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Commit 229a9fec authored by charlie's avatar charlie
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Merge branch 'develop' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into dyn_nms

parents eb4dfb49 f2531606
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Dockerfile
View file @ 229a9fec
......@@ -86,7 +86,7 @@ RUN git clone --single-branch --branch ${ONNXRUNTIME_BRANCH} --recursive ${ONNXR
ADD tools/build_and_test_onnxrt.sh /onnxruntime/build_and_test_onnxrt.sh
RUN PATH=/opt/cmake/bin:$PATH cget -p /usr/local install ROCmSoftwarePlatform/llvm-project-mlir@02078ce236ad90e3aec04c0c770ef5bfc99e49c2
RUN cget -p /usr/local install ROCmSoftwarePlatform/llvm-project-mlir@26a4b3cfc0a1a15181490f24ae461608fef1b04e -DBUILD_MIXR_TARGET=On
ENV MIOPEN_FIND_DB_PATH=/tmp/miopen/find-db
ENV MIOPEN_USER_DB_PATH=/tmp/miopen/user-db
......
src/eliminate_contiguous.cpp
View file @ 229a9fec
......@@ -93,9 +93,11 @@ static bool try_compute_shape(instruction_ref ins,
return try_compute_shape(ins, inputs, mods);
}
void eliminate_contiguous::apply(module& m) const
template <class F>
static void remove_contiguous(const std::string& op_name, module& m, F f)
{
std::vector<instruction_ref> const_instruction;
auto last = std::prev(m.end());
std::vector<instruction_ref> const_instructions;
for(auto ins : iterator_for(m))
{
......@@ -103,6 +105,12 @@ void eliminate_contiguous::apply(module& m) const
if(ins->name() == "@return")
continue;
if(ins != last and ins->outputs().empty())
continue;
if(not f(ins))
continue;
// Make a copy so we can modify it while we iterate
auto args = ins->inputs();
auto new_args = args;
......@@ -110,36 +118,46 @@ void eliminate_contiguous::apply(module& m) const
for(auto arg : ins->inputs())
{
if(arg->name() == op_name)
if(arg->name() != op_name)
continue;
auto prev = arg->inputs().front();
replace(new_args, arg, prev);
if(try_compute_shape(ins, new_args, mod_args))
{
instruction::replace_argument(ins, arg, prev);
}
else if(prev->can_eval())
{
auto prev = arg->inputs().front();
replace(new_args, arg, prev);
if(try_compute_shape(ins, new_args, mod_args))
{
instruction::replace_argument(ins, arg, prev);
}
else if(prev->can_eval())
{
const_instruction.push_back(arg);
}
const_instructions.push_back(arg);
}
}
}
// Perform evaluations in parallel
std::vector<argument> literals(const_instruction.size());
par_for(const_instruction.size(), 1, [&](const auto i) {
std::vector<argument> literals(const_instructions.size());
par_for(const_instructions.size(), 1, [&](const auto i) {
auto c = op::contiguous{};
auto prev = const_instruction[i]->inputs().front();
auto prev = const_instructions[i]->inputs().front();
literals[i] = c.compute(c.compute_shape({prev->get_shape()}), {prev->eval()});
});
for(size_t i = 0; i < const_instruction.size(); i++)
for(size_t i = 0; i < const_instructions.size(); i++)
{
auto l = m.add_literal(literals[i].get_shape(), literals[i].data());
m.replace_instruction(const_instruction[i], l);
m.replace_instruction(const_instructions[i], l);
}
}
void eliminate_contiguous::apply(module& m) const
{
// Skip contiguous from splits first
remove_contiguous(op_name, m, [](auto ins) {
if(ins->name() != "slice")
return true;
return (ins->inputs().front()->outputs().size() == 1);
});
remove_contiguous(op_name, m, [](auto) { return true; });
}
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/include/migraphx/matcher.hpp
View file @ 229a9fec
......@@ -349,25 +349,27 @@ match::matcher_result find_match(module& modl, M&& m)
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_TRACE_MATCHES)
/// Find matches for an instruction in the module
template <class... Ms>
void find_matches(module& mod, instruction_ref ins, Ms&&... ms)
template <class Mod, class... Ms>
void find_matches(Mod& mod, instruction_ref ins, Ms&&... ms)
{
#if !defined(__GNUC__) || defined(__clang__) || __GNUC__ > 5
const
#endif
bool trace = enabled(MIGRAPHX_TRACE_MATCHES{});
bool match = false;
int trace = value_of(MIGRAPHX_TRACE_MATCHES{});
bool match = false;
each_args(
[&](auto&& m) {
if(match)
return;
auto r = match_instruction(mod, ins, m.matcher());
if(r.result == mod.end())
if(trace > 1)
std::cout << "Match: " << get_type_name(m) << std::endl;
auto r = match_instruction(get_module(mod), ins, m.matcher());
if(r.result == get_module(mod).end())
return;
if(trace)
if(trace > 0)
{
std::cout << "Matched by " << get_type_name(m) << std::endl;
mod.debug_print(ins);
get_module(mod).debug_print(ins);
}
m.apply(mod, r);
match = true;
......@@ -376,10 +378,10 @@ void find_matches(module& mod, instruction_ref ins, Ms&&... ms)
}
/// Find matches in a module
template <class... Ms>
void find_matches(module& mod, Ms&&... ms)
template <class Mod, class... Ms>
void find_matches(Mod& mod, Ms&&... ms)
{
for(auto ins : iterator_for(mod))
for(auto ins : iterator_for(get_module(mod)))
{
find_matches(mod, ins, ms...);
}
......
src/include/migraphx/module.hpp
View file @ 229a9fec
......@@ -124,7 +124,7 @@ struct module
std::unordered_map<instruction_ref, instruction_ref> map_ins = {});
std::vector<instruction_ref>
add_instructions(module_ref m,
add_instructions(const_module_ref m,
std::unordered_map<instruction_ref, instruction_ref> map_ins = {});
std::vector<instruction_ref>
......@@ -139,7 +139,7 @@ struct module
std::vector<instruction_ref>
insert_instructions(instruction_ref ins,
module_ref m,
const_module_ref m,
std::unordered_map<instruction_ref, instruction_ref> map_ins = {});
std::vector<instruction_ref>
......@@ -164,6 +164,10 @@ struct module
instruction_ref replace_return(std::vector<instruction_ref> args);
instruction_ref insert_literal(instruction_ref ins, literal l);
instruction_ref insert_parameter(instruction_ref ins, std::string name, shape s);
std::vector<std::string> get_parameter_names() const;
shape get_parameter_shape(std::string name) const;
......@@ -227,6 +231,8 @@ struct module
std::unique_ptr<module_impl> impl;
};
inline module& get_module(module& m) { return m; }
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......
src/include/migraphx/module_ref.hpp
View file @ 229a9fec
......@@ -32,7 +32,8 @@ namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
struct module;
using module_ref = module*;
using module_ref = module*;
using const_module_ref = const module*;
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......
src/include/migraphx/ranges.hpp
View file @ 229a9fec
......@@ -198,6 +198,12 @@ void transform(Range&& r, Iterator it, F f)
std::transform(r.begin(), r.end(), it, f);
}
template <class Range1, class Range2, class Iterator, class F>
void transform(Range1&& r1, Range2&& r2, Iterator it, F f)
{
std::transform(r1.begin(), r1.end(), r2.begin(), it, f);
}
template <class Range>
auto reverse(Range& r)
{
......
src/include/migraphx/shape.hpp
View file @ 229a9fec
......@@ -256,6 +256,10 @@ struct shape
std::size_t size(std::size_t n = 1) const { return sizeof(type) * n; }
auto is_integral() const { return std::is_integral<type>{}; }
auto is_signed() const { return std::is_signed<type>{}; }
auto is_unsigned() const { return std::is_unsigned<type>{}; }
template <class U>
type* from(U* buffer, std::size_t n = 0) const
{
......
src/module.cpp
View file @ 229a9fec
......@@ -399,7 +399,8 @@ module::add_instructions(const std::vector<instruction_ref>& instructions,
}
std::vector<instruction_ref>
module::add_instructions(module_ref m, std::unordered_map<instruction_ref, instruction_ref> map_ins)
module::add_instructions(const_module_ref m,
std::unordered_map<instruction_ref, instruction_ref> map_ins)
{
return this->insert_instructions(this->end(), m, std::move(map_ins));
}
......@@ -420,8 +421,10 @@ module::insert_instructions(instruction_ref ins,
return insert_generic_instructions(*this, ins, instructions, std::move(map_ins));
}
std::vector<instruction_ref> module::insert_instructions(
instruction_ref ins, module_ref m, std::unordered_map<instruction_ref, instruction_ref> map_ins)
std::vector<instruction_ref>
module::insert_instructions(instruction_ref ins,
const_module_ref m,
std::unordered_map<instruction_ref, instruction_ref> map_ins)
{
return insert_generic_instructions(*this, ins, iterator_for(*m), std::move(map_ins));
}
......@@ -436,11 +439,7 @@ module::insert_instructions(instruction_ref ins,
return insert_generic_instructions(*this, ins, iterator_for(r), std::move(map_ins));
}
instruction_ref module::add_literal(literal l)
{
impl->emplace_front(std::move(l));
return impl->instructions.begin();
}
instruction_ref module::add_literal(literal l) { return insert_literal(begin(), std::move(l)); }
instruction_ref module::add_outline(const shape& s)
{
......@@ -450,10 +449,7 @@ instruction_ref module::add_outline(const shape& s)
instruction_ref module::add_parameter(std::string name, shape s)
{
assert(get_parameter_shape(name) == shape{});
impl->push_front({builtin::param{std::move(name), impl->nparams}, std::move(s), {}});
impl->nparams++;
return impl->instructions.begin();
return insert_parameter(begin(), std::move(name), std::move(s));
}
instruction_ref module::add_return(std::vector<instruction_ref> args)
......@@ -466,6 +462,20 @@ instruction_ref module::add_return(std::vector<instruction_ref> args)
return result;
}
instruction_ref module::insert_literal(instruction_ref ins, literal l)
{
impl->emplace(ins, std::move(l));
return std::prev(ins);
}
instruction_ref module::insert_parameter(instruction_ref ins, std::string name, shape s)
{
assert(get_parameter_shape(name) == shape{});
impl->insert(ins, {builtin::param{std::move(name), impl->nparams}, std::move(s), {}});
impl->nparams++;
return std::prev(ins);
}
instruction_ref module::replace_return(std::vector<instruction_ref> args)
{
auto last = std::prev(this->end());
......
src/program.cpp
View file @ 229a9fec
......@@ -542,12 +542,14 @@ static void mod_from_val(module_ref mod,
if(name == "@param")
{
output = mod->add_parameter(fields["parameter"].to<std::string>(),
migraphx::from_value<shape>(node.at("shape")));
output = mod->insert_parameter(mod->end(),
fields["parameter"].to<std::string>(),
migraphx::from_value<shape>(node.at("shape")));
}
else if(name == "@literal")
{
output = mod->add_literal(migraphx::from_value<literal>(node.at("literal")));
output =
mod->insert_literal(mod->end(), migraphx::from_value<literal>(node.at("literal")));
}
else
{
......@@ -582,11 +584,11 @@ static void mod_from_val(module_ref mod,
}
else if(module_inputs.empty())
{
output = mod->add_instruction(op, inputs);
output = mod->insert_instruction(mod->end(), op, inputs);
}
else
{
output = mod->add_instruction(op, inputs, module_inputs);
output = mod->insert_instruction(mod->end(), op, inputs, module_inputs);
}
}
output->set_normalized(normalized);
......
src/serialize.cpp
View file @ 229a9fec
......@@ -36,7 +36,7 @@ void raw_data_to_value(value& v, const RawData& rd)
result["shape"] = migraphx::to_value(rd.get_shape());
if(rd.get_shape().type() == shape::tuple_type)
result["sub"] = migraphx::to_value(rd.get_sub_objects());
else
else if(not rd.empty())
result["data"] = migraphx::value::binary(rd.data(), rd.get_shape().bytes());
v = result;
}
......@@ -56,7 +56,7 @@ void migraphx_from_value(const value& v, argument& a)
literal l = migraphx::from_value<literal>(v);
a = l.get_argument();
}
else
else if(v.contains("sub"))
{
a = migraphx::from_value<std::vector<argument>>(v.at("sub"));
}
......
src/simplify_reshapes.cpp
View file @ 229a9fec
......@@ -601,6 +601,69 @@ struct find_transpose_contiguous_reshaper_unary
}
};
struct find_slice_transpose
{
auto matcher() const
{
return match::any(match::any_of[match::outputs()](
match::name("slice")(match::output(match::name("transpose")))));
}
static std::vector<int64_t> find_common_perm(const std::vector<instruction_ref>& transposes)
{
std::map<std::vector<int64_t>, int64_t> count;
for(auto t : transposes)
{
auto perm = t->get_operator().to_value()["permutation"].to_vector<int64_t>();
count[perm]++;
}
return std::max_element(
count.begin(), count.end(), by(std::less<>{}, [](auto&& p) { return p.second; }))
->first;
}
void apply(module& m, const match::matcher_result& r) const
{
auto ins = r.result;
std::vector<instruction_ref> splits;
std::copy_if(ins->outputs().begin(),
ins->outputs().end(),
std::back_inserter(splits),
[&](instruction_ref out) {
return out->name() == "slice" and out->outputs().size() == 1 and
out->outputs().front()->name() == "transpose";
});
if(splits.size() < 2)
return;
std::vector<instruction_ref> transposes;
std::transform(splits.begin(),
splits.end(),
std::back_inserter(transposes),
[](auto split) { return split->outputs().front(); });
auto perm = find_common_perm(transposes);
auto iperm = invert_permutation(perm);
auto pre = m.insert_instruction(
std::next(ins), make_op("transpose", {{"permutation", perm}}), ins);
for(auto i : range(transposes.size()))
{
auto split = splits[i];
auto t = transposes[i];
auto op = any_cast<op::slice>(split->get_operator());
std::transform(op.axes.begin(), op.axes.end(), op.axes.begin(), [&](auto axis) {
return iperm[axis];
});
auto new_ins = m.insert_instruction(t, op, pre);
if(t->get_operator() != pre->get_operator())
{
auto curr = t->get_operator().to_value()["permutation"].to_vector<int64_t>();
new_ins = m.insert_instruction(
t, make_op("transpose", {{"permutation", reorder_dims(iperm, curr)}}), new_ins);
}
m.replace_instruction(t, new_ins);
}
}
};
void simplify_reshapes::apply(module& m) const
{
for(int i = 0; i < 2; i++)
......@@ -616,6 +679,7 @@ void simplify_reshapes::apply(module& m) const
find_nested_convert{},
find_nested_slice{},
find_nested_concat{},
find_slice_transpose{},
find_transpose_contiguous_reshaper_unary{});
dead_code_elimination{}.apply(m);
}
......
src/targets/cpu/write_literals.cpp
View file @ 229a9fec
......@@ -25,6 +25,7 @@
#include <migraphx/module.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/register_op.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -52,6 +53,7 @@ struct cpu_literal
return os;
}
};
MIGRAPHX_REGISTER_OP(cpu_literal);
void write_literals::apply(module& m) const
{
......
src/targets/gpu/CMakeLists.txt
View file @ 229a9fec
......@@ -164,6 +164,7 @@ add_library(migraphx_gpu
deconvolution.cpp
device_name.cpp
elu.cpp
fuse_mlir.cpp
fuse_ops.cpp
gather.cpp
gemm_impl.cpp
......@@ -176,7 +177,7 @@ add_library(migraphx_gpu
loop.cpp
lrn.cpp
leaky_relu.cpp
mlir_conv.cpp
mlir.cpp
multinomial.cpp
nonzero.cpp
pack_args.cpp
......@@ -320,16 +321,26 @@ message(STATUS "extractkernel: ${MIGRAPHX_EXTRACT_KERNEL}")
set(MIGRAPHX_ENABLE_MLIR OFF CACHE BOOL "")
if(MIGRAPHX_ENABLE_MLIR)
find_library(LIBMLIRMIOPEN MLIRMIOpenThin REQUIRED)
find_library(MLIRAPI_LIBRARY MLIRMIOpen
PATH_SUFFIXES
# Workaournd broken mlir install
lib/ lib/lib)
# REQUIRED is not supported before cmake 3.18
if(NOT LIBMLIRMIOPEN)
message(FATAL_ERROR "libMLIRMIOpenThin not found")
if(NOT MLIRAPI_LIBRARY)
message(FATAL_ERROR "libMLIRMIOpen not found")
else()
message(STATUS "Build with libMLIRMIOpenThin: " ${LIBMLIRMIOPEN})
message(STATUS "Build with libMLIRMIOpen: " ${MLIRAPI_LIBRARY})
endif()
target_compile_definitions(migraphx_gpu PRIVATE "-DMIGRAPHX_MLIR_MIOPEN_SUPPORT")
target_link_libraries(migraphx_gpu PUBLIC ${LIBMLIRMIOPEN})
find_path(MLIRAPI_HEADERS NAMES mlir-c/Dialect/MIGraphX.h)
# Workaround MLIR broken installation
find_path(MLIRAPI_HEADERS2 NAMES mlir-c/Registration.h
PATH_SUFFIXES
include/external/include external/include)
target_compile_definitions(migraphx_gpu PRIVATE "-DMIGRAPHX_MLIR")
target_include_directories(migraphx_gpu SYSTEM PRIVATE ${MLIRAPI_HEADERS} ${MLIRAPI_HEADERS2})
target_link_libraries(migraphx_gpu PUBLIC ${MLIRAPI_LIBRARY})
endif()
set(MIGRAPHX_USE_HIPRTC OFF CACHE BOOL "")
......
src/targets/gpu/code_object_op.cpp
View file @ 229a9fec
......@@ -52,7 +52,7 @@ code_object_op::compute(context& ctx, const shape&, const std::vector<argument>&
std::transform(
args.begin(), args.end(), kargs.begin(), [](const argument& a) { return a.data(); });
k.launch(ctx.get_stream().get(), global, local, std::move(kargs));
return args.back();
return args[get_output_arg(args.size())];
}
void code_object_op::finalize(context&, const shape&, const std::vector<shape>&)
{
......
src/targets/gpu/compile_gen.cpp
View file @ 229a9fec
......@@ -43,6 +43,9 @@ static std::vector<std::size_t> vector_sizes(const std::vector<shape>& inputs)
vectorize vectorize::elements(std::size_t axis, const std::vector<shape>& inputs)
{
if(std::all_of(
inputs.begin(), inputs.end(), [&](const auto& s) { return s.lens()[axis] == 1; }))
return {1, axis};
auto sizes = vector_sizes(inputs);
std::vector<std::size_t> max_vec_size;
std::transform(inputs.begin(),
......
src/targets/gpu/deconvolution.cpp
View file @ 229a9fec
......@@ -59,31 +59,30 @@ argument miopen_deconvolution::compute(context& ctx,
auto w_desc = make_tensor(reshape_if_1d(args[1].get_shape()));
auto y_desc = make_tensor(reshape_if_1d(output_shape));
float alpha = 1;
float beta = 0;
auto status = miopenConvolutionForward(ctx.get_stream().get_miopen(),
&alpha,
x_desc.get(),
args[0].implicit(),
w_desc.get(),
args[1].implicit(),
cd.get(),
algo,
&beta,
y_desc.get(),
args[3].implicit(),
args[2].implicit(),
args[2].get_shape().bytes());
if(solution_id == 0)
MIGRAPHX_THROW("MIOpen Deconvolution: invalid solution ID");
auto status = miopenConvolutionForwardImmediate(ctx.get_stream().get_miopen(),
w_desc.get(),
args[1].implicit(),
x_desc.get(),
args[0].implicit(),
cd.get(),
y_desc.get(),
args[3].implicit(),
args[2].implicit(),
args[2].get_shape().bytes(),
solution_id);
if(status != miopenStatusSuccess)
MIGRAPHX_THROW("Running deconvolution failed");
MIGRAPHX_THROW("MIOpen Deconvolution: running convolution failed");
return args[3];
}
shape miopen_deconvolution::compile(context& ctx,
const shape& output_shape,
std::vector<shape> inputs)
shape miopen_deconvolution::find(context& ctx, const shape& output_shape, std::vector<shape> inputs)
{
shape workspace_shape{};
auto x_desc = make_tensor(reshape_if_1d(inputs[0]));
auto w_desc = make_tensor(reshape_if_1d(inputs[1]));
auto y_desc = make_tensor(reshape_if_1d(output_shape));
......@@ -119,9 +118,35 @@ shape miopen_deconvolution::compile(context& ctx,
workspace_size,
false);
if(status != miopenStatusSuccess)
MIGRAPHX_THROW("Find deconvolution failed");
handle = ctx.get_stream().get_miopen();
algo = perf.fwd_algo;
MIGRAPHX_THROW("MIOpen Deconvolution: find convolution failed");
algo = perf.fwd_algo;
size_t solution_count;
status = miopenConvolutionForwardGetSolutionCount(ctx.get_stream().get_miopen(),
w_desc.get(),
x_desc.get(),
cd.get(),
y_desc.get(),
&solution_count);
if(status != miopenStatusSuccess)
MIGRAPHX_THROW("MIOpen Deconvolution: get solution count failed");
std::vector<miopenConvSolution_t> solutions(solution_count);
status = miopenConvolutionForwardGetSolution(ctx.get_stream().get_miopen(),
w_desc.get(),
x_desc.get(),
cd.get(),
y_desc.get(),
solution_count,
&solution_count,
solutions.data());
if(status != miopenStatusSuccess)
MIGRAPHX_THROW("MIOpen Deconvolution: get solution failed");
solution_id = solutions.front().solution_id;
return shape{shape::int8_type, {perf.memory}};
}
......@@ -129,13 +154,29 @@ void miopen_deconvolution::finalize(context& ctx,
const shape& output_shape,
std::vector<shape> inputs)
{
if(handle == ctx.get_stream().get_miopen())
return;
// Check that workspace hasn't changed
auto size = inputs.at(2).bytes();
auto ws = compile(ctx, output_shape, std::move(inputs));
if(ws.bytes() > size)
MIGRAPHX_THROW("Workspace has changed during finalization.");
if(cd == nullptr)
cd = make_deconv(op);
if(solution_id == 0)
{
// Check that workspace hasn't changed
auto size = inputs.at(2).bytes();
auto ws = find(ctx, output_shape, inputs);
if(ws.bytes() > size)
MIGRAPHX_THROW("MIOpen Deconvolution: workspace has changed during finalization.");
}
auto x_desc = make_tensor(reshape_if_1d(inputs[0]));
auto w_desc = make_tensor(reshape_if_1d(inputs[1]));
auto y_desc = make_tensor(reshape_if_1d(output_shape));
auto status = miopenConvolutionForwardCompileSolution(ctx.get_stream().get_miopen(),
w_desc.get(),
x_desc.get(),
cd.get(),
y_desc.get(),
solution_id);
if(status != miopenStatusSuccess)
MIGRAPHX_THROW("MIOpen Deconvolution: compile solution failed");
}
} // namespace gpu
......
src/targets/gpu/fuse_mlir.cpp 0 → 100644
View file @ 229a9fec
/*
* 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/gpu/fuse_mlir.hpp>
#include <migraphx/gpu/mlir.hpp>
#include <migraphx/matcher.hpp>
#include <migraphx/pass_manager.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/register_op.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
struct module;
namespace gpu {
#ifdef MIGRAPHX_MLIR
struct mlir_conv
{
operation op = make_op("convolution");
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.op, "op"));
}
std::string name() const { return "gpu::mlir_conv"; }
shape compute_shape(std::vector<shape> inputs, const std::vector<module_ref>& mods) const
{
check_shapes{inputs, *this}.standard();
if(mods.size() != 1)
MIGRAPHX_THROW("should have one submodule.");
if(inputs.size() < 2)
MIGRAPHX_THROW("should have at least two inputs.");
auto n = inputs.size();
return op.compute_shape({inputs[n - 2], inputs[n - 1]});
}
};
MIGRAPHX_REGISTER_OP(mlir_conv);
namespace {
struct find_conv_pointwise
{
// Find a convolution followed by a pointwise operation.
auto matcher() const
{
auto convolution =
match::skip(match::name("contiguous"))(match::name("convolution").bind("convolution"));
return match::name("pointwise")(match::any_of[match::inputs()](convolution.bind("x")));
}
void apply(module_pass_manager& mpm, const match::matcher_result& r) const
{
auto ins = r.result;
auto conv_ins = r.instructions["convolution"];
auto x_ins = r.instructions["x"]; // input after contiguous
auto* pm = ins->module_inputs().front();
auto names = pm->get_parameter_names();
// Whitelist pointwise operators
if(std::any_of(pm->begin(), pm->end(), [](const auto& i) {
return not contains({"@literal", "@param", "@return", "convolution", "add", "relu"},
i.name());
}))
return;
// Only fuse with fp32 for now
if(std::any_of(ins->inputs().begin(), ins->inputs().end(), [&](auto i) {
return i->get_shape().type() != shape::type_t::float_type;
}))
return;
std::sort(names.begin(), names.end());
module_ref mm = mpm.create_module("mlir_" + pm->name());
mm->set_bypass();
std::unordered_map<instruction_ref, instruction_ref> param_map;
auto x = mm->add_parameter("x" + std::to_string(names.size()),
conv_ins->inputs().at(0)->get_shape());
auto w = mm->add_parameter("x" + std::to_string(names.size() + 1),
conv_ins->inputs().at(1)->get_shape());
auto conv = mm->add_instruction(conv_ins->get_operator(), {x, w});
std::transform(names.begin(),
names.end(),
ins->inputs().begin(),
std::inserter(param_map, param_map.end()),
[&](auto name, auto input) {
if(input == x_ins)
return std::make_pair(pm->get_parameter(name), conv);
return std::make_pair(pm->get_parameter(name),
mm->add_parameter(name, input->get_shape()));
});
mm->add_return(mm->insert_instructions(mm->end(), pm, param_map));
std::vector<instruction_ref> inputs;
std::copy_if(ins->inputs().begin(),
ins->inputs().end(),
std::back_inserter(inputs),
[&](auto input) { return input != conv_ins; });
inputs.insert(inputs.end(), conv_ins->inputs().begin(), conv_ins->inputs().end());
mpm.get_module().replace_instruction(
ins, mlir_conv{conv_ins->get_operator()}, inputs, {mm});
}
};
} // namespace
#endif
void fuse_mlir::apply(module_pass_manager& mpm) const
{
#ifdef MIGRAPHX_MLIR
match::find_matches(mpm, find_conv_pointwise{});
#else
(void)mpm;
#endif
}
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/targets/gpu/fuse_ops.cpp
View file @ 229a9fec
......@@ -336,6 +336,7 @@ void move_standard_front(std::vector<instruction_ref>& args)
auto gpu_name(const std::string& s) { return match::name("gpu::" + s); }
namespace {
struct find_layernorm
{
auto matcher() const { return match::layernorm(&gpu_name); }
......@@ -836,15 +837,6 @@ inline auto precompile_name(std::string s) // NOLINT
});
}
template <class... Ms>
auto conv_bias_pointwise(Ms... ms)
{
return precompile_name("pointwise")(
match::either_arg(0, 1)(bias_shape(match::used_once()).bind("bias"),
fusable_conv(match::used_once()).bind("conv")),
ms...);
}
struct find_conv_bias
{
context* ctx = nullptr;
......@@ -1013,6 +1005,7 @@ struct find_commutative_broadcast
m.replace_instruction(ins, ins->get_operator(), args);
}
};
} // namespace
struct find_contiguous
{
......
src/targets/gpu/include/migraphx/gpu/code_object_op.hpp
View file @ 229a9fec
......@@ -38,12 +38,13 @@ struct context;
struct code_object_op
{
value::binary code_object;
std::string symbol_name;
std::size_t global;
std::size_t local;
std::vector<shape> expected_inputs;
shape output;
value::binary code_object{};
std::string symbol_name = "";
std::size_t global = 0;
std::size_t local = 0;
std::vector<shape> expected_inputs{};
shape output{};
std::int64_t output_arg = -1;
kernel k{};
template <class Self, class F>
......@@ -66,9 +67,13 @@ struct code_object_op
argument
compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
void finalize(context&, const shape&, const std::vector<shape>&);
std::int64_t get_output_arg(std::size_t n) const
{
return output_arg < 0 ? n + output_arg : output_arg;
}
std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
{
return shapes.size() - 1;
return get_output_arg(shapes.size());
}
friend std::ostream& operator<<(std::ostream& os, const code_object_op& op)
......
src/targets/gpu/include/migraphx/gpu/deconvolution.hpp
View file @ 229a9fec
......@@ -39,20 +39,20 @@ struct miopen_deconvolution
op::deconvolution op;
shared<convolution_descriptor> cd;
miopenConvFwdAlgorithm_t algo{};
miopenHandle_t handle = nullptr;
uint64_t solution_id = 0;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
// TODO: Add algo
return op::convolution::reflect(self.op, f);
return pack_join(op::deconvolution::reflect(self.op, f),
pack(f(self.solution_id, "solution_id")));
}
std::string name() const { return "gpu::deconv"; }
shape compute_shape(const std::vector<shape>& inputs) const;
argument
compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
shape compile(context& ctx, const shape& output_shape, std::vector<shape> inputs);
shape find(context& ctx, const shape& output_shape, std::vector<shape> inputs);
void finalize(context& ctx, const shape& output_shape, std::vector<shape> inputs);
std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
{
......
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