Commit 4da0e5e6 authored by Shucai Xiao's avatar Shucai Xiao
Browse files

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

parents c8dc5f7b 2a79a9ff
...@@ -142,10 +142,12 @@ jobs: ...@@ -142,10 +142,12 @@ jobs:
with: with:
python-version: 3.6 python-version: 3.6
- name: Install pyflakes - name: Install pyflakes
run: pip install pyflakes==2.3.1 run: pip install pyflakes==2.3.1 mypy==0.931
- name: Run pyflakes - name: Run pyflakes
run: pyflakes examples/ tools/ src/ test/ doc/ run: |
pyflakes examples/ tools/ src/ test/ doc/
mypy tools/api.py
linux: linux:
......
...@@ -163,9 +163,9 @@ static std::string get_nearest_mode(const onnx_parser::attribute_map& attr) ...@@ -163,9 +163,9 @@ static std::string get_nearest_mode(const onnx_parser::attribute_map& attr)
struct parse_resize : op_parser<parse_resize> struct parse_resize : op_parser<parse_resize>
{ {
std::vector<op_desc> operators() const { return {{"Resize"}}; } std::vector<op_desc> operators() const { return {{"Resize"}, {"Upsample"}}; }
instruction_ref parse(const op_desc& /*opd*/, instruction_ref parse(const op_desc& opd,
const onnx_parser& /*parser*/, const onnx_parser& /*parser*/,
onnx_parser::node_info info, onnx_parser::node_info info,
std::vector<instruction_ref> args) const std::vector<instruction_ref> args) const
...@@ -183,7 +183,7 @@ struct parse_resize : op_parser<parse_resize> ...@@ -183,7 +183,7 @@ struct parse_resize : op_parser<parse_resize>
if(contains(info.attributes, "exclude_outside") and if(contains(info.attributes, "exclude_outside") and
info.attributes.at("exclude_outside").i() == 1) info.attributes.at("exclude_outside").i() == 1)
{ {
MIGRAPHX_THROW("PARSE_RESIZE: exclude_outside 1 is not supported!"); MIGRAPHX_THROW("PARSE_" + opd.op_name + ": exclude_outside 1 is not supported!");
} }
// input data shape info // input data shape info
...@@ -215,12 +215,14 @@ struct parse_resize : op_parser<parse_resize> ...@@ -215,12 +215,14 @@ struct parse_resize : op_parser<parse_resize>
if(type == shape::int64_type) if(type == shape::int64_type)
{ {
auto arg_out_s = arg->eval(); auto arg_out_s = arg->eval();
check_arg_empty(arg_out_s, "PARSE_RESIZE: dynamic output size is not supported!"); check_arg_empty(arg_out_s,
"PARSE_" + opd.op_name + ": dynamic output size is not supported!");
arg_out_s.visit([&](auto ol) { out_lens.assign(ol.begin(), ol.end()); }); arg_out_s.visit([&](auto ol) { out_lens.assign(ol.begin(), ol.end()); });
if(out_lens.size() != in_lens.size()) if(out_lens.size() != in_lens.size())
{ {
MIGRAPHX_THROW("PARSE_RESIZE: specified output size does not match input size"); MIGRAPHX_THROW("PARSE_" + opd.op_name +
": specified output size does not match input size");
} }
// compute the scale // compute the scale
...@@ -239,12 +241,14 @@ struct parse_resize : op_parser<parse_resize> ...@@ -239,12 +241,14 @@ struct parse_resize : op_parser<parse_resize>
{ {
auto arg_scale = arg->eval(); auto arg_scale = arg->eval();
check_arg_empty(arg_scale, check_arg_empty(arg_scale,
"PARSE_RESIZE: dynamic input scale is not supported!"); "PARSE_" + opd.op_name +
": dynamic input scale is not supported!");
arg_scale.visit([&](auto v) { vec_scale.assign(v.begin(), v.end()); }); arg_scale.visit([&](auto v) { vec_scale.assign(v.begin(), v.end()); });
if(in_lens.size() != vec_scale.size()) if(in_lens.size() != vec_scale.size())
{ {
MIGRAPHX_THROW("PARSE_RESIZE: ranks of input and scale are different!"); MIGRAPHX_THROW("PARSE_" + opd.op_name +
": ranks of input and scale are different!");
} }
std::transform(in_lens.begin(), std::transform(in_lens.begin(),
......
#include <migraphx/onnx/op_parser.hpp>
#include <migraphx/onnx/checks.hpp>
#include <migraphx/ranges.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/make_op.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace onnx {
struct parse_upsample : op_parser<parse_upsample>
{
std::vector<op_desc> operators() const { return {{"Upsample"}}; }
instruction_ref parse(const op_desc& /*opd*/,
const onnx_parser& /*parser*/,
onnx_parser::node_info info,
std::vector<instruction_ref> args) const
{
if(contains(info.attributes, "mode"))
{
auto mode = info.attributes.at("mode").s();
if(mode != "nearest")
{
MIGRAPHX_THROW("PARSE_UPSAMPLE: only nearest mode is supported!");
}
}
auto arg_scale = args[1]->eval();
check_arg_empty(arg_scale, "PARSE_UPSAMPLE: only constant scale is supported!");
std::vector<float> vec_scale;
arg_scale.visit([&](auto v) { vec_scale.assign(v.begin(), v.end()); });
auto in_s = args[0]->get_shape();
auto in_lens = in_s.lens();
if(in_lens.size() != vec_scale.size())
{
MIGRAPHX_THROW("PARSE_UPSAMPLE: ranks of input and scale are different!");
}
std::vector<std::size_t> out_lens(in_lens.size());
std::transform(in_lens.begin(),
in_lens.end(),
vec_scale.begin(),
out_lens.begin(),
[&](auto idx, auto scale) { return static_cast<std::size_t>(idx * scale); });
std::vector<float> idx_scale(in_lens.size());
std::transform(
out_lens.begin(),
out_lens.end(),
in_lens.begin(),
idx_scale.begin(),
[](auto od, auto id) { return (od == id) ? 1.0f : (id - 1.0f) / (od - 1.0f); });
shape out_s{in_s.type(), out_lens};
std::vector<int> ind(out_s.elements());
// map out_idx to in_idx
shape_for_each(out_s, [&](auto idx) {
auto in_idx = idx;
std::transform(idx.begin(),
idx.end(),
idx_scale.begin(),
in_idx.begin(),
// nearest mode
[](auto index, auto scale) {
return static_cast<std::size_t>(std::round(index * scale));
});
ind[out_s.index(idx)] = static_cast<int64_t>(in_s.index(in_idx));
});
// reshape input to one-dimension
std::vector<int64_t> rsp_lens = {static_cast<int64_t>(in_s.elements())};
shape ind_s{shape::int32_type, out_lens};
auto rsp = info.add_instruction(make_op("reshape", {{"dims", rsp_lens}}), args[0]);
auto ins_ind = info.add_literal(literal(ind_s, ind));
return info.add_instruction(make_op("gather", {{"axis", 0}}), rsp, ins_ind);
}
};
} // namespace onnx
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
...@@ -5074,6 +5074,25 @@ def unknown_aten_test(): ...@@ -5074,6 +5074,25 @@ def unknown_aten_test():
return ([node], [x, y], [a]) return ([node], [x, y], [a])
@onnx_test
def upsample_linear_test():
scales = np.array([1.0, 1.0, 2.0, 2.0], dtype=np.float32)
scales_tensor = helper.make_tensor(name='scales',
data_type=TensorProto.FLOAT,
dims=scales.shape,
vals=scales.flatten().astype(
np.float32))
X = helper.make_tensor_value_info('X', TensorProto.FLOAT, [1, 1, 2, 2])
Y = helper.make_tensor_value_info('Y', TensorProto.FLOAT, [])
node = onnx.helper.make_node('Upsample',
inputs=['X', '', 'scales'],
outputs=['Y'],
mode='linear')
return ([node], [X], [Y], [scales_tensor])
@onnx_test @onnx_test
def upsample_test(): def upsample_test():
scales = np.array([1.0, 1.0, 2.0, 3.0], dtype=np.float32) scales = np.array([1.0, 1.0, 2.0, 3.0], dtype=np.float32)
......
...@@ -3643,7 +3643,7 @@ TEST_CASE(resize_nonstd_input_test) ...@@ -3643,7 +3643,7 @@ TEST_CASE(resize_nonstd_input_test)
EXPECT(p == prog); EXPECT(p == prog);
} }
TEST_CASE(resize_upsample_linear_ac_test) static auto create_upsample_linear_prog()
{ {
migraphx::program p; migraphx::program p;
auto* mm = p.get_main_module(); auto* mm = p.get_main_module();
...@@ -3734,6 +3734,12 @@ TEST_CASE(resize_upsample_linear_ac_test) ...@@ -3734,6 +3734,12 @@ TEST_CASE(resize_upsample_linear_ac_test)
auto add1 = mm->add_instruction(migraphx::make_op("add"), mul1, slc10); auto add1 = mm->add_instruction(migraphx::make_op("add"), mul1, slc10);
mm->add_return({add1}); mm->add_return({add1});
return p;
}
TEST_CASE(resize_upsample_linear_ac_test)
{
auto p = create_upsample_linear_prog();
auto prog = migraphx::parse_onnx("resize_upsample_linear_ac_test.onnx"); auto prog = migraphx::parse_onnx("resize_upsample_linear_ac_test.onnx");
EXPECT(p == prog); EXPECT(p == prog);
} }
...@@ -4753,6 +4759,13 @@ TEST_CASE(unknown_test_throw) ...@@ -4753,6 +4759,13 @@ TEST_CASE(unknown_test_throw)
EXPECT(test::throws([&] { migraphx::parse_onnx("unknown_test.onnx"); })); EXPECT(test::throws([&] { migraphx::parse_onnx("unknown_test.onnx"); }));
} }
TEST_CASE(upsample_linear_test)
{
auto p = create_upsample_linear_prog();
auto prog = migraphx::parse_onnx("upsample_linear_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(upsample_test) TEST_CASE(upsample_test)
{ {
migraphx::program p; migraphx::program p;
......
This diff is collapsed.
DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )" DIR="$( cd "$( dirname "${BASH_SOURCE[0]}" )" && pwd )"
SRC_DIR=$DIR/../src SRC_DIR=$DIR/../src
ls -1 $DIR/include/ | xargs -n 1 -P $(nproc) -I{} -t bash -c "python3.6 $DIR/te.py $DIR/include/{} | clang-format-5.0 -style=file > $SRC_DIR/include/migraphx/{}" PYTHON=python3
if type -p python3.6 > /dev/null ; then
PYTHON=python3.6
fi
if type -p python3.8 > /dev/null ; then
PYTHON=python3.8
fi
ls -1 $DIR/include/ | xargs -n 1 -P $(nproc) -I{} -t bash -c "$PYTHON $DIR/te.py $DIR/include/{} | clang-format-5.0 -style=file > $SRC_DIR/include/migraphx/{}"
function api { function api {
python3.6 $DIR/api.py $SRC_DIR/api/migraphx.py $1 | clang-format-5.0 -style=file > $2 $PYTHON $DIR/api.py $SRC_DIR/api/migraphx.py $1 | clang-format-5.0 -style=file > $2
} }
api $DIR/api/migraphx.h $SRC_DIR/api/include/migraphx/migraphx.h api $DIR/api/migraphx.h $SRC_DIR/api/include/migraphx/migraphx.h
......
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