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Commit be5f3539 authored by Shucai Xiao's avatar Shucai Xiao
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merge develop branch changes

parents 7e3bdc34 ebfe9735
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Showing with 989 additions and 189 deletions
src/targets/gpu/target.cpp
View file @ be5f3539
......@@ -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/CMakeLists.txt
View file @ be5f3539
......@@ -31,7 +31,7 @@ rocm_install_targets(
add_executable(read_tf read_tf.cpp)
rocm_clang_tidy_check(read_tf)
target_link_libraries(read_tf migraphx_tf)
target_link_libraries(read_tf migraphx_tf migraphx_cpu)
if(MIGRAPHX_ENABLE_GPU)
add_executable(verify_tf verify_tf.cpp)
......
src/tf/tf.cpp
View file @ be5f3539
......@@ -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
......@@ -302,21 +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 weights = to_kcxy(args[1]);
auto l0 = args[0];
if(contains(attributes, "padding"))
{
const std::string& pad_mode = attributes.at("padding").s();
......@@ -326,8 +360,24 @@ struct tf_parser
std::vector<size_t> weight_dims = weights->get_shape().lens();
size_t weight_h = weight_dims[2];
size_t weight_w = weight_dims[3];
op.padding[0] = calculate_padding(weight_h, op.dilation[0]);
op.padding[1] = calculate_padding(weight_w, op.dilation[1]);
auto input_dims = l0->get_shape().lens();
size_t input_h = input_dims[2];
size_t input_w = input_dims[3];
std::vector<int64_t> pads(input_dims.size());
calculate_padding(0, pads, input_h, op.stride[0], op.dilation[0], weight_h);
calculate_padding(1, pads, input_w, op.stride[1], op.dilation[1], weight_w);
if(pads[0] != pads[2] || pads[1] != pads[3])
{
std::vector<int64_t> padding = {0, 0, pads[0], pads[1], 0, 0, pads[2], pads[3]};
l0 = prog.add_instruction(migraphx::op::pad{padding}, l0);
}
else
{
op.padding[0] = pads[0];
op.padding[1] = pads[1];
}
}
else if(pad_mode.find("VALID") != std::string::npos)
{
......@@ -349,8 +399,7 @@ struct tf_parser
op.padding[1] = padding[1];
}
}
return prog.add_instruction(op, {args[0], weights});
return prog.add_instruction(op, {l0, to_kcxy(args[1])});
}
instruction_ref parse_depthwiseconv(const std::string&,
......@@ -373,6 +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;
......@@ -386,31 +437,35 @@ 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"))
{
const std::string& pad_mode = attributes.at("padding").s();
std::vector<size_t> weight_dims = weights->get_shape().lens();
size_t weight_h = weight_dims[2];
size_t weight_w = weight_dims[3];
const std::string& pad_mode = attributes.at("padding").s();
if(pad_mode.find("SAME") != std::string::npos)
{
op.padding_mode = op::padding_mode_t::same;
op.padding[0] = calculate_padding(weight_h, op.dilation[0]);
op.padding[1] = calculate_padding(weight_w, op.dilation[1]);
op.padding_mode = op::padding_mode_t::same;
std::vector<size_t> weight_dims = weights->get_shape().lens();
size_t weight_h = weight_dims[2];
size_t weight_w = weight_dims[3];
auto input_dims = l0->get_shape().lens();
size_t input_h = input_dims[2];
size_t input_w = input_dims[3];
std::vector<int64_t> pads(input_dims.size());
calculate_padding(0, pads, input_h, op.stride[0], op.dilation[0], weight_h);
calculate_padding(1, pads, input_w, op.stride[1], op.dilation[1], weight_w);
if(pads[0] != pads[2] || pads[1] != pads[3])
{
std::vector<int64_t> padding = {0, 0, pads[0], pads[1], 0, 0, pads[2], pads[3]};
l0 = prog.add_instruction(migraphx::op::pad{padding}, l0);
}
else
{
op.padding[0] = pads[0];
op.padding[1] = pads[1];
}
}
else if(pad_mode.find("VALID") != std::string::npos)
{
......@@ -429,10 +484,10 @@ 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, {args[0], new_weights});
return prog.add_instruction(op, {l0, new_weights});
}
instruction_ref
......@@ -498,16 +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
......@@ -567,21 +620,39 @@ struct tf_parser
op.lengths[0] = ksize[2];
op.lengths[1] = ksize[3];
}
auto l0 = args[0];
if(contains(attributes, "padding"))
{
const std::string& pad_mode = attributes.at("padding").s();
if(pad_mode.find("SAME") != std::string::npos)
{
op.padding_mode = op::padding_mode_t::same;
op.padding[0] = calculate_padding(op.lengths[0], 1);
op.padding[1] = calculate_padding(op.lengths[1], 1);
auto input_dims = l0->get_shape().lens();
size_t input_h = input_dims[2];
size_t input_w = input_dims[3];
std::vector<int64_t> pads(input_dims.size());
calculate_padding(0, pads, input_h, op.stride[0], 1, op.lengths[0]);
calculate_padding(1, pads, input_w, op.stride[1], 1, op.lengths[1]);
if(pads[0] != pads[2] || pads[1] != pads[3])
{
std::vector<int64_t> padding = {0, 0, pads[0], pads[1], 0, 0, pads[2], pads[3]};
l0 = prog.add_instruction(
migraphx::op::pad{padding, std::numeric_limits<float>::lowest()}, l0);
}
else
{
op.padding[0] = pads[0];
op.padding[1] = pads[1];
}
}
else if(pad_mode.find("VALID") != std::string::npos)
{
op.padding_mode = op::padding_mode_t::valid;
}
}
return prog.add_instruction(op, args[0]);
return prog.add_instruction(op, l0);
}
instruction_ref
......@@ -592,7 +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)
......@@ -623,7 +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
......@@ -636,7 +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&,
......@@ -647,11 +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());
......@@ -670,13 +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)
......@@ -693,7 +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)
{
......@@ -1043,6 +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/CMakeLists.txt
View file @ be5f3539
......@@ -119,7 +119,7 @@ foreach(ONNX_TEST ${ONNX_TESTS})
set(TEST_NAME test_${BASE_NAME})
add_executable(${TEST_NAME} ${TES_ONNX_DIR}/${ONNX_TEST})
rocm_clang_tidy_check(${TEST_NAME})
target_link_libraries(${TEST_NAME} migraphx_onnx)
target_link_libraries(${TEST_NAME} migraphx_onnx migraphx_cpu)
target_include_directories(${TEST_NAME} PUBLIC include)
add_test(NAME ${TEST_NAME} COMMAND $<TARGET_FILE:${TEST_NAME}> WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/onnx)
add_dependencies(tests ${TEST_NAME})
......@@ -129,7 +129,7 @@ endforeach()
# tf test
add_executable(test_tf tf/tf_test.cpp)
rocm_clang_tidy_check(test_tf)
target_link_libraries(test_tf migraphx_tf)
target_link_libraries(test_tf migraphx_tf migraphx_cpu)
target_include_directories(test_tf PUBLIC include)
add_test(NAME test_tf COMMAND $<TARGET_FILE:test_tf> WORKING_DIRECTORY ${CMAKE_CURRENT_SOURCE_DIR}/tf)
add_dependencies(tests test_tf)
......
test/cpu_ops_test.cpp
View file @ be5f3539
......@@ -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;
......@@ -941,9 +956,6 @@ TEST_CASE(softmax_simple_test)
auto result = p.eval({});
std::vector<float> results_vector(2);
result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
for(auto v : results_vector)
std::cout << v << "\t";
std::cout << std::endl;
EXPECT(migraphx::verify_range(results_vector, s));
}
......@@ -1138,6 +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;
......@@ -1754,4 +1874,79 @@ 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/eliminate_pad_test.cpp
View file @ be5f3539
......@@ -83,23 +83,4 @@ TEST_CASE(rewrite_test_asymmetric)
p.begin(), p.end(), [](const migraphx::instruction& ins) { return ins.name() == "pad"; }));
}
TEST_CASE(rewrite_test_same_padding)
{
migraphx::program p;
size_t img_dim[2] = {2, 2};
size_t channels = 1;
std::vector<int32_t> input(channels * img_dim[0] * img_dim[1]);
std::iota(input.begin(), input.end(), 0);
migraphx::shape s_img{migraphx::shape::int32_type, {1, channels, img_dim[0], img_dim[1]}};
auto l_img = p.add_literal(migraphx::literal{s_img, input});
auto padded_img = p.add_instruction(migraphx::op::pad{{0, 0, 1, 1, 0, 0, 1, 1}}, l_img);
create_conv(padded_img, channels, p, migraphx::op::padding_mode_t::same);
p.compile(eliminate_pad_target{});
EXPECT(std::any_of(
p.begin(), p.end(), [](const migraphx::instruction& ins) { return ins.name() == "pad"; }));
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
test/gpu/miopen.cpp
View file @ be5f3539
......@@ -243,6 +243,18 @@ struct test_exp : verify_program<test_exp>
}
};
struct test_erf : verify_program<test_erf>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {2, 3, 4, 6}};
auto param = p.add_parameter("x", s);
p.add_instruction(migraphx::op::erf{}, param);
return p;
}
};
struct test_log : verify_program<test_log>
{
migraphx::program create_program() const
......@@ -592,13 +604,13 @@ struct test_softmax2 : verify_program<test_softmax2>
}
};
template <int Axis>
struct test_softmax : verify_program<test_softmax<Axis>>
template <int Axis, migraphx::shape::type_t T>
struct test_softmax : verify_program<test_softmax<Axis, T>>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
migraphx::shape s{T, {512, 4, 1067, 6}};
auto param = p.add_parameter("0", s);
p.add_instruction(migraphx::op::softmax{Axis}, param);
......@@ -606,10 +618,38 @@ struct test_softmax : verify_program<test_softmax<Axis>>
}
};
template struct test_softmax<0>;
template struct test_softmax<1>;
template struct test_softmax<2>;
template struct test_softmax<3>;
template struct test_softmax<0, migraphx::shape::float_type>;
template struct test_softmax<2, migraphx::shape::float_type>;
template struct test_softmax<1, migraphx::shape::double_type>;
template struct test_softmax<3, migraphx::shape::double_type>;
template struct test_softmax<0, migraphx::shape::half_type>;
template struct test_softmax<1, migraphx::shape::half_type>;
template struct test_softmax<2, migraphx::shape::half_type>;
template struct test_softmax<3, migraphx::shape::half_type>;
template <class T, int Axis>
struct test_arg_ops : verify_program<test_arg_ops<T, Axis>>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {2, 3, 4, 1025}};
auto param = p.add_parameter("data", s);
p.add_instruction(T{Axis}, param);
return p;
}
};
template struct test_arg_ops<migraphx::op::argmax, 0>;
template struct test_arg_ops<migraphx::op::argmax, 1>;
template struct test_arg_ops<migraphx::op::argmax, 2>;
template struct test_arg_ops<migraphx::op::argmax, 3>;
template struct test_arg_ops<migraphx::op::argmin, 0>;
template struct test_arg_ops<migraphx::op::argmin, 1>;
template struct test_arg_ops<migraphx::op::argmin, 2>;
template struct test_arg_ops<migraphx::op::argmin, 3>;
struct test_conv : verify_program<test_conv>
{
......@@ -1646,6 +1686,22 @@ struct test_pad : verify_program<test_pad>
}
};
struct test_pad_int8 : verify_program<test_pad_int8>
{
migraphx::program create_program() const
{
migraphx::program p;
std::vector<int8_t> data0 = {0, 1, 2, 3};
migraphx::shape s0{migraphx::shape::float_type, {2, 2}};
auto l0 = p.add_literal(migraphx::literal{s0, data0});
migraphx::op::pad op{};
op.value = std::numeric_limits<int8_t>::lowest();
op.pads = {0, 0, 1, 1};
p.add_instruction(op, l0);
return p;
}
};
struct test_pooling_autopad : verify_program<test_pooling_autopad>
{
migraphx::program create_program() const
......@@ -2836,10 +2892,11 @@ struct test_lstm_forward_last : verify_program<test_lstm_forward_last>
auto und = p.add_instruction(migraphx::op::undefined{});
auto output = p.add_instruction(
migraphx::op::gru{hidden_size,
{migraphx::op::sigmoid{}, migraphx::op::tanh{}, migraphx::op::tanh{}},
migraphx::op::rnn_direction::forward,
clip},
migraphx::op::lstm{
hidden_size,
{migraphx::op::sigmoid{}, migraphx::op::tanh{}, migraphx::op::tanh{}},
migraphx::op::rnn_direction::forward,
clip},
seq,
w,
r,
......@@ -3513,13 +3570,13 @@ struct test_lstm_bidirct_default_actv2 : verify_program<test_lstm_bidirct_defaul
}
};
template <int Axis>
struct test_logsoftmax : verify_program<test_logsoftmax<Axis>>
template <int Axis, migraphx::shape::type_t T>
struct test_logsoftmax : verify_program<test_logsoftmax<Axis, T>>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 4, 5, 6}};
migraphx::shape s{T, {10, 4, 2080, 6}};
auto param = p.add_parameter("0", s);
p.add_instruction(migraphx::op::logsoftmax{Axis}, param);
......@@ -3527,26 +3584,16 @@ struct test_logsoftmax : verify_program<test_logsoftmax<Axis>>
}
};
template struct test_logsoftmax<0>;
template struct test_logsoftmax<1>;
template struct test_logsoftmax<2>;
template struct test_logsoftmax<3>;
template <int Axis>
struct test_logsoftmax_1 : verify_program<test_logsoftmax_1<Axis>>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3}};
auto param = p.add_parameter("0", s);
p.add_instruction(migraphx::op::logsoftmax{Axis}, param);
return p;
}
};
template struct test_logsoftmax_1<0>;
template struct test_logsoftmax<0, migraphx::shape::float_type>;
template struct test_logsoftmax<1, migraphx::shape::float_type>;
template struct test_logsoftmax<2, migraphx::shape::float_type>;
template struct test_logsoftmax<3, migraphx::shape::float_type>;
template struct test_logsoftmax<1, migraphx::shape::double_type>;
template struct test_logsoftmax<3, migraphx::shape::double_type>;
template struct test_logsoftmax<1, migraphx::shape::half_type>;
template struct test_logsoftmax<0, migraphx::shape::half_type>;
template struct test_logsoftmax<2, migraphx::shape::half_type>;
template struct test_logsoftmax<3, migraphx::shape::half_type>;
struct test_fp32_fp16_lall : verify_program<test_fp32_fp16_lall>
{
......@@ -3614,4 +3661,40 @@ struct test_fp32_fp16_sub : verify_program<test_fp32_fp16_sub>
};
};
struct test_reduce_sum : verify_program<test_reduce_sum>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::float_type, {3, 1026, 4, 3}};
auto x = p.add_parameter("x", s);
p.add_instruction(migraphx::op::reduce_sum{{1}}, x);
return p;
};
};
struct test_reduce_sum_int : verify_program<test_reduce_sum_int>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::int32_type, {3, 4, 8, 8}};
auto x = p.add_parameter("x", s);
p.add_instruction(migraphx::op::reduce_sum{{1}}, x);
return p;
};
};
struct test_reduce_sum_half : verify_program<test_reduce_sum_half>
{
migraphx::program create_program() const
{
migraphx::program p;
migraphx::shape s{migraphx::shape::half_type, {3, 4, 8, 8}};
auto x = p.add_parameter("x", s);
p.add_instruction(migraphx::op::reduce_sum{{1}}, x);
return p;
};
};
int main(int argc, const char* argv[]) { test::run(argc, argv); }
test/matcher.cpp
View file @ be5f3539
......@@ -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 @ be5f3539
 erf-example:A
xy"Erftest_erfZ
x


b
y


B
test/onnx/implicit_bcast_test.onnx
View file @ be5f3539
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 @ be5f3539
 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 @ be5f3539
......@@ -192,6 +192,16 @@ TEST_CASE(exp_test)
EXPECT(p == prog);
}
TEST_CASE(erf_test)
{
migraphx::program p;
auto input = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {10, 15}});
p.add_instruction(migraphx::op::erf{}, input);
auto prog = migraphx::parse_onnx("erf_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(log_test)
{
migraphx::program p;
......@@ -350,7 +360,7 @@ TEST_CASE(implicit_add_bcast_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4, 1}});
auto l2 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l0);
auto l3 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l1);
p.add_instruction(migraphx::op::add{}, l2, l3);
......@@ -377,7 +387,7 @@ TEST_CASE(implicit_sub_bcast_test)
{
migraphx::program p;
auto l0 = p.add_parameter("0", migraphx::shape{migraphx::shape::float_type, {2, 3, 4, 5}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {3, 4}});
auto l1 = p.add_parameter("1", migraphx::shape{migraphx::shape::float_type, {4, 5}});
auto l2 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l0);
auto l3 = p.add_instruction(migraphx::op::multibroadcast{{2, 3, 4, 5}}, l1);
p.add_instruction(migraphx::op::sub{}, l2, l3);
......@@ -784,6 +794,28 @@ TEST_CASE(logsoftmax)
EXPECT(p == prog);
}
TEST_CASE(argmax)
{
migraphx::program p;
auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
auto ins = p.add_instruction(migraphx::op::argmax{2}, l0);
p.add_instruction(migraphx::op::squeeze{{2}}, ins);
auto prog = migraphx::parse_onnx("argmax_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(argmin)
{
migraphx::program p;
auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
auto ins = p.add_instruction(migraphx::op::argmin{3}, l0);
p.add_instruction(migraphx::op::squeeze{{3}}, ins);
auto prog = migraphx::parse_onnx("argmin_test.onnx");
EXPECT(p == prog);
}
TEST_CASE(no_pad_test)
{
migraphx::program p;
......@@ -794,6 +826,38 @@ TEST_CASE(no_pad_test)
EXPECT(p == prog);
}
TEST_CASE(reducesum_test1)
{
migraphx::program p;
auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
auto l1 = p.add_instruction(migraphx::op::reduce_sum{{2}}, l0);
p.add_instruction(migraphx::op::squeeze{{2}}, l1);
auto prog = migraphx::parse_onnx("reducesum_test1.onnx");
EXPECT(p == prog);
}
TEST_CASE(reducesum_test2)
{
migraphx::program p;
auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
auto l1 = p.add_instruction(migraphx::op::reduce_sum{{2, 3}}, l0);
p.add_instruction(migraphx::op::squeeze{{2, 3}}, l1);
auto prog = migraphx::parse_onnx("reducesum_test2.onnx");
EXPECT(p == prog);
}
TEST_CASE(reducesum_test3)
{
migraphx::program p;
auto l0 = p.add_parameter("x", migraphx::shape{migraphx::shape::float_type, {3, 4, 5, 6}});
p.add_instruction(migraphx::op::reduce_sum{{2, 3}}, l0);
auto prog = migraphx::parse_onnx("reducesum_test3.onnx");
EXPECT(p == prog);
}
TEST_CASE(clip_test)
{
migraphx::program p;
......
test/onnx/reducesum_test3.onnx 0 → 100644
View file @ be5f3539
reducesum-example:}
1
xy" ReduceSum*
axes@@*
keepdimstest_reducesumZ
x




b
y




B
test/op_shape_test.cpp
View file @ be5f3539
......@@ -257,6 +257,16 @@ TEST_CASE(multibroadcast)
migraphx::shape input{migraphx::shape::float_type, {}};
throws_shape(migraphx::op::multibroadcast{lens}, input);
}
{
std::vector<std::size_t> lens{2, 3, 4, 5};
migraphx::shape input{migraphx::shape::float_type, {3, 4}};
throws_shape(migraphx::op::multibroadcast{lens}, input);
}
{
std::vector<std::size_t> lens{2, 3, 4, 5};
migraphx::shape input{migraphx::shape::float_type, {2, 3, 4}};
throws_shape(migraphx::op::multibroadcast{lens}, input);
}
}
TEST_CASE(broadcast)
......@@ -410,6 +420,38 @@ TEST_CASE(softmax) { test_softmax_variations<migraphx::op::softmax>(); }
TEST_CASE(logsoftmax) { test_softmax_variations<migraphx::op::logsoftmax>(); }
template <class T>
void test_argop_var()
{
{
migraphx::shape input{migraphx::shape::half_type, {2, 3, 4, 5}};
expect_shape(migraphx::shape{migraphx::shape::int64_type, {1, 3, 4, 5}}, T{0}, input);
}
{
migraphx::shape input{migraphx::shape::half_type, {2, 3, 4, 5}};
expect_shape(migraphx::shape{migraphx::shape::int64_type, {2, 1, 4, 5}}, T{1}, input);
}
{
migraphx::shape input{migraphx::shape::half_type, {2, 3, 4, 5}};
expect_shape(migraphx::shape{migraphx::shape::int64_type, {2, 3, 1, 5}}, T{2}, input);
}
{
migraphx::shape input{migraphx::shape::half_type, {2, 3, 4, 5}};
expect_shape(migraphx::shape{migraphx::shape::int64_type, {2, 3, 4, 1}}, T{3}, input);
}
{
migraphx::shape input{migraphx::shape::float_type, {2, 3, 4, 5}};
throws_shape(T{4}, input);
}
}
TEST_CASE(argmax) { test_argop_var<migraphx::op::argmax>(); }
TEST_CASE(argmin) { test_argop_var<migraphx::op::argmin>(); }
// 2 inputs arguments
TEST_CASE(matmul)
{
......
test/shape_test.cpp
View file @ be5f3539
......@@ -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 @ be5f3539
#include <migraphx/simplify_reshapes.hpp>
#include <migraphx/dead_code_elimination.hpp>
#include <migraphx/operators.hpp>
#include <migraphx/instruction.hpp>
#include <basic_ops.hpp>
#include <test.hpp>
......@@ -165,4 +166,144 @@ TEST_CASE(transpose_double_contiguous)
EXPECT(p.has_instruction(t));
}
TEST_CASE(transpose_partial1)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3}};
auto x = p.add_parameter("x", s);
auto t1 = p.add_instruction(migraphx::op::transpose{{1, 0, 2}}, x);
auto t2 = p.add_instruction(migraphx::op::transpose{{1, 2, 0}}, t1);
p.add_instruction(pass_op{}, t2);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape() == out_shape);
EXPECT(std::distance(p.begin(), p.end()) == n - 1);
}
TEST_CASE(transpose_partial2)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3}};
auto x = p.add_parameter("x", s);
auto t1 = p.add_instruction(migraphx::op::transpose{{1, 0, 2}}, x);
auto t2 = p.add_instruction(migraphx::op::transpose{{1, 2, 0}}, t1);
auto t3 = p.add_instruction(migraphx::op::transpose{{1, 0, 2}}, t2);
p.add_instruction(pass_op{}, t3);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape() == out_shape);
EXPECT(std::distance(p.begin(), p.end()) == n - 2);
}
TEST_CASE(transpose_partial3)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3}};
auto x = p.add_parameter("x", s);
auto t1 = p.add_instruction(migraphx::op::transpose{{1, 0, 2}}, x);
auto t2 = p.add_instruction(migraphx::op::transpose{{1, 2, 0}}, t1);
auto t3 = p.add_instruction(migraphx::op::transpose{{1, 0, 2}}, t2);
auto t4 = p.add_instruction(migraphx::op::transpose{{1, 0, 2}}, t3);
p.add_instruction(pass_op{}, t4);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape() == out_shape);
EXPECT(std::distance(p.begin(), p.end()) == n - 3);
}
TEST_CASE(nop_transpose1)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3}};
auto x = p.add_parameter("x", s);
auto t = p.add_instruction(migraphx::op::transpose{{0, 1, 2}}, x);
p.add_instruction(pass_op{}, t);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape() == out_shape);
EXPECT(std::distance(p.begin(), p.end()) == n - 1);
}
TEST_CASE(nop_transpose2)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3}};
auto x = p.add_parameter("x", s);
auto t1 = p.add_instruction(migraphx::op::transpose{{0, 1, 2}}, x);
auto t2 = p.add_instruction(migraphx::op::transpose{{0, 1, 2}}, t1);
auto t3 = p.add_instruction(migraphx::op::transpose{{0, 1, 2}}, t2);
auto t4 = p.add_instruction(migraphx::op::transpose{{0, 1, 2}}, t3);
p.add_instruction(pass_op{}, t4);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape() == out_shape);
EXPECT(std::distance(p.begin(), p.end()) == n - 4);
}
TEST_CASE(nop_transpose3)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3, 4}};
auto x = p.add_parameter("x", s);
auto y = p.add_parameter("y", s);
auto concat = p.add_instruction(migraphx::op::concat{3}, x, y);
auto t1 = p.add_instruction(migraphx::op::transpose{{0, 1, 2, 3}}, concat);
auto t2 = p.add_instruction(migraphx::op::transpose{{0, 1, 3, 2}}, t1);
p.add_instruction(pass_op{}, t2);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape() == out_shape);
EXPECT(std::distance(p.begin(), p.end()) == n - 1);
}
TEST_CASE(concat_transpose1)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3, 4}};
auto x = p.add_parameter("x", s);
auto y = p.add_parameter("y", s);
auto xt = p.add_instruction(migraphx::op::transpose{{0, 1, 3, 2}}, x);
auto yt = p.add_instruction(migraphx::op::transpose{{0, 1, 3, 2}}, y);
auto concat = p.add_instruction(migraphx::op::concat{2}, xt, yt);
auto t = p.add_instruction(migraphx::op::transpose{{0, 1, 3, 2}}, concat);
p.add_instruction(pass_op{}, t);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape().lens() == out_shape.lens());
EXPECT(std::distance(p.begin(), p.end()) == n - 3);
auto new_concat =
std::find_if(p.begin(), p.end(), [](auto ins) { return ins.name() == "concat"; });
EXPECT(bool{new_concat != p.end()});
EXPECT(migraphx::any_cast<migraphx::op::concat>(new_concat->get_operator()).axis == 3);
}
TEST_CASE(concat_transpose2)
{
migraphx::program p;
auto s = migraphx::shape{migraphx::shape::float_type, {1, 2, 3, 4}};
auto x = p.add_parameter("x", s);
auto y = p.add_parameter("y", s);
auto xt = p.add_instruction(migraphx::op::transpose{{0, 2, 3, 1}}, x);
auto yt = p.add_instruction(migraphx::op::transpose{{0, 2, 3, 1}}, y);
auto concat = p.add_instruction(migraphx::op::concat{3}, xt, yt);
auto t = p.add_instruction(migraphx::op::transpose{{0, 2, 3, 1}}, concat);
p.add_instruction(pass_op{}, t);
auto out_shape = p.get_shape();
auto n = std::distance(p.begin(), p.end());
p.compile(simplify_reshapes_target{});
EXPECT(p.get_shape().lens() == out_shape.lens());
EXPECT(std::distance(p.begin(), p.end()) == n - 2);
auto new_concat =
std::find_if(p.begin(), p.end(), [](auto ins) { return ins.name() == "concat"; });
EXPECT(bool{new_concat != p.end()});
EXPECT(migraphx::any_cast<migraphx::op::concat>(new_concat->get_operator()).axis == 1);
}
int main(int argc, const char* argv[]) { test::run(argc, argv); }
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