are considered for broadcasting
* @return std::vector<instruction_ref> a modified argument list
*/
std::vector<instruction_ref>
insert_common_args(module& m, instruction_ref ins, std::vector<instruction_ref> inputs);
std::vector<instruction_ref> add_common_args(module& m, std::vector<instruction_ref> inputs);
instruction_ref insert_common_op(module& m,
instruction_ref ins,
const operation& op,
std::vector<instruction_ref> inputs);
/**
* @brief Wrapper for insert_common_args() which inserts operation at the end of the module.
*/
instruction_ref add_common_op(module& m, const operation& op, std::vector<instruction_ref> inputs);
} // namespace MIGRAPHX_INLINE_NS
......
src/include/migraphx/compile_options.hpp
View file @ cd4ab535
......@@ -32,7 +32,12 @@ inline namespace MIGRAPHX_INLINE_NS {
struct compile_options
{
bool offload_copy = false;
/**
* Have MIGX allocate memory for parameters and add instructions
* to copy parameters and output to/from an offload device like a GPU.
*/
bool offload_copy = false;
bool fast_math = true;
bool exhaustive_tune = false;
tracer trace{};
......
src/include/migraphx/convolution.hpp 0 → 100644
View file @ cd4ab535
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_RTGLIB_CONVOLUTION_HPP
#define MIGRAPHX_GUARD_RTGLIB_CONVOLUTION_HPP
#include <migraphx/config.hpp>
#include <migraphx/dfor.hpp>
#include <migraphx/par_for.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/tensor_view.hpp>
#include <vector>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
template <class Output, class T, class Padding, class Stride>
void convolution(Output output, T input, T weights, Padding padding, Stride stride, int group)
{
auto output_shape = output.get_shape();
auto in_lens = input.get_shape().lens();
auto wei_lens = weights.get_shape().lens();
auto wei_n = wei_lens[0];
auto wei_c = wei_lens[1];
std::vector<std::size_t> win_size(wei_lens.begin() + 1, wei_lens.end());
par_for(output_shape.elements(), [&](auto i) {
auto idx_o = output_shape.multi(i);
auto w = idx_o[1];
auto n_dim = idx_o.size();
std::vector<std::ptrdiff_t> win_start;
for(std::size_t dim = 2; dim < n_dim; ++dim)
{
auto d_2 = dim - 2;
win_start.push_back(std::ptrdiff_t(idx_o[dim] * stride[d_2]) -
std::ptrdiff_t(padding[d_2]));
}
const auto group_id = w / (wei_n / group);
shape win_shape{output_shape.type(), win_size};
double acc = 0.0;
shape_for_each(win_shape, [&](auto idx_win) {
auto k = idx_win[0];
const auto in_ch = group_id * wei_c + k;
std::vector<std::ptrdiff_t> idx(idx_o.begin(), idx_o.end());
idx[1] = in_ch;
std::transform(idx_win.begin() + 1,
idx_win.end(),
win_start.begin(),
idx.begin() + 2,
[](std::ptrdiff_t ii, std::ptrdiff_t jj) { return ii + jj; });
std::vector<std::ptrdiff_t> idx_wei(idx_o.size());
idx_wei[0] = w;
std::copy(idx_win.begin(), idx_win.end(), idx_wei.begin() + 1);
if(std::all_of(idx.begin() + 2, idx.end(), [&](auto ii) { return ii >= 0; }) and
std::equal(idx.begin(),
idx.end(),
in_lens.begin(),
in_lens.end(),
std::less<std::ptrdiff_t>{}))
{
acc += input(idx.begin(), idx.end()) * weights(idx_wei.begin(), idx_wei.end());
}
});
output[i] = acc;
});
}
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif
src/include/migraphx/cpp_generator.hpp
View file @ cd4ab535
......@@ -77,6 +77,8 @@ struct cpp_generator
function& set_types(const module& m);
function& set_types(const module& m, const std::function<std::string(shape)>& parse);
function& set_generic_types(const module& m);
function& add_generic_param(const std::string& pname);
function& unused_param(const std::string& pname);
};
cpp_generator();
......@@ -105,6 +107,10 @@ struct cpp_generator
std::string create_function(const function& f);
static std::vector<std::string>
to_args(const std::vector<instruction_ref>& inputs,
const std::unordered_map<instruction_ref, std::string>& names);
private:
std::unique_ptr<cpp_generator_impl> impl;
};
......
src/include/migraphx/dynamic_loader.hpp
View file @ cd4ab535
......@@ -37,6 +37,12 @@ struct dynamic_loader_impl;
struct dynamic_loader
{
template <class T>
static fs::path path(T* address)
{
return path(reinterpret_cast<void*>(address));
}
static fs::path path(void* address);
dynamic_loader() = default;
dynamic_loader(const fs::path& p);
......
src/include/migraphx/fuse_reduce.hpp 0 → 100644
View file @ cd4ab535
/*
* The MIT License (MIT)
*
* Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#ifndef MIGRAPHX_GUARD_MIGRAPHX_FUSE_REDUCE_HPP
#define MIGRAPHX_GUARD_MIGRAPHX_FUSE_REDUCE_HPP
#include <migraphx/config.hpp>
#include <string>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
struct module_pass_manager;
struct fuse_reduce
{
std::string name() const { return "fuse_reduce"; }
void apply(module_pass_manager& mpm) const;
};
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif // MIGRAPHX_GUARD_MIGRAPHX_FUSE_POINTWISE_HPP
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