Merge branch 'dyn_squeeze' of github.com:ROCmSoftwarePlatform/AMDMIGraphX into dyn_model_test

src/include/migraphx/schedule_model.hpp

@@ -208,7 +208,7 @@ struct schedule_model
         template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
         private_detail_te_handle_type(
             PrivateDetailTypeErasedT value,
-            typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
+            typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
                                     int>::type* = nullptr) noexcept
             : private_detail_te_value(std::move(value))
         {
@@ -274,7 +274,7 @@ struct schedule_model
     private_detail_te_handle_base_type& private_detail_te_get_handle()
     {
         assert(private_detail_te_handle_mem_var != nullptr);
-        if(!private_detail_te_handle_mem_var.unique())
+        if(not private_detail_te_handle_mem_var.unique())
             private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
         return *private_detail_te_handle_mem_var;
     }

src/include/migraphx/shape.hpp

@@ -30,6 +30,7 @@
 #include <numeric>
 #include <memory>
 
+#include <migraphx/functional.hpp>
 #include <migraphx/errors.hpp>
 #include <migraphx/half.hpp>
 #include <migraphx/config.hpp>
@@ -89,7 +90,10 @@ struct shape
         std::size_t opt = 0;
 
         template <class Self, class F>
-        static auto reflect(Self& self, F f);
+        static auto reflect(Self& self, F f)
+        {
+            return pack(f(self.min, "min"), f(self.max, "max"), f(self.opt, "opt"));
+        }
 
         bool is_fixed() const;
         bool has_optimal() const;
@@ -115,6 +119,12 @@ struct shape
 
     shape(type_t t, std::vector<dynamic_dimension> dims);
 
+    // Construct a dynamic shape from three sets of lengths (of the same rank)
+    shape(type_t t,
+          std::vector<std::size_t> mins,
+          std::vector<std::size_t> maxes,
+          std::vector<std::size_t> opts);
+
     template <class Range>
     shape(type_t t, const Range& l) : shape(t, std::vector<std::size_t>(l.begin(), l.end()))
     {
@@ -136,6 +146,12 @@ struct shape
     const std::vector<std::size_t>& lens() const;
     const std::vector<std::size_t>& strides() const;
 
+    /*!
+     * The number of dimensions in the shape.
+     * Same as the number of indices required to get a data value.
+     */
+    std::size_t ndim() const;
+
     /*!
      * Return the number of elements in the tensor.
      */
@@ -221,6 +237,9 @@ struct shape
 
     shape with_type(type_t t) const;
 
+    // convert the shape to an equivalent dynamic shape
+    shape to_dynamic() 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);

src/include/migraphx/stream_model.hpp

@@ -216,7 +216,7 @@ struct stream_model
         template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
         private_detail_te_handle_type(
             PrivateDetailTypeErasedT value,
-            typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
+            typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
                                     int>::type* = nullptr) noexcept
             : private_detail_te_value(std::move(value))
         {
@@ -288,7 +288,7 @@ struct stream_model
     private_detail_te_handle_base_type& private_detail_te_get_handle()
     {
         assert(private_detail_te_handle_mem_var != nullptr);
-        if(!private_detail_te_handle_mem_var.unique())
+        if(not private_detail_te_handle_mem_var.unique())
             private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
         return *private_detail_te_handle_mem_var;
     }

src/include/migraphx/streamutils.hpp

@@ -26,8 +26,11 @@
 
 #include <ostream>
 #include <algorithm>
+#include <migraphx/reflect.hpp>
 #include <migraphx/rank.hpp>
+#include <migraphx/requires.hpp>
 #include <migraphx/config.hpp>
+#include <vector>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -41,7 +44,7 @@ struct stream_range_container
     friend std::ostream& operator<<(std::ostream& os, const stream_range_container& sr)
     {
         assert(sr.r != nullptr);
-        if(!sr.r->empty())
+        if(not sr.r->empty())
         {
             os << sr.r->front();
             std::for_each(
@@ -59,10 +62,22 @@ inline stream_range_container<Range> stream_range(const Range& r)
 
 namespace detail {
 
-inline void stream_write_value_impl(rank<2>, std::ostream& os, const std::string& x) { os << x; }
+template <class T>
+auto stream_write_value_impl(rank<1>, std::ostream& os, const T& x) -> decltype(os << x, void())
+{
+    os << x;
+}
+
+template <class T>
+void stream_write_value_impl(rank<1>, std::ostream& os, const std::vector<T>& r)
+{
+    os << "{";
+    os << stream_range(r);
+    os << "}";
+}
 
 template <class Range>
-auto stream_write_value_impl(rank<1>, std::ostream& os, const Range& r)
+auto stream_write_value_impl(rank<0>, std::ostream& os, const Range& r)
     -> decltype(r.begin(), r.end(), void())
 {
     os << "{";
@@ -70,17 +85,26 @@ auto stream_write_value_impl(rank<1>, std::ostream& os, const Range& r)
     os << "}";
 }
 
-template <class T>
+template <class T, MIGRAPHX_REQUIRES(is_reflectable<T>{})>
 void stream_write_value_impl(rank<0>, std::ostream& os, const T& x)
 {
-    os << x;
+    char delim = '{';
+    reflect_each(x, [&](auto&& y, auto name) {
+        os << delim;
+        os << name << "=";
+        stream_write_value_impl(rank<2>{}, os, y);
+        delim = ',';
+    });
+    if(delim == ',')
+        os << "}";
 }
+
 } // namespace detail
 
 template <class T>
 void stream_write_value(std::ostream& os, const T& x)
 {
-    detail::stream_write_value_impl(rank<2>{}, os, x);
+    detail::stream_write_value_impl(rank<1>{}, os, x);
 }
 
 } // namespace MIGRAPHX_INLINE_NS

src/targets/gpu/include/migraphx/gpu/greater.hpp → src/include/migraphx/supported_segments.hpp

@@ -21,22 +21,24 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#ifndef MIGRAPHX_GUARD_RTGLIB_GREATER_HPP
-#define MIGRAPHX_GUARD_RTGLIB_GREATER_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
+#define MIGRAPHX_GUARD_MIGRAPHX_SUPPORTED_SEGMENTS_HPP
 
-#include <migraphx/gpu/oper.hpp>
-#include <migraphx/gpu/device/greater.hpp>
+#include <unordered_set>
+
+#include <migraphx/instruction_ref.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
 
-struct hip_greater : binary_device<hip_greater, device::greater>
+struct supported_segment
 {
+    std::unordered_set<instruction_ref> instructions;
+    float metric;
 };
 
-} // namespace gpu
+using supported_segments = std::vector<supported_segment>;
+
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
-
-#endif
+#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
@@ -261,33 +263,33 @@ struct target
         virtual std::shared_ptr<private_detail_te_handle_base_type> clone() const = 0;
         virtual const std::type_info& type() const                                = 0;
 
-        virtual std::string name() const                                           = 0;
+        virtual std::string name() const                                                        = 0;
         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 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;
+                                             const compile_options& options) const              = 0;
+        virtual context get_context() 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,
-                                                       T&& private_detail_te_self,
-                                                       instruction_ref ins,
-                                                       support_metric m)
-        -> decltype(private_detail_te_self.is_supported(ins, m))
+    static auto private_detail_te_default_find_supported(char,
+                                                         T&& private_detail_te_self,
+                                                         const_module_ref mod,
+                                                         support_metric 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,
-                                                        T&& private_detail_te_self,
-                                                        instruction_ref ins,
-                                                        support_metric m)
+    static supported_segments private_detail_te_default_find_supported(float,
+                                                                       T&& private_detail_te_self,
+                                                                       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>
@@ -349,7 +351,7 @@ struct target
         template <typename PrivateDetailTypeErasedU = PrivateDetailTypeErasedT>
         private_detail_te_handle_type(
             PrivateDetailTypeErasedT value,
-            typename std::enable_if<!std::is_reference<PrivateDetailTypeErasedU>::value,
+            typename std::enable_if<not std::is_reference<PrivateDetailTypeErasedU>::value,
                                     int>::type* = nullptr) noexcept
             : private_detail_te_value(std::move(value))
         {
@@ -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
@@ -423,7 +426,7 @@ struct target
     private_detail_te_handle_base_type& private_detail_te_get_handle()
     {
         assert(private_detail_te_handle_mem_var != nullptr);
-        if(!private_detail_te_handle_mem_var.unique())
+        if(not private_detail_te_handle_mem_var.unique())
             private_detail_te_handle_mem_var = private_detail_te_handle_mem_var->clone();
         return *private_detail_te_handle_mem_var;
     }

src/include/migraphx/target_assignments.hpp

@@ -25,6 +25,7 @@
 #define MIGRAPHX_GUARD_MIGRAPHX_ASSIGNMENT_HPP
 
 #include <unordered_map>
+#include <string>
 
 #include <migraphx/instruction_ref.hpp>
 
@@ -33,10 +34,20 @@ 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/include/migraphx/tensor_view.hpp

@@ -67,7 +67,7 @@ struct tensor_view
 
     const shape& get_shape() const { return this->m_shape; }
 
-    bool empty() const { return m_data == nullptr || m_shape.lens().empty(); }
+    bool empty() const { return m_data == nullptr or m_shape.lens().empty(); }
 
     std::size_t size() const { return m_shape.elements(); }
 
@@ -109,37 +109,37 @@ struct tensor_view
 
     T& operator[](std::size_t i)
     {
-        assert(!this->empty() && i < this->size());
+        assert(not this->empty() && i < this->size());
         return m_data[m_shape.index(i)];
     }
 
     const T& operator[](std::size_t i) const
     {
-        assert(!this->empty() && i < this->size());
+        assert(not this->empty() && i < this->size());
         return m_data[m_shape.index(i)];
     }
 
     T& front()
     {
-        assert(!this->empty());
+        assert(not this->empty());
         return m_data[0];
     }
 
     const T& front() const
     {
-        assert(!this->empty());
+        assert(not this->empty());
         return m_data[0];
     }
 
     T& back()
     {
-        assert(!this->empty());
+        assert(not this->empty());
         return m_data[m_shape.index(this->size() - 1)];
     }
 
     const T& back() const
     {
-        assert(!this->empty());
+        assert(not this->empty());
         return m_data[m_shape.index(this->size() - 1)];
     }
 
@@ -159,7 +159,7 @@ struct tensor_view
 
     friend std::ostream& operator<<(std::ostream& os, const tensor_view<T>& x)
     {
-        if(!x.empty())
+        if(not x.empty())
         {
             os << as_number(x.front());
             for(std::size_t i = 1; i < x.m_shape.elements(); i++)
@@ -182,7 +182,7 @@ bool operator==(const tensor_view<T>& x, const tensor_view<U>& y)
     {
         for(std::size_t i = 0; i < x.get_shape().elements(); i++)
         {
-            if(!float_equal(x[i], y[i]))
+            if(not float_equal(x[i], y[i]))
                 return false;
         }
         return true;
@@ -193,7 +193,7 @@ bool operator==(const tensor_view<T>& x, const tensor_view<U>& y)
 template <class T, class U>
 bool operator!=(const tensor_view<T>& x, const tensor_view<U>& y)
 {
-    return !(x == y);
+    return not(x == y);
 }
 
 template <class T>

src/include/migraphx/tune_axis.hpp

@@ -34,7 +34,7 @@ inline namespace MIGRAPHX_INLINE_NS {
 
 inline int tune_axis(const int n_dim, const int axis, const std::string& op_name = "OPERATOR")
 {
-    if(axis >= n_dim || std::abs(axis) > n_dim)
+    if(axis >= n_dim or std::abs(axis) > n_dim)
     {
         MIGRAPHX_THROW(to_upper(op_name) + ": axis is out of range.");
     }

src/include/migraphx/value.hpp

@@ -184,6 +184,12 @@ struct value
         {
         }
         explicit binary(std::size_t s) : base(s) {}
+
+        friend std::ostream& operator<<(std::ostream& os, const binary& obj)
+        {
+            os << "{binary_object: " << obj.size() << "}";
+            return os;
+        }
     };
 
     value() = default;

src/instruction.cpp

@@ -176,13 +176,13 @@ bool operator==(const instruction& x, const instruction& y)
     return true;
 }
 
-bool operator!=(const instruction& x, const instruction& y) { return !(x == y); }
+bool operator!=(const instruction& x, const instruction& y) { return not(x == y); }
 
 bool operator==(instruction_ref ref, const instruction& i) { return i == ref; }
 
-bool operator!=(const instruction& i, instruction_ref ref) { return !(i == ref); }
+bool operator!=(const instruction& i, instruction_ref ref) { return not(i == ref); }
 
-bool operator!=(instruction_ref ref, const instruction& i) { return !(i == ref); }
+bool operator!=(instruction_ref ref, const instruction& i) { return not(i == ref); }
 
 void instruction::add_output(instruction_ref ins)
 {
@@ -361,7 +361,7 @@ void instruction::print(std::ostream& os,
             os << "{" << ins->get_literal() << "}";
     }
 
-    if(!ins->inputs().empty())
+    if(not ins->inputs().empty())
     {
         char delim = '(';
         for(auto&& arg : ins->inputs())
@@ -374,7 +374,7 @@ void instruction::print(std::ostream& os,
     }
 
     // print module inputs
-    if(!ins->module_inputs().empty())
+    if(not ins->module_inputs().empty())
     {
         std::string delim = ", [";
         for(auto&& mod_arg : ins->module_inputs())
@@ -446,7 +446,7 @@ operation instruction::normalized_operator() const
     if(this->need_normalization())
     {
         auto s = this->inputs().front()->get_shape();
-        if(!normalize_attributes(o, s.max_lens()))
+        if(not normalize_attributes(o, s.max_lens()))
             return this->get_operator();
     }
     return o;

src/load_save.cpp

@@ -25,7 +25,6 @@
 #include <migraphx/file_buffer.hpp>
 #include <migraphx/json.hpp>
 #include <migraphx/msgpack.hpp>
-#include <migraphx/file_buffer.hpp>
 #include <fstream>
 
 namespace migraphx {

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

@@ -34,7 +34,6 @@
 #include <migraphx/pass_manager.hpp>
 #include <migraphx/make_op.hpp>
 #include <migraphx/register_target.hpp>
-#include <migraphx/make_op.hpp>
 #include <migraphx/json.hpp>
 #include <iostream>
 #include <sstream>
@@ -141,12 +140,12 @@ void module::set_bypass(bool b) { impl->bypass = b; }
 void module::assign(const module& m)
 {
     // copy the impl
-    if(!impl)
+    if(not impl)
         impl = std::make_unique<module_impl>();
     *impl = *m.impl;
 
     // clear instructions
-    if(!impl->instructions.empty())
+    if(not impl->instructions.empty())
     {
         impl->clear();
     }
@@ -346,7 +345,7 @@ instruction_ref module::replace_instruction(instruction_ref ins, instruction_ref
         assert(out->valid(begin()));
     }
     // Replacement should not be dead code unless its the last instruction
-    assert(!rep->outputs().empty() or rep == std::prev(end()));
+    assert(not rep->outputs().empty() or rep == std::prev(end()));
     // Output of the original instruction should only be the replacement or empty
     assert(ins->outputs().empty() or std::all_of(ins->outputs().begin(),
                                                  ins->outputs().end(),
@@ -385,9 +384,13 @@ instruction_ref module::move_instruction(instruction_ref src, instruction_ref ds
 
 instruction_ref module::move_instructions(instruction_ref src, instruction_ref dst)
 {
-    this->move_instruction(src, dst);
     for(auto ins : src->inputs())
-        this->move_instruction(ins, src);
+    {
+        if(not contains(this->impl->instructions, ins))
+            continue;
+        this->move_instructions(ins, dst);
+    }
+    this->move_instruction(src, dst);
     return src;
 }
 
@@ -598,7 +601,7 @@ instruction_ref module::validate() const
             auto inputs      = i.inputs();
             bool check_order = std::all_of(
                 inputs.begin(), inputs.end(), [&](auto in) { return has_instruction(in); });
-            return !i.valid(impl->instructions.begin(), check_order);
+            return not i.valid(impl->instructions.begin(), check_order);
         });
 }
 
@@ -754,7 +757,7 @@ void module::print_graph(std::ostream& os, bool brief) const
             label = to_string(ins->get_operator());
         os << "\t" << enclose_name(ins_names.at(ins)) << "[label=" << enclose_name(label) << "]";
         os << ";" << std::endl;
-        if(!ins->inputs().empty())
+        if(not ins->inputs().empty())
         {
             for(auto&& arg : ins->inputs())
             {
@@ -788,12 +791,15 @@ 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 << ")";
 }
@@ -905,7 +911,7 @@ module& module::sort()
         this->move_instruction(ins, this->begin());
         for(auto child : ins->inputs())
         {
-            if(!contains(this->impl->instructions, child))
+            if(not contains(this->impl->instructions, child))
             {
                 continue;
             }

src/normalize_attributes.cpp

@@ -79,14 +79,14 @@ auto tune_attribute(const std::vector<int64_t>& vec,
     {
         if(contains(vec_attrs, op::normalize_attribute::include_max))
         {
-            if(!std::equal(result.begin(), result.end(), max_vals.begin(), std::less_equal<>{}))
+            if(not std::equal(result.begin(), result.end(), max_vals.begin(), std::less_equal<>{}))
             {
                 MIGRAPHX_THROW("TUNE_VECTOR: value out of range!");
             }
         }
         else
         {
-            if(!std::equal(result.begin(), result.end(), max_vals.begin(), std::less<>{}))
+            if(not std::equal(result.begin(), result.end(), max_vals.begin(), std::less<>{}))
             {
                 MIGRAPHX_THROW("TUNE_VECTOR: value out of range!");
             }
@@ -118,14 +118,15 @@ auto tune_attribute(const std::vector<int64_t>& vec,
     {
         if(contains(vec_attrs, op::normalize_attribute::include_min))
         {
-            if(!std::equal(min_vals.begin(), min_vals.end(), result.begin(), std::less_equal<>{}))
+            if(not std::equal(
+                   min_vals.begin(), min_vals.end(), result.begin(), std::less_equal<>{}))
             {
                 MIGRAPHX_THROW("TUNE_VECTOR: attribute out of range!");
             }
         }
         else
         {
-            if(!std::equal(result.begin(), result.end(), min_vals.begin(), std::less<>{}))
+            if(not std::equal(result.begin(), result.end(), min_vals.begin(), std::less<>{}))
             {
                 MIGRAPHX_THROW("TUNE_VECTOR: attribute out of range!");
             }
@@ -174,7 +175,7 @@ bool normalize_attributes(operation& op, const std::vector<std::size_t>& lens)
             tuned = true;
         }
     }
-    if(!attrs.contains("normalize_axes"))
+    if(not attrs.contains("normalize_axes"))
     {
         return tuned;
     }

src/onnx/conv.cpp

@@ -30,7 +30,7 @@ namespace onnx {
 
 void recalc_conv_attributes(value& v, size_t kdims)
 {
-    if(not(v["padding"].size() == kdims or v["padding"].size() == kdims * 2))
+    if(v["padding"].size() != kdims and v["padding"].size() != kdims * 2)
     {
         v["padding"].resize(kdims);
         std::fill_n(v["padding"].begin(), kdims, 0);

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

@@ -187,7 +187,7 @@ operation onnx_parser::load(const std::string& name, const node_info& info) cons
 
 void onnx_parser::parse_undefined(module* mod, const std::string& name)
 {
-    if(!contains(instructions, name))
+    if(not contains(instructions, name))
     {
         auto ins           = mod->add_instruction(make_op("undefined"));
         instructions[name] = ins;
@@ -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())
     {
@@ -272,7 +267,7 @@ void onnx_parser::parse_graph(module* mod, const onnx::GraphProto& graph)
     {
         const std::string& name = input.name();
         // input not in initializer_data, so it is a real input
-        if(!contains(mod_insts, name))
+        if(not contains(mod_insts, name))
         {
             // ONNX specification does not specify how to deal with the
             // scenario that a nested subgraph contains a parameter with the
@@ -359,7 +354,7 @@ void onnx_parser::parse_graph(module* mod, const onnx::GraphProto& graph)
         all_output_names.begin(),
         all_output_names.end(),
         std::back_inserter(prog_output_names),
-        [&](const auto& name) { return !(name.empty() or instructions.count(name) == 0); });
+        [&](const auto& name) { return not(name.empty() or instructions.count(name) == 0); });
 
     std::vector<instruction_ref> output_ins;
     std::transform(prog_output_names.begin(),
@@ -449,7 +444,7 @@ shape onnx_parser::parse_type(const onnx::TypeProto& t,
                               const std::vector<std::size_t>& input_dims) const
 {
     shape::type_t shape_type = get_type(t.tensor_type().elem_type());
-    if(!input_dims.empty())
+    if(not input_dims.empty())
     {
         return {shape_type, input_dims};
     }
@@ -516,7 +511,7 @@ shape::type_t get_type(int dtype)
 bool is_type_float(shape::type_t dtype)
 {
     bool r = false;
-    if(dtype == shape::float_type || dtype == shape::double_type || dtype == shape::half_type)
+    if(dtype == shape::float_type or dtype == shape::double_type or dtype == shape::half_type)
     {
         r = true;
     }

src/onnx/padding.cpp

@@ -42,7 +42,7 @@ void cal_auto_padding_size(onnx_parser::node_info info,
     size_t kdims = in_lens.size() - 2;
     assert(k_lens.size() == kdims and dilation.size() == kdims);
 
-    if(!contains(info.attributes, "auto_pad"))
+    if(not contains(info.attributes, "auto_pad"))
     {
         return;
     }
@@ -124,7 +124,7 @@ void tune_padding_size(const value& v,
     }
 
     // if padding is symmetric, return directly
-    if(!is_asym_padding(padding))
+    if(not is_asym_padding(padding))
     {
         return;
     }