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Commit 8b25fd3e authored by charlie's avatar charlie
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Merge branch 'develop' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into dyn_ref_broadcast

parents a88810da 4f3cc417
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Showing with 950 additions and 123 deletions
examples/migraphx/custom_op_hip_kernel/custom_op_hip_kernel.cpp
View file @ 8b25fd3e
......@@ -45,6 +45,13 @@ __global__ void vector_square(T* C_d, const T* A_d, size_t N)
struct square_custom_op final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "square_custom_op"; }
// flag to identify whether custom op runs on the GPU or on the host.
// Based on this flag MIGraphX would inject necessary copies to and from GPU for the input and
// output buffers as necessary. Therefore if custom_op runs on GPU then it can assume its input
// buffers are in GPU memory, and similarly for the host
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::argument
compute(migraphx::context ctx, migraphx::shape, migraphx::arguments inputs) const override
{
......@@ -54,7 +61,7 @@ struct square_custom_op final : migraphx::experimental_custom_op_base
// is output argument, so it should be returned from compute method.
auto* input_buffer = reinterpret_cast<float*>(inputs[0].data());
auto* output_buffer = reinterpret_cast<float*>(inputs[1].data());
size_t n_elements = inputs[0].get_shape().bytes() / sizeof(inputs[0].get_shape().type());
size_t n_elements = inputs[0].get_shape().elements();
MIGRAPHX_HIP_ASSERT(hipSetDevice(0));
const unsigned blocks = 512;
const unsigned threads_per_block = 256;
......@@ -103,7 +110,7 @@ int main(int argc, const char* argv[])
options.set_offload_copy();
p.compile(migraphx::target("gpu"), options);
migraphx::program_parameters pp;
std::vector<float> x_data(s.bytes() / sizeof(s.type()));
std::vector<float> x_data(s.elements());
std::iota(x_data.begin(), x_data.end(), 0);
pp.add("x", migraphx::argument(s, x_data.data()));
auto results = p.eval(pp);
......
examples/migraphx/custom_op_miopen_kernel/custom_op_miopen_kernel.cpp
View file @ 8b25fd3e
......@@ -93,6 +93,13 @@ inline auto make_activation_descriptor(miopenActivationMode_t mode,
struct abs_custom_op final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "abs_custom_op"; }
// flag to identify whether custom op runs on the GPU or on the host.
// Based on this flag MIGraphX would inject necessary copies to and from GPU for the input and
// output buffers as necessary. Therefore if custom_op runs on GPU then it can assume its input
// buffers are in GPU memory, and similarly for the host
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::argument compute(migraphx::context ctx,
migraphx::shape output_shape,
migraphx::arguments args) const override
......
examples/migraphx/custom_op_rocblas_kernel/custom_op_rocblas_kernel.cpp
View file @ 8b25fd3e
......@@ -51,6 +51,13 @@ rocblas_handle create_rocblas_handle_ptr(migraphx::context& ctx)
struct sscal_custom_op final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "sscal_custom_op"; }
// flag to identify whether custom op runs on the GPU or on the host.
// Based on this flag MIGraphX would inject necessary copies to and from GPU for the input and
// output buffers as necessary. Therefore if custom_op runs on GPU then it can assume its input
// buffers are in GPU memory, and similarly for the host
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::argument compute(migraphx::context ctx,
migraphx::shape output_shape,
migraphx::arguments args) const override
......@@ -107,7 +114,7 @@ int main(int argc, const char* argv[])
options.set_offload_copy();
p.compile(migraphx::target("gpu"), options);
migraphx::program_parameters pp;
std::vector<float> x_data(x_shape.bytes() / sizeof(x_shape.type()));
std::vector<float> x_data(x_shape.elements());
std::vector<float> scale_data{-1};
std::iota(x_data.begin(), x_data.end(), 0);
pp.add("x", migraphx::argument(x_shape, x_data.data()));
......
src/api/api.cpp
View file @ 8b25fd3e
......@@ -21,6 +21,7 @@
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
#include <migraphx/execution_environment.hpp>
#include <migraphx/migraphx.h>
#include <migraphx/rank.hpp>
#include <migraphx/shape.hpp>
......@@ -166,6 +167,13 @@ void set_output_names(tf_options& options, std::vector<const char*> names)
options.output_node_names = std::vector<std::string>(names.begin(), names.end());
}
std::vector<argument>
run_async(program& p, const parameter_map& params, void* s, std::string_view name)
{
execution_environment exec_env{any_ptr(s, name), true};
return p.eval(params, exec_env);
}
template <class Value>
std::vector<const char*> get_names(const std::unordered_map<std::string, Value>& m)
{
......@@ -265,11 +273,18 @@ struct experimental_custom_op
template <class CustomOp>
struct custom_operation
{
template <class Self, class F>
static auto reflect(Self&, F)
{
return pack();
}
value attributes() const
{
return {{"custom_op", true}, {"target", op.runs_on_offload_target() ? "gpu" : "cpu"}};
}
CustomOp op;
std::string name() const { return op.xobject.name; }
......@@ -284,6 +299,23 @@ struct custom_operation
{
return op.compute(std::move(ctx), std::move(output_shape), std::move(inputs));
}
std::ptrdiff_t output_alias(std::vector<shape> inputs) const
{
auto alias_vec = op.output_alias(std::move(inputs));
// TODO: For now, only support one output alias
if(alias_vec.empty())
{
return -1;
}
if(alias_vec.size() > 1)
{
MIGRAPHX_THROW("Currently, CustomOps in MIGraphX only supports one output_alias");
}
return alias_vec.front();
}
bool runs_on_offload_target() const { return op.runs_on_offload_target(); }
};
template <class CustomOp>
......@@ -613,9 +645,9 @@ struct migraphx_experimental_custom_op
migraphx::shape output,
std::vector<migraphx::argument> inputs) const
{
std::remove_pointer_t<migraphx_argument_t> out;
if(compute_f == nullptr)
throw std::runtime_error("compute function is missing.");
std::remove_pointer_t<migraphx_argument_t> out;
std::array<char, 256> exception_msg;
exception_msg.front() = '\0';
auto api_error_result = compute_f(&out,
......@@ -637,9 +669,9 @@ struct migraphx_experimental_custom_op
migraphx_experimental_custom_op_compute_shape compute_shape_f = nullptr;
migraphx::shape compute_shape(std::vector<migraphx::shape> inputs) const
{
std::remove_pointer_t<migraphx_shape_t> out;
if(compute_shape_f == nullptr)
throw std::runtime_error("compute_shape function is missing.");
std::remove_pointer_t<migraphx_shape_t> out;
std::array<char, 256> exception_msg;
exception_msg.front() = '\0';
auto api_error_result = compute_shape_f(&out,
......@@ -655,6 +687,49 @@ struct migraphx_experimental_custom_op
}
return (&out)->object;
}
migraphx_experimental_custom_op_output_alias output_alias_f = nullptr;
std::vector<size_t> output_alias(std::vector<migraphx::shape> inputs) const
{
if(output_alias_f == nullptr)
throw std::runtime_error("output_alias function is missing.");
std::array<size_t, 1024> out;
std::remove_pointer_t<size_t*> out_size = 1024;
std::array<char, 256> exception_msg;
exception_msg.front() = '\0';
auto api_error_result = output_alias_f(out.data(),
&out_size,
object_ptr.data,
exception_msg.data(),
exception_msg.size(),
object_cast<migraphx_shapes_t>(&(inputs)));
if(api_error_result != migraphx_status_success)
{
const std::string exception_str(exception_msg.data());
throw std::runtime_error("Error in output_alias of: " +
std::string(object_ptr.obj_typename) + ": " + exception_str);
}
return {out.begin(), out.begin() + out_size}; // cppcheck-suppress returnDanglingLifetime;
}
migraphx_experimental_custom_op_runs_on_offload_target runs_on_offload_target_f = nullptr;
bool runs_on_offload_target() const
{
if(runs_on_offload_target_f == nullptr)
throw std::runtime_error("runs_on_offload_target function is missing.");
std::remove_pointer_t<bool*> out;
std::array<char, 256> exception_msg;
exception_msg.front() = '\0';
auto api_error_result = runs_on_offload_target_f(
&out, object_ptr.data, exception_msg.data(), exception_msg.size());
if(api_error_result != migraphx_status_success)
{
const std::string exception_str(exception_msg.data());
throw std::runtime_error("Error in runs_on_offload_target of: " +
std::string(object_ptr.obj_typename) + ": " + exception_str);
}
return out;
}
};
extern "C" migraphx_status migraphx_shape_destroy(migraphx_shape_t shape)
......@@ -758,6 +833,16 @@ extern "C" migraphx_status migraphx_shape_type(migraphx_shape_datatype_t* out,
return api_error_result;
}
extern "C" migraphx_status migraphx_shape_elements(size_t* out, const_migraphx_shape_t shape)
{
auto api_error_result = migraphx::try_([&] {
if(shape == nullptr)
MIGRAPHX_THROW(migraphx_status_bad_param, "Bad parameter shape: Null pointer");
*out = (shape->object).elements();
});
return api_error_result;
}
extern "C" migraphx_status migraphx_shape_bytes(size_t* out, const_migraphx_shape_t shape)
{
auto api_error_result = migraphx::try_([&] {
......@@ -791,6 +876,16 @@ extern "C" migraphx_status migraphx_shape_standard(bool* out, const_migraphx_sha
return api_error_result;
}
extern "C" migraphx_status migraphx_shape_index(size_t* out, const_migraphx_shape_t shape, size_t i)
{
auto api_error_result = migraphx::try_([&] {
if(shape == nullptr)
MIGRAPHX_THROW(migraphx_status_bad_param, "Bad parameter shape: Null pointer");
*out = (shape->object).index((i));
});
return api_error_result;
}
extern "C" migraphx_status migraphx_argument_destroy(migraphx_argument_t argument)
{
auto api_error_result = migraphx::try_([&] { destroy((argument)); });
......@@ -1348,6 +1443,23 @@ extern "C" migraphx_status migraphx_program_run(migraphx_arguments_t* out,
return api_error_result;
}
extern "C" migraphx_status migraphx_program_run_async(migraphx_arguments_t* out,
migraphx_program_t program,
migraphx_program_parameters_t params,
void* s,
const char* name)
{
auto api_error_result = migraphx::try_([&] {
if(program == nullptr)
MIGRAPHX_THROW(migraphx_status_bad_param, "Bad parameter program: Null pointer");
if(params == nullptr)
MIGRAPHX_THROW(migraphx_status_bad_param, "Bad parameter params: Null pointer");
*out = allocate<migraphx_arguments_t>(
migraphx::run_async((program->object), (params->object), (s), (name)));
});
return api_error_result;
}
extern "C" migraphx_status
migraphx_program_equal(bool* out, const_migraphx_program_t program, const_migraphx_program_t x)
{
......@@ -1879,6 +1991,22 @@ extern "C" migraphx_status migraphx_experimental_custom_op_set_compute_shape(
return api_error_result;
}
extern "C" migraphx_status
migraphx_experimental_custom_op_set_output_alias(migraphx_experimental_custom_op_t obj,
migraphx_experimental_custom_op_output_alias input)
{
auto api_error_result = migraphx::try_([&] { (obj)->output_alias_f = (input); });
return api_error_result;
}
extern "C" migraphx_status migraphx_experimental_custom_op_set_runs_on_offload_target(
migraphx_experimental_custom_op_t obj,
migraphx_experimental_custom_op_runs_on_offload_target input)
{
auto api_error_result = migraphx::try_([&] { (obj)->runs_on_offload_target_f = (input); });
return api_error_result;
}
extern "C" migraphx_status
migraphx_experimental_custom_op_register(migraphx_experimental_custom_op_t experimental_custom_op)
{
......
src/api/include/migraphx/migraphx.h
View file @ 8b25fd3e
......@@ -26,7 +26,6 @@
#include <stdlib.h>
#include <stdbool.h>
// Add new types here
// clang-format off
#define MIGRAPHX_SHAPE_VISIT_TYPES(m) \
......@@ -144,6 +143,16 @@ typedef migraphx_status (*migraphx_experimental_custom_op_compute_shape)(migraph
size_t exception_msg_size,
migraphx_shapes_t inputs);
typedef migraphx_status (*migraphx_experimental_custom_op_output_alias)(size_t* out,
size_t* out_size,
void* obj,
char* exception_msg,
size_t exception_msg_size,
migraphx_shapes_t inputs);
typedef migraphx_status (*migraphx_experimental_custom_op_runs_on_offload_target)(
bool* out, void* obj, char* exception_msg, size_t exception_msg_size);
typedef migraphx_status (*migraphx_experimental_custom_op_copy)(void** out, void* input);
typedef migraphx_status (*migraphx_experimental_custom_op_delete)(void* input);
......@@ -175,6 +184,8 @@ migraphx_shape_strides(const size_t** out, size_t* out_size, const_migraphx_shap
migraphx_status migraphx_shape_type(migraphx_shape_datatype_t* out, const_migraphx_shape_t shape);
migraphx_status migraphx_shape_elements(size_t* out, const_migraphx_shape_t shape);
migraphx_status migraphx_shape_bytes(size_t* out, const_migraphx_shape_t shape);
migraphx_status
......@@ -182,6 +193,8 @@ migraphx_shape_equal(bool* out, const_migraphx_shape_t shape, const_migraphx_sha
migraphx_status migraphx_shape_standard(bool* out, const_migraphx_shape_t shape);
migraphx_status migraphx_shape_index(size_t* out, const_migraphx_shape_t shape, size_t i);
migraphx_status migraphx_argument_destroy(migraphx_argument_t argument);
migraphx_status migraphx_argument_assign_to(migraphx_argument_t output,
......@@ -344,6 +357,12 @@ migraphx_status migraphx_program_run(migraphx_arguments_t* out,
migraphx_program_t program,
migraphx_program_parameters_t params);
migraphx_status migraphx_program_run_async(migraphx_arguments_t* out,
migraphx_program_t program,
migraphx_program_parameters_t params,
void* s,
const char* name);
migraphx_status
migraphx_program_equal(bool* out, const_migraphx_program_t program, const_migraphx_program_t x);
......@@ -502,6 +521,13 @@ migraphx_experimental_custom_op_set_compute(migraphx_experimental_custom_op_t ob
migraphx_status migraphx_experimental_custom_op_set_compute_shape(
migraphx_experimental_custom_op_t obj, migraphx_experimental_custom_op_compute_shape input);
migraphx_status migraphx_experimental_custom_op_set_output_alias(
migraphx_experimental_custom_op_t obj, migraphx_experimental_custom_op_output_alias input);
migraphx_status migraphx_experimental_custom_op_set_runs_on_offload_target(
migraphx_experimental_custom_op_t obj,
migraphx_experimental_custom_op_runs_on_offload_target input);
migraphx_status
migraphx_experimental_custom_op_register(migraphx_experimental_custom_op_t experimental_custom_op);
......
src/api/include/migraphx/migraphx.hpp
View file @ 8b25fd3e
......@@ -25,10 +25,12 @@
#define MIGRAPHX_GUARD_API_RTGLIB_MIGRAPHX_HPP
#include "migraphx.h"
#include <algorithm>
#include <cstring>
#include <initializer_list>
#include <migraphx/migraphx.h>
#include <memory>
#include <numeric>
#include <exception>
#include <vector>
#include <cassert>
......@@ -340,6 +342,11 @@ struct handle_base : handle_lookup<Derived, std::remove_cv_t<T>>
this->set_handle(p, std::move(lifetime)); \
}
template <size_t N>
struct out_params
{
};
template <class Base>
struct interface_base : Base
{
......@@ -391,7 +398,22 @@ struct interface_base : Base
}
template <class T, class Setter, class F>
void set_fp(Setter setter, F pf)
void set_fp(Setter setter, F pf, out_params<2>)
{
static F f = pf;
(void)f; // avoid warning on gcc
call(setter,
this->get_handle_ptr(),
[](auto out1, auto out2, void* obj, char* ex_msg, size_t ex_msg_size, auto... xs)
-> migraphx_status {
return try_([&] { call_cast_arg<T>(rank<2>{}, f, out1, out2, obj, xs...); },
ex_msg,
ex_msg_size);
});
}
template <class T, class Setter, class F>
void set_fp(Setter setter, F pf, out_params<1>)
{
static F f = pf;
(void)f; // avoid warning on gcc
......@@ -405,13 +427,29 @@ struct interface_base : Base
}
template <class T, class Setter, class F>
void set_auto_fp(Setter setter, F f)
void set_fp(Setter setter, F pf, out_params<0>)
{
return set_fp<T>(setter, [=](T& obj, auto out, auto... xs) {
auto_invoke(f, out, obj, auto_convert_param(rank<2>{}, xs)...);
static F f = pf;
(void)f; // avoid warning on gcc
call(setter,
this->get_handle_ptr(),
[](void* obj, char* ex_msg, size_t ex_msg_size, auto... xs) -> migraphx_status {
return try_(
[&] { call_cast_arg<T>(rank<0>{}, f, obj, xs...); }, ex_msg, ex_msg_size);
});
}
template <class T, class Setter, class F, class Out>
void set_auto_fp(Setter setter, F f, Out nums)
{
return set_fp<T>(
setter,
[=](T& obj, auto out1, auto out2, auto... xs) {
auto_invoke(f, out1, out2, obj, auto_convert_param(rank<2>{}, xs)...);
},
nums);
}
struct no_out_arg
{
};
......@@ -419,7 +457,7 @@ struct interface_base : Base
template <class T, class F, class X, class... Xs, class = std::enable_if_t<std::is_void<X>{}>>
static void call_cast_arg(rank<0>, F f, X* obj, Xs... xs)
{
f(reinterpret_cast<T*>(obj), no_out_arg{}, xs...);
f(reinterpret_cast<T*>(obj), no_out_arg{}, no_out_arg{}, xs...);
}
template <class T,
......@@ -430,17 +468,35 @@ struct interface_base : Base
class = std::enable_if_t<std::is_void<X>{}>>
static void call_cast_arg(rank<1>, F f, R result, X* obj, Xs... xs)
{
f(*reinterpret_cast<T*>(obj), result, xs...);
f(*reinterpret_cast<T*>(obj), result, no_out_arg{}, xs...);
}
template <class T,
class F,
class R1,
class R2,
class X,
class... Xs,
class = std::enable_if_t<std::is_void<X>{}>>
static void call_cast_arg(rank<2>, F f, R1 result1, R2 result2, X* obj, Xs... xs)
{
f(*reinterpret_cast<T*>(obj), result1, result2, xs...);
}
template <class F, class T1, class T2, class... Ts>
void auto_invoke(F f, T1* out1, T2* out2, Ts&&... xs)
{
auto_assign(rank<2>{}, out1, out2, f(std::forward<Ts>(xs)...));
}
template <class F, class T, class... Ts>
void auto_invoke(F f, T* out, Ts&&... xs)
void auto_invoke(F f, T* out, no_out_arg, Ts&&... xs)
{
auto_assign(rank<2>{}, out, f(std::forward<Ts>(xs)...));
auto_assign(rank<1>{}, out, f(std::forward<Ts>(xs)...));
}
template <class F, class T, class... Ts>
void auto_invoke(F f, no_out_arg, Ts&&... xs)
void auto_invoke(F f, no_out_arg, no_out_arg, Ts&&... xs)
{
f(std::forward<Ts>(xs)...);
}
......@@ -469,7 +525,7 @@ struct interface_base : Base
template <class T, class U>
void auto_assign(rank<0>, T* out, U x)
{
return *out = x;
*out = x;
}
template <class T, class U>
......@@ -477,12 +533,21 @@ struct interface_base : Base
{
x.assign_to_handle(out);
}
template <class T1, class T2, class U, class = std::enable_if_t<std::is_same<T2, size_t>{}>>
auto auto_assign(rank<2>, T1* out_ptr, T2* out_size, U x)
{
*out_size = std::min(*out_size, x.size());
std::copy_n(x.begin(), *out_size, out_ptr);
}
};
// NOLINTNEXTLINE
#define MIGRAPHX_INTERFACE_LIFT(T, prefix, name) \
this->set_auto_fp<T>(&migraphx_##prefix##_set_##name, \
[](T& x, auto... xs) { return x.name(xs...); })
#define MIGRAPHX_INTERFACE_LIFT(n_out, T, prefix, name) \
this->set_auto_fp<T>( \
&migraphx_##prefix##_set_##name, \
[](T& x, auto... xs) { return x.name(xs...); }, \
out_params<n_out>{})
template <class Base, class T>
using require_interface =
......@@ -567,6 +632,13 @@ struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
return pout;
}
size_t elements() const
{
size_t pout;
call(&migraphx_shape_elements, &pout, this->get_handle_ptr());
return pout;
}
size_t bytes() const
{
size_t pout;
......@@ -581,6 +653,14 @@ struct shape : MIGRAPHX_CONST_HANDLE_BASE(shape)
return result;
}
// map element index to space index
size_t index(size_t i) const
{
size_t result;
call(&migraphx_shape_index, &result, this->get_handle_ptr(), i);
return result;
}
friend bool operator==(const shape& px, const shape& py)
{
bool pout;
......@@ -628,9 +708,15 @@ struct argument : MIGRAPHX_CONST_HANDLE_BASE(argument)
template <typename T>
std::vector<T> as_vector() const
{
size_t vector_len = this->get_shape().bytes() / sizeof(T);
auto ss = this->get_shape();
auto num_elements = ss.elements();
std::vector<T> res(num_elements);
T* buffer_ptr = reinterpret_cast<T*>(this->data());
return {buffer_ptr, buffer_ptr + vector_len};
for(size_t i = 0; i < num_elements; i++)
{
res[i] = buffer_ptr[ss.index(i)];
}
return res;
}
/// Generate an argument using random data
......@@ -979,6 +1065,20 @@ struct program : MIGRAPHX_HANDLE_BASE(program)
return arguments(pout, own{});
}
template <class Stream>
/// Overloaded to allow for execution_environment input
arguments run_async(const program_parameters& pparams, Stream* s) const
{
migraphx_arguments_t pout;
call(&migraphx_program_run_async,
&pout,
this->get_handle_ptr(),
pparams.get_handle_ptr(),
s,
get_type_name<Stream>().c_str());
return arguments(pout, own{});
}
void print() const { call(&migraphx_program_print, this->get_handle_ptr()); }
program sort()
......@@ -1255,6 +1355,9 @@ struct experimental_custom_op_base
virtual std::string name() const = 0;
virtual argument compute(context ctx, shape output, arguments inputs) const = 0;
virtual shape compute_shape(shapes inputs) const = 0;
virtual std::vector<size_t> output_alias(shapes) const { return {}; }
// TODO: Return target string instead of bool
virtual bool runs_on_offload_target() const = 0;
virtual ~experimental_custom_op_base() = default;
};
......@@ -1267,8 +1370,10 @@ struct experimental_custom_op : interface_base<MIGRAPHX_HANDLE_BASE(experimental
obj,
get_type_name(obj).c_str(),
obj.name().c_str());
MIGRAPHX_INTERFACE_LIFT(T, experimental_custom_op, compute_shape);
MIGRAPHX_INTERFACE_LIFT(T, experimental_custom_op, compute);
MIGRAPHX_INTERFACE_LIFT(1, T, experimental_custom_op, compute_shape);
MIGRAPHX_INTERFACE_LIFT(1, T, experimental_custom_op, compute);
MIGRAPHX_INTERFACE_LIFT(2, T, experimental_custom_op, output_alias);
MIGRAPHX_INTERFACE_LIFT(1, T, experimental_custom_op, runs_on_offload_target);
}
void register_op() { call(&migraphx_experimental_custom_op_register, this->get_handle_ptr()); }
......
src/api/migraphx.py
View file @ 8b25fd3e
......@@ -115,6 +115,7 @@ def shape(h):
const=True)
h.method('strides', returns='const std::vector<size_t>&', 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('equal',
api.params(x='const migraphx::shape&'),
......@@ -122,6 +123,7 @@ def shape(h):
returns='bool',
const=True)
h.method('standard', returns='bool', const=True)
h.method('index', api.params(i='size_t'), returns='size_t', const=True)
@auto_handle()
......@@ -274,6 +276,13 @@ def program(h):
params='std::unordered_map<std::string, migraphx::argument>'),
invoke='migraphx::run($@)',
returns='std::vector<migraphx::argument>')
h.method('run_async',
api.params(
params='std::unordered_map<std::string, migraphx::argument>',
s='void*',
name='const char *'),
invoke='migraphx::run_async($@)',
returns='std::vector<migraphx::argument>')
h.method('equal',
api.params(x='const migraphx::program&'),
invoke='migraphx::equal($@)',
......@@ -450,4 +459,8 @@ def experimental_custom_op(h):
h.virtual('compute_shape',
api.params(inputs='std::vector<migraphx::shape>'),
returns='migraphx::shape')
h.virtual('output_alias',
api.params(inputs='std::vector<migraphx::shape>'),
returns='std::vector<size_t>')
h.virtual('runs_on_offload_target', returns='bool')
h.method('register', invoke='migraphx::register_custom_op($@)')
src/include/migraphx/context.hpp
View file @ 8b25fd3e
......@@ -66,6 +66,15 @@ any_ptr get_queue_context(T&)
{
return {};
}
template <class T>
void wait_for_context(T&, any_ptr)
{
}
template <class T>
void finish_on_context(T&, any_ptr)
{
}
#ifdef TYPE_ERASED_DECLARATION
......@@ -78,6 +87,10 @@ struct context
void from_value(const value& v);
// (optional)
any_ptr get_queue();
// (optional)
void wait_for(any_ptr queue);
// (optional)
void finish_on(any_ptr queue);
//
void finish() const;
};
......@@ -165,6 +178,18 @@ struct context
return (*this).private_detail_te_get_handle().get_queue();
}
void wait_for(any_ptr queue)
{
assert((*this).private_detail_te_handle_mem_var);
(*this).private_detail_te_get_handle().wait_for(queue);
}
void finish_on(any_ptr queue)
{
assert((*this).private_detail_te_handle_mem_var);
(*this).private_detail_te_get_handle().finish_on(queue);
}
void finish() const
{
assert((*this).private_detail_te_handle_mem_var);
......@@ -187,6 +212,8 @@ struct context
virtual value to_value() const = 0;
virtual void from_value(const value& v) = 0;
virtual any_ptr get_queue() = 0;
virtual void wait_for(any_ptr queue) = 0;
virtual void finish_on(any_ptr queue) = 0;
virtual void finish() const = 0;
};
......@@ -231,6 +258,33 @@ struct context
return get_queue_context(private_detail_te_self);
}
template <class T>
static auto private_detail_te_default_wait_for(char, T&& private_detail_te_self, any_ptr queue)
-> decltype(private_detail_te_self.wait_for(queue))
{
private_detail_te_self.wait_for(queue);
}
template <class T>
static void private_detail_te_default_wait_for(float, T&& private_detail_te_self, any_ptr queue)
{
wait_for_context(private_detail_te_self, queue);
}
template <class T>
static auto private_detail_te_default_finish_on(char, T&& private_detail_te_self, any_ptr queue)
-> decltype(private_detail_te_self.finish_on(queue))
{
private_detail_te_self.finish_on(queue);
}
template <class T>
static void
private_detail_te_default_finish_on(float, T&& private_detail_te_self, any_ptr queue)
{
finish_on_context(private_detail_te_self, queue);
}
template <typename PrivateDetailTypeErasedT>
struct private_detail_te_handle_type : private_detail_te_handle_base_type
{
......@@ -248,7 +302,7 @@ struct context
PrivateDetailTypeErasedT value,
typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
int>::type* = nullptr) noexcept
: private_detail_te_value(std::move(value))
: private_detail_te_value(value)
{
}
......@@ -277,6 +331,18 @@ struct context
return private_detail_te_default_get_queue(char(0), private_detail_te_value);
}
void wait_for(any_ptr queue) override
{
private_detail_te_default_wait_for(char(0), private_detail_te_value, queue);
}
void finish_on(any_ptr queue) override
{
private_detail_te_default_finish_on(char(0), private_detail_te_value, queue);
}
void finish() const override { private_detail_te_value.finish(); }
PrivateDetailTypeErasedT private_detail_te_value;
......
src/include/migraphx/execution_environment.hpp 0 → 100644
View file @ 8b25fd3e
/*
* 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_MIGRAPHLIB_EXECUTION_ENV_HPP
#define MIGRAPHX_GUARD_MIGRAPHLIB_EXECUTION_ENV_HPP
#include <migraphx/any_ptr.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
struct execution_environment
{
any_ptr queue = any_ptr{};
bool async = false;
};
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
#endif /* MIGRAPHX_GUARD_MIGRAPHLIB_EXECUTION_ENV_HPP */
src/include/migraphx/program.hpp
View file @ 8b25fd3e
......@@ -37,6 +37,7 @@
#include <migraphx/assignment_options.hpp>
#include <migraphx/env.hpp>
#include <migraphx/config.hpp>
#include <migraphx/execution_environment.hpp>
#include <algorithm>
#include <iostream>
......@@ -76,8 +77,8 @@ struct program
std::unordered_map<std::string, shape> get_parameter_shapes() const;
std::vector<argument> eval(parameter_map params) const;
std::vector<argument> eval(parameter_map params,
execution_environment exec_env = execution_environment{}) const;
std::size_t size() const;
std::vector<shape> get_output_shapes() const;
......
src/program.cpp
View file @ 8b25fd3e
......@@ -398,7 +398,7 @@ std::vector<argument> generic_eval(const program& p,
return generic_eval(mm, ctx, params, {}, make_trace);
}
std::vector<argument> program::eval(parameter_map params) const
std::vector<argument> program::eval(parameter_map params, execution_environment exec_env) const
{
auto& ctx = this->impl->ctx;
#ifndef NDEBUG
......@@ -423,6 +423,12 @@ std::vector<argument> program::eval(parameter_map params) const
#endif
auto trace_level = value_of(MIGRAPHX_TRACE_EVAL{});
std::vector<argument> ret;
if(exec_env.async)
{
ctx.wait_for(exec_env.queue);
}
if(trace_level > 0)
{
......@@ -434,7 +440,7 @@ std::vector<argument> program::eval(parameter_map params) const
ins_out[x] = ss.str();
});
return generic_eval(*this,
ret = generic_eval(*this,
ctx,
std::move(params),
with_check_context([&](auto& ins, auto f, auto&& check_context) {
......@@ -470,13 +476,20 @@ std::vector<argument> program::eval(parameter_map params) const
}
else
{
return generic_eval(*this,
ret = generic_eval(*this,
ctx,
std::move(params),
with_check_context([&](auto&, auto f, auto&& check_context) {
return check_context(f);
}));
}
if(exec_env.async)
{
ctx.finish_on(exec_env.queue);
}
return ret;
}
const int program_file_version = 5;
......
src/py/migraphx_py.cpp
View file @ 8b25fd3e
......@@ -355,6 +355,23 @@ MIGRAPHX_PYBIND11_MODULE(migraphx, m)
}
return p.eval(pm);
})
.def("run_async",
[](migraphx::program& p,
py::dict params,
std::uintptr_t stream,
std::string stream_name) {
migraphx::parameter_map pm;
for(auto x : params)
{
std::string key = x.first.cast<std::string>();
py::buffer b = x.second.cast<py::buffer>();
py::buffer_info info = b.request();
pm[key] = migraphx::argument(to_shape(info), info.ptr);
}
migraphx::execution_environment exec_env{
migraphx::any_ptr(reinterpret_cast<void*>(stream), stream_name), true};
return p.eval(pm, exec_env);
})
.def("sort", &migraphx::program::sort)
.def("print", [](const migraphx::program& p) { std::cout << p << std::endl; })
.def("__eq__", std::equal_to<migraphx::program>{})
......
src/simplify_algebra.cpp
View file @ 8b25fd3e
......@@ -933,6 +933,73 @@ struct find_div_const
}
};
struct find_unit_ops
{
auto matcher() const
{
auto mul_1 = match::name("mul")(
match::either_arg(0, 1)(match::has_value(1.0f), match::any().bind("x")));
auto div_1 =
match::name("div")(match::args(match::any().bind("x"), match::has_value(1.0f)));
auto add_0 = match::name("add")(
match::either_arg(0, 1)(match::has_value(0.0f, 1e-12), match::any().bind("x")));
auto sub_0 =
match::name("sub")(match::args(match::any().bind("x"), match::has_value(0.0f)));
return match::any_of(mul_1, div_1, add_0, sub_0);
}
void apply(module& m, const match::matcher_result& r) const
{
auto ins = r.result;
auto c_in = r.instructions["x"];
m.replace_instruction(ins, c_in);
}
};
struct find_neg_unit_ops
{
auto matcher() const
{
auto mul_neg_1 = match::name("mul")(
match::either_arg(0, 1)(match::has_value(-1.0f), match::any().bind("x")));
auto div_neg_1 =
match::name("div")(match::args(match::any().bind("x"), match::has_value(-1.0f)));
auto sub_0 =
match::name("sub")(match::args(match::has_value(0.0f), match::any().bind("x")));
return match::any_of(mul_neg_1, div_neg_1, sub_0);
}
void apply(module& m, const match::matcher_result& r) const
{
auto ins = r.result;
auto c_in = r.instructions["x"];
auto neg = m.add_instruction(make_op("neg"), c_in);
m.replace_instruction(ins, neg);
}
};
struct find_zero_ops
{
auto matcher() const
{
auto mul_zero = match::name("mul")(
match::either_arg(0, 1)(match::has_value(0.0f).bind("x"), match::any()));
auto div_zero =
match::name("div")(match::args(match::has_value(0.0f).bind("x"), match::any()));
return match::any_of(mul_zero, div_zero);
}
void apply(module& m, const match::matcher_result& r) const
{
auto ins = r.result;
auto zero_ins = r.instructions["x"];
m.replace_instruction(ins, zero_ins);
}
};
struct find_sub_const
{
auto matcher() const
......@@ -1149,6 +1216,9 @@ void simplify_algebra::apply(module& m) const
find_mul_conv{},
find_mul_slice_conv{},
find_mul_add{},
find_unit_ops{},
find_neg_unit_ops{},
find_zero_ops{},
find_dot_add{},
find_div_const{},
find_sub_const{},
......
src/targets/gpu/include/migraphx/gpu/context.hpp
View file @ 8b25fd3e
......@@ -197,7 +197,9 @@ struct hip_device
struct context
{
context(std::size_t device_id = 0, std::size_t n = value_of(MIGRAPHX_NSTREAMS{}, 1))
: current_device(std::make_shared<hip_device>(device_id, n))
: current_device(std::make_shared<hip_device>(device_id, n)),
begin_event(create_event()),
finish_event(create_event())
{
}
......@@ -274,6 +276,24 @@ struct context
this->current_device = std::make_shared<hip_device>(0, n_streams);
}
void wait_for(any_ptr queue)
{
auto status = hipEventRecord(begin_event.get(), queue.get<hipStream_t>());
if(status != hipSuccess)
MIGRAPHX_THROW("failed to record " + hip_error(status));
get_stream().wait(begin_event.get());
}
void finish_on(any_ptr queue)
{
get_stream().record(finish_event.get());
auto status = hipStreamWaitEvent(queue.get<hipStream_t>(), finish_event.get(), 0);
if(status != hipSuccess)
MIGRAPHX_THROW("Failed to wait on event " + hip_error(status));
}
any_ptr get_queue() { return get_stream().get(); }
void enable_perf_measurement(bool b = true)
......@@ -317,8 +337,12 @@ struct context
std::shared_ptr<hip_device> current_device;
std::vector<shared<hip_event_ptr>> events;
bool measure_perf = false;
// for event perf timing
shared<hip_event_ptr> start_event = nullptr;
shared<hip_event_ptr> stop_event = nullptr;
// for stream syncronization
shared<hip_event_ptr> begin_event = nullptr;
shared<hip_event_ptr> finish_event = nullptr;
};
inline void migraphx_to_value(value& v, const context& ctx) { v = ctx.to_value(); }
......
src/targets/gpu/jit/softmax.cpp
View file @ 8b25fd3e
......@@ -32,6 +32,8 @@ namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_USE_FAST_SOFTMAX)
using namespace migraphx::gpu::gen; // NOLINT
static const char* const softmax_kernel = R"__migraphx__(
......@@ -81,6 +83,9 @@ struct softmax_compiler : compiler<softmax_compiler>
options.inputs = inputs;
options.kernel_name = "softmax_kernel";
if(enabled(MIGRAPHX_USE_FAST_SOFTMAX{}))
options.params = "-DMIGRAPHX_USE_FAST_SOFTMAX";
auto src = interpolate_string(
softmax_kernel,
{{"transformers", make_transformer_args(vec)}, {"axis", to_string(axis)}});
......
src/targets/gpu/kernels/include/migraphx/kernels/reduce.hpp
View file @ 8b25fd3e
......@@ -197,11 +197,11 @@ struct block
struct reducer
{
index idx;
Slicer slicer;
Slicer slice;
template <class Op, class T, class Read>
__device__ auto reduce(Op op, T init, Read read) const
{
return sliced(slicer, [=](auto x, auto... xs) {
return sliced(slice, [=](auto x, auto... xs) {
return block_reduce(idx, op, init, x.get_shape().elements(), [&](auto j) {
return vec_reduce(read(x[j], xs[j]...), op);
});
......@@ -218,7 +218,7 @@ struct block
template <class F>
__device__ auto inner(F f) const
{
return sliced(slicer, [=](auto x, auto... xs) {
return sliced(slice, [=](auto x, auto... xs) {
idx.local_stride(x.get_shape().elements(), [&](auto j) { f(x[j], xs[j]...); });
});
}
......@@ -226,7 +226,7 @@ struct block
template <class Input>
constexpr auto elements() const
{
using reduce_type = decltype(slicer(Input{}));
using reduce_type = decltype(slice(Input{}));
using value_type = typename Input::type;
constexpr auto relements = get_shape_c<reduce_type>{}.elements();
if constexpr(vec_size<value_type>() > 1)
......@@ -260,11 +260,11 @@ struct lane
struct reducer
{
index idx;
Slicer slicer;
Slicer slice;
template <class Op, class T, class Read>
__device__ auto reduce(Op op, T init, Read read) const
{
return sliced(slicer, [=](auto x, auto... xs) {
return sliced(slice, [=](auto x, auto... xs) {
using type = typename decltype(x)::type;
type r = init;
for(index_int j = 0; j < x.get_shape().elements(); j++)
......@@ -284,7 +284,7 @@ struct lane
template <class F>
__device__ auto inner(F f) const
{
return sliced(slicer, [=](auto x, auto... xs) {
return sliced(slice, [=](auto x, auto... xs) {
for(index_int j = 0; j < x.get_shape().elements(); j++)
{
f(x[j], xs[j]...);
......@@ -295,7 +295,7 @@ struct lane
template <class Input>
constexpr auto elements() const
{
using reduce_type = decltype(slicer(Input{}));
using reduce_type = decltype(slice(Input{}));
return get_shape_c<reduce_type>{}.elements();
}
};
......
src/targets/gpu/kernels/include/migraphx/kernels/softmax.hpp
View file @ 8b25fd3e
......@@ -33,11 +33,15 @@ template <index_int Axis, class Input, class Output>
__device__ void softmax(Input input, Output output)
{
reduce::block::run<reduce::with_axis<Input, Axis>>([&](auto, auto r) {
auto batch_max = r.reduce(op::max{}, lowest{}, op::id{})(input);
auto batch_sum =
r.reduce(op::sum{}, 0, [&](auto x) { return migraphx::exp(x - batch_max); })(input);
r.inner([&](auto& y, auto x) { y = migraphx::exp(x - batch_max) / batch_sum; })(output,
input);
#ifdef MIGRAPHX_USE_FAST_SOFTMAX
const auto c = vec_at(r.slice(input)[0], 0);
#else
const auto c = r.reduce(op::max{}, lowest{}, op::id{})(input);
#endif
auto batch_sum = r.reduce(op::sum{}, 0, [&](auto x) {
return migraphx::convert<float>(migraphx::exp(x - c));
})(input);
r.inner([&](auto& y, auto x) { y = migraphx::exp(x - c) / batch_sum; })(output, input);
});
}
......
src/targets/gpu/lowering.cpp
View file @ 8b25fd3e
......@@ -26,6 +26,8 @@
#include <migraphx/manage_ptr.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/instruction_ref.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/op/convolution.hpp>
#include <migraphx/op/deconvolution.hpp>
......@@ -172,6 +174,7 @@ struct miopen_apply
for(auto it = mod->begin(); it != mod->end(); it++)
{
auto s = it->get_shape();
auto attrs = it->get_operator().attributes();
if(apply_map.count(it->name()) > 0)
{
check_shape(s, apply_map.at(it->name())(it));
......@@ -180,11 +183,37 @@ struct miopen_apply
{
check_shape(s, insert_precompile_op(it));
}
else if(attrs.contains("target"))
{
check_shape(s, insert_custom_op(it, attrs));
}
}
copy_params();
}
instruction_ref insert_custom_op(instruction_ref ins, const value& attrs) const
{
const auto& custom_op = ins->get_operator();
if(attrs.at("target") == "cpu")
{
auto s = ins->get_shape();
std::vector<instruction_ref> cpu_inputs;
auto inputs = ins->inputs();
auto output = inputs.back();
std::transform(
inputs.begin(), inputs.end(), std::back_inserter(cpu_inputs), [&](auto in) {
return mod->insert_instruction(ins, make_op("hip::copy_from_gpu"), in);
});
cpu_inputs.front() =
mod->insert_instruction(ins, make_op("hip::sync_stream"), cpu_inputs);
auto cpu_out = mod->insert_instruction(ins, custom_op, cpu_inputs);
auto gpu_out =
mod->insert_instruction(ins, make_op("hip::copy_to_gpu"), cpu_out, output);
return mod->replace_instruction(ins, gpu_out);
}
return ins;
}
instruction_ref insert_precompile_op(instruction_ref ins) const
{
auto output = insert_allocation(ins, ins->get_shape());
......
test/api/test_custom_op.cpp
View file @ 8b25fd3e
......@@ -43,6 +43,8 @@ struct sigmoid_custom_op final : migraphx::experimental_custom_op_base
return inputs[1];
}
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::shape compute_shape(migraphx::shapes inputs) const override
{
if(inputs.size() != 2)
......@@ -111,4 +113,45 @@ TEST_CASE(run_sigmoid_with_incorrect_shape)
"Error in compute_shape of: sigmoid_custom_op: op must have two inputs"));
}
struct identity_custom_op final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "identity_custom_op"; }
virtual migraphx::argument
compute(migraphx::context, migraphx::shape, migraphx::arguments inputs) const override
{
return inputs[0];
}
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::shape compute_shape(migraphx::shapes inputs) const override
{
if(inputs.size() != 1)
{
throw std::runtime_error("Identity op must have only one input");
}
return inputs.back();
}
virtual std::vector<size_t> output_alias(migraphx::shapes) const override { return {0, 1}; }
};
TEST_CASE(run_custom_op_with_invalid_output_alias)
{
identity_custom_op i_op;
migraphx::register_experimental_custom_op(i_op);
auto op = migraphx::operation("identity_custom_op");
EXPECT(op.name() == "identity_custom_op");
migraphx::program p;
migraphx::shape s{migraphx_shape_float_type, {12}};
migraphx::module m = p.get_main_module();
auto x = m.add_parameter("x", s);
auto i_ins = m.add_instruction(migraphx::operation("identity_custom_op"), {x});
migraphx_test_private_disable_exception_catch(true);
EXPECT(test::throws<std::exception>(
[&] { p.compile(migraphx::target("ref")); },
"Currently, CustomOps in MIGraphX only supports one output_alias"));
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
test/api/test_custom_op_gpu.cpp
View file @ 8b25fd3e
......@@ -24,40 +24,89 @@
#include <hip/hip_runtime_api.h>
#include <migraphx/migraphx.h>
#include <migraphx/migraphx.hpp>
#include <numeric>
#include <stdexcept>
#include "test.hpp"
#define MIGRAPHX_HIP_ASSERT(x) (EXPECT(x == hipSuccess))
struct simple_custom_op final : migraphx::experimental_custom_op_base
struct half_copy_host final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "simple_custom_op"; }
virtual std::string name() const override { return "half_copy_host"; }
virtual bool runs_on_offload_target() const override { return false; }
virtual migraphx::argument
compute(migraphx::context ctx, migraphx::shape, migraphx::arguments inputs) const override
{
// sets first half size_bytes of the input 0, and rest of the half bytes are copied.
int* h_output = nullptr;
auto* d_output = reinterpret_cast<int*>(inputs[0].data());
// This custom op simply sets first half size_bytes of the input to 0, and rest of the half
// bytes are copied. for this custom_op, it does its computation on the host. Therefore,
// `runs_on_offload_target()` is set to false. MIGraphX would inject necessary buffer copies
// to and from GPU to Host based on `runs_on_offload_targe()` flag for input buffers as well
// as the output buffers
auto* input_buffer_ptr = inputs[0].data();
auto* output_buffer_ptr = inputs[1].data();
auto input_bytes = inputs[0].get_shape().bytes();
auto* output_ptr = inputs[1].data();
auto copy_bytes = input_bytes / 2;
MIGRAPHX_HIP_ASSERT(hipSetDevice(0));
MIGRAPHX_HIP_ASSERT(hipHostMalloc(&h_output, input_bytes));
MIGRAPHX_HIP_ASSERT(hipMemcpyAsync(
h_output, d_output, input_bytes, hipMemcpyDeviceToHost, ctx.get_queue<hipStream_t>()));
MIGRAPHX_HIP_ASSERT(hipMemcpyAsync(output_buffer_ptr,
input_buffer_ptr,
input_bytes,
hipMemcpyHostToHost,
ctx.get_queue<hipStream_t>()));
MIGRAPHX_HIP_ASSERT(hipDeviceSynchronize());
MIGRAPHX_HIP_ASSERT(hipMemset(h_output, 0, copy_bytes));
MIGRAPHX_HIP_ASSERT(hipMemset(output_buffer_ptr, 0, copy_bytes));
MIGRAPHX_HIP_ASSERT(hipDeviceSynchronize());
MIGRAPHX_HIP_ASSERT(hipMemcpy(output_ptr, h_output, input_bytes, hipMemcpyHostToDevice));
return inputs[1];
}
virtual migraphx::shape compute_shape(migraphx::shapes inputs) const override
{
if(not inputs[0].standard() or not inputs[1].standard())
{
throw std::runtime_error("Input args must be standard shaped");
}
if(inputs.size() != 2)
{
throw std::runtime_error("number of inputs must be 2");
}
return inputs.back();
}
};
struct half_copy_device final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "half_copy_device"; }
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::argument
compute(migraphx::context ctx, migraphx::shape, migraphx::arguments inputs) const override
{
// This custom op simply sets first half size_bytes of the input to 0, and rest of the half
// bytes are copied. for this custom_op, it does its computation on the "GPU". Therefore,
// `runs_on_offload_target()` is set to "true".
auto* input_buffer_ptr = inputs[0].data();
auto* output_buffer_ptr = inputs[1].data();
auto input_bytes = inputs[0].get_shape().bytes();
auto copy_bytes = input_bytes / 2;
MIGRAPHX_HIP_ASSERT(hipSetDevice(0));
MIGRAPHX_HIP_ASSERT(hipMemcpyAsync(output_buffer_ptr,
input_buffer_ptr,
input_bytes,
hipMemcpyDeviceToDevice,
ctx.get_queue<hipStream_t>()));
MIGRAPHX_HIP_ASSERT(hipDeviceSynchronize());
MIGRAPHX_HIP_ASSERT(hipMemset(output_buffer_ptr, 0, copy_bytes));
MIGRAPHX_HIP_ASSERT(hipDeviceSynchronize());
MIGRAPHX_HIP_ASSERT(hipHostFree(h_output));
return inputs[1];
}
virtual migraphx::shape compute_shape(migraphx::shapes inputs) const override
{
if(not inputs[0].standard())
if(not inputs[0].standard() or not inputs[1].standard())
{
throw std::runtime_error("first arg must be standard shaped");
throw std::runtime_error("Input args must be standard shaped");
}
if(inputs.size() != 2)
{
......@@ -67,36 +116,208 @@ struct simple_custom_op final : migraphx::experimental_custom_op_base
}
};
TEST_CASE(run_simple_custom_op)
// overwrites input buffer
struct half_copy_device_same_buffer final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "half_copy_device_same_buffer"; }
virtual bool runs_on_offload_target() const override { return true; }
virtual migraphx::argument
compute(migraphx::context, migraphx::shape, migraphx::arguments inputs) const override
{
// This custom op simply sets first half size_bytes of the input 0, and rest of the half
// bytes are copied. for this custom_op, it does its computation on the "device". Therefore,
// `runs_on_offload_target()` is set to "true"
auto* buffer_ptr = inputs[0].data();
auto input_bytes = inputs[0].get_shape().bytes();
auto copy_bytes = input_bytes / 2;
MIGRAPHX_HIP_ASSERT(hipSetDevice(0));
MIGRAPHX_HIP_ASSERT(hipMemset(buffer_ptr, 0, copy_bytes));
MIGRAPHX_HIP_ASSERT(hipDeviceSynchronize());
return inputs[0];
}
virtual migraphx::shape compute_shape(migraphx::shapes inputs) const override
{
if(not inputs[0].standard())
{
throw std::runtime_error("Input arg must be standard shaped");
}
return inputs.front();
}
};
TEST_CASE(register_half_copy_op)
{
half_copy_host hch;
migraphx::register_experimental_custom_op(hch);
auto op = migraphx::operation("half_copy_host");
EXPECT(op.name() == "half_copy_host");
half_copy_device hcd;
migraphx::register_experimental_custom_op(hcd);
op = migraphx::operation("half_copy_device");
EXPECT(op.name() == "half_copy_device");
half_copy_device_same_buffer hcdsb;
migraphx::register_experimental_custom_op(hcdsb);
op = migraphx::operation("half_copy_device_same_buffer");
EXPECT(op.name() == "half_copy_device_same_buffer");
}
TEST_CASE(half_copy_custom_op_test)
{
simple_custom_op simple_op;
migraphx::register_experimental_custom_op(simple_op);
auto run_test_prog = [](const std::string& op_name, bool buffer_alloc) {
migraphx::program p;
migraphx::module m = p.get_main_module();
migraphx::shape s{migraphx_shape_float_type, {4, 3}};
auto x = m.add_parameter("x", s);
migraphx::instructions inputs = {x};
if(buffer_alloc)
{
auto alloc = m.add_allocation(s);
inputs = {x, alloc};
}
auto half_copy_ins = m.add_instruction(migraphx::operation(op_name.c_str()), inputs);
m.add_return({half_copy_ins});
migraphx::compile_options options;
options.set_offload_copy();
p.compile(migraphx::target("gpu"), options);
migraphx::program_parameters pp;
std::vector<float> x_data(12);
std::iota(x_data.begin(), x_data.end(), 0);
pp.add("x", migraphx::argument(s, x_data.data()));
auto results = p.eval(pp);
auto result = results[0];
auto result_vec = result.as_vector<float>();
std::vector<float> expected_result(12, 0);
std::iota(expected_result.begin() + 6, expected_result.end(), 6);
EXPECT(bool{result == migraphx::argument(s, expected_result.data())});
};
// register all the ops
half_copy_host hch;
migraphx::register_experimental_custom_op(hch);
half_copy_device hcd;
migraphx::register_experimental_custom_op(hcd);
half_copy_device_same_buffer hcdsb;
migraphx::register_experimental_custom_op(hcdsb);
std::vector<std::pair<std::string, bool>> tests_config = {
{"half_copy_host", true},
{"half_copy_device", true},
{"half_copy_device_same_buffer", false}};
for(const auto& i : tests_config)
{
run_test_prog(i.first, i.second);
}
}
struct stride_two final : migraphx::experimental_custom_op_base
{
virtual std::string name() const override { return "stride_two"; }
virtual migraphx::argument
compute(migraphx::context, migraphx::shape out_shape, migraphx::arguments inputs) const override
{
return {out_shape, inputs[0].data()};
}
virtual migraphx::shape compute_shape(migraphx::shapes inputs) const override
{
if(inputs.size() != 1)
{
throw std::runtime_error("stride_two op must have only one input argument");
};
if(not inputs[0].standard())
{
throw std::runtime_error("stride_two op only works on the standard input shapes");
}
migraphx::shape input_s = inputs[0];
std::vector<size_t> dims = input_s.lengths();
std::vector<size_t> new_dims;
std::vector<size_t> strides = input_s.strides();
std::vector<size_t> new_strides;
std::for_each(dims.begin(), dims.end(), [&](auto i) { new_dims.push_back(i / 2); });
std::for_each(
strides.begin(), strides.end(), [&](auto i) { new_strides.push_back(i * 2); });
migraphx::shape output_shape{input_s.type(), new_dims, new_strides};
return output_shape;
}
virtual bool runs_on_offload_target() const override { return true; }
virtual std::vector<size_t> output_alias(migraphx::shapes) const override { return {0}; };
};
TEST_CASE(stride_two_custom_op_test)
{
stride_two st;
migraphx::register_experimental_custom_op(st);
migraphx::program p;
migraphx::module m = p.get_main_module();
migraphx::shape s{migraphx_shape_float_type, {4, 4, 4}};
auto x = m.add_parameter("x", s);
auto stride_two_ins = m.add_instruction(migraphx::operation("stride_two"), {x});
m.add_return({stride_two_ins});
migraphx::compile_options options;
options.set_offload_copy();
p.compile(migraphx::target("gpu"), options);
migraphx::program_parameters pp;
std::vector<float> x_data(64);
std::iota(x_data.begin(), x_data.end(), 0);
pp.add("x", migraphx::argument(s, x_data.data()));
auto results = p.eval(pp);
auto result = results[0];
auto result_vec = result.as_vector<float>();
std::vector<float> expected_result = {0, 2, 8, 10, 32, 34, 40, 42};
EXPECT(result_vec == expected_result);
}
TEST_CASE(custom_op_with_pre_and_post_subgraph_test)
{
half_copy_host hco;
migraphx::register_experimental_custom_op(hco);
stride_two st;
migraphx::register_experimental_custom_op(st);
migraphx::program p;
migraphx::shape s{migraphx_shape_int32_type, {4, 3}};
migraphx::shape trans_shape{migraphx_shape_int32_type, {3, 4}};
migraphx::shape s{migraphx_shape_float_type, {4, 6}};
migraphx::module m = p.get_main_module();
auto x = m.add_parameter("x", s);
auto neg = m.add_instruction(migraphx::operation("neg"), x);
// pre-subgraph
auto neg_ins = m.add_instruction(migraphx::operation("neg"), x);
auto trans_ins =
m.add_instruction(migraphx::operation("transpose", "{permutation: [1, 0]}"), {neg_ins});
auto cont_ins = m.add_instruction(migraphx::operation("contiguous"), {trans_ins});
// custom_op
migraphx::shape trans_shape{migraphx_shape_float_type, {6, 4}};
auto alloc = m.add_allocation(trans_shape);
auto neg_trans =
m.add_instruction(migraphx::operation("transpose", "{permutation: [1, 0]}"), {neg});
auto neg_cont = m.add_instruction(migraphx::operation("contiguous"), {neg_trans});
auto custom_kernel =
m.add_instruction(migraphx::operation("simple_custom_op"), {neg_cont, alloc});
auto relu = m.add_instruction(migraphx::operation("relu"), custom_kernel);
m.add_return({relu});
auto half_copy_ins =
m.add_instruction(migraphx::operation("half_copy_host"), {cont_ins, alloc});
// post-subgraph
auto abs_ins = m.add_instruction(migraphx::operation("abs"), {half_copy_ins});
// another custom_op
auto stride_two_ins = m.add_instruction(migraphx::operation("stride_two"), {abs_ins});
// post-subgraph
auto relu_ins = m.add_instruction(migraphx::operation("relu"), {stride_two_ins});
m.add_return({relu_ins});
migraphx::compile_options options;
options.set_offload_copy();
p.compile(migraphx::target("gpu"), options);
migraphx::program_parameters pp;
std::vector<int> x_data(12, -3);
std::vector<float> x_data(s.elements());
std::iota(x_data.begin(), x_data.end(), 0);
pp.add("x", migraphx::argument(s, x_data.data()));
auto results = p.eval(pp);
auto result = results[0];
auto result_vec = result.as_vector<int>();
std::vector<int> expected_result(12, 0);
std::fill(expected_result.begin() + 6, expected_result.end(), 3);
EXPECT(bool{result == migraphx::argument(trans_shape, expected_result.data())});
auto result_vec = result.as_vector<float>();
std::vector<float> expected_result = {0, 0, 0, 0, 4, 16};
EXPECT(bool{result == migraphx::argument(migraphx::shape{migraphx_shape_float_type, {3, 2}},
expected_result.data())});
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
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