"src/turbomind/utils/conv2d.h" did not exist on "720fc533da804ac3f46ee938864403e51fcd9fa7"
Commit 3a4d36cf authored by charlie's avatar charlie
Browse files

Merge branch 'develop' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into dyn_model_test

parents 6bec381f e19f78ae
......@@ -205,7 +205,7 @@ struct allocation_model
template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
private_detail_te_handle_type(
PrivateDetailTypeErasedT value,
typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
int>::type* = nullptr) noexcept
: private_detail_te_value(std::move(value))
{
......@@ -267,7 +267,7 @@ struct allocation_model
private_detail_te_handle_base_type& private_detail_te_get_handle()
{
assert(private_detail_te_handle_mem_var != nullptr);
if(!private_detail_te_handle_mem_var.unique())
if(not private_detail_te_handle_mem_var.unique())
private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
return *private_detail_te_handle_mem_var;
}
......
......@@ -101,7 +101,7 @@ struct check_shapes
const check_shapes& nelements(std::size_t n) const
{
if(!this->all_of([&](const shape& s) { return s.elements() == n; }))
if(not this->all_of([&](const shape& s) { return s.elements() == n; }))
MIGRAPHX_THROW(prefix() + "Shapes must have only " + std::to_string(n) + " elements");
return *this;
}
......@@ -164,7 +164,7 @@ struct check_shapes
*/
const check_shapes& same_shape() const
{
if(!this->same([](const shape& s) { return s; }))
if(not this->same([](const shape& s) { return s; }))
MIGRAPHX_THROW(prefix() + "Shapes do not match");
return *this;
}
......@@ -174,7 +174,7 @@ struct check_shapes
*/
const check_shapes& same_type() const
{
if(!this->same([](const shape& s) { return s.type(); }))
if(not this->same([](const shape& s) { return s.type(); }))
MIGRAPHX_THROW(prefix() + "Types do not match");
return *this;
}
......@@ -184,10 +184,10 @@ struct check_shapes
*/
const check_shapes& same_dims() const
{
if(!this->same([](const shape& s) { return s.max_lens(); }))
if(not this->same([](const shape& s) { return s.max_lens(); }))
MIGRAPHX_THROW(prefix() + "Dimensions do not match");
if(this->any_of([&](const shape& s) { return s.dynamic(); }))
if(!this->same([](const shape& s) { return s.min_lens(); }))
if(not this->same([](const shape& s) { return s.min_lens(); }))
MIGRAPHX_THROW(prefix() + "Min dynamic dimensions do not match");
return *this;
}
......@@ -197,7 +197,7 @@ struct check_shapes
*/
const check_shapes& same_ndims() const
{
if(!this->same([](const shape& s) { return s.max_lens().size(); }))
if(not this->same([](const shape& s) { return s.max_lens().size(); }))
MIGRAPHX_THROW(prefix() + "Number of dimensions do not match");
return *this;
}
......@@ -207,7 +207,7 @@ struct check_shapes
*/
const check_shapes& standard() const
{
if(!this->all_of([](const shape& s) { return s.standard(); }))
if(not this->all_of([](const shape& s) { return s.standard(); }))
MIGRAPHX_THROW(prefix() + "Shapes are not in standard layout");
return *this;
}
......@@ -217,7 +217,7 @@ struct check_shapes
*/
const check_shapes& standard_or_scalar() const
{
if(!this->all_of([](const shape& s) { return s.standard() or s.scalar(); }))
if(not this->all_of([](const shape& s) { return s.standard() or s.scalar(); }))
MIGRAPHX_THROW(prefix() + "Shapes are not a scalar or in standard layout");
return *this;
}
......@@ -227,7 +227,7 @@ struct check_shapes
*/
const check_shapes& packed() const
{
if(!this->all_of([](const shape& s) { return s.packed(); }))
if(not this->all_of([](const shape& s) { return s.packed(); }))
MIGRAPHX_THROW(prefix() + "Shapes are not packed");
return *this;
}
......@@ -237,7 +237,7 @@ struct check_shapes
*/
const check_shapes& packed_or_broadcasted() const
{
if(!this->all_of([](const shape& s) { return s.packed() or s.broadcasted(); }))
if(not this->all_of([](const shape& s) { return s.packed() or s.broadcasted(); }))
MIGRAPHX_THROW(prefix() + "Shapes are not packed nor broadcasted");
return *this;
}
......@@ -247,7 +247,7 @@ struct check_shapes
*/
const check_shapes& tuple_type() const
{
if(!this->all_of([](const shape& s) { return s.type() == shape::tuple_type; }))
if(not this->all_of([](const shape& s) { return s.type() == shape::tuple_type; }))
MIGRAPHX_THROW(prefix() + "Shapes are not tuple!");
return *this;
}
......@@ -257,7 +257,7 @@ struct check_shapes
*/
const check_shapes& not_transposed() const
{
if(!this->all_of([](const shape& s) { return not s.transposed(); }))
if(not this->all_of([](const shape& s) { return not s.transposed(); }))
MIGRAPHX_THROW(prefix() + "Shapes are transposed");
return *this;
}
......@@ -267,7 +267,7 @@ struct check_shapes
*/
const check_shapes& not_broadcasted() const
{
if(!this->all_of([](const shape& s) { return not s.broadcasted(); }))
if(not this->all_of([](const shape& s) { return not s.broadcasted(); }))
MIGRAPHX_THROW(prefix() + "Shapes are broadcasted");
return *this;
}
......@@ -278,7 +278,7 @@ struct check_shapes
*/
const check_shapes& elements(std::size_t n) const
{
if(!this->all_of([&](const shape& s) { return s.elements() == n; }))
if(not this->all_of([&](const shape& s) { return s.elements() == n; }))
MIGRAPHX_THROW(prefix() + "Wrong number of elements");
return *this;
}
......@@ -288,7 +288,8 @@ struct check_shapes
*/
const check_shapes& batch_not_transposed() const
{
if(!this->all_of([&](const shape& s) { return batch_not_transposed_strides(s.strides()); }))
if(not this->all_of(
[&](const shape& s) { return batch_not_transposed_strides(s.strides()); }))
MIGRAPHX_THROW(prefix() + "Batch size is transposed");
return *this;
}
......
......@@ -183,7 +183,7 @@ struct concat_optimization
template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
private_detail_te_handle_type(
PrivateDetailTypeErasedT value,
typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
int>::type* = nullptr) noexcept
: private_detail_te_value(std::move(value))
{
......@@ -233,7 +233,7 @@ struct concat_optimization
private_detail_te_handle_base_type& private_detail_te_get_handle()
{
assert(private_detail_te_handle_mem_var != nullptr);
if(!private_detail_te_handle_mem_var.unique())
if(not private_detail_te_handle_mem_var.unique())
private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
return *private_detail_te_handle_mem_var;
}
......
......@@ -246,7 +246,7 @@ struct context
template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
private_detail_te_handle_type(
PrivateDetailTypeErasedT value,
typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
int>::type* = nullptr) noexcept
: private_detail_te_value(std::move(value))
{
......@@ -306,7 +306,7 @@ struct context
private_detail_te_handle_base_type& private_detail_te_get_handle()
{
assert(private_detail_te_handle_mem_var != nullptr);
if(!private_detail_te_handle_mem_var.unique())
if(not private_detail_te_handle_mem_var.unique())
private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
return *private_detail_te_handle_mem_var;
}
......
......@@ -31,9 +31,9 @@ namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
template <class Iterator, class EndIterator>
auto is_end(rank<2>, Iterator it, EndIterator) -> decltype(!it._M_dereferenceable())
auto is_end(rank<2>, Iterator it, EndIterator) -> decltype(not it._M_dereferenceable())
{
return !it._M_dereferenceable();
return not it._M_dereferenceable();
}
template <class Iterator, class EndIterator>
......
......@@ -27,6 +27,8 @@
#include <migraphx/config.hpp>
#include <migraphx/operation.hpp>
#include <migraphx/value.hpp>
#include <migraphx/json.hpp>
#include <migraphx/convert_to_json.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -46,6 +48,8 @@ operation make_op(const std::string& name, const Value& v)
return make_op_from_value(name, v);
}
operation make_json_op(const std::string& name, const std::string& s);
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
......
......@@ -181,7 +181,7 @@ struct marker
template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
private_detail_te_handle_type(
PrivateDetailTypeErasedT value,
typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
int>::type* = nullptr) noexcept
: private_detail_te_value(std::move(value))
{
......@@ -233,7 +233,7 @@ struct marker
private_detail_te_handle_base_type& private_detail_te_get_handle()
{
assert(private_detail_te_handle_mem_var != nullptr);
if(!private_detail_te_handle_mem_var.unique())
if(not private_detail_te_handle_mem_var.unique())
private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
return *private_detail_te_handle_mem_var;
}
......
......@@ -38,11 +38,11 @@ struct gelu_erf_matcher
F f;
auto erf_fn() const
{
return f("erf")(
used_once(),
arg(0)(used_once(),
f("mul")(either_arg(0, 1)(none_of(has_value(M_SQRT1_2, 1e-3)).bind("x"),
has_value(M_SQRT1_2, 1e-3)))));
auto mul_1_sqrt_2 = f("mul")(either_arg(0, 1)(none_of(has_value(M_SQRT1_2, 1e-3)).bind("x"),
has_value(M_SQRT1_2, 1e-3)));
auto div_sqrt_2 =
f("div")(args(none_of(has_value(M_SQRT2, 1e-3)).bind("x"), has_value(M_SQRT2, 1e-3)));
return f("erf")(used_once(), arg(0)(used_once(), any_of(mul_1_sqrt_2, div_sqrt_2)));
}
auto add_erf() const
......
......@@ -50,8 +50,8 @@ struct layernorm_matcher
{
return f("div")(arg(0)(x_minus_mean()),
arg(1)(skip_broadcasts(f("sqrt")(
arg(0)(f("add")(either_arg(0, 1)(variance(), has_value(1e-12f))))))));
arg(1)(skip_broadcasts(f("sqrt")(arg(0)(
f("add")(either_arg(0, 1)(variance(), is_constant().bind("eps"))))))));
}
auto matcher() const { return layernorm_onnx(); }
......
......@@ -564,6 +564,11 @@ MIGRAPHX_BASIC_MATCHER(is_unused, const matcher_context& ctx, instruction_ref in
return nullopt;
}
MIGRAPHX_PRED_MATCHER(broadcast, instruction_ref ins)
{
return contains({"broadcast", "multibroadcast"}, ins->name());
}
template <class... Ms>
auto skip(Ms... ms)
{
......@@ -813,8 +818,7 @@ inline auto has_attribute(const std::string& name)
template <class... Ms>
auto pointwise(Ms... ms)
{
return match::has_attribute("pointwise")(match::any_of(match::nargs(1), match::nargs(2)),
ms...);
return match::has_attribute("pointwise")(ms...);
}
} // namespace match
......
......@@ -219,7 +219,7 @@ struct module
friend std::ostream& operator<<(std::ostream& os, const module& m);
friend bool operator==(const module& x, const module& y);
friend bool operator!=(const module& x, const module& y) { return !(x == y); }
friend bool operator!=(const module& x, const module& y) { return not(x == y); }
private:
void assign(const module& m);
......
......@@ -35,17 +35,13 @@ struct onnx_options
{
/// Old way to set default fixed dimension size
std::size_t default_dim_value = 0;
/*!
* Default dynamic dimension size (if both default_dim_value and default_dyn_dim_value
* set parser throws)
*/
/// Default dynamic dimension size (if both default_dim_value and default_dyn_dim_value set
/// parser throws)
shape::dynamic_dimension default_dyn_dim_value = {1, 1, 0};
/// Explicitly specify the dims of an input
std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims = {};
/*!
* Explicitly specify dynamic dims of an input (if both map_input_dims and
* map_dyn_input_dims set parser throws)
*/
/// Explicitly specify dynamic dims of an input (if both map_input_dims and map_dyn_input_dims
/// set parser throws)
std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims = {};
/// Continue parsing onnx file if an unknown operator is found
bool skip_unknown_operators = false;
......@@ -53,6 +49,8 @@ struct onnx_options
bool print_program_on_error = false;
/// Max iter num for the loop operator
int64_t max_loop_iterations = 10;
/// Use dynamic output for operators when available
bool use_dyn_output = false;
};
/// Create a program from an onnx file
......
......@@ -70,7 +70,7 @@ struct broadcast
MIGRAPHX_THROW("BROADCAST: (broadcast ndims - axis) is less than input ndims");
}
if(!std::equal(input.lens().begin(), input.lens().end(), broadcast_lens.begin() + axis))
if(not std::equal(input.lens().begin(), input.lens().end(), broadcast_lens.begin() + axis))
{
MIGRAPHX_THROW("BROADCAST: when broadcasting, succeeding sizes must match");
}
......
......@@ -86,7 +86,7 @@ struct concat
{
if(l != axis)
{
if(!std::all_of(inputs.begin(), inputs.end(), [&](auto s) {
if(not std::all_of(inputs.begin(), inputs.end(), [&](auto s) {
return s.lens()[l] == first_shape_lens[l];
}))
{
......
......@@ -45,7 +45,15 @@ struct convert : unary<convert>
shape compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this}.has(1);
return {target_type, inputs.at(0).lens(), inputs.at(0).strides()};
auto input = inputs.at(0);
if(input.dynamic())
{
return {target_type, input.dyn_dims()};
}
else
{
return {target_type, input.lens(), input.strides()};
}
}
std::string point_op() const
......
......@@ -43,13 +43,14 @@ struct dot
const shape& b = inputs.at(1);
auto t = a.type();
if(!std::all_of(inputs.begin(), inputs.end(), [](auto s) { return s.lens().size() >= 2; }))
if(not std::all_of(
inputs.begin(), inputs.end(), [](auto s) { return s.lens().size() >= 2; }))
{
MIGRAPHX_THROW("DOT: dot only accept 2 or more dims operands");
}
// only handle the case that the batch size of a and b are the same
if(!std::equal(
if(not std::equal(
a.lens().rbegin() + 2, a.lens().rend(), b.lens().rbegin() + 2, b.lens().rend()))
{
MIGRAPHX_THROW("DOT: batch size of A and B mismatch: {" + to_string_range(a.lens()) +
......
......@@ -24,17 +24,8 @@
#ifndef MIGRAPHX_GUARD_OPERATORS_FMOD_HPP
#define MIGRAPHX_GUARD_OPERATORS_FMOD_HPP
#include <array>
#include <migraphx/op/binary.hpp>
#include <migraphx/check_shapes.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/streamutils.hpp>
#include <migraphx/literal.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/config.hpp>
#include <cmath>
#include <utility>
#include <type_traits>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -49,7 +40,6 @@ struct fmod : binary<fmod>
a["commutative"] = false;
return a;
}
std::string point_function() const { return "fmod"; }
auto apply() const
{
return [](auto x, auto y) { return std::fmod(x, y); };
......
......@@ -65,7 +65,7 @@ struct gather
auto lens = inputs[0].lens();
auto type = inputs[0].type();
lens.erase(lens.begin() + axis);
if(!inputs[1].scalar())
if(not inputs[1].scalar())
{
auto ind_lens = inputs[1].lens();
lens.insert(lens.begin() + axis, ind_lens.begin(), ind_lens.end());
......
......@@ -24,17 +24,8 @@
#ifndef MIGRAPHX_GUARD_OPERATORS_MOD_HPP
#define MIGRAPHX_GUARD_OPERATORS_MOD_HPP
#include <array>
#include <migraphx/op/binary.hpp>
#include <migraphx/check_shapes.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/streamutils.hpp>
#include <migraphx/literal.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/config.hpp>
#include <cmath>
#include <utility>
#include <type_traits>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -47,9 +38,9 @@ struct mod : binary<mod>
{
auto a = base_attributes();
a["commutative"] = false;
a["point_op"] = "${function:fmod}((${function:remainder}(${0}, ${1})) + ${1}, ${1})";
return a;
}
std::string point_function() const { return "mod"; }
auto apply() const
{
return [](auto x, auto y) { return std::fmod((std::remainder(x, y)) + y, y); };
......
......@@ -45,11 +45,13 @@ namespace op {
struct nonmaxsuppression
{
bool center_point_box = false;
bool use_dyn_output = false;
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.center_point_box, "center_point_box"));
return pack(f(self.center_point_box, "center_point_box"),
f(self.use_dyn_output, "use_dyn_output"));
}
std::string name() const { return "nonmaxsuppression"; }
......@@ -57,27 +59,81 @@ struct nonmaxsuppression
shape compute_shape(std::vector<shape> inputs) const
{
// requires at least 2 inputs
check_shapes{{inputs.at(0), inputs.at(1)}, *this}.only_dims(3);
auto lens = inputs.front().lens();
check_shapes{{inputs.at(0), inputs.at(1)}, *this, true}.only_dims(3).same_ndims();
auto boxes_max_lens = inputs.at(0).max_lens();
// num batches * num boxes
const auto max_num_boxes = boxes_max_lens.at(0) * boxes_max_lens.at(1);
// check input shape
if(lens[1] != inputs.at(1).lens()[2])
auto fixed_shape_error_check = [&]() {
auto lens = inputs.front().lens();
if(lens[1] != inputs.at(1).lens()[2])
{
MIGRAPHX_THROW(
"NonMaxSuppression: spatial dimension mismatch between boxes and scores input");
}
if(lens[0] != inputs.at(1).lens()[0])
{
MIGRAPHX_THROW(
"NonMaxSuppression: number of batches mismatch between boxes and scores input");
}
};
if(use_dyn_output)
{
MIGRAPHX_THROW(
"NonMaxSuppression: spatial dimension mismatch between boxes and scores input");
if(inputs.at(0).dynamic())
{
// both boxes and scores should be dynamic
// check dynamic dimensions are consistent
const auto boxes_dims = inputs.at(0).dyn_dims();
const auto scores_dims = inputs.at(1).dyn_dims();
if(boxes_dims.at(1) != scores_dims.at(2))
{
MIGRAPHX_THROW("NonMaxSuppression: dynamic spatial dimension mismatch between "
"boxes and scores input");
}
if(boxes_dims.at(0) != scores_dims.at(0))
{
MIGRAPHX_THROW("NonMaxSuppression: dynamic number of batches mismatch between "
"boxes and scores input");
}
}
else if(inputs.at(1).dynamic())
{
// scores has dynamic shape, boxes fixed shape
// check that it is only a dynamic number of classes
const auto scores_dims = inputs.at(1).dyn_dims();
const auto boxes_lens = inputs.at(0).lens();
if(not scores_dims.at(0).is_fixed() or scores_dims.at(0).max != boxes_lens.at(0))
{
MIGRAPHX_THROW("NonMaxSuppression: scores dynamic num_classes; num_batches not "
"fixed or mismatched");
}
if(not scores_dims.at(2).is_fixed() or scores_dims.at(2).max != boxes_lens.at(1))
{
MIGRAPHX_THROW("NonMaxSuppression: scores dynamic num_classes; "
"spatial_dimension not fixed or mismatches");
}
}
else
{
fixed_shape_error_check();
}
std::vector<shape::dynamic_dimension> out_lens = {};
out_lens.push_back({0, max_num_boxes, 0});
out_lens.push_back({3, 3, 0});
return {shape::int64_type, out_lens};
}
// check batch sizes
if(lens[0] != inputs.at(1).lens()[0])
else
{
MIGRAPHX_THROW(
"NonMaxSuppression: number of batches mismatch between boxes and scores input");
if(inputs.at(0).dynamic() or inputs.at(1).dynamic())
{
MIGRAPHX_THROW(
"NonMaxSuppression: dynamic input shape with use_dyn_output set to false");
}
fixed_shape_error_check();
std::vector<std::size_t> out_lens = {max_num_boxes, 3};
return {shape::int64_type, out_lens};
}
std::vector<int64_t> out_lens(2);
out_lens.at(0) = lens.at(1);
out_lens.at(1) = 3;
return {shape::int64_type, out_lens};
}
struct box
......@@ -181,13 +237,13 @@ struct nonmaxsuppression
}
template <class Output, class Boxes, class Scores>
void compute_nms(Output output,
Boxes boxes,
Scores scores,
const shape& output_shape,
std::size_t max_output_boxes_per_class,
double iou_threshold,
double score_threshold) const
std::size_t compute_nms(Output output,
Boxes boxes,
Scores scores,
const shape& max_output_shape,
std::size_t max_output_boxes_per_class,
double iou_threshold,
double score_threshold) const
{
std::fill(output.begin(), output.end(), 0);
const auto& lens = scores.get_shape().lens();
......@@ -197,7 +253,7 @@ struct nonmaxsuppression
// boxes of a class with NMS applied [score, index]
std::vector<std::pair<double, int64_t>> selected_boxes_inside_class;
std::vector<int64_t> selected_indices;
selected_boxes_inside_class.reserve(output_shape.elements());
selected_boxes_inside_class.reserve(max_output_shape.elements());
// iterate over batches and classes
shape comp_s{shape::double_type, {num_batches, num_classes}};
shape_for_each(comp_s, [&](auto idx) {
......@@ -210,7 +266,7 @@ struct nonmaxsuppression
auto boxes_heap = filter_boxes_by_score(scores_start, num_boxes, score_threshold);
selected_boxes_inside_class.clear();
// Get the next box with top score, filter by iou_threshold
while(!boxes_heap.empty() &&
while(not boxes_heap.empty() &&
selected_boxes_inside_class.size() < max_output_boxes_per_class)
{
// Check with existing selected boxes for this class, remove box if it
......@@ -237,11 +293,14 @@ struct nonmaxsuppression
}
});
std::copy(selected_indices.begin(), selected_indices.end(), output.begin());
return selected_indices.size() / 3;
}
argument compute(const shape& output_shape, std::vector<argument> args) const
{
argument result{output_shape};
// make buffer of maximum size
shape max_output_shape = {output_shape.type(), output_shape.max_lens()};
argument result{max_output_shape};
std::size_t max_output_boxes_per_class =
(args.size() > 2) ? (args.at(2).at<std::size_t>()) : 0;
......@@ -249,22 +308,29 @@ struct nonmaxsuppression
{
return result;
}
double iou_threshold = (args.size() > 3) ? (args.at(3).at<double>()) : 0.0f;
double score_threshold = (args.size() > 4) ? (args.at(4).at<double>()) : 0.0f;
double iou_threshold = (args.size() > 3) ? (args.at(3).at<double>()) : 0.0f;
double score_threshold = (args.size() > 4) ? (args.at(4).at<double>()) : 0.0f;
std::size_t num_selected = 0;
result.visit([&](auto output) {
visit_all(args[0], args[1])([&](auto boxes, auto scores) {
compute_nms(output,
boxes,
scores,
output_shape,
max_output_boxes_per_class,
iou_threshold,
score_threshold);
num_selected = compute_nms(output,
boxes,
scores,
max_output_shape,
max_output_boxes_per_class,
iou_threshold,
score_threshold);
});
});
return result;
if(use_dyn_output)
{
return result.reshape({output_shape.type(), {num_selected, 3}});
}
else
{
return result;
}
}
};
......
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