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Commit f12064ee authored by umangyadav's avatar umangyadav
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Merge branch 'develop' into resnet50_partition

parents 2c4f70be 6f1c947f
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Showing with 712 additions and 386 deletions
src/api/CMakeLists.txt
View file @ f12064ee
......@@ -26,6 +26,7 @@ add_library(migraphx_c
api.cpp
)
set_target_properties(migraphx_c PROPERTIES EXPORT_NAME c)
migraphx_generate_export_header(migraphx_c DIRECTORY migraphx/api)
# migraphx_c is stable API interface library. SO version of this should be
# bumped when binary compatibility is broken.
......
src/api/api.cpp
View file @ f12064ee
......@@ -44,7 +44,7 @@ namespace migraphx {
static thread_local bool disable_exception_catch = false; // NOLINT
extern "C" void migraphx_test_private_disable_exception_catch(bool b)
extern "C" MIGRAPHX_C_EXPORT void migraphx_test_private_disable_exception_catch(bool b)
{
disable_exception_catch = b;
}
......@@ -899,7 +899,7 @@ migraphx_dynamic_dimensions_assign_to(migraphx_dynamic_dimensions_t output,
extern "C" migraphx_status
migraphx_dynamic_dimensions_create(migraphx_dynamic_dimensions_t* dynamic_dimensions,
const_migraphx_dynamic_dimension_t* ptr,
const const_migraphx_dynamic_dimension_t* ptr,
size_t size)
{
auto api_error_result = migraphx::try_([&] {
......@@ -1432,7 +1432,7 @@ extern "C" migraphx_status migraphx_instructions_assign_to(migraphx_instructions
}
extern "C" migraphx_status migraphx_instructions_create(migraphx_instructions_t* instructions,
const_migraphx_instruction_t* ptr,
const const_migraphx_instruction_t* ptr,
size_t size)
{
auto api_error_result = migraphx::try_([&] {
......
src/api/include/migraphx/migraphx.h
View file @ f12064ee
This diff is collapsed.
src/api/migraphx.py
View file @ f12064ee
......@@ -79,7 +79,8 @@ def dynamic_dimension(h):
def dynamic_dimensions(h):
h.constructor(
'create',
api.params(ptr='const_migraphx_dynamic_dimension_t*', size='size_t'),
api.params(ptr='const 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',
......@@ -215,7 +216,7 @@ def instruction(h):
def instructions(h):
h.constructor(
'create',
api.params(ptr='const_migraphx_instruction_t*', size='size_t'),
api.params(ptr='const const_migraphx_instruction_t*', size='size_t'),
fname='migraphx::to_obj_vector<const_migraphx_instruction_t>')
......
src/driver/CMakeLists.txt
View file @ f12064ee
......@@ -45,7 +45,7 @@ if(NOT WIN32)
endif()
rocm_clang_tidy_check(driver)
target_link_libraries(driver migraphx_all_targets migraphx_onnx migraphx_tf)
target_link_libraries(driver migraphx_all_targets migraphx_onnx migraphx_tf migraphx_py)
rocm_install_targets(
TARGETS driver
......
src/driver/argument_parser.hpp
View file @ f12064ee
......@@ -338,11 +338,22 @@ struct argument_parser
MIGRAPHX_DRIVER_STATIC auto file_exist()
{
return validate([](auto&, auto&, auto& params) {
return validate([](auto&, auto&, const auto& params) {
if(params.empty())
throw std::runtime_error("No argument passed.");
if(not fs::exists(params.back()))
throw std::runtime_error("Path does not exists: " + params.back());
throw std::runtime_error("Path does not exist: " + params.back());
});
}
MIGRAPHX_DRIVER_STATIC auto matches(const std::unordered_set<std::string>& names)
{
return validate([=](auto&, auto&, const auto& params) {
auto invalid_param = std::find_if(
params.begin(), params.end(), [&](const auto& p) { return names.count(p) == 0; });
if(invalid_param != params.end())
throw std::runtime_error("Invalid argument: " + *invalid_param +
". Valid arguments are {" + to_string_range(names) + "}");
});
}
......@@ -570,8 +581,7 @@ struct argument_parser
continue;
if(flag[0] != '-')
continue;
auto d =
levenshtein_distance(flag.begin(), flag.end(), input.begin(), input.end());
std::ptrdiff_t d = levenshtein_distance(flag, input);
if(d < result.distance)
result = result_t{&arg, flag, input, d};
}
......
src/driver/main.cpp
View file @ f12064ee
......@@ -32,6 +32,7 @@
#include <migraphx/tf.hpp>
#include <migraphx/onnx.hpp>
#include <migraphx/py.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/convert_to_json.hpp>
#include <migraphx/load_save.hpp>
......@@ -81,6 +82,7 @@ struct loader
{"--model"},
ap.help("Load model"),
ap.type("resnet50|inceptionv3|alexnet"),
ap.matches({"resnet50", "inceptionv3", "alexnet"}),
ap.group("input"));
ap(file_type, {"--onnx"}, ap.help("Load as onnx"), ap.set_value("onnx"));
ap(file_type, {"--tf"}, ap.help("Load as tensorflow"), ap.set_value("tf"));
......@@ -241,6 +243,20 @@ struct loader
return options;
}
static std::string get_file_type(const std::string& file)
{
if(ends_with(file, ".onnx"))
return "onnx";
else if(ends_with(file, ".pb"))
return "tf";
else if(ends_with(file, ".json"))
return "json";
else if(ends_with(file, ".py"))
return "py";
else
return "migraphx";
}
program load()
{
program p;
......@@ -248,14 +264,7 @@ struct loader
{
if(file_type.empty())
{
if(ends_with(file, ".onnx"))
file_type = "onnx";
else if(ends_with(file, ".pb"))
file_type = "tf";
else if(ends_with(file, ".json"))
file_type = "json";
else
file_type = "migraphx";
file_type = get_file_type(file);
}
std::cout << "Reading: " << file << std::endl;
if(file_type == "onnx")
......@@ -272,6 +281,10 @@ struct loader
options.format = "json";
p = migraphx::load(file, options);
}
else if(file_type == "py")
{
p = migraphx::load_py(file);
}
else if(file_type == "migraphx")
{
p = migraphx::load(file);
......@@ -757,7 +770,7 @@ struct main_command
{
std::cout << "'" << color::fg_yellow << wrong_commands.front() << color::reset
<< "' is not a valid command." << std::endl;
std::cout << get_command_help("Available commands:") << std::endl;
std::cout << get_command_help("Available commands:");
}
else
{
......
src/dynamic_loader.cpp
View file @ f12064ee
......@@ -48,7 +48,7 @@ struct dynamic_loader_impl
#pragma GCC diagnostic ignored "-Wignored-attributes"
#endif
dynamic_loader_impl(const fs::path& p, std::shared_ptr<tmp_dir> t = nullptr)
: handle(dlopen(p.string().c_str(), RTLD_LAZY),
: handle(dlopen(p.string().c_str(), RTLD_GLOBAL | RTLD_NOW),
manage_deleter<decltype(&dlclose), &dlclose>{}),
temp(std::move(t))
{
......@@ -81,6 +81,18 @@ fs::path dynamic_loader::path(void* address)
return p;
}
optional<dynamic_loader> dynamic_loader::try_load(const fs::path& p)
{
try
{
return dynamic_loader{p};
}
catch(const std::exception&)
{
return nullopt;
}
}
dynamic_loader::dynamic_loader(const fs::path& p) : impl(std::make_shared<dynamic_loader_impl>(p))
{
}
......
src/eliminate_contiguous.cpp
View file @ f12064ee
......@@ -35,6 +35,8 @@
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_TRACE_ELIMINATE_CONTIGUOUS)
static bool try_compute_shape(instruction_ref ins,
const std::vector<shape>& inputs,
const std::vector<module_ref>& mods)
......@@ -78,14 +80,26 @@ static bool try_compute_shape(instruction_ref ins,
return (arg == ins) ? new_shape : arg->get_shape();
});
if(not try_compute_shape(output, input_shapes, mods))
if(not try_compute_shape(output, input_shapes, output->module_inputs()))
{
return false;
}
}
}
catch(const std::exception& e)
{
if(enabled(MIGRAPHX_TRACE_ELIMINATE_CONTIGUOUS{}))
{
std::cout << "Exception: " << e.what() << std::endl;
}
return false;
}
catch(...)
{
if(enabled(MIGRAPHX_TRACE_ELIMINATE_CONTIGUOUS{}))
{
std::cout << "Unknown exception" << std::endl;
}
return false;
}
......@@ -127,6 +141,11 @@ static void remove_contiguous(const std::string& op_name, module& m, F f)
{
if(arg->name() != op_name)
continue;
if(enabled(MIGRAPHX_TRACE_ELIMINATE_CONTIGUOUS{}))
{
std::cout << "eliminate_contiguous: ";
m.debug_print(ins);
}
auto prev = arg->inputs().front();
replace(new_args, arg, prev);
if(try_compute_shape(ins, new_args, mod_args))
......
src/fuse_pointwise.cpp
View file @ f12064ee
......@@ -41,7 +41,7 @@ static literal get_scalar(instruction_ref ins)
if(ins->name() == "contiguous")
return get_scalar(ins->inputs().front());
const auto& s = ins->get_shape();
if(s.elements() != 1 && not(s.scalar()))
if(s.elements() != 1 and not(s.scalar()))
return {};
if(not ins->can_eval())
return {};
......
src/fuse_reduce.cpp
View file @ f12064ee
......@@ -52,7 +52,7 @@ struct fused_reduce
{
if(mods.size() != 1)
MIGRAPHX_THROW("should have one submodule.");
auto* sm = mods.front();
const auto* sm = mods.front();
if(sm->get_output_shapes().size() != 1)
MIGRAPHX_THROW("Only one output supported");
auto names = sm->get_parameter_names();
......@@ -143,7 +143,7 @@ insert_module_in_submodule(module_ref sm,
}
static std::vector<instruction_ref>
find_inputs(module_ref sm,
find_inputs(const_module_ref sm,
const module& parent,
const std::unordered_map<instruction_ref, instruction_ref>& map_ins)
{
......
src/include/migraphx/algorithm.hpp
View file @ f12064ee
......@@ -26,6 +26,8 @@
#include <algorithm>
#include <numeric>
#include <string>
#include <vector>
#include <migraphx/config.hpp>
namespace migraphx {
......@@ -90,6 +92,42 @@ levenshtein_distance(Iterator1 first1, Iterator1 last1, Iterator2 first2, Iterat
return std::ptrdiff_t{1} + std::min({x1, x2, x3});
}
inline size_t levenshtein_distance(const std::string& s1, const std::string& s2)
{
const size_t l1 = s1.length();
const size_t l2 = s2.length();
if(l1 < l2)
levenshtein_distance(s2, s1);
std::vector<size_t> d(l2 + 1);
std::iota(d.begin(), d.end(), 0);
for(size_t i = 1; i <= l1; i++)
{
size_t prev_cost = d[0];
d[0] = i;
for(size_t j = 1; j <= l2; j++)
{
if(s1[i - 1] == s2[j - 1])
{
d[j] = prev_cost;
}
else
{
size_t cost_insert_or_delete = std::min(d[j - 1], d[j]);
size_t cost_substitute = prev_cost;
prev_cost = d[j];
d[j] = std::min(cost_substitute, cost_insert_or_delete) + 1;
}
}
}
return d[l2];
}
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......
src/include/migraphx/builtin.hpp
View file @ f12064ee
......@@ -90,7 +90,17 @@ struct param
struct returns
{
std::string name() const { return "@return"; }
shape compute_shape(const std::vector<shape>&) const { return {}; }
shape compute_shape(const std::vector<shape>& arg) const
{
if(arg.empty())
return {};
else if(arg.size() == 1)
return arg[0];
else
return arg;
}
argument compute(context&, const shape&, const std::vector<argument>&) const
{
MIGRAPHX_THROW("builtin");
......
src/include/migraphx/check_shapes.hpp
View file @ f12064ee
/*
* 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
......@@ -34,21 +34,37 @@
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
// Check that deduced type is incrementable, dereferencable, and comparable
template <class, class = void>
struct is_iterator
{
};
template <class T>
struct is_iterator<T,
std::void_t<decltype(++std::declval<T&>()),
decltype(*std::declval<T&>()),
decltype(std::declval<T&>() == std::declval<T&>())>> : std::true_type
{
};
template <class Iterator>
struct check_shapes
{
const shape* begin;
const shape* end;
static_assert(is_iterator<Iterator>{}, "CHECK_SHAPES: Deduced type must be an iterator");
Iterator begin;
Iterator end;
std::string name;
bool dynamic_allowed;
check_shapes(const shape* b, const shape* e, const std::string& n, const bool d = false)
check_shapes(Iterator b, Iterator e, const std::string& n, const bool d = false)
: begin(b), end(e), name(n), dynamic_allowed(d)
{
check_dynamic();
}
template <class Op>
check_shapes(const shape* b, const shape* e, const Op& op, const bool d = false)
check_shapes(Iterator b, Iterator e, const Op& op, const bool d = false)
: begin(b), end(e), name(op.name()), dynamic_allowed(d)
{
check_dynamic();
......@@ -56,7 +72,7 @@ struct check_shapes
template <class Op>
check_shapes(const std::vector<shape>& s, const Op& op, const bool d = false)
: begin(s.data()), end(s.data() + s.size()), name(op.name()), dynamic_allowed(d)
: begin(s.begin()), end(s.end()), name(op.name()), dynamic_allowed(d)
{
check_dynamic();
}
......@@ -81,8 +97,6 @@ struct check_shapes
{
if(begin == end)
return 0;
assert(begin != nullptr);
assert(end != nullptr);
return end - begin;
}
......@@ -131,8 +145,6 @@ struct check_shapes
*/
const check_shapes& only_dims(std::size_t n) const
{
assert(begin != nullptr);
assert(end != nullptr);
if(begin != end)
{
if(begin->max_lens().size() != n)
......@@ -148,8 +160,6 @@ struct check_shapes
*/
const check_shapes& max_ndims(std::size_t n) const
{
assert(begin != nullptr);
assert(end != nullptr);
if(begin != end)
{
if(begin->max_lens().size() > n)
......@@ -166,8 +176,6 @@ struct check_shapes
*/
const check_shapes& min_ndims(std::size_t n) const
{
assert(begin != nullptr);
assert(end != nullptr);
if(begin != end)
{
if(begin->max_lens().size() < n)
......@@ -330,8 +338,6 @@ struct check_shapes
{
if(begin == end)
return true;
assert(begin != nullptr);
assert(end != nullptr);
auto&& key = f(*begin);
return this->all_of([&](const shape& s) { return f(s) == key; });
}
......@@ -341,8 +347,6 @@ struct check_shapes
{
if(begin == end)
return true;
assert(begin != nullptr);
assert(end != nullptr);
return std::all_of(begin, end, p);
}
......@@ -351,17 +355,13 @@ struct check_shapes
{
if(begin == end)
return false;
assert(begin != nullptr);
assert(end != nullptr);
return std::any_of(begin, end, p);
}
const shape* get(long i) const
Iterator get(long i) const
{
if(i >= size())
MIGRAPHX_THROW(prefix() + "Accessing shape out of bounds");
assert(begin != nullptr);
assert(end != nullptr);
if(i < 0)
return end - i;
return begin + i;
......@@ -394,6 +394,11 @@ struct check_shapes
}
};
// Deduction guide for std::vector constructor
template <class Op>
check_shapes(const std::vector<shape>&, const Op&, bool d = false)
-> check_shapes<std::vector<shape>::const_iterator>;
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......
src/include/migraphx/dynamic_loader.hpp
View file @ f12064ee
......@@ -26,6 +26,7 @@
#include <migraphx/config.hpp>
#include <migraphx/filesystem.hpp>
#include <migraphx/optional.hpp>
#include <functional>
#include <memory>
#include <vector>
......@@ -43,6 +44,9 @@ struct MIGRAPHX_EXPORT dynamic_loader
return path(reinterpret_cast<void*>(address));
}
static fs::path path(void* address);
static optional<dynamic_loader> try_load(const fs::path& p);
dynamic_loader() = default;
dynamic_loader(const fs::path& p);
......
src/include/migraphx/normalize_attributes.hpp
View file @ f12064ee
/*
* 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
......@@ -28,6 +28,7 @@
#include <migraphx/shape.hpp>
#include <cstring>
#include <vector>
#include <migraphx/op/normalize_attribute.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -42,6 +43,36 @@ struct select_dependent_type
template <class T, class... Ts>
using dependent_type = typename select_dependent_type<T, Ts...>::type;
/**
* Used to normalize variable input axes at model runtime.
* Example: the axes inputs of the slice operator.
*
* \param axes the axes to normalize
* \param input_shape shape of the input tensor
* \param attr_val the normalize_axes attributes from the operator
* \param prefix error message prefix
*/
std::vector<int64_t> normalize_axes(const std::vector<int64_t>& axes,
const shape& input_shape,
const value& attr_val,
const std::string& prefix = "");
/**
* Used to normalize variable input axes at model runtime.
* Example: the starts and ends inputs of the slice operator.
*
* \param indices the indices to normalize
* \param axes which axes the indices apply over
* \param input_shape shape of the input tensor
* \param attr_val the normalize_axes attributes from the operator
* \param prefix error message prefix
*/
std::vector<int64_t> normalize_indices(const std::vector<int64_t>& indices,
const std::vector<int64_t>& axes,
const shape& input_shape,
const value& attr_val,
const std::string& prefix = "");
MIGRAPHX_EXPORT
bool normalize_attributes(operation& op, const shape& input_shape);
......
src/include/migraphx/op/convolution.hpp
View file @ f12064ee
......@@ -82,7 +82,7 @@ struct convolution
const auto input_ndim = inputs[0].ndim();
const auto padding_size = padding.size();
if(input_ndim != padding_size / 2 + 2 && input_ndim != padding_size + 2)
if(input_ndim != padding_size / 2 + 2 and input_ndim != padding_size + 2)
{
MIGRAPHX_THROW("CONVOLUTION: input and attribute size mismatch!");
}
......
src/include/migraphx/op/if_op.hpp
View file @ f12064ee
......@@ -71,7 +71,7 @@ struct if_op
std::unordered_map<std::string, argument> params;
std::set<std::string> pnames;
for(const auto& smod : mods)
for(const_module_ref smod : mods)
{
auto names = smod->get_parameter_names();
pnames.insert(names.begin(), names.end());
......
src/include/migraphx/op/loop.hpp
View file @ f12064ee
......@@ -59,9 +59,9 @@ struct loop
MIGRAPHX_THROW("LOOP: operator should have one submodule.");
}
const auto& mod = mods.front();
auto mod_out_shapes = mod->get_output_shapes();
auto dep_param_num = inputs.size() - 2;
const_module_ref mod = mods.front();
auto mod_out_shapes = mod->get_output_shapes();
auto dep_param_num = inputs.size() - 2;
// first item of the mod output shapes is condition used in loop,
// which is not needed to compute output shape
......
src/include/migraphx/op/slice.hpp
View file @ f12064ee
......@@ -27,19 +27,34 @@
#include <migraphx/check_shapes.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/config.hpp>
#include <migraphx/dyn_output.hpp>
#include <migraphx/value.hpp>
#include <migraphx/dyn_output.hpp>
#include <migraphx/op/normalize_attribute.hpp>
#include <migraphx/normalize_attributes.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {
/**
* Slice operator that accepts variable axes, starts and ends.
*
* Attributes:
* axes: constant axes to slice over (optional)
* starts: constant slice starting indices (optional)
* ends: constant slice ending indices (optional)
*
* Parameters:
* data: the input tensor to slice (dynamic or static shape)
* input_starts: starting indicies of slice (optional, static shape)
* input_ends: ending indicies of slice (optional, static shape)
* input_axes: axes to slice over (optional, static shape)
*/
struct slice
{
std::vector<int64_t> axes;
std::vector<int64_t> starts;
std::vector<int64_t> ends;
std::vector<int64_t> axes{};
std::vector<int64_t> starts{};
std::vector<int64_t> ends{};
template <class Self, class F>
static auto reflect(Self& self, F f)
......@@ -48,8 +63,8 @@ struct slice
}
/**
* Ensure that attribute vectors axes, starts, and ends are all the same size and values are in
* limits.
* Ensure that attribute vectors axes, starts, and ends are all the same size and values are
* within limits.
*/
value attributes() const
{
......@@ -70,6 +85,90 @@ struct slice
std::string name() const { return "slice"; }
/**
* Computes the slice output shape dimensions for given starts, ends,and axes.
* Templated to also handle tensor views.
* Possibily different type between [in_starts, in_ends] and [in_axes] if in_axes is this
* object's axes attribute. Assumes in_starts and in_ends are normalized; in_axes are valid.
*/
template <class A, class B>
std::vector<std::size_t>
lens_calc(const std::vector<std::size_t>& lengths, A in_starts, A in_ends, B in_axes) const
{
auto new_lens = lengths;
for(std::size_t i = 0; i < in_axes.size(); ++i)
{
auto axis = in_axes[i];
new_lens[axis] = in_ends[i] - in_starts[i];
}
return new_lens;
}
shape normalize_compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this, true}.has(1, 3, 4);
auto input_shape = inputs[0];
if(inputs.size() == 1)
{
auto t = input_shape.type();
if(input_shape.dynamic() and std::any_of(axes.begin(), axes.end(), [&](auto axis) {
return not input_shape.dyn_dims()[axis].is_fixed();
}))
{
MIGRAPHX_THROW("SLICE: slicing is not allowed on non-fixed dynamic input axis ");
}
if(input_shape.dynamic())
{
return shape{t,
lens_calc(input_shape.min_lens(), starts, ends, axes),
lens_calc(input_shape.max_lens(), starts, ends, axes),
{}};
}
else
{
return shape{
t, lens_calc(input_shape.lens(), starts, ends, axes), input_shape.strides()};
}
}
else
{
// check that starts, ends, and optionally input_axes are all 1D, have the same
// dimension, and are static
check_shapes{inputs.begin() + 1,
inputs.end(),
std::string("SLICE: inputs (starts, ends, and input_axes)"),
false}
.only_dims(1)
.same_dims();
auto dds = input_shape.to_dynamic().dyn_dims();
if(inputs.size() == 3)
{
if(inputs[1].lens().at(0) != axes.size())
{
MIGRAPHX_THROW("SLICE: inputs starts and ends do not have the same dimension "
"as the axes attribute");
}
std::for_each(axes.cbegin(), axes.cend(), [&](const auto& axis) {
dds.at(axis) = {0, dds.at(axis).max};
});
}
else
{
// if axes is an input, then all the output dimensions could be 0 to the max value
std::transform(dds.begin(), dds.end(), dds.begin(), [](auto dd) {
return shape::dynamic_dimension{0, dd.max};
});
}
return shape{input_shape.type(), dds};
}
}
/**
* Calculates the starting offset for the sliced tensor.
* Used in compute when only data input and all other information are in the attributes.
*
* \param s static input shape
*/
auto compute_offset(const shape& s) const
{
const std::vector<std::size_t>& lens = s.lens();
......@@ -90,80 +189,131 @@ struct slice
offset += starts[axis] * strides[axis];
}
}
return offset;
return offset * s.type_size();
}
shape normalize_compute_shape(std::vector<shape> inputs) const
/**
* Calculates the starting offset for the sliced tensor (for aliasing).
* Used when the starts and/or the axes are inputs.
*
* \param s static input shape
* \param input_starts starting indices of slice
* \param ax_vec axes to slice on
*/
template <class IndView, class Axes>
auto compute_offset(const shape& s, const IndView& input_starts, const Axes& ax_vec) const
{
check_shapes{inputs, *this, true}.has(1);
auto input_shape = inputs[0];
auto t = input_shape.type();
// TODO: When support for dynamic shapes is added to normalize_attributes,
// remove this restriction.
if(input_shape.dynamic() and std::any_of(axes.begin(), axes.end(), [&](auto axis) {
return not input_shape.dyn_dims()[axis].is_fixed();
}))
auto ret = 0;
for(std::size_t i = 0; i < ax_vec.size(); ++i)
{
MIGRAPHX_THROW("SLICE: slicing is not allowed on non-fixed dynamic input axis ");
auto axis = ax_vec[i];
ret += input_starts[i] * s.strides().at(axis);
}
return ret * s.type_size();
}
std::unordered_map<std::string, std::vector<int64_t>>
normalize_inputs(const shape& input_shape,
const std::vector<int64_t>& input_starts,
const std::vector<int64_t>& input_ends) const
{
auto attrs = this->attributes().at("normalize_axes");
return {{"input_starts",
normalize_indices(input_starts,
this->axes,
input_shape,
attrs.at("starts"),
"Slice variable input_starts")},
{"input_ends",
normalize_indices(input_ends,
this->axes,
input_shape,
attrs.at("ends"),
"Slice variable input_ends")}};
}
/**
* Three input version of the normalize_inputs.
* This one also checks that the input_axes are valid.
*/
std::unordered_map<std::string, std::vector<int64_t>>
normalize_inputs(shape input_shape,
const std::vector<int64_t>& input_starts,
const std::vector<int64_t>& input_ends,
const std::vector<int64_t>& input_axes) const
{
auto attrs = this->attributes().at("normalize_axes");
auto norm_axes =
normalize_axes(input_axes, input_shape, attrs.at("axes"), "Slice variable input_axes");
return {{"input_starts",
normalize_indices(input_starts,
norm_axes,
input_shape,
attrs.at("starts"),
"Slice variable input_starts")},
{"input_ends",
normalize_indices(input_ends,
norm_axes,
input_shape,
attrs.at("ends"),
"Slice variable input ends")},
{"input_axes", norm_axes}};
}
// For a static shape, old_lens will be adjusted to a new size
// for those axes that are sliced.
// For dynamic shape, the adjusted old_lens become the new max values,
// while updating the old mins and optimals if possible.
std::vector<std::size_t> new_mins;
std::vector<std::size_t> old_lens;
std::vector<std::size_t> old_strides;
// Doesn't handle optimals
if(input_shape.dynamic())
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
auto input = args[0];
auto input_shape = input.get_shape();
switch(args.size())
{
old_lens = input_shape.max_lens();
new_mins = input_shape.min_lens();
case 1: {
std::size_t offset = compute_offset(input_shape);
return {dyn_out.computed_shape, [=] { return input.data() + offset; }};
}
else
{
old_lens = input_shape.lens();
// For static shape (including during eval step after a dynamic input) the strides are
// indexed into the pre-slice array, so they are larger than the apparent size of the
// resulting shape.
old_strides = input_shape.strides();
case 3: {
shape calc_shape;
std::size_t offset = 0;
visit_all(args[1], args[2])([&](auto input_starts, auto input_ends) {
auto norm_inputs = normalize_inputs(input_shape,
input_starts.template to_vector<int64_t>(),
input_ends.template to_vector<int64_t>());
offset = compute_offset(input_shape, norm_inputs.at("input_starts"), this->axes);
calc_shape = {input_shape.type(),
lens_calc(input_shape.lens(),
norm_inputs.at("input_starts"),
norm_inputs.at("input_ends"),
this->axes),
input_shape.strides()};
});
return {calc_shape, [=] { return input.data() + offset; }};
}
std::vector<std::size_t> new_lens = old_lens;
for(std::size_t i = 0; i < axes.size(); i++)
{
auto axis = axes[i];
size_t sliced_length = ends[i] - starts[i];
// A Numpy indexing convention: a slice size larger than the actual dimension
// is legal and the "ends" value is clipped to the axis size
new_lens[axis] = std::min(new_lens[axis], sliced_length);
if(input_shape.dynamic())
{
// TODO: when non-fixed shape slicing is allowed, this will be different than
// sliced_length, making use of TBD start/end values.
std::size_t sliced_min_length = ends[i] - starts[i];
// if the slice size is smaller than maxes but larger than mins
new_mins[axis] = std::min(sliced_min_length, new_mins[axis]);
}
case 4: {
shape calc_shape;
std::size_t offset = 0;
visit_all(args[1], args[2], args[3])(
[&](auto input_starts, auto input_ends, auto input_axes) {
auto norm_inputs = normalize_inputs(input_shape,
input_starts.template to_vector<int64_t>(),
input_ends.template to_vector<int64_t>(),
input_axes.template to_vector<int64_t>());
offset = compute_offset(
input_shape, norm_inputs.at("input_starts"), norm_inputs.at("input_axes"));
calc_shape = shape{input_shape.type(),
lens_calc(input_shape.lens(),
norm_inputs.at("input_starts"),
norm_inputs.at("input_ends"),
norm_inputs.at("input_axes")),
input_shape.strides()};
});
return {calc_shape, [=] { return input.data() + offset; }};
}
if(input_shape.dynamic())
{
return shape{t, new_mins, new_lens, {}};
default: {
// Should never get here; covering in case some code change occurs
MIGRAPHX_THROW("SLICE: invalid number of inputs");
}
else
{
return shape{t, new_lens, old_strides};
}
}
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
auto input = args[0];
auto offset = compute_offset(input.get_shape()) * dyn_out.computed_shape.type_size();
return {dyn_out.computed_shape, [=] { return input.data() + offset; }};
}
std::ptrdiff_t output_alias(const std::vector<shape>&) const { return 0; }
};
......
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