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

src/cpp_generator.cpp

@@ -88,6 +88,7 @@ struct cpp_generator_impl
     std::stringstream fs{};
     std::size_t function_count                                = 0;
     std::function<std::string(std::string)> fmap              = nullptr;
+    std::function<std::string(shape)> fresult                 = nullptr;
     std::unordered_map<std::string, std::string> point_op_map = {};
 };
 cpp_generator::cpp_generator() : impl(std::make_unique<cpp_generator_impl>()) {}
@@ -104,6 +105,8 @@ cpp_generator::~cpp_generator() noexcept = default;
 
 void cpp_generator::fmap(const std::function<std::string(std::string)>& f) { impl->fmap = f; }
 
+void cpp_generator::fresult(const std::function<std::string(shape)>& f) { impl->fresult = f; }
+
 void cpp_generator::add_point_op(const std::string& op_name, const std::string& code)
 {
     impl->point_op_map[op_name] = code;
@@ -174,7 +177,12 @@ cpp_generator::function cpp_generator::generate_module(const module& m)
                            ins->inputs().end(),
                            std::back_inserter(args),
                            [&](auto i) { return names.at(i); });
-            return this->generate_point_op(ins->get_operator(), args);
+
+            auto s = this->generate_point_op(ins->get_operator(), args);
+            if(impl->fresult)
+                return impl->fresult(ins->get_shape()) + '(' + s + ')';
+            else
+                return s;
         });
     return f;
 }

src/include/migraphx/cpp_generator.hpp

@@ -68,6 +68,8 @@ struct cpp_generator
 
     void fmap(const std::function<std::string(std::string)>& f);
 
+    void fresult(const std::function<std::string(shape)>& f);
+
     void add_point_op(const std::string& op_name, const std::string& code);
 
     std::string generate_point_op(const operation& op, const std::vector<std::string>& args);

src/include/migraphx/iota_iterator.hpp

@@ -89,6 +89,13 @@ inline std::ptrdiff_t operator-(basic_iota_iterator<F, Iterator> x,
     return x.index - y.index;
 }
 
+template <class F, class Iterator>
+inline basic_iota_iterator<F, Iterator> operator-(basic_iota_iterator<F, Iterator> x,
+                                                  std::ptrdiff_t y)
+{
+    return x -= y;
+}
+
 template <class F, class Iterator>
 inline bool operator==(basic_iota_iterator<F, Iterator> x, basic_iota_iterator<F, Iterator> y)
 {

src/include/migraphx/par_for.hpp

@@ -78,8 +78,8 @@ void par_for_impl(std::size_t n, std::size_t threadsize, F f)
 template <class F>
 void par_for(std::size_t n, std::size_t min_grain, F f)
 {
-    const auto threadsize =
-        std::min<std::size_t>(std::thread::hardware_concurrency(), n / min_grain);
+    const auto threadsize = std::min<std::size_t>(std::thread::hardware_concurrency(),
+                                                  n / std::max<std::size_t>(1, min_grain));
     par_for_impl(n, threadsize, f);
 }
 

src/program.cpp

@@ -180,6 +180,63 @@ void program::finalize()
     mm->finalize(this->impl->ctx);
 }
 
+template <class T>
+std::string classify(T x)
+{
+    switch(std::fpclassify(x))
+    {
+    case FP_INFINITE: return "inf";
+    case FP_NAN: return "nan";
+    case FP_NORMAL: return "normal";
+    case FP_SUBNORMAL: return "subnormal";
+    case FP_ZERO: return "zero";
+    default: return "unknown";
+    }
+}
+
+std::unordered_set<std::string> classify_argument(const argument& a)
+{
+    std::unordered_set<std::string> result;
+    a.visit(
+        [&](auto t) {
+            for(const auto& x : t)
+                result.insert(classify(x));
+        },
+        [&](const auto& xs) {
+            for(const auto& x : xs)
+            {
+                auto r = classify_argument(x);
+                result.insert(r.begin(), r.end());
+            }
+        });
+    return result;
+}
+
+void preview_argument(std::ostream& os, const argument& a)
+{
+    a.visit(
+        [&](auto t) {
+            if(t.size() <= 10)
+            {
+                os << t;
+            }
+            else
+            {
+                os << to_string_range(t.begin(), t.begin() + 5);
+                os << ", ..., ";
+                os << to_string_range(t.end() - 5, t.end());
+            }
+        },
+        [&](const auto& xs) {
+            for(const auto& x : xs)
+            {
+                os << '{';
+                preview_argument(os, x);
+                os << '}';
+            }
+        });
+}
+
 template <class F>
 std::vector<argument> generic_eval(const module* mod,
                                    context& ctx,
@@ -313,7 +370,20 @@ std::vector<argument> program::eval(parameter_map params) const
                                    ins->name() != "load" and not result.empty())
                                 {
                                     target tgt  = make_target(this->impl->target_name);
-                                    std::cout << "Output: " << tgt.copy_from(result) << std::endl;
+                                    auto buffer = tgt.copy_from(result);
+                                    if(trace_level == 2)
+                                    {
+                                        std::cout << "Output has "
+                                                  << to_string_range(classify_argument(buffer))
+                                                  << std::endl;
+                                        std::cout << "Output: ";
+                                        preview_argument(std::cout, buffer);
+                                        std::cout << std::endl;
+                                    }
+                                    else
+                                    {
+                                        std::cout << "Output: " << buffer << std::endl;
+                                    }
                                 }
                                 return result;
                             }));

src/targets/gpu/compile_ops.cpp

@@ -12,6 +12,8 @@ namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace gpu {
 
+MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_GPU_COMPILE_PARALLEL);
+
 struct precompile_op
 {
     operation op = op::identity{};
@@ -70,6 +72,14 @@ struct compiled_result
     instruction_ref ins;
 };
 
+template <class F>
+void par_compile(std::size_t n, F f)
+{
+    if(n == 0)
+        return;
+    par_for(n, n / value_of(MIGRAPHX_GPU_COMPILE_PARALLEL{}, n), f);
+}
+
 void compile_ops::apply(module& m) const
 {
     auto compilers = make_compilers(pointwise_compiler{});
@@ -85,7 +95,7 @@ void compile_ops::apply(module& m) const
         compiles.emplace_back([=]() -> compiled_result { return {c(*ctx, ins, preop), ins}; });
     }
     std::vector<compiled_result> results(compiles.size());
-    par_for(compiles.size(), 1, [&](auto i) { results[i] = compiles[i](); });
+    par_compile(compiles.size(), [&](auto i) { results[i] = compiles[i](); });
     for(const auto& cr : results)
     {
         m.replace_instruction(cr.ins, cr.op, cr.ins->inputs());

src/targets/gpu/compile_pointwise.cpp

@@ -70,6 +70,9 @@ operation compile_pointwise(context& ctx, const std::vector<shape>& inputs, modu
     g.add_point_op("less", "migraphx::abs(${0} < ${1})");
     g.add_point_op("greater", "migraphx::abs(${0} > ${1})");
     g.add_point_op("not", "migraphx::abs(not ${0})");
+    // Add explict conversions
+    g.fresult(
+        [](const shape& s) { return "migraphx::convert<" + shape::cpp_type(s.type()) + ">"; });
     auto name =
         g.create_function(g.generate_module(m).set_attributes({"__device__"}).set_generic_types(m));
     return compile_pointwise((ctx), inputs, "MIGRAPHX_LIFT(" + name + ")", g.str());

src/targets/gpu/kernels/include/migraphx/kernels/vec.hpp

@@ -66,6 +66,9 @@ __device__ __host__ auto as_vec(T* x)
         return reinterpret_cast<vec<T, N>*>(x);
 }
 
+template <class T, index_int N>
+using safe_vec = vec<std::conditional_t<std::is_same<T, bool>{}, uint8_t, T>, N>;
+
 template <class... Ts>
 constexpr auto vec_transform(Ts... xs)
 {
@@ -74,7 +77,7 @@ constexpr auto vec_transform(Ts... xs)
         {
             using type                  = decltype(f(vec_at(xs, 0)...));
             constexpr auto size         = common_vec_size<Ts...>();
-            vec<type, size> result = {0};
+            safe_vec<type, size> result = {0};
             for(int i = 0; i < size; i++)
                 result[i] = f(vec_at(xs, i)...);
             return result;

src/targets/gpu/kernels/include/migraphx/kernels/vectorize.hpp

@@ -50,14 +50,14 @@ constexpr auto shape_step(Shape s, Axis)
     });
 }
 
-// Bools can not be used as a vector type so convert it to int8
+// Bools can not be used as a vector type so convert it to uint8
 template <class T>
 __device__ __host__ T* remove_bool(T* x)
 {
     return x;
 }
 
-inline __device__ __host__ int8_t* remove_bool(bool* x) { return reinterpret_cast<int8_t*>(x); }
+inline __device__ __host__ uint8_t* remove_bool(bool* x) { return reinterpret_cast<uint8_t*>(x); }
 
 template <index_int N, class T, class Axis>
 __device__ __host__ auto as_vec(T x, Axis axis)