Merge branch 'develop' into fastsoftmax

.github/workflows/ci.yaml

@@ -53,6 +53,7 @@ jobs:
         CXX=/opt/rocm/llvm/bin/clang++ CC=/opt/rocm/llvm/bin/clang cmake \
           -DMIGRAPHX_ENABLE_GPU=On \
           -DMIGRAPHX_ENABLE_CPU=On \
+          -DMIGRAPHX_ENABLE_FPGA=On \
           -DROCM_ENABLE_GH_ANNOTATIONS=On \
           -DCLANG_TIDY_DEPEND_ON_TARGET=Off \
           -DCLANG_TIDY_CACHE=/data/tidy-cache \

src/CMakeLists.txt

@@ -90,7 +90,6 @@ add_library(migraphx
     shape.cpp
     simplify_algebra.cpp
     simplify_reshapes.cpp
-    target_assignments.cpp
     tmp_dir.cpp
     value.cpp
     verify_args.cpp

src/driver/alexnet.cpp

@@ -25,13 +25,10 @@
 #include <migraphx/make_op.hpp>
 #include <migraphx/program.hpp>
 #include <migraphx/generate.hpp>
-#include <migraphx/json.hpp>
 #include "models.hpp"
-
 namespace migraphx {
 namespace driver {
 inline namespace MIGRAPHX_INLINE_NS {
-
 migraphx::program alexnet(unsigned batch) // NOLINT(readability-function-size)
 {
     migraphx::program p;
@@ -42,179 +39,153 @@ migraphx::program alexnet(unsigned batch) // NOLINT(readability-function-size)
         migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 1)));
     auto x_main_module_2       = mmain->add_literal(migraphx::abs(
         migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1}}, 2)));
-    auto x_input_1             = mmain->add_parameter(
-        "input.1", migraphx::shape{migraphx::shape::float_type, {batch, 3, 224, 224}});
+    auto x_0                   = mmain->add_parameter(
+        "0", migraphx::shape{migraphx::shape::float_type, {batch, 3, 224, 224}});
     auto x_main_module_4 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 4096}}, 3));
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000}}, 3));
     auto x_main_module_5 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 4));
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000, 4096}}, 4));
     auto x_main_module_6 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 9216}}, 5));
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 5));
     auto x_main_module_7 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 6));
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 4096}}, 6));
     auto x_main_module_8 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000, 4096}}, 7));
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096}}, 7));
     auto x_main_module_9 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {1000}}, 8));
-    auto x_main_module_10 = mmain->add_literal(migraphx::generate_literal(
-        migraphx::shape{migraphx::shape::float_type, {256, 384, 3, 3}}, 9));
-    auto x_main_module_11 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 10));
-    auto x_main_module_12 = mmain->add_literal(migraphx::generate_literal(
-        migraphx::shape{migraphx::shape::float_type, {384, 192, 3, 3}}, 11));
-    auto x_main_module_13 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 12));
-    auto x_main_module_14 = mmain->add_literal(migraphx::generate_literal(
-        migraphx::shape{migraphx::shape::float_type, {192, 64, 5, 5}}, 13));
-    auto x_main_module_15 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {192}}, 14));
-    auto x_main_module_16 = mmain->add_literal(migraphx::generate_literal(
-        migraphx::shape{migraphx::shape::float_type, {256, 256, 3, 3}}, 15));
-    auto x_main_module_17 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 16));
-    auto x_main_module_18 = mmain->add_literal(migraphx::generate_literal(
-        migraphx::shape{migraphx::shape::float_type, {64, 3, 11, 11}}, 17));
-    auto x_main_module_19 = mmain->add_literal(
-        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {64}}, 18));
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {4096, 9216}}, 8));
+    auto x_main_module_10 = mmain->add_literal(
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 9));
+    auto x_main_module_11 = mmain->add_literal(migraphx::generate_literal(
+        migraphx::shape{migraphx::shape::float_type, {256, 256, 3, 3}}, 10));
+    auto x_main_module_12 = mmain->add_literal(
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {256}}, 11));
+    auto x_main_module_13 = mmain->add_literal(migraphx::generate_literal(
+        migraphx::shape{migraphx::shape::float_type, {256, 384, 3, 3}}, 12));
+    auto x_main_module_14 = mmain->add_literal(
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {384}}, 13));
+    auto x_main_module_15 = mmain->add_literal(migraphx::generate_literal(
+        migraphx::shape{migraphx::shape::float_type, {384, 192, 3, 3}}, 14));
+    auto x_main_module_16 = mmain->add_literal(
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {192}}, 15));
+    auto x_main_module_17 = mmain->add_literal(migraphx::generate_literal(
+        migraphx::shape{migraphx::shape::float_type, {192, 64, 5, 5}}, 16));
+    auto x_main_module_18 = mmain->add_literal(
+        migraphx::generate_literal(migraphx::shape{migraphx::shape::float_type, {64}}, 17));
+    auto x_main_module_19 = mmain->add_literal(migraphx::generate_literal(
+        migraphx::shape{migraphx::shape::float_type, {64, 3, 11, 11}}, 18));
     auto x_main_module_20 = mmain->add_instruction(
-        migraphx::make_op(
-            "convolution",
-            migraphx::from_json_string(
-                "{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[4,4]}")),
-        x_input_1,
-        x_main_module_18);
-    auto x_main_module_21 = mmain->add_instruction(
-        migraphx::make_op("broadcast",
-                          migraphx::from_json_string("{axis:1,out_lens:[1,64,55,55]}")),
+        migraphx::make_json_op("convolution",
+                               "{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[4,"
+                               "4],use_dynamic_same_auto_pad:0}"),
+        x_0,
         x_main_module_19);
+    auto x_main_module_21 = mmain->add_instruction(
+        migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,64,55,55]}"), x_main_module_18);
     auto x_main_module_22 =
         mmain->add_instruction(migraphx::make_op("add"), x_main_module_20, x_main_module_21);
     auto x_main_module_23 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_22);
     auto x_main_module_24 = mmain->add_instruction(
-        migraphx::make_op(
+        migraphx::make_json_op(
             "pooling",
-            migraphx::from_json_string(
-                "{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}")),
+            "{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
         x_main_module_23);
     auto x_main_module_25 = mmain->add_instruction(
-        migraphx::make_op(
-            "convolution",
-            migraphx::from_json_string(
-                "{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[1,1]}")),
+        migraphx::make_json_op("convolution",
+                               "{dilation:[1,1],group:1,padding:[2,2,2,2],padding_mode:0,stride:[1,"
+                               "1],use_dynamic_same_auto_pad:0}"),
         x_main_module_24,
-        x_main_module_14);
+        x_main_module_17);
     auto x_main_module_26 = mmain->add_instruction(
-        migraphx::make_op("broadcast",
-                          migraphx::from_json_string("{axis:1,out_lens:[1,192,27,27]}")),
-        x_main_module_15);
+        migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,192,27,27]}"), x_main_module_16);
     auto x_main_module_27 =
         mmain->add_instruction(migraphx::make_op("add"), x_main_module_25, x_main_module_26);
     auto x_main_module_28 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_27);
     auto x_main_module_29 = mmain->add_instruction(
-        migraphx::make_op(
+        migraphx::make_json_op(
             "pooling",
-            migraphx::from_json_string(
-                "{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}")),
+            "{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
         x_main_module_28);
     auto x_main_module_30 = mmain->add_instruction(
-        migraphx::make_op(
-            "convolution",
-            migraphx::from_json_string(
-                "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}")),
+        migraphx::make_json_op("convolution",
+                               "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,"
+                               "1],use_dynamic_same_auto_pad:0}"),
         x_main_module_29,
-        x_main_module_12);
+        x_main_module_15);
     auto x_main_module_31 = mmain->add_instruction(
-        migraphx::make_op("broadcast",
-                          migraphx::from_json_string("{axis:1,out_lens:[1,384,13,13]}")),
-        x_main_module_13);
+        migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,384,13,13]}"), x_main_module_14);
     auto x_main_module_32 =
         mmain->add_instruction(migraphx::make_op("add"), x_main_module_30, x_main_module_31);
     auto x_main_module_33 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_32);
     auto x_main_module_34 = mmain->add_instruction(
-        migraphx::make_op(
-            "convolution",
-            migraphx::from_json_string(
-                "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}")),
+        migraphx::make_json_op("convolution",
+                               "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,"
+                               "1],use_dynamic_same_auto_pad:0}"),
         x_main_module_33,
-        x_main_module_10);
+        x_main_module_13);
     auto x_main_module_35 = mmain->add_instruction(
-        migraphx::make_op("broadcast",
-                          migraphx::from_json_string("{axis:1,out_lens:[1,256,13,13]}")),
-        x_main_module_11);
+        migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,13,13]}"), x_main_module_12);
     auto x_main_module_36 =
         mmain->add_instruction(migraphx::make_op("add"), x_main_module_34, x_main_module_35);
     auto x_main_module_37 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_36);
     auto x_main_module_38 = mmain->add_instruction(
-        migraphx::make_op(
-            "convolution",
-            migraphx::from_json_string(
-                "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,1]}")),
+        migraphx::make_json_op("convolution",
+                               "{dilation:[1,1],group:1,padding:[1,1,1,1],padding_mode:0,stride:[1,"
+                               "1],use_dynamic_same_auto_pad:0}"),
         x_main_module_37,
-        x_main_module_16);
+        x_main_module_11);
     auto x_main_module_39 = mmain->add_instruction(
-        migraphx::make_op("broadcast",
-                          migraphx::from_json_string("{axis:1,out_lens:[1,256,13,13]}")),
-        x_main_module_17);
+        migraphx::make_json_op("broadcast", "{axis:1,out_lens:[1,256,13,13]}"), x_main_module_10);
     auto x_main_module_40 =
         mmain->add_instruction(migraphx::make_op("add"), x_main_module_38, x_main_module_39);
     auto x_main_module_41 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_40);
     auto x_main_module_42 = mmain->add_instruction(
-        migraphx::make_op(
+        migraphx::make_json_op(
             "pooling",
-            migraphx::from_json_string(
-                "{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}")),
+            "{ceil_mode:0,lengths:[3,3],lp_order:2,mode:1,padding:[0,0,0,0],stride:[2,2]}"),
         x_main_module_41);
-    auto x_main_module_43 = mmain->add_instruction(
-        migraphx::make_op("reshape", migraphx::from_json_string("{dims:[1,9216]}")),
-        x_main_module_42);
-    auto x_main_module_44 = mmain->add_instruction(
-        migraphx::make_op("transpose", migraphx::from_json_string("{permutation:[1,0]}")),
-        x_main_module_6);
-    auto x_main_module_45 =
-        mmain->add_instruction(migraphx::make_op("dot"), x_main_module_43, x_main_module_44);
-    auto x_main_module_46 = mmain->add_instruction(
-        migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
-        x_main_module_7);
+    auto x_main_module_43 =
+        mmain->add_instruction(migraphx::make_json_op("flatten", "{axis:1}"), x_main_module_42);
+    auto x_main_module_44 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_43);
+    auto x_main_module_45 = mmain->add_instruction(
+        migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_9);
+    auto x_main_module_46 =
+        mmain->add_instruction(migraphx::make_op("dot"), x_main_module_44, x_main_module_45);
     auto x_main_module_47 = mmain->add_instruction(
-        migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
-        x_main_module_2);
-    auto x_main_module_48 =
-        mmain->add_instruction(migraphx::make_op("mul"), x_main_module_46, x_main_module_47);
+        migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_8);
+    auto x_main_module_48 = mmain->add_instruction(
+        migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_2);
     auto x_main_module_49 =
-        mmain->add_instruction(migraphx::make_op("add"), x_main_module_45, x_main_module_48);
-    auto x_main_module_50 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_49);
-    auto x_main_module_51 = mmain->add_instruction(
-        migraphx::make_op("transpose", migraphx::from_json_string("{permutation:[1,0]}")),
-        x_main_module_4);
-    auto x_main_module_52 =
-        mmain->add_instruction(migraphx::make_op("dot"), x_main_module_50, x_main_module_51);
+        mmain->add_instruction(migraphx::make_op("mul"), x_main_module_47, x_main_module_48);
+    auto x_main_module_50 =
+        mmain->add_instruction(migraphx::make_op("add"), x_main_module_46, x_main_module_49);
+    auto x_main_module_51 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_50);
+    auto x_main_module_52 = mmain->add_instruction(migraphx::make_op("identity"), x_main_module_51);
     auto x_main_module_53 = mmain->add_instruction(
-        migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
-        x_main_module_5);
-    auto x_main_module_54 = mmain->add_instruction(
-        migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,4096]}")),
-        x_main_module_1);
-    auto x_main_module_55 =
-        mmain->add_instruction(migraphx::make_op("mul"), x_main_module_53, x_main_module_54);
-    auto x_main_module_56 =
-        mmain->add_instruction(migraphx::make_op("add"), x_main_module_52, x_main_module_55);
-    auto x_main_module_57 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_56);
-    auto x_main_module_58 = mmain->add_instruction(
-        migraphx::make_op("transpose", migraphx::from_json_string("{permutation:[1,0]}")),
-        x_main_module_8);
-    auto x_main_module_59 =
-        mmain->add_instruction(migraphx::make_op("dot"), x_main_module_57, x_main_module_58);
+        migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_7);
+    auto x_main_module_54 =
+        mmain->add_instruction(migraphx::make_op("dot"), x_main_module_52, x_main_module_53);
+    auto x_main_module_55 = mmain->add_instruction(
+        migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_6);
+    auto x_main_module_56 = mmain->add_instruction(
+        migraphx::make_json_op("multibroadcast", "{out_lens:[1,4096]}"), x_main_module_1);
+    auto x_main_module_57 =
+        mmain->add_instruction(migraphx::make_op("mul"), x_main_module_55, x_main_module_56);
+    auto x_main_module_58 =
+        mmain->add_instruction(migraphx::make_op("add"), x_main_module_54, x_main_module_57);
+    auto x_main_module_59 = mmain->add_instruction(migraphx::make_op("relu"), x_main_module_58);
     auto x_main_module_60 = mmain->add_instruction(
-        migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,1000]}")),
-        x_main_module_9);
-    auto x_main_module_61 = mmain->add_instruction(
-        migraphx::make_op("multibroadcast", migraphx::from_json_string("{out_lens:[1,1000]}")),
-        x_main_module_0);
-    auto x_main_module_62 =
-        mmain->add_instruction(migraphx::make_op("mul"), x_main_module_60, x_main_module_61);
-    auto x_main_module_63 =
-        mmain->add_instruction(migraphx::make_op("add"), x_main_module_59, x_main_module_62);
-    mmain->add_return({x_main_module_63});
+        migraphx::make_json_op("transpose", "{permutation:[1,0]}"), x_main_module_5);
+    auto x_main_module_61 =
+        mmain->add_instruction(migraphx::make_op("dot"), x_main_module_59, x_main_module_60);
+    auto x_main_module_62 = mmain->add_instruction(
+        migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_4);
+    auto x_main_module_63 = mmain->add_instruction(
+        migraphx::make_json_op("multibroadcast", "{out_lens:[1,1000]}"), x_main_module_0);
+    auto x_main_module_64 =
+        mmain->add_instruction(migraphx::make_op("mul"), x_main_module_62, x_main_module_63);
+    auto x_main_module_65 =
+        mmain->add_instruction(migraphx::make_op("add"), x_main_module_61, x_main_module_64);
+    mmain->add_return({x_main_module_65});
 
     return p;
 }

src/include/migraphx/make_op.hpp

@@ -27,6 +27,8 @@
 #include <migraphx/config.hpp>
 #include <migraphx/operation.hpp>
 #include <migraphx/value.hpp>
+#include <migraphx/json.hpp>
+#include <migraphx/convert_to_json.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -46,6 +48,8 @@ operation make_op(const std::string& name, const Value& v)
     return make_op_from_value(name, v);
 }
 
+operation make_json_op(const std::string& name, const std::string& s);
+
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 

src/include/migraphx/onnx.hpp

@@ -35,17 +35,13 @@ struct onnx_options
 {
     /// Old way to set default fixed dimension size
     std::size_t default_dim_value = 0;
-    /*!
-     * Default dynamic dimension size (if both default_dim_value and default_dyn_dim_value
-     * set parser throws)
-     */
+    /// Default dynamic dimension size (if both default_dim_value and default_dyn_dim_value set
+    /// parser throws)
     shape::dynamic_dimension default_dyn_dim_value = {1, 1, 0};
     /// Explicitly specify the dims of an input
     std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims = {};
-    /*!
-     * Explicitly specify dynamic dims of an input (if both map_input_dims and
-     * map_dyn_input_dims set parser throws)
-     */
+    /// Explicitly specify dynamic dims of an input (if both map_input_dims and map_dyn_input_dims
+    /// set parser throws)
     std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims = {};
     /// Continue parsing onnx file if an unknown operator is found
     bool skip_unknown_operators = false;
@@ -53,6 +49,8 @@ struct onnx_options
     bool print_program_on_error = false;
     /// Max iter num for the loop operator
     int64_t max_loop_iterations = 10;
+    /// Use dynamic output for operators when available
+    bool use_dyn_output = false;
 };
 
 /// Create a program from an onnx file

src/include/migraphx/op/convert.hpp

@@ -45,7 +45,15 @@ struct convert : unary<convert>
     shape compute_shape(std::vector<shape> inputs) const
     {
         check_shapes{inputs, *this}.has(1);
-        return {target_type, inputs.at(0).lens(), inputs.at(0).strides()};
+        auto input = inputs.at(0);
+        if(input.dynamic())
+        {
+            return {target_type, input.dyn_dims()};
+        }
+        else
+        {
+            return {target_type, input.lens(), input.strides()};
+        }
     }
 
     std::string point_op() const

src/include/migraphx/op/nonmaxsuppression.hpp

@@ -45,11 +45,13 @@ namespace op {
 struct nonmaxsuppression
 {
     bool center_point_box = false;
+    bool use_dyn_output   = false;
 
     template <class Self, class F>
     static auto reflect(Self& self, F f)
     {
-        return pack(f(self.center_point_box, "center_point_box"));
+        return pack(f(self.center_point_box, "center_point_box"),
+                    f(self.use_dyn_output, "use_dyn_output"));
     }
 
     std::string name() const { return "nonmaxsuppression"; }
@@ -57,28 +59,82 @@ struct nonmaxsuppression
     shape compute_shape(std::vector<shape> inputs) const
     {
         // requires at least 2 inputs
-        check_shapes{{inputs.at(0), inputs.at(1)}, *this}.only_dims(3);
-        auto lens = inputs.front().lens();
+        check_shapes{{inputs.at(0), inputs.at(1)}, *this, true}.only_dims(3).same_ndims();
+        auto boxes_max_lens = inputs.at(0).max_lens();
+        // num batches * num boxes
+        const auto max_num_boxes = boxes_max_lens.at(0) * boxes_max_lens.at(1);
 
-        // check input shape
+        auto fixed_shape_error_check = [&]() {
+            auto lens = inputs.front().lens();
             if(lens[1] != inputs.at(1).lens()[2])
             {
                 MIGRAPHX_THROW(
                     "NonMaxSuppression: spatial dimension mismatch between boxes and scores input");
             }
-
-        // check batch sizes
             if(lens[0] != inputs.at(1).lens()[0])
             {
                 MIGRAPHX_THROW(
                     "NonMaxSuppression: number of batches mismatch between boxes and scores input");
             }
+        };
 
-        std::vector<int64_t> out_lens(2);
-        out_lens.at(0) = lens.at(1);
-        out_lens.at(1) = 3;
+        if(use_dyn_output)
+        {
+            if(inputs.at(0).dynamic())
+            {
+                // both boxes and scores should be dynamic
+                // check dynamic dimensions are consistent
+                const auto boxes_dims  = inputs.at(0).dyn_dims();
+                const auto scores_dims = inputs.at(1).dyn_dims();
+                if(boxes_dims.at(1) != scores_dims.at(2))
+                {
+                    MIGRAPHX_THROW("NonMaxSuppression: dynamic spatial dimension mismatch between "
+                                   "boxes and scores input");
+                }
+                if(boxes_dims.at(0) != scores_dims.at(0))
+                {
+                    MIGRAPHX_THROW("NonMaxSuppression: dynamic number of batches mismatch between "
+                                   "boxes and scores input");
+                }
+            }
+            else if(inputs.at(1).dynamic())
+            {
+                // scores has dynamic shape, boxes fixed shape
+                // check that it is only a dynamic number of classes
+                const auto scores_dims = inputs.at(1).dyn_dims();
+                const auto boxes_lens  = inputs.at(0).lens();
+                if(not scores_dims.at(0).is_fixed() or scores_dims.at(0).max != boxes_lens.at(0))
+                {
+                    MIGRAPHX_THROW("NonMaxSuppression: scores dynamic num_classes; num_batches not "
+                                   "fixed or mismatched");
+                }
+                if(not scores_dims.at(2).is_fixed() or scores_dims.at(2).max != boxes_lens.at(1))
+                {
+                    MIGRAPHX_THROW("NonMaxSuppression: scores dynamic num_classes; "
+                                   "spatial_dimension not fixed or mismatches");
+                }
+            }
+            else
+            {
+                fixed_shape_error_check();
+            }
+            std::vector<shape::dynamic_dimension> out_lens = {};
+            out_lens.push_back({0, max_num_boxes, 0});
+            out_lens.push_back({3, 3, 0});
             return {shape::int64_type, out_lens};
         }
+        else
+        {
+            if(inputs.at(0).dynamic() or inputs.at(1).dynamic())
+            {
+                MIGRAPHX_THROW(
+                    "NonMaxSuppression: dynamic input shape with use_dyn_output set to false");
+            }
+            fixed_shape_error_check();
+            std::vector<std::size_t> out_lens = {max_num_boxes, 3};
+            return {shape::int64_type, out_lens};
+        }
+    }
 
     struct box
     {
@@ -181,10 +237,10 @@ struct nonmaxsuppression
     }
 
     template <class Output, class Boxes, class Scores>
-    void compute_nms(Output output,
+    std::size_t compute_nms(Output output,
                             Boxes boxes,
                             Scores scores,
-                     const shape& output_shape,
+                            const shape& max_output_shape,
                             std::size_t max_output_boxes_per_class,
                             double iou_threshold,
                             double score_threshold) const
@@ -197,7 +253,7 @@ struct nonmaxsuppression
         // boxes of a class with NMS applied [score, index]
         std::vector<std::pair<double, int64_t>> selected_boxes_inside_class;
         std::vector<int64_t> selected_indices;
-        selected_boxes_inside_class.reserve(output_shape.elements());
+        selected_boxes_inside_class.reserve(max_output_shape.elements());
         // iterate over batches and classes
         shape comp_s{shape::double_type, {num_batches, num_classes}};
         shape_for_each(comp_s, [&](auto idx) {
@@ -237,11 +293,14 @@ struct nonmaxsuppression
             }
         });
         std::copy(selected_indices.begin(), selected_indices.end(), output.begin());
+        return selected_indices.size() / 3;
     }
 
     argument compute(const shape& output_shape, std::vector<argument> args) const
     {
-        argument result{output_shape};
+        // make buffer of maximum size
+        shape max_output_shape = {output_shape.type(), output_shape.max_lens()};
+        argument result{max_output_shape};
 
         std::size_t max_output_boxes_per_class =
             (args.size() > 2) ? (args.at(2).at<std::size_t>()) : 0;
@@ -251,21 +310,28 @@ struct nonmaxsuppression
         }
         double iou_threshold     = (args.size() > 3) ? (args.at(3).at<double>()) : 0.0f;
         double score_threshold   = (args.size() > 4) ? (args.at(4).at<double>()) : 0.0f;
+        std::size_t num_selected = 0;
 
         result.visit([&](auto output) {
             visit_all(args[0], args[1])([&](auto boxes, auto scores) {
-                compute_nms(output,
+                num_selected = compute_nms(output,
                                            boxes,
                                            scores,
-                            output_shape,
+                                           max_output_shape,
                                            max_output_boxes_per_class,
                                            iou_threshold,
                                            score_threshold);
             });
         });
-
+        if(use_dyn_output)
+        {
+            return result.reshape({output_shape.type(), {num_selected, 3}});
+        }
+        else
+        {
             return result;
         }
+    }
 };
 
 } // namespace op

src/target_assignments.cpp → src/include/migraphx/supported_segments.hpp

@@ -21,16 +21,24 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
+#ifndef MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
+#define MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
 
-#include <migraphx/target_assignments.hpp>
+#include <unordered_set>
+
+#include <migraphx/instruction_ref.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 
-void target_assignments::add_assignment(instruction_ref ins, const std::string& target)
+struct supported_segment
 {
-    assignments.emplace(ins, target);
-}
+    std::unordered_set<instruction_ref> instructions;
+    float metric;
+};
+
+using supported_segments = std::vector<supported_segment>;
 
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
+#endif // MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP

src/include/migraphx/target.hpp

@@ -37,8 +37,10 @@
 #include <migraphx/compile_options.hpp>
 #include <migraphx/argument.hpp>
 #include <migraphx/rank.hpp>
+#include <migraphx/module_ref.hpp>
 #include <migraphx/support_metric.hpp>
 #include <migraphx/instruction_ref.hpp>
+#include <migraphx/supported_segments.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -64,12 +66,12 @@ struct target
      */
     context get_context() const;
     /**
-     * @brief Check how well an instruction is supported on a target with the given metric
-     * @param ins Instruction to check if it's supported
-     * @param metric Used to define how the return value should be interpreted
-     * @return The value based on the chosen metric. Negative numbers mean unsupported
+     * @brief Get the ranges of instructions that are supported on a target
+     * @param module Module to check for supported instructions
+     * @param metric Used to define how the quality of the support should be measured
+     * @return the supported segments of the graph
      */
-    float is_supported(T&, instruction_ref ins, support_metric m) const;
+    supported_segments target_is_supported(T&, const_module_ref mod, support_metric metric) const;
     /**
      * @brief copy an argument to the current target.
      *
@@ -115,9 +117,9 @@ argument copy_from_target(T&, const argument& arg)
 }
 
 template <class T>
-float target_is_supported(T&, instruction_ref, support_metric)
+supported_segments target_find_supported(T&, const_module_ref, support_metric)
 {
-    return 0;
+    return {};
 }
 
 #ifdef TYPE_ERASED_DECLARATION
@@ -132,7 +134,7 @@ struct target
     //
     context get_context() const;
     // (optional)
-    float is_supported(instruction_ref ins, support_metric m) const;
+    supported_segments find_supported(const_module_ref mod, support_metric m) const;
     // (optional)
     argument copy_to(const argument& input) const;
     // (optional)
@@ -224,10 +226,10 @@ struct target
         return (*this).private_detail_te_get_handle().get_context();
     }
 
-    float is_supported(instruction_ref ins, support_metric m) const
+    supported_segments find_supported(const_module_ref mod, support_metric m) const
     {
         assert((*this).private_detail_te_handle_mem_var);
-        return (*this).private_detail_te_get_handle().is_supported(ins, m);
+        return (*this).private_detail_te_get_handle().find_supported(mod, m);
     }
 
     argument copy_to(const argument& input) const
@@ -265,29 +267,29 @@ struct target
         virtual std::vector<pass> get_passes(context& ctx,
                                              const compile_options& options) const              = 0;
         virtual context get_context() const                                                     = 0;
-        virtual float is_supported(instruction_ref ins, support_metric m) const    = 0;
+        virtual supported_segments find_supported(const_module_ref mod, support_metric m) const = 0;
         virtual argument copy_to(const argument& input) const                                   = 0;
         virtual argument copy_from(const argument& input) const                                 = 0;
         virtual argument allocate(const shape& s) const                                         = 0;
     };
 
     template <class T>
-    static auto private_detail_te_default_is_supported(char,
+    static auto private_detail_te_default_find_supported(char,
                                                          T&& private_detail_te_self,
-                                                       instruction_ref ins,
+                                                         const_module_ref mod,
                                                          support_metric m)
-        -> decltype(private_detail_te_self.is_supported(ins, m))
+        -> decltype(private_detail_te_self.find_supported(mod, m))
     {
-        return private_detail_te_self.is_supported(ins, m);
+        return private_detail_te_self.find_supported(mod, m);
     }
 
     template <class T>
-    static float private_detail_te_default_is_supported(float,
+    static supported_segments private_detail_te_default_find_supported(float,
                                                                        T&& private_detail_te_self,
-                                                        instruction_ref ins,
+                                                                       const_module_ref mod,
                                                                        support_metric m)
     {
-        return target_is_supported(private_detail_te_self, ins, m);
+        return target_find_supported(private_detail_te_self, mod, m);
     }
 
     template <class T>
@@ -372,10 +374,11 @@ struct target
 
         context get_context() const override { return private_detail_te_value.get_context(); }
 
-        float is_supported(instruction_ref ins, support_metric m) const override
+        supported_segments find_supported(const_module_ref mod, support_metric m) const override
         {
 
-            return private_detail_te_default_is_supported(char(0), private_detail_te_value, ins, m);
+            return private_detail_te_default_find_supported(
+                char(0), private_detail_te_value, mod, m);
         }
 
         argument copy_to(const argument& input) const override

src/include/migraphx/target_assignments.hpp

@@ -33,10 +33,20 @@ inline namespace MIGRAPHX_INLINE_NS {
 
 struct target_assignments
 {
-    void add_assignment(instruction_ref ins, const std::string& target);
+    using iterator   = std::unordered_map<instruction_ref, std::string>::const_iterator;
+    using value_type = std::pair<instruction_ref, std::string>;
 
-    auto begin() const { return assignments.cbegin(); }
-    auto end() const { return assignments.cend(); }
+    auto size() const { return assignments.size(); }
+    auto& at(instruction_ref ins) const { return assignments.at(ins); }
+
+    auto insert(iterator it, const std::pair<instruction_ref, std::string>& assignment)
+    {
+        return assignments.insert(it, assignment);
+    }
+    auto find(instruction_ref ins) const { return assignments.find(ins); }
+
+    auto begin() const { return assignments.begin(); }
+    auto end() const { return assignments.end(); }
 
     private:
     std::unordered_map<instruction_ref, std::string> assignments;

src/make_op.cpp

@@ -64,5 +64,10 @@ operation make_op_from_value(const std::string& name, const value& v)
     });
 }
 
+operation make_json_op(const std::string& name, const std::string& s)
+{
+    return make_op(name, from_json_string(convert_to_json(s)));
+}
+
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/module.cpp

@@ -788,12 +788,15 @@ static std::string cpp_var_name(const std::string& name)
 
 static void print_make_op(std::ostream& os, const operation& op)
 {
-    os << "migraphx::make_op(" << enclose_name(op.name());
     auto v = op.to_value();
     if(not v.empty())
     {
-        os << ", "
-           << "migraphx::from_json_string(" << enclose_name(to_json_string(v)) << ")";
+        os << "migraphx::make_json_op(" << enclose_name(op.name());
+        os << ", " << enclose_name(to_json_string(v));
+    }
+    else
+    {
+        os << "migraphx::make_op(" << enclose_name(op.name());
     }
     os << ")";
 }

src/onnx/include/migraphx/onnx/onnx_parser.hpp

@@ -97,6 +97,7 @@ struct onnx_parser
     shape::dynamic_dimension default_dyn_dim_value = {1, 1, 0};
     std::unordered_map<std::string, std::vector<std::size_t>> map_input_dims;
     std::unordered_map<std::string, std::vector<shape::dynamic_dimension>> map_dyn_input_dims;
+    bool use_dyn_output         = false;
     bool skip_unknown_operators = false;
     int64_t max_loop_iterations = 10;
     int64_t opset_version       = 13;

src/onnx/onnx.cpp

@@ -60,8 +60,14 @@ program parse_onnx_from(const onnx_options& options, Ts&&... xs)
     {
         parser.default_dyn_dim_value = options.default_dyn_dim_value;
     }
+    if(not options.map_input_dims.empty() and not options.map_dyn_input_dims.empty())
+    {
+        MIGRAPHX_THROW("PARSE_ONNX_FROM: both map_input_dims and map_dyn_input_dims non-empty, only"
+                       "one should be used");
+    }
     parser.skip_unknown_operators = options.skip_unknown_operators;
     parser.max_loop_iterations    = options.max_loop_iterations;
+    parser.use_dyn_output         = options.use_dyn_output;
 
     if(options.print_program_on_error)
     {
@@ -80,6 +86,7 @@ program parse_onnx_from(const onnx_options& options, Ts&&... xs)
     {
         parser.parse_from(std::forward<Ts>(xs)...);
     }
+
     return std::move(parser.prog);
 }
 

src/onnx/onnx_parser.cpp

@@ -256,11 +256,6 @@ int64_t onnx_parser::get_opset_version(const onnx::ModelProto& model)
 
 void onnx_parser::parse_graph(module* mod, const onnx::GraphProto& graph)
 {
-    if(not map_input_dims.empty() and not map_dyn_input_dims.empty())
-    {
-        MIGRAPHX_THROW("PARSE_GRAPH: both map_input_dims and map_dyn_input_dims non-empty, only"
-                       "one should be used");
-    }
     std::unordered_map<std::string, instruction_ref> mod_insts;
     for(auto&& f : graph.initializer())
     {

src/onnx/parse_generic_op.cpp

@@ -58,7 +58,6 @@ struct parse_generic_op : op_parser<parse_generic_op>
                 {"Log", "log"},
                 {"LRN", "lrn"},
                 {"Neg", "neg"},
-                {"NonMaxSuppression", "nonmaxsuppression"},
                 {"Reciprocal", "recip"},
                 {"Relu", "relu"},
                 {"Round", "round"},
@@ -75,7 +74,7 @@ struct parse_generic_op : op_parser<parse_generic_op>
 
     bool needs_contiguous(const std::string& op_name) const
     {
-        return contains({"flatten", "gather", "nonmaxsuppression", "scatter"}, op_name);
+        return contains({"flatten", "gather", "scatter"}, op_name);
     }
 
     instruction_ref parse(const op_desc& opd,

src/onnx/parse_nonmaxsuppression.cpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+#include <migraphx/onnx/op_parser.hpp>
+#include <migraphx/ranges.hpp>
+#include <migraphx/make_op.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace onnx {
+
+struct parse_nonmaxsuppression : op_parser<parse_nonmaxsuppression>
+{
+    std::vector<op_desc> operators() const { return {{"NonMaxSuppression", "nonmaxsuppression"}}; }
+
+    instruction_ref parse(const op_desc& opd,
+                          const onnx_parser& parser,
+                          const onnx_parser::node_info& info,
+                          const std::vector<instruction_ref>& args) const
+    {
+        auto op = parser.load(opd.op_name, info);
+        op.from_value({{"use_dyn_output", parser.use_dyn_output}});
+        return info.add_instruction(op, args);
+    }
+};
+
+} // namespace onnx
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/program.cpp

@@ -37,6 +37,7 @@
 #include <migraphx/output_iterator.hpp>
 #include <migraphx/make_op.hpp>
 #include <migraphx/marker.hpp>
+#include <migraphx/supported_segments.hpp>
 #include <iostream>
 #include <sstream>
 #include <algorithm>
@@ -167,13 +168,37 @@ target_assignments program::get_target_assignments(const std::vector<target>& ta
     target_assignments p;
 
     const auto* mod = get_main_module();
-    for(auto it : iterator_for(*mod))
+    std::vector<std::pair<target, supported_segments>> target_subgraphs;
+    target_subgraphs.reserve(targets.size());
+    std::transform(targets.begin(),
+                   targets.end(),
+                   std::back_inserter(target_subgraphs),
+                   [&](const auto& t) { return std::make_pair(t, t.find_supported(mod, m)); });
+
+    for(const auto ins : iterator_for(*mod))
     {
-        auto t = std::max_element(
-            targets.begin(), targets.end(), [it, m](const target& lhs, const target& rhs) {
-                return lhs.is_supported(it, m) < rhs.is_supported(it, m);
-            });
-        p.add_assignment(it, t->name());
+        if(contains(p, ins))
+        {
+            continue;
+        }
+
+        for(const auto& [target, subgraph] : target_subgraphs)
+        {
+            // can't pass a structured binding into lambda in C++17 so create a variable for it
+            const auto& t = target;
+            for(const auto& segment : subgraph)
+            {
+                const auto& instructions = segment.instructions;
+                if(not contains(instructions, ins))
+                {
+                    continue;
+                }
+                std::transform(instructions.begin(),
+                               instructions.end(),
+                               std::inserter(p, p.end()),
+                               [&](auto instr) { return std::make_pair(instr, t.name()); });
+            }
+        }
     }
     return p;
 }