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Commit f06f6aa3 authored by Shucai Xiao's avatar Shucai Xiao
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merge changes from develop branch

parents 80a35596 ebfe9735
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Showing with 851 additions and 122 deletions
src/targets/gpu/lowering.cpp
View file @ f06f6aa3
......@@ -11,6 +11,8 @@
#include <migraphx/gpu/device/contiguous.hpp>
#include <migraphx/gpu/device/add.hpp>
#include <migraphx/iterator_for.hpp>
#include <migraphx/gpu/argmax.hpp>
#include <migraphx/gpu/argmin.hpp>
#include <migraphx/gpu/rocblas.hpp>
#include <migraphx/gpu/context.hpp>
#include <migraphx/gpu/convolution.hpp>
......@@ -26,6 +28,7 @@
#include <migraphx/gpu/add.hpp>
#include <migraphx/gpu/sub.hpp>
#include <migraphx/gpu/exp.hpp>
#include <migraphx/gpu/erf.hpp>
#include <migraphx/gpu/log.hpp>
#include <migraphx/gpu/sin.hpp>
#include <migraphx/gpu/cos.hpp>
......@@ -49,6 +52,7 @@
#include <migraphx/gpu/lrn.hpp>
#include <migraphx/gpu/convert.hpp>
#include <migraphx/gpu/clip.hpp>
#include <migraphx/gpu/reduce_sum.hpp>
#include <utility>
#include <functional>
#include <algorithm>
......@@ -85,6 +89,7 @@ struct miopen_apply
add_generic_op<hip_add>("add");
add_generic_op<hip_sub>("sub");
add_generic_op<hip_exp>("exp");
add_generic_op<hip_erf>("erf");
add_generic_op<hip_log>("log");
add_generic_op<hip_sin>("sin");
add_generic_op<hip_cos>("cos");
......@@ -103,10 +108,13 @@ struct miopen_apply
add_extend_op<hip_concat, op::concat>("concat");
add_extend_op<hip_softmax, op::softmax>("softmax");
add_extend_op<hip_logsoftmax, op::logsoftmax>("logsoftmax");
add_extend_op<hip_argmax, op::argmax>("argmax");
add_extend_op<hip_argmin, op::argmin>("argmin");
add_extend_op<hip_gather, op::gather>("gather");
add_extend_op<hip_pad, op::pad>("pad");
add_extend_op<hip_convert, op::convert>("convert");
add_extend_op<hip_clip, op::clip>("clip");
add_extend_op<hip_reduce_sum, op::reduce_sum>("reduce_sum");
add_lrn_op();
add_convolution_op();
......
src/targets/gpu/reduce_sum.cpp 0 → 100644
View file @ f06f6aa3
#include <migraphx/gpu/reduce_sum.hpp>
#include <migraphx/gpu/context.hpp>
#include <migraphx/gpu/device/reduce_sum.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace gpu {
shape hip_reduce_sum::compute_shape(std::vector<shape> inputs) const
{
inputs.pop_back();
return op.compute_shape(inputs);
}
argument
hip_reduce_sum::compute(context& ctx, const shape&, const std::vector<argument>& args) const
{
device::reduce_sum(ctx.get_stream().get(), args.back(), args.front());
return args.back();
}
} // namespace gpu
} // namespace MIGRAPHX_INLINE_NS
} // namespace migraphx
src/targets/gpu/softmax.cpp
View file @ f06f6aa3
......@@ -37,11 +37,10 @@ shape hip_softmax::compute_shape(const std::vector<shape>& inputs) const
return op.compute_shape({inputs.at(0)});
}
argument hip_softmax::compute(context& ctx,
const shape& output_shape,
const std::vector<argument>& args) const
argument hip_softmax::compute(context& ctx, const shape&, const std::vector<argument>& args) const
{
return device::softmax(ctx.get_stream().get(), output_shape, args, op.axis);
device::softmax(ctx.get_stream().get(), args.back(), args.front(), op.axis);
return args.back();
}
} // namespace gpu
......
src/targets/gpu/target.cpp
View file @ f06f6aa3
......@@ -36,6 +36,8 @@ std::vector<pass> target::get_passes(migraphx::context& gctx) const
// clang-format off
return
{
dead_code_elimination{},
simplify_reshapes{},
dead_code_elimination{},
eliminate_identity{},
eliminate_pad{},
......@@ -48,11 +50,11 @@ std::vector<pass> target::get_passes(migraphx::context& gctx) const
//dead_code_elimination{},
simplify_algebra{},
dead_code_elimination{},
propagate_constant{},
dead_code_elimination{},
auto_contiguous{},
simplify_reshapes{},
dead_code_elimination{},
propagate_constant{},
dead_code_elimination{},
lowering{ctx},
eliminate_concat{concat_gpu_optimization{}},
dead_code_elimination{},
......
src/tf/tf.cpp
View file @ f06f6aa3
......@@ -37,6 +37,48 @@ struct tf_parser
std::unordered_map<std::string, op_func> ops;
bool should_transpose(instruction_ref ins) const
{
return is_nhwc and ins->get_shape().lens().size() == 4;
}
instruction_ref to_nhwc(instruction_ref ins)
{
if(should_transpose(ins))
return prog.add_instruction(op::transpose{{0, 2, 3, 1}}, ins);
return ins;
}
instruction_ref to_nchw(instruction_ref ins)
{
if(should_transpose(ins))
return prog.add_instruction(op::transpose{{0, 3, 1, 2}}, ins);
return ins;
}
instruction_ref to_kcxy(instruction_ref ins)
{
if(should_transpose(ins))
return prog.add_instruction(op::transpose{{3, 2, 0, 1}}, ins);
return ins;
}
instruction_ref make_contiguous(instruction_ref ins)
{
if(ins->get_shape().standard())
return ins;
else
return prog.add_instruction(op::contiguous{}, ins);
}
std::vector<instruction_ref> to_nchw(const std::vector<instruction_ref>& args)
{
std::vector<instruction_ref> result(args.size());
std::transform(
args.begin(), args.end(), result.begin(), [&](auto ins) { return this->to_nchw(ins); });
return result;
}
std::vector<size_t> parse_axes(const attribute_map& attributes, const std::string& s) const
{
auto attrs = attributes.at(s).list().i();
......@@ -111,65 +153,75 @@ struct tf_parser
add_generic_op("Identity", op::identity{});
add_generic_op("Relu", op::relu{});
add_generic_op("Relu6", op::clip{6.0, 0.0});
add_generic_op("Tanh", op::tanh{});
add_binary_op("Add", op::add{});
add_binary_op("Mul", op::mul{});
add_binary_op("Sub", op::sub{});
add_mem_op("AvgPool", &tf_parser::parse_pooling);
add_mem_op("BiasAdd", &tf_parser::parse_biasadd);
add_mem_op("ConcatV2", &tf_parser::parse_concat);
add_mem_op("ConcatV2", &tf_parser::parse_concat, false);
add_mem_op("Const", &tf_parser::parse_constant);
add_mem_op("Conv2D", &tf_parser::parse_conv);
add_mem_op("DepthwiseConv2dNative", &tf_parser::parse_depthwiseconv);
add_mem_op("FusedBatchNorm", &tf_parser::parse_batchnorm);
add_mem_op("MatMul", &tf_parser::parse_matmul);
add_mem_op("MatMul", &tf_parser::parse_matmul, false);
add_mem_op("MaxPool", &tf_parser::parse_pooling);
add_mem_op("Mean", &tf_parser::parse_mean);
add_mem_op("Pack", &tf_parser::parse_pack);
add_mem_op("Pack", &tf_parser::parse_pack, false);
add_mem_op("Pad", &tf_parser::parse_pad);
add_mem_op("Reshape", &tf_parser::parse_reshape);
add_mem_op("Reshape", &tf_parser::parse_reshape, false);
add_mem_op("Softmax", &tf_parser::parse_softmax);
add_mem_op("Squeeze", &tf_parser::parse_squeeze);
add_mem_op("Squeeze", &tf_parser::parse_squeeze, false);
add_mem_op("StridedSlice", &tf_parser::parse_stridedslice);
}
template <class F>
void add_op(std::string name, F f)
void add_op(std::string name, F f, bool transpose = true)
{
ops.emplace(name, f);
}
// Multi output op
template <class F>
void add_multi_op(std::string name, F f)
{
ops.emplace(name, f);
if(transpose)
{
ops.emplace(name,
op_func{[=](const attribute_map& attributes,
const std::vector<instruction_ref>& args) -> instruction_ref {
return to_nhwc(f(attributes, to_nchw(args)));
}});
}
else
{
ops.emplace(name, f);
}
}
template <class F>
void add_mem_op(std::string name, F f)
void add_mem_op(std::string name, F f, bool transpose = true)
{
add_op(name, [=](auto&&... xs) {
return std::mem_fn(f)(*this, name, std::forward<decltype(xs)>(xs)...);
});
add_op(name,
[=](auto&&... xs) {
return std::mem_fn(f)(*this, name, std::forward<decltype(xs)>(xs)...);
},
transpose);
}
template <class T>
void add_binary_op(std::string name, T x)
{
add_op(name, [this, x](const attribute_map& attributes, std::vector<instruction_ref> args) {
if(args.size() != 2)
MIGRAPHX_THROW("binary operators should have 2 operands");
auto l0 = args[1];
if(contains(attributes, "data_format"))
{
if(is_nhwc)
{
l0 = prog.add_instruction(op::transpose{{0, 3, 1, 2}}, args[1]);
}
}
return add_broadcastable_binary_op(args[0], l0, x);
});
add_op(name,
[this, x](const attribute_map&, std::vector<instruction_ref> args) {
if(args.size() != 2)
MIGRAPHX_THROW("binary operators should have 2 operands");
// TODO
// if(contains(attributes, "data_format"))
// {
// if(is_nhwc)
// {
// l0 = prog.add_instruction(op::transpose{{0, 3, 1, 2}}, args[1]);
// }
// }
return add_broadcastable_binary_op(args[0], args[1], x);
},
false);
}
template <class T>
......@@ -208,20 +260,22 @@ struct tf_parser
auto l0 = prog.add_instruction(op::multibroadcast{output_lens}, arg0);
auto l1 = prog.add_instruction(op::multibroadcast{output_lens}, arg1);
return prog.add_instruction(x, l0, l1);
return to_nhwc(prog.add_instruction(x, to_nchw(l0), to_nchw(l1)));
}
else
{
return prog.add_instruction(x, {arg0, arg1});
return to_nhwc(prog.add_instruction(x, {to_nchw(arg0), to_nchw(arg1)}));
}
}
template <class T>
void add_generic_op(std::string name, T x)
void add_generic_op(std::string name, T x, bool transpose = true)
{
add_op(name, [this, x](const attribute_map&, std::vector<instruction_ref> args) {
return prog.add_instruction(x, args);
});
add_op(name,
[this, x](const attribute_map&, std::vector<instruction_ref> args) {
return prog.add_instruction(x, args);
},
transpose);
}
instruction_ref
......@@ -251,7 +305,7 @@ struct tf_parser
{
// get index for axis within args
size_t axis_idx = attributes.at("N").i();
size_t axis = parse_axis(args[axis_idx]->eval().at<int64_t>());
size_t axis = args[axis_idx]->eval().at<int64_t>();
op::concat op{axis};
// return only first N arguments (assuming last index is the axis value)
return prog.add_instruction(
......@@ -262,16 +316,8 @@ struct tf_parser
attribute_map attributes,
const std::vector<instruction_ref>&)
{
literal v = parse_tensor(attributes.at("value").tensor());
auto l0 = prog.add_literal(v);
size_t num_axes = l0->get_shape().lens().size();
if(num_axes >= 4)
{
std::vector<int64_t> transpose_axes = get_axes(num_axes);
reorder_data(transpose_axes);
l0 = prog.add_instruction(op::transpose{transpose_axes}, l0);
}
return l0;
literal v = parse_tensor(attributes.at("value").tensor());
return prog.add_literal(v);
}
instruction_ref
......@@ -302,22 +348,9 @@ struct tf_parser
op.dilation[0] = dilation[2];
op.dilation[1] = dilation[3];
}
auto weights = args[1];
// check if weights are from a constant
if(weights->name() != "@param")
{
if(is_nhwc)
{
weights = prog.add_instruction(op::transpose{{1, 3, 0, 2}}, args[1]);
}
else
{
weights = prog.add_instruction(op::transpose{{3, 2, 0, 1}}, args[1]);
}
}
auto l0 = args[0];
auto weights = to_kcxy(args[1]);
auto l0 = args[0];
if(contains(attributes, "padding"))
{
const std::string& pad_mode = attributes.at("padding").s();
......@@ -366,8 +399,7 @@ struct tf_parser
op.padding[1] = padding[1];
}
}
return prog.add_instruction(op, {l0, weights});
return prog.add_instruction(op, {l0, to_kcxy(args[1])});
}
instruction_ref parse_depthwiseconv(const std::string&,
......@@ -390,6 +422,8 @@ struct tf_parser
op.stride[0] = stride[2];
op.stride[1] = stride[3];
}
auto weights = to_kcxy(args[1]);
if(contains(attributes, "dilations"))
{
std::vector<size_t> dilation;
......@@ -403,20 +437,6 @@ struct tf_parser
op.dilation[1] = dilation[3];
}
auto weights = args[1];
// check if weights are from a constant
if(weights->name() != "@param")
{
if(is_nhwc)
{
weights = prog.add_instruction(op::transpose{{1, 3, 0, 2}}, args[1]);
}
else
{
weights = prog.add_instruction(op::transpose{{3, 2, 0, 1}}, args[1]);
}
}
auto l0 = args[0];
if(contains(attributes, "padding"))
{
......@@ -464,8 +484,8 @@ struct tf_parser
new_weights_shape[0] = out_channels;
new_weights_shape[1] = 1;
// Make sure weights are contiguous before doing reshape
auto cweights = prog.add_instruction(op::contiguous{}, weights);
auto new_weights = prog.add_instruction(op::reshape{new_weights_shape}, cweights);
auto new_weights =
prog.add_instruction(op::reshape{new_weights_shape}, make_contiguous(weights));
return prog.add_instruction(op, {l0, new_weights});
}
......@@ -533,16 +553,14 @@ struct tf_parser
MIGRAPHX_THROW("TF_PARSER: axis value of " + to_string(axis) +
" must be smaller than input size " + to_string(input_size));
}
// check if input arg needs axis to be converted to NCHW
if(input_size >= 4)
axis = parse_axis(axis);
std::transform(
args.begin(),
args.end(),
std::back_inserter(unsqueezed_args),
[&](instruction_ref arg) { return prog.add_instruction(op::unsqueeze{{axis}}, arg); });
return prog.add_instruction(op::concat{static_cast<size_t>(axis)}, unsqueezed_args);
return to_nhwc(
prog.add_instruction(op::concat{static_cast<size_t>(axis)}, unsqueezed_args));
}
instruction_ref
......@@ -645,7 +663,7 @@ struct tf_parser
MIGRAPHX_THROW("reshape needs 2 arguments (input, new_shape)");
auto s = args[1]->eval();
s.visit([&](auto v) { copy(v, std::back_inserter(op.dims)); });
return prog.add_instruction(op, args[0]);
return prog.add_instruction(op, make_contiguous(args[0]));
}
void parse_from(std::istream& is)
......@@ -676,7 +694,7 @@ struct tf_parser
std::vector<instruction_ref> args)
{
op::squeeze op;
auto axes = parse_axes(attributes, "squeeze_dims");
auto axes = attributes.at("squeeze_dims").list().i();
copy(axes, std::back_inserter(op.axes));
auto args0_dims = args[0]->get_shape().lens();
if(op.axes.empty()) // no squeeze_dims provided, remove any dim that equals 1
......@@ -689,7 +707,7 @@ struct tf_parser
}
}
}
return prog.add_instruction(op, args[0]);
return prog.add_instruction(op, make_contiguous(args[0]));
}
instruction_ref parse_stridedslice(const std::string&,
......@@ -700,11 +718,6 @@ struct tf_parser
auto starts = args[1]->eval().get<int32_t>().to_vector();
auto ends = args[2]->eval().get<int32_t>().to_vector();
size_t num_axes = args[0]->get_shape().lens().size();
if(num_axes >= 4)
{
reorder_data(starts);
reorder_data(ends);
}
op.starts = std::vector<int64_t>(starts.begin(), starts.end());
op.ends = std::vector<int64_t>(ends.begin(), ends.end());
......@@ -723,13 +736,9 @@ struct tf_parser
if(((shrink_axis_mask >> i) & bitwise_compare) == 1)
squeeze_axes.push_back(i);
}
if(num_axes >= 4)
{
squeeze_axes = parse_axes(squeeze_axes);
}
auto l0 = prog.add_instruction(op, args[0]);
return prog.add_instruction(op::squeeze{squeeze_axes}, l0);
auto l0 = prog.add_instruction(op, make_contiguous(args[0]));
return to_nhwc(prog.add_instruction(op::squeeze{squeeze_axes}, l0));
}
void parse_graph(const tensorflow::GraphDef& graph)
......@@ -746,7 +755,7 @@ struct tf_parser
reorder_data(dims);
}
shape s = shape{shape_type, dims};
instructions[name] = prog.add_parameter(name, s);
instructions[name] = to_nhwc(prog.add_parameter(name, s));
}
for(auto&& p : nodes)
{
......@@ -1096,6 +1105,7 @@ program parse_tf(const std::string& name, bool is_nhwc)
#else
parser.parse_from(input);
#endif
parser.to_nchw(std::prev(parser.prog.end()));
return std::move(parser.prog);
}
......
test/cpu_ops_test.cpp
View file @ f06f6aa3
......@@ -527,6 +527,21 @@ TEST_CASE(exp_test)
EXPECT(migraphx::verify_range(results_vector, gold));
}
TEST_CASE(erf_test)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {4}};
auto l =
p.add_literal(migraphx::literal{s, {0.73785057, 1.58165966, -0.43597795, -0.01677432}});
p.add_instruction(migraphx::op::erf{}, l);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold = {0.70327317, 0.97470088, -0.46247893, -0.01892602};
EXPECT(migraphx::verify_range(results_vector, gold));
}
TEST_CASE(log_test)
{
migraphx::program p;
......@@ -1135,6 +1150,114 @@ TEST_CASE(logsoftmax_test_axis_3)
EXPECT(migraphx::verify_range(results_vector, s));
}
TEST_CASE(argmax_test_0)
{
migraphx::program p;
std::vector<float> data = {1.2255, 1.6834, -2.0305, -0.3221, 0.4701, 0.2583, 0.7545, 2.5758,
-1.6849, 0.0928, 0.9022, -0.8765, -0.4090, 0.9301, 2.0724, -1.5706,
0.4867, -0.1493, 0.6957, -0.2179, 0.7142, 0.7177, 0.0183, 1.3497};
std::vector<int64_t> res_gold = {0, 0, 1, 0, 1, 0, 0, 0, 1, 1, 0, 1};
migraphx::shape data_shape{migraphx::shape::float_type, {2, 3, 4}};
auto dl = p.add_literal(migraphx::literal{data_shape, data});
p.add_instruction(migraphx::op::argmax{0}, dl);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<int64_t> result_vec;
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(result_vec, res_gold));
}
TEST_CASE(argmax_test_1)
{
migraphx::program p;
std::vector<float> data = {1.2255, 1.6834, -2.0305, -0.3221, 0.4701, 0.2583, 0.7545, 2.5758,
-1.6849, 0.0928, 0.9022, -0.8765, -0.4090, 0.9301, 2.0724, -1.5706,
0.4867, -0.1493, 0.6957, -0.2179, 0.7142, 0.7177, 0.0183, 1.3497};
std::vector<int64_t> res_gold = {0, 0, 2, 1, 2, 0, 0, 2};
migraphx::shape data_shape{migraphx::shape::float_type, {2, 3, 4}};
auto dl = p.add_literal(migraphx::literal{data_shape, data});
p.add_instruction(migraphx::op::argmax{1}, dl);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<int64_t> result_vec;
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(result_vec, res_gold));
}
TEST_CASE(argmax_test_2)
{
migraphx::program p;
std::vector<float> data = {1.2255, 1.6834, -2.0305, -0.3221, 0.4701, 0.2583, 0.7545, 2.5758,
-1.6849, 0.0928, 0.9022, -0.8765, -0.4090, 0.9301, 2.0724, -1.5706,
0.4867, -0.1493, 0.6957, -0.2179, 0.7142, 0.7177, 0.0183, 1.3497};
std::vector<int64_t> res_gold = {1, 3, 2, 2, 2, 3};
migraphx::shape data_shape{migraphx::shape::float_type, {2, 3, 4}};
auto dl = p.add_literal(migraphx::literal{data_shape, data});
p.add_instruction(migraphx::op::argmax{2}, dl);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<int64_t> result_vec;
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(result_vec, res_gold));
}
TEST_CASE(argmin_test_0)
{
migraphx::program p;
std::vector<float> data = {1.2255, 1.6834, -2.0305, -0.3221, 0.4701, 0.2583, 0.7545, 2.5758,
-1.6849, 0.0928, 0.9022, -0.8765, -0.4090, 0.9301, 2.0724, -1.5706,
0.4867, -0.1493, 0.6957, -0.2179, 0.7142, 0.7177, 0.0183, 1.3497};
std::vector<int64_t> res_gold = {1, 1, 0, 1, 0, 1, 1, 1, 0, 0, 1, 0};
migraphx::shape data_shape{migraphx::shape::float_type, {2, 3, 4}};
auto dl = p.add_literal(migraphx::literal{data_shape, data});
p.add_instruction(migraphx::op::argmin{0}, dl);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<int64_t> result_vec;
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(result_vec, res_gold));
}
TEST_CASE(argmin_test_1)
{
migraphx::program p;
std::vector<float> data = {1.2255, 1.6834, -2.0305, -0.3221, 0.4701, 0.2583, 0.7545, 2.5758,
-1.6849, 0.0928, 0.9022, -0.8765, -0.4090, 0.9301, 2.0724, -1.5706,
0.4867, -0.1493, 0.6957, -0.2179, 0.7142, 0.7177, 0.0183, 1.3497};
std::vector<int64_t> res_gold = {2, 2, 0, 2, 0, 1, 2, 0};
migraphx::shape data_shape{migraphx::shape::float_type, {2, 3, 4}};
auto dl = p.add_literal(migraphx::literal{data_shape, data});
p.add_instruction(migraphx::op::argmin{1}, dl);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<int64_t> result_vec;
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(result_vec, res_gold));
}
TEST_CASE(argmin_test_2)
{
migraphx::program p;
std::vector<float> data = {1.2255, 1.6834, -2.0305, -0.3221, 0.4701, 0.2583, 0.7545, 2.5758,
-1.6849, 0.0928, 0.9022, -0.8765, -0.4090, 0.9301, 2.0724, -1.5706,
0.4867, -0.1493, 0.6957, -0.2179, 0.7142, 0.7177, 0.0183, 1.3497};
std::vector<int64_t> res_gold = {2, 1, 0, 3, 3, 2};
migraphx::shape data_shape{migraphx::shape::float_type, {2, 3, 4}};
auto dl = p.add_literal(migraphx::literal{data_shape, data});
p.add_instruction(migraphx::op::argmin{2}, dl);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<int64_t> result_vec;
result.visit([&](auto output) { result_vec.assign(output.begin(), output.end()); });
EXPECT(migraphx::verify_range(result_vec, res_gold));
}
TEST_CASE(conv2d_test)
{
migraphx::program p;
......@@ -1681,4 +1804,79 @@ TEST_CASE(clip_test)
EXPECT(migraphx::verify_range(results_vector, gold));
}
TEST_CASE(reduce_sum_test0)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 2, 2}};
auto input = migraphx::literal{s, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}};
auto l0 = p.add_literal(input);
p.add_instruction(migraphx::op::reduce_sum{{0}}, l0);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold{15, 18, 21, 24};
EXPECT(results_vector == gold);
}
TEST_CASE(reduce_sum_test1)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 2, 2}};
auto input = migraphx::literal{s, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}};
auto l0 = p.add_literal(input);
p.add_instruction(migraphx::op::reduce_sum{{1}}, l0);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold{4, 6, 12, 14, 20, 22};
EXPECT(results_vector == gold);
}
TEST_CASE(reduce_sum_test2)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 2, 2}};
auto input = migraphx::literal{s, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}};
auto l0 = p.add_literal(input);
p.add_instruction(migraphx::op::reduce_sum{{2}}, l0);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold{3, 7, 11, 15, 19, 23};
EXPECT(results_vector == gold);
}
TEST_CASE(reduce_sum_test02)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 2, 2}};
auto input = migraphx::literal{s, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}};
auto l0 = p.add_literal(input);
p.add_instruction(migraphx::op::reduce_sum{{0, 2}}, l0);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold{33, 45};
EXPECT(results_vector == gold);
}
TEST_CASE(reduce_sum_test12)
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 2, 2}};
auto input = migraphx::literal{s, {1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}};
auto l0 = p.add_literal(input);
p.add_instruction(migraphx::op::reduce_sum{{1, 2}}, l0);
p.compile(migraphx::cpu::target{});
auto result = p.eval({});
std::vector<float> results_vector;
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
std::vector<float> gold{10, 26, 42};
EXPECT(results_vector == gold);
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
test/matcher.cpp
View file @ f06f6aa3
......@@ -148,6 +148,56 @@ TEST_CASE(match_arg7)
EXPECT(bool{r.result == sum});
}
TEST_CASE(match_arg8)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto sum = p.add_instruction(sum_op{}, one, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("sum")(match::all_of(match::arg(0)(match::name("@literal")),
match::arg(1)(match::name("@literal"))),
match::standard_shape());
auto r = find_match(p, m);
EXPECT(bool{r.result == sum});
}
TEST_CASE(match_nargs1)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto sum = p.add_instruction(sum_op{}, one, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("sum")(match::nargs(2));
auto r = find_match(p, m);
EXPECT(bool{r.result == sum});
}
TEST_CASE(match_nargs2)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto sum = p.add_instruction(sum_op{}, one, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("sum")(match::nargs(2), match::standard_shape());
auto r = find_match(p, m);
EXPECT(bool{r.result == sum});
}
TEST_CASE(match_nargs3)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto sum = p.add_instruction(sum_op{}, one, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("sum")(match::all_of(match::nargs(2)));
auto r = find_match(p, m);
EXPECT(bool{r.result == sum});
}
TEST_CASE(match_args1)
{
migraphx::program p;
......@@ -307,6 +357,19 @@ TEST_CASE(match_all_of2)
EXPECT(bool{r.result == p.end()});
}
TEST_CASE(match_all_of3)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto sum = p.add_instruction(sum_op{}, one, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("sum")(match::all_of(match::all_of(
match::arg(0)(match::name("@literal")), match::arg(1)(match::name("@literal")))));
auto r = find_match(p, m);
EXPECT(bool{r.result == sum});
}
TEST_CASE(match_any_of1)
{
migraphx::program p;
......@@ -359,6 +422,132 @@ TEST_CASE(match_none_of2)
EXPECT(bool{r.result == p.end()});
}
TEST_CASE(match_output1)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus = p.add_instruction(minus_op{}, two, one);
auto sum = p.add_instruction(sum_op{}, minus, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("minus")(match::output(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == minus});
}
TEST_CASE(match_output2)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus = p.add_instruction(minus_op{}, two, one);
auto sum = p.add_instruction(sum_op{}, minus, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("@literal")(match::output(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == p.end()});
}
TEST_CASE(match_skip_output1)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus = p.add_instruction(minus_op{}, two, one);
auto sum = p.add_instruction(sum_op{}, minus, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("minus")(match::skip_output(match::name("pass"))(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == minus});
}
TEST_CASE(match_skip_output2)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus = p.add_instruction(minus_op{}, two, one);
auto minus_pass = p.add_instruction(pass_op{}, minus);
auto sum = p.add_instruction(sum_op{}, minus_pass, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("minus")(match::skip_output(match::name("pass"))(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == minus});
}
TEST_CASE(match_skip_output3)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus = p.add_instruction(minus_op{}, two, one);
auto minus_pass1 = p.add_instruction(pass_op{}, minus);
auto minus_pass2 = p.add_instruction(pass_op{}, minus_pass1);
auto minus_pass3 = p.add_instruction(pass_op{}, minus_pass2);
auto sum = p.add_instruction(sum_op{}, minus_pass3, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("minus")(match::skip_output(match::name("pass"))(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == minus});
}
TEST_CASE(match_skip_output4)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto pass = p.add_instruction(pass_op{}, one);
auto sum = p.add_instruction(sum_op{}, pass, two);
p.add_instruction(pass_op{}, sum);
auto m = match::name("@literal")(match::skip_output(match::name("pass"))(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == two});
}
TEST_CASE(match_skip_output5)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto pass = p.add_instruction(pass_op{}, one);
auto sum1 = p.add_instruction(sum_op{}, pass, two);
auto sum2 = p.add_instruction(sum_op{}, sum1, one);
auto sum3 = p.add_instruction(sum_op{}, sum2, two);
p.add_instruction(pass_op{}, sum3);
auto m = match::name("@literal")(match::skip_output(match::name("pass"))(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == p.end()});
}
TEST_CASE(match_skip_output6)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus = p.add_instruction(minus_op{}, two, one);
auto sum1 = p.add_instruction(sum_op{}, minus, two);
auto sum2 = p.add_instruction(sum_op{}, sum1, one);
auto sum3 = p.add_instruction(sum_op{}, sum2, two);
p.add_instruction(pass_op{}, sum3);
auto m = match::name("minus")(match::skip_output(match::name("pass"))(match::name("sum")));
auto r = find_match(p, m);
EXPECT(bool{r.result == minus});
}
TEST_CASE(match_skip_output7)
{
migraphx::program p;
auto one = p.add_literal(1);
auto two = p.add_literal(2);
auto minus1 = p.add_instruction(minus_op{}, two, one);
auto minus2 = p.add_instruction(minus_op{}, two, minus1);
auto sum = p.add_instruction(sum_op{}, one, minus2);
p.add_instruction(pass_op{}, sum);
auto m = match::name("minus")(match::skip_output(match::name("pass"))(match::name("minus")));
auto r = find_match(p, m);
EXPECT(bool{r.result == minus1});
}
TEST_CASE(match_bind1)
{
migraphx::program p;
......
test/onnx/erf_test.onnx 0 → 100644
View file @ f06f6aa3
 erf-example:A
xy"Erftest_erfZ
x


b
y


B
test/onnx/implicit_bcast_test.onnx
View file @ f06f6aa3
implicit_bcast-example:q

add2:u

0
12"Addtest-multi_bcastZ
1out"Add subtraction2Z
0




Z
1

Z
1


b
2

b
out




B
\ No newline at end of file
B
test/onnx/implicit_sub_bcast_test.onnx
View file @ f06f6aa3
 subtraction2:q
add2:q

0
1out"Sub subtraction2Z
......@@ -10,11 +10,11 @@
Z
1


b

b
out




B
\ No newline at end of file
B
test/onnx/onnx_test.cpp
View file @ f06f6aa3
This diff is collapsed.
test/onnx/reducesum_test3.onnx 0 → 100644
View file @ f06f6aa3
reducesum-example:}
1
xy" ReduceSum*
axes@@*
keepdimstest_reducesumZ
x




b
y




B
test/op_shape_test.cpp
View file @ f06f6aa3
This diff is collapsed.
test/shape_test.cpp
View file @ f06f6aa3
......@@ -38,7 +38,7 @@ TEST_CASE(test_shape_packed)
EXPECT(not s.broadcasted());
}
TEST_CASE(test_shape_transposed)
TEST_CASE(test_shape_transposed1)
{
migraphx::shape s{migraphx::shape::float_type, {2, 2}, {1, 2}};
EXPECT(not s.standard());
......@@ -47,6 +47,15 @@ TEST_CASE(test_shape_transposed)
EXPECT(not s.broadcasted());
}
TEST_CASE(test_shape_transposed2)
{
migraphx::shape s{migraphx::shape::float_type, {1, 1, 1, 1, 2}, {2, 2, 2, 2, 1}};
EXPECT(s.standard());
EXPECT(s.packed());
EXPECT(not s.transposed());
EXPECT(not s.broadcasted());
}
TEST_CASE(test_shape_broadcasted)
{
migraphx::shape s{migraphx::shape::float_type, {2, 2}, {1, 0}};
......
test/simplify_reshapes_test.cpp
View file @ f06f6aa3
This diff is collapsed.
test/tf/sub_test.pb 0 → 100644
View file @ f06f6aa3
:
0 Placeholder*
shape:*
dtype0
:
1 Placeholder*
shape:*
dtype0

sub1Sub01*
T0"
\ No newline at end of file
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