* standalone attention sane offloads to mlir but mlir is broken

src/targets/gpu/fuse_mlir.cpp

@@ -81,6 +81,7 @@ struct mlir_op
             MIGRAPHX_THROW("should have at least two inputs.");
 
         module_ref mod = mods[0];
+        std::cerr << "mod:" << *mod << std::endl;
         auto type      = mod->get_output_shapes().front().type();
         std::unordered_map<instruction_ref, shape> ins_shapes;
         size_t param_cnt               = 0;
@@ -448,19 +449,31 @@ struct find_mlir_standalone_attention_op : find_mlir_standalone_op
                      [&](auto input) { return input != top_ins; });
       }
       auto softmax = mm->add_instruction(r.instructions["softmax"]->get_operator(), new_top_ins);
-      insert_to_map(ins_map, r.instructions["softmax"], softmax);
+      std::transform(r.instructions["bottom_dot"]->inputs().begin(),
+                     r.instructions["bottom_dot"]->inputs().end(),
+                     std::inserter(ins_map, ins_map.end()),
+                     [&](auto old_ins) {
+                        if(old_ins == r.instructions["softmax"]){
+                            return std::make_pair(old_ins, softmax);
+                        }
+                        inputs.push_back(old_ins);
+                        return std::make_pair(old_ins,
+                                              mm->add_parameter("bdot_non_smax_in", old_ins->get_shape()));
+                     });
       auto bottom_dot_a = get_from_map(ins_map, r.instructions["bottom_dot"]->inputs().front());
       auto bottom_dot_b = get_from_map(ins_map, r.instructions["bottom_dot"]->inputs().back());
       auto new_bottom_dot = mm->add_instruction(make_op("dot"), {bottom_dot_a, bottom_dot_b});
       mm->add_return({new_bottom_dot});
+
+
       inputs.insert(inputs.end(), top_inputs.begin(), top_inputs.end());
       mpm.get_module().replace_instruction(
-      top_ins, mlir_op{new_bottom_dot->get_operator()}, inputs, {mm});
+      r.instructions["bottom_dot"], mlir_op{new_bottom_dot->get_operator()}, inputs, {mm});
     }
 
     auto matcher() const {
         auto match_softmax_input =  match::any_of[match::inputs()](match::name("dot").bind("top_dot"), match::name("pointwise")(match::any_of[match::inputs()](match::name("dot").bind("top_dot"))).bind("scale"));
-        auto is_mlir_attention = match::name("dot")(match::any_of[match::inputs()](match::name("softmax").bind("softmax"))).bind("bottom_dot");
+        auto is_mlir_attention = match::name("dot")(match::any_of[match::inputs()](match::name("softmax")(match_softmax_input).bind("softmax"))).bind("bottom_dot");
         return is_mlir_attention;
     }
 
@@ -554,12 +567,12 @@ bool is_enabled(std::string_view op_name, context* ctx)
 void fuse_mlir::apply(module_pass_manager& mpm) const
 {
 #ifdef MIGRAPHX_MLIR
+    match::find_matches(mpm, find_mlir_standalone_attention_op{});
     if(is_enabled("fused", this->ctx))
     {   
         match::find_matches(mpm, find_mlir_attention_fused_ops{});
         match::find_matches(mpm, find_mlir_fused_ops{});
     }
-    match::find_matches(mpm, find_mlir_standalone_attention_op{});
 
     if(is_enabled("convolution", this->ctx))
     {