merge optimization to print flops branch

src/include/migraphx/op/isnan.hpp

+#ifndef MIGRAPHX_GUARD_OPERATORS_ISNAN_HPP
+#define MIGRAPHX_GUARD_OPERATORS_ISNAN_HPP
+
+#include <migraphx/op/unary.hpp>
+#include <migraphx/config.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct isnan : unary<isnan>
+{
+    auto apply() const
+    {
+        return [](auto x) { return std::isnan(x); };
+    }
+
+    std::string name() const { return "isnan"; }
+
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        return unary<isnan>::compute_shape(std::move(inputs)).with_type(shape::bool_type);
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/nonmaxsuppression.hpp

@@ -181,7 +181,8 @@ struct nonmaxsuppression
                 make_function_output_iterator([&](const auto& x) { sorted_boxes.push(x); });
 
             int64_t box_idx = 0;
-            transform_if(scores.begin() + score_offset,
+            transform_if(
+                scores.begin() + score_offset,
                 scores.begin() + score_offset + box_num,
                 insert_to_sorted_boxes,
                 [&](auto sc) {

src/include/migraphx/op/reshape.hpp

@@ -27,7 +27,7 @@ struct reshape
         return pack(f(self.dims, "dims"));
     }
 
-    value attributes() const { return {{"std_shape", true}}; }
+    value attributes() const { return {{"require_std_shape", true}}; }
 
     std::string name() const { return "reshape"; }
     shape compute_shape(std::vector<shape> inputs) const

src/include/migraphx/op/roialign.hpp

@@ -253,7 +253,6 @@ struct roialign
                                                              max_pool{});
                     output(n, c, ph, pw) = output_val;
                 });
-
             });
         });
 

src/include/migraphx/op/scatternd_add.hpp

+#ifndef MIGRAPHX_GUARD_OPERATORS_SCATTERND_ADD_HPP
+#define MIGRAPHX_GUARD_OPERATORS_SCATTERND_ADD_HPP
+
+#include <migraphx/op/scatternd_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct scatternd_add : scatternd_op<scatternd_add>
+{
+    scatternd_add() {}
+
+    auto reduction() const
+    {
+        return [](auto& x, const auto& y) { x += y; };
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/scatternd_mul.hpp

+#ifndef MIGRAPHX_GUARD_OPERATORS_SCATTERND_MUL_HPP
+#define MIGRAPHX_GUARD_OPERATORS_SCATTERND_MUL_HPP
+
+#include <migraphx/op/scatternd_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct scatternd_mul : scatternd_op<scatternd_mul>
+{
+    scatternd_mul() {}
+
+    auto reduction() const
+    {
+        return [](auto& x, const auto& y) { x *= y; };
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/scatternd_none.hpp

+#ifndef MIGRAPHX_GUARD_OPERATORS_SCATTERND_NONE_HPP
+#define MIGRAPHX_GUARD_OPERATORS_SCATTERND_NONE_HPP
+
+#include <migraphx/op/scatternd_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct scatternd_none : scatternd_op<scatternd_none>
+{
+    scatternd_none() {}
+
+    auto reduction() const
+    {
+        return [](auto& x, const auto& y) { x = y; };
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/scatternd_op.hpp

+#ifndef MIGRAPHX_GUARD_OPERATORS_SCATTERND_OP_HPP
+#define MIGRAPHX_GUARD_OPERATORS_SCATTERND_OP_HPP
+
+#include <migraphx/op/name.hpp>
+#include <migraphx/check_shapes.hpp>
+#include <migraphx/par_for.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+template <class Derived>
+struct scatternd_op : op_name<Derived>
+{
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(3);
+        auto r         = inputs.front().lens().size();
+        auto q         = inputs.at(1).lens().size();
+        auto k         = inputs.at(1).lens().back();
+        auto ind_lens  = inputs.at(1).lens();
+        auto upd_lens  = inputs.back().lens();
+        auto data_lens = inputs.front().lens();
+        if(k > r)
+            MIGRAPHX_THROW("ScatterND: index of size " + std::to_string(k) +
+                           " is too large for tensor of rank " + std::to_string(r));
+        if(not(std::equal(ind_lens.begin(), ind_lens.begin() + q - 1, upd_lens.begin()) and
+               std::equal(data_lens.begin() + k, data_lens.end(), upd_lens.begin() + q - 1)))
+            MIGRAPHX_THROW("ScatterND: incorrect update shape. update.lens != indices.lens[0:q-1] "
+                           "++ data.lens[k:r-1]");
+        auto s = inputs.front();
+        if(s.broadcasted())
+        {
+            return {s.type(), s.lens()};
+        }
+        else
+        {
+            return s.with_lens(s.lens());
+        }
+    }
+
+    argument compute(const shape& output_shape, std::vector<argument> args) const
+    {
+        argument result{output_shape};
+        auto& self = static_cast<const Derived&>(*this);
+        visit_all(result, args[0], args[2])([&](auto output, auto data, auto updates) {
+            std::copy(data.begin(), data.end(), output.begin());
+            args[1].visit([&](auto indices) {
+                auto updates_shape = updates.get_shape();
+                auto updates_std   = shape{updates_shape.type(), updates_shape.lens()};
+                auto indices_shape = indices.get_shape();
+                auto k             = indices_shape.lens().back();
+                auto q             = indices_shape.lens().size();
+                auto r             = output_shape.lens().size();
+                par_for(updates_shape.elements(), [&](const auto i) {
+                    auto updates_idx = updates_std.multi(i);
+                    std::vector<std::size_t> indices_idx(q, 0);
+                    std::copy(
+                        updates_idx.begin(), updates_idx.begin() + q - 1, indices_idx.begin());
+                    auto index_start = indices.begin() +
+                                       indices_shape.index(indices_idx.begin(), indices_idx.end());
+                    auto index_end = index_start + k;
+
+                    std::vector<std::size_t> out_idx(r, 0);
+                    std::copy(index_start, index_end, out_idx.begin());
+                    std::copy(updates_idx.begin() + q - 1, updates_idx.end(), out_idx.begin() + k);
+
+                    self.reduction()(output[output_shape.index(out_idx)], updates[i]);
+                });
+            });
+        });
+
+        return result;
+    }
+
+    auto init() const {}
+    scatternd_op() {}
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/unary.hpp

@@ -64,7 +64,6 @@ struct unary : op_name<Derived>
                                input.end(),
                                output.begin(),
                                static_cast<const Derived&>(*this).apply());
-
             });
         });
         return result;

src/include/migraphx/operators.hpp

@@ -41,6 +41,7 @@
 #include <migraphx/op/identity.hpp>
 #include <migraphx/op/if_op.hpp>
 #include <migraphx/op/im2col.hpp>
+#include <migraphx/op/isnan.hpp>
 #include <migraphx/op/leaky_relu.hpp>
 #include <migraphx/op/less.hpp>
 #include <migraphx/op/load.hpp>
@@ -86,6 +87,9 @@
 #include <migraphx/op/rsqrt.hpp>
 #include <migraphx/op/scalar.hpp>
 #include <migraphx/op/scatter.hpp>
+#include <migraphx/op/scatternd_add.hpp>
+#include <migraphx/op/scatternd_none.hpp>
+#include <migraphx/op/scatternd_mul.hpp>
 #include <migraphx/op/sigmoid.hpp>
 #include <migraphx/op/sign.hpp>
 #include <migraphx/op/sinh.hpp>

src/include/migraphx/par_dfor.hpp

@@ -41,7 +41,6 @@ auto par_dfor(Ts... xs)
         {
             dfor(xs...)(f);
         }
-
     };
 }
 

src/include/migraphx/program.hpp

@@ -80,6 +80,8 @@ struct program
     void debug_print(std::ostream& os,
                      instruction_ref ins,
                      const std::unordered_map<instruction_ref, std::string>& names) const;
+    void debug_print(instruction_ref ins,
+                     const std::unordered_map<instruction_ref, std::string>& ins_names) const;
     void print(std::unordered_map<instruction_ref, std::string>& names,
                const std::function<void(instruction_ref,
                                         std::unordered_map<instruction_ref, std::string>)>&

src/include/migraphx/shape.hpp

@@ -35,7 +35,7 @@ struct shape
     m(int64_type, int64_t) \
     m(uint32_type, uint32_t) \
     m(uint64_type, uint64_t)
-// clang-format on
+    // clang-format on
 
 #define MIGRAPHX_SHAPE_GENERATE_ENUM_TYPES(x, t) x,
     enum type_t
@@ -131,6 +131,8 @@ struct shape
     shape with_lens(type_t t, const std::vector<std::size_t>& l) const;
     shape with_lens(const std::vector<std::size_t>& l) const;
 
+    shape with_type(type_t t) const;
+
     friend bool operator==(const shape& x, const shape& y);
     friend bool operator!=(const shape& x, const shape& y);
     friend std::ostream& operator<<(std::ostream& os, const shape& x);
@@ -186,8 +188,7 @@ struct shape
     {
         switch(t)
         {
-        case tuple_type:
-        {
+        case tuple_type: {
             tv();
             return;
         }
@@ -226,6 +227,7 @@ struct shape
     std::size_t element_space() const;
 
     private:
+    shape(std::shared_ptr<shape_impl> pimpl);
     std::shared_ptr<const shape_impl> impl;
 };
 

src/include/migraphx/stringutils.hpp

@@ -131,7 +131,8 @@ inline std::string interpolate_string(const std::string& input,
                                       std::string start = "${",
                                       std::string end   = "}")
 {
-    return interpolate_string(input,
+    return interpolate_string(
+        input,
         [&](auto start_it, auto last_it) {
             auto key = trim({start_it, last_it});
             auto it  = vars.find(key);

src/include/migraphx/value.hpp

@@ -315,8 +315,7 @@ struct value
     {
         switch(this->get_type())
         {
-        case null_type:
-        {
+        case null_type: {
             std::nullptr_t null{};
             if(this->key.empty())
                 v(null);
@@ -325,8 +324,7 @@ struct value
             return;
         }
 #define MIGRAPHX_VALUE_GENERATE_CASE(vt, cpp_type)                          \
-    case vt##_type:                                                         \
-    {                                                                       \
+    case vt##_type: {                                                       \
         if(this->key.empty())                                               \
             v(this->get_##vt());                                            \
         else                                                                \
@@ -346,15 +344,13 @@ struct value
     {
         switch(this->get_type())
         {
-        case null_type:
-        {
+        case null_type: {
             std::nullptr_t null{};
             v(null);
             return;
         }
 #define MIGRAPHX_VALUE_GENERATE_CASE_VALUE(vt, cpp_type) \
-    case vt##_type:                                      \
-    {                                                    \
+    case vt##_type: {                                    \
         v(this->get_##vt());                             \
         return;                                          \
     }

src/module.cpp

@@ -628,7 +628,7 @@ std::unordered_map<instruction_ref, std::string> module::print(
             var_name.append((this->name().empty() ? "@" : ":@"));
             var_name.append(std::to_string(count));
         }
-        // make instruction index to be the line num in the printed module
+        // count every instruction so index matches loc in the printout program
         count++;
         names.emplace(ins, var_name);
 

src/msgpack.cpp

@@ -14,44 +14,36 @@ MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
         {
             switch(o.type)
             {
-            case msgpack::type::NIL:
-            {
+            case msgpack::type::NIL: {
                 v = nullptr;
                 break;
             }
-            case msgpack::type::BOOLEAN:
-            {
+            case msgpack::type::BOOLEAN: {
                 v = o.as<bool>();
                 break;
             }
-            case msgpack::type::POSITIVE_INTEGER:
-            {
+            case msgpack::type::POSITIVE_INTEGER: {
                 v = o.as<std::uint64_t>();
                 break;
             }
-            case msgpack::type::NEGATIVE_INTEGER:
-            {
+            case msgpack::type::NEGATIVE_INTEGER: {
                 v = o.as<std::int64_t>();
                 break;
             }
             case msgpack::type::FLOAT32:
-            case msgpack::type::FLOAT64:
-            {
+            case msgpack::type::FLOAT64: {
                 v = o.as<double>();
                 break;
             }
-            case msgpack::type::STR:
-            {
+            case msgpack::type::STR: {
                 v = o.as<std::string>();
                 break;
             }
-            case msgpack::type::BIN:
-            {
+            case msgpack::type::BIN: {
                 v = migraphx::value::binary{o.via.bin.ptr, o.via.bin.size};
                 break;
             }
-            case msgpack::type::ARRAY:
-            {
+            case msgpack::type::ARRAY: {
                 migraphx::value r = migraphx::value::array{};
                 std::for_each(
                     o.via.array.ptr,
@@ -60,8 +52,7 @@ MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
                 v = r;
                 break;
             }
-            case msgpack::type::MAP:
-            {
+            case msgpack::type::MAP: {
                 migraphx::value r = migraphx::value::object{};
                 std::for_each(o.via.map.ptr,
                               o.via.map.ptr + o.via.map.size,
@@ -71,7 +62,8 @@ MSGPACK_API_VERSION_NAMESPACE(MSGPACK_DEFAULT_API_NS)
                 v = r;
                 break;
             }
-            case msgpack::type::EXT: { MIGRAPHX_THROW("msgpack EXT type not supported.");
+            case msgpack::type::EXT: {
+                MIGRAPHX_THROW("msgpack EXT type not supported.");
             }
             }
             return o;

src/onnx/CMakeLists.txt

@@ -7,7 +7,7 @@ target_compile_options(onnx-proto PRIVATE -w)
 target_link_libraries(onnx-proto PRIVATE ${PROTOBUF_LIBRARY})
 set_target_properties(onnx-proto PROPERTIES POSITION_INDEPENDENT_CODE On)
 
-file(GLOB ONNX_SRCS *.cpp)
+file(GLOB ONNX_SRCS ${CONFIGURE_DEPENDS} *.cpp)
 add_library(migraphx_onnx ${ONNX_SRCS})
 target_include_directories(migraphx_onnx PRIVATE include)
 set_target_properties(migraphx_onnx PROPERTIES EXPORT_NAME onnx)

src/onnx/onnx_parser.cpp

@@ -70,12 +70,14 @@ static literal from_repeated(shape::type_t t, const T& r)
 
 instruction_ref onnx_parser::node_info::make_contiguous(instruction_ref ins) const
 {
-    if(ins->get_shape().standard())
+    auto attr       = ins->get_operator().to_value();
+    std::string key = "require_std_shape";
+    if((attr.get(key, false)) or (not ins->get_shape().standard()))
     {
-        return ins;
+        return add_instruction(make_op("contiguous"), ins);
     }
 
-    return add_instruction(make_op("contiguous"), ins);
+    return ins;
 }
 
 instruction_ref onnx_parser::node_info::add_bias(const std::vector<instruction_ref>& args,
@@ -380,8 +382,7 @@ literal onnx_parser::parse_tensor(const onnx::TensorProto& t) const
     case onnx::TensorProto::INT64: return create_literal(shape::int64_type, dims, t.int64_data());
     case onnx::TensorProto::UINT64:
         return create_literal(shape::uint64_type, dims, t.uint64_data());
-    case onnx::TensorProto::FLOAT16:
-    {
+    case onnx::TensorProto::FLOAT16: {
         std::vector<uint16_t> data_uint16(t.int32_data().begin(), t.int32_data().end());
         std::vector<half> data_half;
         std::transform(data_uint16.begin(),
@@ -451,7 +452,8 @@ shape::type_t get_type(int dtype)
     case 11: return shape::double_type;
     case 12: return shape::uint32_type;
     case 13: return shape::uint64_type;
-    default: { MIGRAPHX_THROW("Prototensor data type " + std::to_string(dtype) + " not supported");
+    default: {
+        MIGRAPHX_THROW("Prototensor data type " + std::to_string(dtype) + " not supported");
     }
     }
 }

src/onnx/parse_generic_op.cpp

@@ -28,6 +28,7 @@ struct parse_generic_op : op_parser<parse_generic_op>
                 {"Floor", "floor"},
                 {"Gather", "gather"},
                 {"Identity", "identity"},
+                {"IsNaN", "isnan"},
                 {"LeakyRelu", "leaky_relu"},
                 {"Log", "log"},
                 {"Neg", "neg"},