Merge branch 'develop' into mem_color_ordering_fix

src/include/migraphx/erase.hpp

-#ifndef MIGRAPH_GUARD_ERASE_HPP
-#define MIGRAPH_GUARD_ERASE_HPP
+#ifndef MIGRAPHX_GUARD_ERASE_HPP
+#define MIGRAPHX_GUARD_ERASE_HPP
 
 #include <algorithm>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 /**
  * @brief Erase all elements from a container
@@ -33,7 +33,7 @@ auto erase_if(R&& r, P&& pred)
     return r.erase(std::remove_if(r.begin(), r.end(), pred), r.end());
 }
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/errors.hpp

-#ifndef MIGRAPH_GUARD_ERRORS_HPP
-#define MIGRAPH_GUARD_ERRORS_HPP
+#ifndef MIGRAPHX_GUARD_ERRORS_HPP
+#define MIGRAPHX_GUARD_ERRORS_HPP
 
 #include <exception>
 #include <stdexcept>
@@ -7,7 +7,7 @@
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 /// Represents exceptions that can be thrown by migraphxlib
 struct exception : std::runtime_error
@@ -43,10 +43,10 @@ inline std::string make_source_context(const std::string& file, int line)
 /**
  * @brief Throw an exception with context information
  */
-#define MIGRAPH_THROW(...) \
+#define MIGRAPHX_THROW(...) \
     throw migraphx::make_exception(migraphx::make_source_context(__FILE__, __LINE__), __VA_ARGS__)
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/fallthrough.hpp

-#ifndef MIGRAPH_GUARD_FALLTHROUGH_HPP
-#define MIGRAPH_GUARD_FALLTHROUGH_HPP
+#ifndef MIGRAPHX_GUARD_FALLTHROUGH_HPP
+#define MIGRAPHX_GUARD_FALLTHROUGH_HPP
 
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 #ifdef __clang__
-#define MIGRAPH_FALLTHROUGH [[clang::fallthrough]]
+#define MIGRAPHX_FALLTHROUGH [[clang::fallthrough]]
 #else
-#define MIGRAPH_FALLTHROUGH
+#define MIGRAPHX_FALLTHROUGH
 #endif
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/float_equal.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_FLOAT_EQUAL_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_FLOAT_EQUAL_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_FLOAT_EQUAL_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_FLOAT_EQUAL_HPP
 
 #include <algorithm>
 #include <cmath>
@@ -12,14 +12,14 @@
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 template <class... Ts>
 using common_type = typename std::common_type<Ts...>::type;
 
 struct float_equal_fn
 {
-    template <class T, MIGRAPH_REQUIRES(std::is_floating_point<T>{})>
+    template <class T, MIGRAPHX_REQUIRES(std::is_floating_point<T>{})>
     static bool apply(T x, T y)
     {
         return std::isfinite(x) and std::isfinite(y) and
@@ -27,7 +27,7 @@ struct float_equal_fn
                std::nextafter(x, std::numeric_limits<T>::max()) >= y;
     }
 
-    template <class T, MIGRAPH_REQUIRES(not std::is_floating_point<T>{})>
+    template <class T, MIGRAPHX_REQUIRES(not std::is_floating_point<T>{})>
     static bool apply(T x, T y)
     {
         return x == y;
@@ -42,7 +42,7 @@ struct float_equal_fn
 
 static constexpr float_equal_fn float_equal{};
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/functional.hpp

-#ifndef MIGRAPH_GUARD_RTGLIB_FUNCTIONAL_HPP
-#define MIGRAPH_GUARD_RTGLIB_FUNCTIONAL_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_FUNCTIONAL_HPP
+#define MIGRAPHX_GUARD_RTGLIB_FUNCTIONAL_HPP
 
 #include <utility>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 struct swallow
 {
@@ -94,6 +94,12 @@ constexpr void each_args(F)
 {
 }
 
+template <class F, class T>
+auto unpack(F f, T& x)
+{
+    return sequence_c<std::tuple_size<T>{}>([&](auto... is) { f(std::get<is>(x)...); });
+}
+
 /// Implements a fix-point combinator
 template <class R, class F>
 detail::fix_f<R, F> fix(F f)
@@ -131,7 +137,7 @@ auto fold(F f)
     return [=](auto&&... xs) { return fold_impl(f, std::forward<decltype(xs)>(xs)...); };
 }
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/fwd_conv_batchnorm_rewrite.hpp

-#ifndef MIGRAPH_GUARD_RTGLIB_FWD_CONV_BATCHNORM_REWRITE_HPP
-#define MIGRAPH_GUARD_RTGLIB_FWD_CONV_BATCHNORM_REWRITE_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_FWD_CONV_BATCHNORM_REWRITE_HPP
+#define MIGRAPHX_GUARD_RTGLIB_FWD_CONV_BATCHNORM_REWRITE_HPP
 
 #include <string>
 #include <migraphx/instruction_ref.hpp>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 struct program;
 
@@ -19,7 +19,7 @@ struct fwd_conv_batchnorm_rewrite
     void apply(program& p) const;
 };
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/generate.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_GENERATE_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_GENERATE_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_GENERATE_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_GENERATE_HPP
 
 #include <migraphx/argument.hpp>
 #include <migraphx/literal.hpp>
@@ -8,9 +8,9 @@
 #include <random>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
-template <class T, MIGRAPH_REQUIRES(is_floating_point<T>{})>
+template <class T, MIGRAPHX_REQUIRES(is_floating_point<T>{})>
 constexpr T normalize(unsigned long z)
 {
     if(z == 0)
@@ -22,7 +22,7 @@ constexpr T normalize(unsigned long z)
     return T(result);
 }
 
-template <class T, MIGRAPH_REQUIRES(is_signed<T>{} and not is_floating_point<T>{})>
+template <class T, MIGRAPHX_REQUIRES(is_signed<T>{} and not is_floating_point<T>{})>
 constexpr T normalize(unsigned long z)
 {
     const auto max      = std::numeric_limits<T>::max();
@@ -30,7 +30,7 @@ constexpr T normalize(unsigned long z)
     return half_max - (z % max);
 }
 
-template <class T, MIGRAPH_REQUIRES(not is_signed<T>{} and std::is_integral<T>{})>
+template <class T, MIGRAPHX_REQUIRES(not is_signed<T>{} and std::is_integral<T>{})>
 constexpr T normalize(unsigned long z)
 {
     const auto max = std::numeric_limits<T>::max();
@@ -93,7 +93,7 @@ literal generate_literal(shape s, unsigned long seed = 0);
 
 literal abs(literal l);
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/half.hpp

@@ -5,14 +5,14 @@
     file LICENSE_1_0.txt or copy at http://www.boost.org/LICENSE_1_0.txt)
 ==============================================================================*/
 
-#ifndef MIGRAPH_GUARD_RTGLIB_HALF_HPP
-#define MIGRAPH_GUARD_RTGLIB_HALF_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_HALF_HPP
+#define MIGRAPHX_GUARD_RTGLIB_HALF_HPP
 
 #include <half.hpp>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 using half = half_float::half;
 
@@ -33,7 +33,7 @@ struct deduce<half_float::detail::expr>
 template <class T>
 using deduce = typename detail::deduce<T>::type;
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/instruction.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_INSTRUCTION_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_INSTRUCTION_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_INSTRUCTION_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_INSTRUCTION_HPP
 
 #include <migraphx/literal.hpp>
 #include <migraphx/shape.hpp>
@@ -11,9 +11,10 @@
 #include <utility>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 shape compute_shape(const operation& op, const std::vector<instruction_ref>& args);
+std::vector<shape> to_shapes(const std::vector<instruction_ref>& args);
 
 struct instruction
 {
@@ -71,7 +72,11 @@ struct instruction
     static void
     replace(instruction_ref ins, operation o, const shape& r, std::vector<instruction_ref> args);
 
-    static instruction_ref get_output_alias(instruction_ref ins);
+    argument eval() const;
+
+    void finalize(context& ctx);
+
+    static instruction_ref get_output_alias(instruction_ref ins, bool shallow = false);
 
     private:
     // internal
@@ -90,7 +95,7 @@ struct instruction
     std::vector<instruction_ref> arguments;
     literal lit;
 };
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 namespace std {

src/include/migraphx/instruction_ref.hpp

-#ifndef MIGRAPH_GUARD_INSTRUCTION_REF_HPP
-#define MIGRAPH_GUARD_INSTRUCTION_REF_HPP
+#ifndef MIGRAPHX_GUARD_INSTRUCTION_REF_HPP
+#define MIGRAPHX_GUARD_INSTRUCTION_REF_HPP
 
 #include <list>
 #include <functional>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 struct instruction;
 using instruction_ref = std::list<instruction>::iterator;
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/iterator_for.hpp

-#ifndef MIGRAPH_GUARD_RTGLIB_ITERATOR_FOR_HPP
-#define MIGRAPH_GUARD_RTGLIB_ITERATOR_FOR_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_ITERATOR_FOR_HPP
+#define MIGRAPHX_GUARD_RTGLIB_ITERATOR_FOR_HPP
 
 #include <cassert>
 #include <type_traits>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 template <class T>
 struct iterator_for_range
@@ -17,9 +17,9 @@ struct iterator_for_range
     struct iterator
     {
         base_iterator i;
-        base_iterator operator*() { return i; }
+        base_iterator operator*() const { return i; }
         base_iterator operator++() { return ++i; }
-        bool operator!=(const iterator& rhs) { return i != rhs.i; }
+        bool operator!=(const iterator& rhs) const { return i != rhs.i; }
     };
 
     iterator begin()
@@ -39,7 +39,7 @@ iterator_for_range<T> iterator_for(T& x)
     return {&x};
 }
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/literal.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_LITERAL_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_LITERAL_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_LITERAL_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_LITERAL_HPP
 
 #include <migraphx/shape.hpp>
 #include <migraphx/shape_for_each.hpp>
@@ -12,7 +12,7 @@
 #include <memory>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 /**
  * @brief Represents a raw literal
@@ -124,7 +124,7 @@ literal transform(literal l1, literal l2, F f)
     return result;
 }
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/make_shared_array.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_MAKE_SHARED_ARRAY_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_MAKE_SHARED_ARRAY_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_MAKE_SHARED_ARRAY_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_MAKE_SHARED_ARRAY_HPP
 
 #include <memory>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 template <typename T>
 std::shared_ptr<T> make_shared_array(size_t size)
 {
-    return std::shared_ptr<T>(new T[size], std::default_delete<T[]>());
+    return std::shared_ptr<T>(new T[size], std::default_delete<T[]>()); // NOLINT
 }
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/manage_ptr.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPH_MANAGE_PTR_HPP
-#define MIGRAPH_GUARD_MIGRAPH_MANAGE_PTR_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHX_MANAGE_PTR_HPP
+#define MIGRAPHX_GUARD_MIGRAPHX_MANAGE_PTR_HPP
 
 #include <memory>
 #include <type_traits>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 template <class F, F f> // NOLINT
 struct manage_deleter
@@ -51,10 +51,10 @@ shared<T> share(T p)
     return shared<T>{std::move(p)};
 }
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
-#define MIGRAPH_MANAGE_PTR(T, F) \
+#define MIGRAPHX_MANAGE_PTR(T, F) \
     migraphx::manage_ptr<std::remove_pointer_t<T>, decltype(&F), &F> // NOLINT
 
 #endif

src/include/migraphx/matcher.hpp

-#ifndef MIGRAPH_GUARD_RTGLIB_MATCHER_HPP
-#define MIGRAPH_GUARD_RTGLIB_MATCHER_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_MATCHER_HPP
+#define MIGRAPHX_GUARD_RTGLIB_MATCHER_HPP
 
 #include <migraphx/functional.hpp>
 #include <migraphx/ranges.hpp>
@@ -10,7 +10,7 @@
 #include <unordered_map>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 
 namespace match {
 
@@ -169,7 +169,7 @@ basic_matcher<predicate_matcher<P>> make_basic_pred_matcher(P p)
 }
 
 /// This macro takes care of the boilerplate for defining a matcher
-#define MIGRAPH_BASIC_MATCHER(name, ...)                                      \
+#define MIGRAPHX_BASIC_MATCHER(name, ...)                                     \
     struct name##_m                                                           \
     {                                                                         \
         instruction_ref match(__VA_ARGS__) const;                             \
@@ -178,7 +178,7 @@ basic_matcher<predicate_matcher<P>> make_basic_pred_matcher(P p)
     inline instruction_ref name##_m::match(__VA_ARGS__) const
 
 /// This macro takes care of the boilerplate for defining a predicate matcher
-#define MIGRAPH_PRED_MATCHER(name, ...)                                                   \
+#define MIGRAPHX_PRED_MATCHER(name, ...)                                                  \
     struct name##_m                                                                       \
     {                                                                                     \
         bool operator()(__VA_ARGS__) const;                                               \
@@ -214,7 +214,6 @@ void find_matches(program& p, Ms&&... ms)
         bool match = false;
         each_args(
             [&](auto&& m) {
-                // cppcheck-suppress knownConditionTrueFalse
                 if(match)
                     return;
                 auto r = match_instruction(p, ins, m.matcher());
@@ -266,22 +265,22 @@ auto any_of(Ts... ms)
     });
 }
 
-MIGRAPH_PRED_MATCHER(any, instruction_ref) { return true; }
-MIGRAPH_PRED_MATCHER(none, instruction_ref) { return false; }
-MIGRAPH_PRED_MATCHER(standard_shape, instruction_ref ins) { return ins->get_shape().standard(); }
-MIGRAPH_PRED_MATCHER(broadcast_shape, instruction_ref ins)
+MIGRAPHX_PRED_MATCHER(any, instruction_ref) { return true; }
+MIGRAPHX_PRED_MATCHER(none, instruction_ref) { return false; }
+MIGRAPHX_PRED_MATCHER(standard_shape, instruction_ref ins) { return ins->get_shape().standard(); }
+MIGRAPHX_PRED_MATCHER(broadcast_shape, instruction_ref ins)
 {
     return ins->get_shape().broadcasted();
 }
 
-MIGRAPH_BASIC_MATCHER(output, matcher_context& ctx, instruction_ref ins)
+MIGRAPHX_BASIC_MATCHER(output, matcher_context& ctx, instruction_ref ins)
 {
     if(ins->outputs().size() == 1)
         return ins->outputs().front();
     return ctx.not_found();
 }
 
-MIGRAPH_BASIC_MATCHER(used_once, matcher_context& ctx, instruction_ref ins)
+MIGRAPHX_BASIC_MATCHER(used_once, matcher_context& ctx, instruction_ref ins)
 {
     if(ins->outputs().size() == 1)
         return ins;
@@ -340,7 +339,7 @@ inline auto either_arg(std::size_t i, std::size_t j)
 }
 
 } // namespace match
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/memory_coloring.hpp

-#ifndef MIGRAPH_GUARD_RTGLIB_MEMORY_COLORING_HPP
-#define MIGRAPH_GUARD_RTGLIB_MEMORY_COLORING_HPP
+#ifndef MIGRAPHX_GUARD_RTGLIB_MEMORY_COLORING_HPP
+#define MIGRAPHX_GUARD_RTGLIB_MEMORY_COLORING_HPP
 
 #include <string>
 #include <migraphx/instruction_ref.hpp>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 struct program;
 
 /**
@@ -20,7 +20,7 @@ struct memory_coloring
     void apply(program& p) const;
 };
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/onnx.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_ONNX_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_ONNX_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_ONNX_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_ONNX_HPP
 
 #include <migraphx/program.hpp>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
+
+struct unknown
+{
+    std::string op;
+    std::string name() const { return "unknown:" + op; }
+    shape compute_shape(std::vector<shape> input) const
+    {
+        if(input.empty())
+            return {};
+        else
+            return input.front();
+    }
+    friend std::ostream& operator<<(std::ostream& os, const unknown& x)
+    {
+        os << x.name();
+        return os;
+    }
+};
 
 /// Create a program from an onnx file
 program parse_onnx(const std::string& name);
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/operation.hpp

-#ifndef MIGRAPH_GUARD_MIGRAPHLIB_OPERAND_HPP
-#define MIGRAPH_GUARD_MIGRAPHLIB_OPERAND_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_OPERAND_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_OPERAND_HPP
 
 #include <cassert>
 #include <string>
@@ -7,16 +7,16 @@
 #include <memory>
 #include <type_traits>
 #include <utility>
-#include <migraphx/shape.hpp>
 #include <migraphx/reflect.hpp>
 #include <migraphx/streamutils.hpp>
 #include <migraphx/argument.hpp>
-#include <migraphx/context.hpp>
 #include <migraphx/auto_any_cast.hpp>
 #include <migraphx/config.hpp>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
+
+struct context;
 
 #ifdef DOXYGEN
 
@@ -26,6 +26,8 @@ struct operation
 {
     /// A unique name identifying the operation
     std::string name() const;
+    /// An optional method that can be used to finalize the operator before running
+    void finalize(context& ctx);
     /// This is used to compute the resulting shape from an operation. If an
     /// operation cannot be run with input shapes, then it should throw an
     /// exception.
@@ -53,6 +55,11 @@ struct operation
     friend std::ostream& operator<<(std::ostream& os, const operation& op);
 };
 
+/// Returns true if operation does not require a context to run compute
+bool is_context_free(const operation& x);
+/// Returns true if the operation has a finalize method
+bool has_finalize(const operation& x);
+
 #else
 
 namespace operation_stream {
@@ -89,7 +96,7 @@ auto operator==(const T& x, const U& y) -> decltype(x.name() == y.name())
 } // namespace operation_equal
 
 template <class T>
-auto compute_op(rank<1>,
+auto compute_op(rank<2>,
                 const T& x,
                 context& ctx,
                 const shape& output_shape,
@@ -99,18 +106,72 @@ auto compute_op(rank<1>,
     return x.compute(auto_any_cast(ctx), output_shape, input);
 }
 
+template <class T>
+auto compute_op(
+    rank<1>, const T& x, context&, const shape& output_shape, const std::vector<argument>& input)
+    -> decltype(x.compute(output_shape, input))
+{
+    return x.compute(output_shape, input);
+}
+
 template <class T>
 argument compute_op(rank<0>, const T& x, context&, const shape&, const std::vector<argument>&)
 {
     std::string name = x.name();
-    MIGRAPH_THROW("Not computable: " + name);
+    MIGRAPHX_THROW("Not computable: " + name);
 }
 
 template <class T>
 argument
 compute_op(const T& x, context& ctx, const shape& output_shape, const std::vector<argument>& input)
 {
-    return compute_op(rank<1>{}, x, ctx, output_shape, input);
+    return compute_op(rank<2>{}, x, ctx, output_shape, input);
+}
+
+template <class T>
+auto compute_op(rank<2>, const T& x, const shape& output_shape, const std::vector<argument>& input)
+    -> decltype(x.compute(output_shape, input))
+{
+    return x.compute(output_shape, input);
+}
+
+template <class T>
+auto compute_op(rank<1>, const T& x, const shape& output_shape, const std::vector<argument>& input)
+    -> decltype(x.compute(auto_any_cast(std::declval<context&>()), output_shape, input))
+{
+    std::string name = x.name();
+    MIGRAPHX_THROW("Not computable without a context: " + name);
+}
+
+template <class T>
+argument compute_op(rank<0>, const T& x, const shape&, const std::vector<argument>&)
+{
+    std::string name = x.name();
+    MIGRAPHX_THROW("Not computable: " + name);
+}
+
+template <class T>
+argument compute_op(const T& x, const shape& output_shape, const std::vector<argument>& input)
+{
+    return compute_op(rank<2>{}, x, output_shape, input);
+}
+
+template <class T>
+auto is_context_free_op(rank<1>,
+                        const T& x,
+                        const shape& output_shape,
+                        const std::vector<argument>& input)
+    -> decltype(x.compute(output_shape, input), std::true_type{});
+
+template <class T>
+auto is_context_free_op(rank<0>, const T&, const shape&, const std::vector<argument>&)
+    -> std::false_type;
+
+template <class T>
+auto is_context_free_op(const T& x) -> decltype(is_context_free_op(
+    rank<1>{}, x, std::declval<const shape&>(), std::declval<std::vector<argument>>()))
+{
+    return {};
 }
 
 template <class T>
@@ -132,15 +193,57 @@ int output_alias_op(const T& x, const std::vector<shape>& shapes)
     return output_alias_op(rank<1>{}, x, shapes);
 }
 
+template <class T>
+auto finalize_op(
+    rank<1>, T& x, context& ctx, const shape& output_shape, const std::vector<shape>& input)
+    -> decltype(x.finalize(auto_any_cast(ctx), output_shape, input), void())
+{
+    x.finalize(auto_any_cast(ctx), output_shape, input);
+}
+
+template <class T>
+void finalize_op(rank<0>, T&, context&, const shape&, const std::vector<shape>&)
+{
+}
+
+template <class T>
+void finalize_op(T& x, context& ctx, const shape& output_shape, const std::vector<shape>& input)
+{
+    finalize_op(rank<1>{}, x, ctx, output_shape, input);
+}
+
+template <class T>
+auto has_finalize_op(
+    rank<1>, T& x, context& ctx, const shape& output_shape, const std::vector<shape>& input)
+    -> decltype(x.finalize(auto_any_cast(ctx), output_shape, input), std::true_type{});
+
+template <class T>
+auto has_finalize_op(rank<0>, T&, context&, const shape&, const std::vector<shape>&)
+    -> std::false_type;
+
+template <class T>
+auto has_finalize_op(const T&) -> decltype(has_finalize_op(rank<1>{},
+                                                           std::declval<T&>(),
+                                                           std::declval<context&>(),
+                                                           std::declval<const shape&>(),
+                                                           std::declval<std::vector<shape>>()))
+{
+    return {};
+}
+
 /*
  * Type-erased interface for:
  *
  * struct operation
  * {
  *      std::string name() const;
+ *      bool is_context_free() const;
+ *      bool has_finalize() const;
  *      int output_alias(const std::vector<shape>& input) const;
+ *      void finalize(context& ctx,const shape& output,const std::vector<shape>& input) ;
  *      shape compute_shape(const std::vector<shape>& input) const;
  *      argument compute(context& ctx,const shape& output,const std::vector<argument>& input) const;
+ *      argument compute(const shape& output,const std::vector<argument>& input) const;
  *     friend std::ostream & operator<<(std::ostream & os,const operation & op) ;
  *     friend bool operator==(const operation & x,const operation & y) ;
  * };
@@ -210,12 +313,30 @@ struct operation
         return (*this).private_detail_te_get_handle().name();
     }
 
+    bool is_context_free() const
+    {
+        assert((*this).private_detail_te_handle_mem_var);
+        return (*this).private_detail_te_get_handle().is_context_free();
+    }
+
+    bool has_finalize() const
+    {
+        assert((*this).private_detail_te_handle_mem_var);
+        return (*this).private_detail_te_get_handle().has_finalize();
+    }
+
     int output_alias(const std::vector<shape>& input) const
     {
         assert((*this).private_detail_te_handle_mem_var);
         return (*this).private_detail_te_get_handle().output_alias(input);
     }
 
+    void finalize(context& ctx, const shape& output, const std::vector<shape>& input)
+    {
+        assert((*this).private_detail_te_handle_mem_var);
+        (*this).private_detail_te_get_handle().finalize(ctx, output, input);
+    }
+
     shape compute_shape(const std::vector<shape>& input) const
     {
         assert((*this).private_detail_te_handle_mem_var);
@@ -228,6 +349,12 @@ struct operation
         return (*this).private_detail_te_get_handle().compute(ctx, output, input);
     }
 
+    argument compute(const shape& output, const std::vector<argument>& input) const
+    {
+        assert((*this).private_detail_te_handle_mem_var);
+        return (*this).private_detail_te_get_handle().compute(output, input);
+    }
+
     friend std::ostream& operator<<(std::ostream& os, const operation& op)
     {
         assert(op.private_detail_te_handle_mem_var);
@@ -240,6 +367,12 @@ struct operation
         return x.private_detail_te_get_handle().operator==(y);
     }
 
+    friend bool is_shared(const operation& private_detail_x, const operation& private_detail_y)
+    {
+        return private_detail_x.private_detail_te_handle_mem_var ==
+               private_detail_y.private_detail_te_handle_mem_var;
+    }
+
     private:
     struct private_detail_te_handle_base_type
     {
@@ -247,13 +380,18 @@ struct operation
         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 int output_alias(const std::vector<shape>& input) const    = 0;
-        virtual shape compute_shape(const std::vector<shape>& input) const = 0;
+        virtual std::string name() const                                = 0;
+        virtual bool is_context_free() const                            = 0;
+        virtual bool has_finalize() const                               = 0;
+        virtual int output_alias(const std::vector<shape>& input) const = 0;
+        virtual void
+        finalize(context& ctx, const shape& output, const std::vector<shape>& input) = 0;
+        virtual shape compute_shape(const std::vector<shape>& input) const           = 0;
         virtual argument
-        compute(context& ctx, const shape& output, const std::vector<argument>& input) const = 0;
-        virtual std::ostream& operator_shift_left(std::ostream& os) const                    = 0;
-        virtual bool operator==(const operation& y) const                                    = 0;
+        compute(context& ctx, const shape& output, const std::vector<argument>& input) const    = 0;
+        virtual argument compute(const shape& output, const std::vector<argument>& input) const = 0;
+        virtual std::ostream& operator_shift_left(std::ostream& os) const                       = 0;
+        virtual bool operator==(const operation& y) const                                       = 0;
     };
 
     template <typename PrivateDetailTypeErasedT>
@@ -286,12 +424,26 @@ struct operation
 
         std::string name() const override { return private_detail_te_value.name(); }
 
+        bool is_context_free() const override
+        {
+
+            return is_context_free_op(private_detail_te_value);
+        }
+
+        bool has_finalize() const override { return has_finalize_op(private_detail_te_value); }
+
         int output_alias(const std::vector<shape>& input) const override
         {
 
             return output_alias_op(private_detail_te_value, input);
         }
 
+        void finalize(context& ctx, const shape& output, const std::vector<shape>& input) override
+        {
+
+            finalize_op(private_detail_te_value, ctx, output, input);
+        }
+
         shape compute_shape(const std::vector<shape>& input) const override
         {
 
@@ -306,6 +458,12 @@ struct operation
             return compute_op(private_detail_te_value, ctx, output, input);
         }
 
+        argument compute(const shape& output, const std::vector<argument>& input) const override
+        {
+
+            return compute_op(private_detail_te_value, output, input);
+        }
+
         std::ostream& operator_shift_left(std::ostream& os) const override
         {
             using migraphx::operation_stream::operator<<;
@@ -385,9 +543,25 @@ inline const ValueType& any_cast(const operation& x)
 
 inline bool operator!=(const operation& x, const operation& y) { return !(x == y); }
 
+inline bool is_context_free(const operation& op) { return op.is_context_free(); }
+
+template <class T>
+bool is_context_free(const T& x)
+{
+    return is_context_free_op(x);
+}
+
+inline bool has_finalize(const operation& op) { return op.has_finalize(); }
+
+template <class T>
+bool has_finalize(const T& x)
+{
+    return has_finalize_op(x);
+}
+
 #endif
 
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/operators.hpp

-#ifndef MIGRAPH_GUARD_OPERATORS_HPP
-#define MIGRAPH_GUARD_OPERATORS_HPP
+#ifndef MIGRAPHX_GUARD_OPERATORS_HPP
+#define MIGRAPHX_GUARD_OPERATORS_HPP
 
 #include <array>
 #include <migraphx/operation.hpp>
 #include <migraphx/check_shapes.hpp>
 #include <migraphx/stringutils.hpp>
 #include <migraphx/streamutils.hpp>
+#include <migraphx/literal.hpp>
+#include <migraphx/shape_for_each.hpp>
 #include <migraphx/config.hpp>
 #include <cmath>
 #include <utility>
 
 namespace migraphx {
-inline namespace MIGRAPH_INLINE_NS {
+inline namespace MIGRAPHX_INLINE_NS {
 namespace op {
 
+enum padding_mode_t
+{
+    default_, // NOLINT
+    same,
+    valid
+};
+
 struct not_computable
 {
-    argument compute(context&, const shape&, const std::vector<argument>&) const
+    argument compute(const shape&, const std::vector<argument>&) const
     {
-        MIGRAPH_THROW("not computable");
+        MIGRAPHX_THROW("not computable");
     }
 };
 
@@ -51,18 +60,38 @@ struct batch_norm_inference
     }
 };
 
+struct lrn
+{
+    float alpha = 0.0001;
+    float beta  = 0.75;
+    float bias  = 1.0;
+    int size    = 1;
+    std::string name() const { return "lrn"; }
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.alpha, "alpha"),
+                    f(self.beta, "beta"),
+                    f(self.bias, "bias"),
+                    f(self.size, "size"));
+    }
+
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(1);
+        return inputs.front();
+    }
+};
+
 struct convolution
 {
     std::array<std::size_t, 2> padding  = {{0, 0}};
     std::array<std::size_t, 2> stride   = {{1, 1}};
     std::array<std::size_t, 2> dilation = {{1, 1}};
-    enum padding_mode_t
-    {
-        default_, // NOLINT
-        same,
-        valid
-    };
+
     padding_mode_t padding_mode = default_;
+    int group                   = 1;
 
     template <class Self, class F>
     static auto reflect(Self& self, F f)
@@ -70,7 +99,8 @@ struct convolution
         return pack(f(self.padding, "padding"),
                     f(self.stride, "stride"),
                     f(self.dilation, "dilation"),
-                    f(self.padding_mode, "padding_mode"));
+                    f(self.padding_mode, "padding_mode"),
+                    f(self.group, "group"));
     }
 
     std::string name() const { return "convolution"; }
@@ -124,7 +154,7 @@ struct convolution
         }
         else
         {
-            MIGRAPH_THROW("Invalid padding mode");
+            MIGRAPHX_THROW("Invalid padding mode");
         }
     }
 };
@@ -134,12 +164,7 @@ struct im2col
     std::array<std::size_t, 2> padding  = {{0, 0}};
     std::array<std::size_t, 2> stride   = {{1, 1}};
     std::array<std::size_t, 2> dilation = {{1, 1}};
-    enum padding_mode_t
-    {
-        default_, // NOLINT
-        same,
-        valid
-    };
+
     padding_mode_t padding_mode = default_;
 
     template <class Self, class F>
@@ -163,7 +188,7 @@ struct im2col
         auto kernel_width   = weights.lens()[3];
         check_shapes{inputs, *this}.has(2);
         if(batch_size != 1)
-            MIGRAPH_THROW("im2col only support batch_size 1");
+            MIGRAPHX_THROW("im2col only support batch_size 1");
         auto output_height = std::size_t(std::max<std::ptrdiff_t>(
             1,
             (input.lens()[2] - (1 + dilation[0] * (kernel_height - 1)) + 2 * padding[0]) /
@@ -185,12 +210,14 @@ struct pooling
     std::array<std::size_t, 2> padding = {{0, 0}};
     std::array<std::size_t, 2> stride  = {{1, 1}};
     std::array<std::size_t, 2> lengths = {{1, 1}};
+    padding_mode_t padding_mode        = default_;
 
     template <class Self, class F>
     static auto reflect(Self& self, F f)
     {
         return pack(f(self.mode, "mode"),
                     f(self.padding, "padding"),
+                    f(self.padding, "padding_mode"),
                     f(self.stride, "stride"),
                     f(self.lengths, "lengths"));
     }
@@ -207,7 +234,10 @@ struct pooling
         assert(lengths[0] <= (input.lens()[2] + 2 * padding[0]));
         assert(lengths[1] <= (input.lens()[3] + 2 * padding[1]));
 
-        return {t,
+        if(padding_mode == default_)
+        {
+            return {
+                t,
                 {
                     input.lens()[0],
                     input.lens()[1],
@@ -222,6 +252,39 @@ struct pooling
                                                   static_cast<float>(stride[1]))) +
                             1)),
                 }};
+        }
+        else if(padding_mode == same)
+        {
+            return {t,
+                    {input.lens()[0],
+                     input.lens()[1],
+                     static_cast<std::size_t>(
+                         std::ceil(static_cast<double>(input.lens()[2]) / stride[0])),
+                     static_cast<std::size_t>(
+                         std::ceil(static_cast<double>(input.lens()[3]) / stride[1]))}};
+        }
+        else if(padding_mode == valid)
+        {
+            return {t,
+                    {
+                        input.lens()[0],
+                        input.lens()[1],
+                        std::size_t(std::max<std::ptrdiff_t>(
+                            1,
+                            std::ptrdiff_t(std::floor((input.lens()[2] - lengths[0]) /
+                                                      static_cast<float>(stride[0]))) +
+                                1)),
+                        std::size_t(std::max<std::ptrdiff_t>(
+                            1,
+                            std::ptrdiff_t(std::floor((input.lens()[3] - lengths[1]) /
+                                                      static_cast<float>(stride[1]))) +
+                                1)),
+                    }};
+        }
+        else
+        {
+            MIGRAPHX_THROW("Invalid padding mode");
+        }
     }
 };
 
@@ -234,10 +297,28 @@ struct leaky_relu
         check_shapes{inputs, *this}.has(1);
         return inputs.front();
     }
-    friend std::ostream& operator<<(std::ostream& os, const leaky_relu& op)
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
     {
-        os << op.name() << ":" << op.alpha;
-        return os;
+        return pack(f(self.alpha, "alpha"));
+    }
+};
+
+struct elu
+{
+    std::string name() const { return "elu"; }
+    float alpha;
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(1);
+        return inputs.front();
+    }
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.alpha, "alpha"));
     }
 };
 
@@ -261,30 +342,36 @@ struct transpose
         auto t             = input.type();
         if(dims.size() != input_lens.size())
         {
-            MIGRAPH_THROW("Permutation has wrong number of axes");
+            MIGRAPHX_THROW("Permutation has wrong number of axes");
         }
         std::vector<int64_t> axes(dims.size());
         std::iota(axes.begin(), axes.end(), 0);
         if(!std::is_permutation(axes.begin(), axes.end(), dims.begin()))
         {
-            MIGRAPH_THROW("Invalid permutation");
+            MIGRAPHX_THROW("Invalid permutation");
         }
         std::vector<size_t> output_lens(input_lens.size());
         std::vector<size_t> output_strides(input_lens.size());
-        for(int i = 0; i < output_lens.size(); i++)
+        for(std::size_t i = 0; i < output_lens.size(); i++)
         {
             output_lens[i]    = input_lens[dims[i]];
             output_strides[i] = input_strides[dims[i]];
         }
         return {t, output_lens, output_strides};
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.front().data)};
     }
     int output_alias(const std::vector<shape>&) const { return 0; }
 };
 
+/// The contiguous operator takes a non-standard input tensor and returns
+/// the same tensor but in standard form. For example, if input tensor A which has lens = (4,5)
+/// is first transposed, i.e. lens = (5,4), this tensor's data layout remained the same
+/// during the transpose operation; only it's shape lengths and strides were changed.
+/// This leaves the tensor in a non-standard form. The contiguous operator copies the
+/// underlying data such that resulting tensor is returned to a standard form.
 struct contiguous
 {
     std::string name() const { return "contiguous"; }
@@ -295,6 +382,17 @@ struct contiguous
         auto t    = inputs.at(0).type();
         return {t, lens};
     }
+    argument compute(const shape& output_shape, std::vector<argument> args) const
+    {
+        assert(output_shape.standard());
+        argument result{output_shape};
+        visit_all(result, args[0])([&](auto output, auto input) {
+            shape_for_each(output.get_shape(), [&](const auto& idx) {
+                output(idx.begin(), idx.end()) = input(idx.begin(), idx.end());
+            });
+        });
+        return result;
+    }
 };
 
 struct concat
@@ -302,7 +400,7 @@ struct concat
     std::size_t axis = 0;
     std::string name() const { return "concat"; }
     std::vector<std::size_t> compute_offsets(const shape& output_shape,
-                                             const std::vector<argument> args) const
+                                             const std::vector<argument>& args) const
     {
         std::vector<std::size_t> offsets;
         std::vector<std::size_t> offset(args[0].get_shape().lens().size(), 0);
@@ -318,7 +416,7 @@ struct concat
     {
         if(inputs.empty())
         {
-            MIGRAPH_THROW("Number of input tensors should exceed 0");
+            MIGRAPHX_THROW("Number of input tensors should exceed 0");
         }
 
         const auto& first_shape_lens = inputs.front().lens();
@@ -331,7 +429,7 @@ struct concat
                        return s.lens()[l] == first_shape_lens[l];
                    }))
                 {
-                    MIGRAPH_THROW("Non-axis dimensions should match");
+                    MIGRAPHX_THROW("Non-axis dimensions should match");
                 }
             }
         }
@@ -346,7 +444,27 @@ struct concat
         new_lens[axis] = new_dim_axis;
         return {type, new_lens};
     }
-    int output_alias(const std::vector<shape>&) const { return 0; }
+    argument compute(const shape& output_shape, std::vector<argument> args) const
+    {
+        argument result{output_shape};
+        std::vector<std::size_t> coffsets = compute_offsets(output_shape, args);
+        for(std::size_t l = 0; l < args.size(); l++)
+        {
+            auto argl             = args[l];
+            std::size_t nelements = argl.get_shape().elements();
+            visit_all(result, argl)([&](auto output, auto input) {
+                auto slice_shape =
+                    shape{output_shape.type(), input.get_shape().lens(), output_shape.strides()};
+                auto slice = make_view(slice_shape, output.data() + coffsets[l]);
+                // cppcheck-suppress useStlAlgorithm
+                for(std::size_t i = 0; i < nelements; i++)
+                {
+                    slice[i] = input[i];
+                }
+            });
+        }
+        return result;
+    }
 };
 
 struct slice
@@ -400,18 +518,9 @@ struct slice
         auto t                  = input_shape.type();
         const auto& old_lens    = input_shape.lens();
         const auto& old_strides = input_shape.strides();
-        // std::vector<int64_t> t_axes(old_lens.size());
-        // if(axes.size() == 0)
-        // {
-        //     std::iota(t_axes.begin(), t_axes.end(), 0);
-        // }
-        // else
-        // {
-        //     std::copy(axes.begin(), axes.end(), t_axes.begin());
-        // }
         if(starts.size() != axes.size() || axes.size() != ends.size())
         {
-            MIGRAPH_THROW("inconsistent sizes");
+            MIGRAPHX_THROW("inconsistent sizes");
         }
         std::vector<std::size_t> new_lens = old_lens;
         for(std::size_t i = 0; i < axes.size(); i++)
@@ -422,7 +531,7 @@ struct slice
         }
         return shape{t, new_lens, old_strides};
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         auto input  = args[0];
         auto offset = compute_offset(input.get_shape()) * output_shape.type_size();
@@ -450,7 +559,7 @@ struct squeeze
         if(std::any_of(
                axes.begin(), axes.end(), [&](auto axis) { return input_shape.lens()[axis] != 1; }))
         {
-            MIGRAPH_THROW("squeeze axis dimension should be equal to 1");
+            MIGRAPHX_THROW("squeeze axis dimension should be equal to 1");
         }
         std::vector<std::size_t> new_lens;
         if(axes.empty())
@@ -472,7 +581,7 @@ struct squeeze
         }
         return shape{type, new_lens};
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.front().data)};
     }
@@ -511,7 +620,7 @@ struct unsqueeze
         }
         return shape{type, new_lens};
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.front().data)};
     }
@@ -536,16 +645,21 @@ struct reshape
         std::vector<std::size_t> rdims(dims.begin(), dims.end());
         auto n_neg_dims = std::count(dims.begin(), dims.end(), -1);
         if(n_neg_dims > 1)
-            MIGRAPH_THROW("Dimensions for reshape can only have one -1 dim");
+            MIGRAPHX_THROW("Dimensions for reshape can only have one -1 dim");
         for(std::size_t i = 0; i < dims.size(); i++)
         {
             if(dims[i] == 0)
                 rdims[i] = idims[i];
+
+            // since rdims using size_t type, -1 is the max value
+            // is size_t that cause later compuation incorrect
+            if(dims[i] == -1)
+                rdims[i] = 1;
         }
         if(n_neg_dims > 0)
         {
             size_t missing_dim =
-                -inputs.front().elements() /
+                inputs.front().elements() /
                 std::accumulate(rdims.begin(), rdims.end(), 1, std::multiplies<int64_t>());
             for(std::size_t i = 0; i < rdims.size(); i++)
             {
@@ -553,23 +667,140 @@ struct reshape
                     rdims[i] = missing_dim;
             }
         }
-        if(dims.back() == -1)
+
+        shape s{inputs.front().type(), rdims};
+        if(s.elements() != inputs.front().elements())
+            MIGRAPHX_THROW("Wrong number of elements for reshape");
+        return s;
+    }
+    argument compute(shape output_shape, std::vector<argument> args) const
+    {
+        return {std::move(output_shape), std::move(args.front().data)};
+    }
+    int output_alias(const std::vector<shape>&) const { return 0; }
+};
+
+struct pad
+{
+    std::vector<int64_t> pads;
+    float value = 0.0f;
+    enum pad_op_mode_t
+    {
+        constant_pad,
+        reflect_pad,
+        edge_pad
+    };
+    pad_op_mode_t mode = constant_pad;
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.mode, "mode"), f(self.pads, "pads"), f(self.value, "value"));
+    }
+
+    std::string name() const { return "pad"; }
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(1);
+        auto&& idims = inputs.front().lens();
+        std::vector<std::size_t> rdims(idims.begin(), idims.end());
+        std::size_t num_dims = rdims.size();
+
+        for(std::size_t i = 0; i < num_dims; i++)
         {
-            rdims.pop_back();
-            std::copy(idims.begin() + rdims.size(), idims.end(), std::back_inserter(rdims));
+            rdims[i] += pads[i] + pads[i + num_dims];
         }
+
         shape s{inputs.front().type(), rdims};
-        if(s.elements() != inputs.front().elements())
-            MIGRAPH_THROW("Wrong number of elements for reshape");
         return s;
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+};
+
+struct as_shape
+{
+    shape s;
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.s, "shape"));
+    }
+
+    std::string name() const { return "as_shape"; }
+    shape compute_shape(const std::vector<shape>& inputs) const
+    {
+        check_shapes{inputs, *this}.has(1).standard();
+        assert(inputs.front().elements() == s.elements());
+        return s;
+    }
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.front().data)};
     }
     int output_alias(const std::vector<shape>&) const { return 0; }
 };
 
+struct gather
+{
+    int axis = 0;
+    std::string name() const { return "gather"; }
+
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(2);
+        auto lens = inputs[0].lens();
+        int n_dim = static_cast<int>(lens.size());
+        if(axis >= n_dim || axis < -n_dim)
+        {
+            MIGRAPHX_THROW("Gather: axis is out of range.");
+        }
+
+        // negative axis means counting dimensions from back
+        int axis_index = (axis < 0) ? (n_dim + axis) : axis;
+
+        auto type        = inputs[0].type();
+        lens[axis_index] = inputs[1].elements();
+
+        return {type, lens};
+    }
+
+    template <class T>
+    void compute_index(const T& out_idx,
+                       const int axis_index,
+                       const std::vector<std::size_t>& vec_indices,
+                       const std::size_t max_dim,
+                       T& in_idx) const
+    {
+        in_idx          = out_idx;
+        std::size_t idx = vec_indices.at(out_idx[axis_index]);
+        if(idx >= max_dim)
+        {
+            MIGRAPHX_THROW("Gather: indices are out of range in input tensor");
+        }
+        in_idx[axis_index] = idx;
+    }
+
+    argument compute(const shape& output_shape, std::vector<argument> args) const
+    {
+        argument result{output_shape};
+        // negative axis means counting dimensions from back
+        int axis_index = (axis < 0) ? (output_shape.lens().size() + axis) : axis;
+
+        // max dimension in axis
+        std::size_t max_dim = args[0].get_shape().lens()[axis_index];
+        std::vector<std::size_t> vec_indices;
+        args[1].visit([&](auto indices) { vec_indices.assign(indices.begin(), indices.end()); });
+        visit_all(result, args[0])([&](auto output, auto input) {
+            std::vector<std::size_t> in_idx;
+            shape_for_each(output.get_shape(), [&](const auto& idx) {
+                this->compute_index(idx, axis_index, vec_indices, max_dim, in_idx);
+                output(idx.begin(), idx.end()) = input(in_idx.begin(), in_idx.end());
+            });
+        });
+
+        return result;
+    }
+};
+
 struct dot
 {
     float alpha = 1.0;
@@ -590,8 +821,8 @@ struct dot
         auto t         = a.type();
 
         if(a.lens()[1] != b.lens()[0])
-            MIGRAPH_THROW("Inner dimensions do not match: {" + to_string_range(a.lens()) + "} x {" +
-                          to_string_range(b.lens()) + "}");
+            MIGRAPHX_THROW("Inner dimensions do not match: {" + to_string_range(a.lens()) +
+                           "} x {" + to_string_range(b.lens()) + "}");
         return {t, {a.lens()[0], b.lens()[1]}};
     }
 };
@@ -609,7 +840,7 @@ struct identity
 {
     std::string name() const { return "identity"; }
     shape compute_shape(std::vector<shape> inputs) const { return inputs.at(0); }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.at(0).data)};
     }
@@ -626,6 +857,11 @@ struct exp : unary
     std::string name() const { return "exp"; }
 };
 
+struct log : unary
+{
+    std::string name() const { return "log"; }
+};
+
 struct sin : unary
 {
     std::string name() const { return "sin"; }
@@ -656,6 +892,16 @@ struct atan : unary
     std::string name() const { return "atan"; }
 };
 
+struct sinh : unary
+{
+    std::string name() const { return "sinh"; }
+};
+
+struct cosh : unary
+{
+    std::string name() const { return "cosh"; }
+};
+
 struct tanh : unary
 {
     std::string name() const { return "tanh"; }
@@ -704,7 +950,7 @@ struct flatten
 
         if(axis > lens.size())
         {
-            MIGRAPH_THROW("axis for flatten must be less than tensor rank");
+            MIGRAPHX_THROW("axis for flatten must be less than tensor rank");
         }
         auto x =
             std::accumulate(lens.begin(), lens.begin() + axis, std::size_t{1}, std::multiplies<>{});
@@ -712,12 +958,21 @@ struct flatten
             std::accumulate(lens.begin() + axis, lens.end(), std::size_t{1}, std::multiplies<>{});
         return {inputs.at(0).type(), {x, y}};
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.front().data)};
     }
     int output_alias(const std::vector<shape>&) const { return 0; }
 };
+
+/// The broadcast operator performs the numpy-style broadcasting of an axis of a given tensor. This
+/// is achieved primarily by setting the stride of the broadcasted axis to zero. Linear indicies are
+/// computed from multi-indicies by computing the inner product on the multi-index with the strides.
+/// For example, if we have a tensor A(2,3) it has lengths of (2,3) and strides of (3,1). If we want
+/// to compute the linear offset that corresponds to the element on the 2nd row (i = 1) and 3rd
+/// column (j = 2), we compute the following inner product (1,2) dot (3, 1) = 1*3 + 2*1 = 5. It is
+/// obvious from there that we can negate the effects of a given axis by setting the stride of that
+/// axis to zero.
 struct broadcast
 {
     uint64_t axis = 0;
@@ -742,7 +997,7 @@ struct broadcast
            }))
         {
             if(axis != 0)
-                MIGRAPH_THROW("when broadcasting tensor of size 1, axis should be 0");
+                MIGRAPHX_THROW("when broadcasting tensor of size 1, axis should be 0");
             return {t, broadcast_shape.lens(), std::move(bcast_strides)};
         }
         else
@@ -750,12 +1005,12 @@ struct broadcast
             assert(broadcast_shape.lens().size() - axis >= input.lens().size());
             if(!std::equal(
                    input.lens().begin(), input.lens().end(), broadcast_shape.lens().begin() + axis))
-                MIGRAPH_THROW("when broadcasting success sizes must match");
+                MIGRAPHX_THROW("when broadcasting success sizes must match");
             std::copy(input.strides().begin(), input.strides().end(), bcast_strides.begin() + axis);
             return {t, broadcast_shape.lens(), std::move(bcast_strides)};
         }
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.at(0).data)};
     }
@@ -781,10 +1036,10 @@ struct multibroadcast
         auto input = inputs.at(0);
 
         if(input.lens().empty())
-            MIGRAPH_THROW("inputs dimensions should be > 0");
+            MIGRAPHX_THROW("inputs dimensions should be > 0");
 
         if(input.lens().size() > output_lens.size())
-            MIGRAPH_THROW("inputs dimensions should <= output size");
+            MIGRAPHX_THROW("inputs dimensions should <= output size");
 
         std::vector<size_t> bcast_strides(output_lens.size(), 0);
         auto offset = output_lens.size() - input.lens().size();
@@ -797,7 +1052,7 @@ struct multibroadcast
         }
         return {t, output_lens, bcast_strides};
     }
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.at(0).data)};
     }
@@ -813,13 +1068,12 @@ struct scalar
     shape compute_shape(std::vector<shape> inputs) const
     {
         assert(check_shapes{inputs}.has(1).only_dims(1).size() == 1);
-        auto t     = inputs.at(0).type();
-        auto input = inputs.at(0);
+        auto t = inputs.at(0).type();
         std::vector<std::size_t> strides(scalar_bcast.lens().size(), 0);
         return {t, scalar_bcast.lens(), strides};
     }
 
-    argument compute(context&, shape output_shape, std::vector<argument> args) const
+    argument compute(shape output_shape, std::vector<argument> args) const
     {
         return {std::move(output_shape), std::move(args.at(0).data)};
     }
@@ -857,6 +1111,16 @@ struct div : binary
     std::string name() const { return "div"; }
 };
 
+struct max : binary
+{
+    std::string name() const { return "max"; }
+};
+
+struct min : binary
+{
+    std::string name() const { return "min"; }
+};
+
 struct load
 {
     shape s;
@@ -874,7 +1138,7 @@ struct load
         check_shapes{inputs}.has(1);
         return s;
     }
-    argument compute(context&, const shape&, const std::vector<argument>& args) const
+    argument compute(const shape&, const std::vector<argument>& args) const
     {
         return {s, args[0].data() + offset};
     }
@@ -897,14 +1161,118 @@ struct outline
         check_shapes{inputs, *this}.has(0);
         return s;
     }
-    argument compute(context&, const shape&, const std::vector<argument>&) const
+    argument compute(const shape&, const std::vector<argument>&) const { return {s, nullptr}; }
+};
+
+// indicate rnn computation direction
+enum class rnn_direction
+{
+    forward,
+    reverse,
+    bidirectional,
+};
+
+struct rnn
+{
+    std::size_t hidden_size = 1;
+    std::vector<operation> actv_funcs{tanh{}, tanh{}};
+    rnn_direction direction = rnn_direction::forward;
+    float clip              = 0.0f;
+
+    std::string name() const { return "rnn"; }
+    shape compute_shape(std::vector<shape> inputs) const
     {
-        return {s, nullptr};
+        auto in_dims     = inputs[0].lens();
+        auto hidden_dims = inputs[2].lens();
+        if(hidden_size != hidden_dims[2])
+        {
+            MIGRAPHX_THROW("RNN: hidden size mismatch in attribute and input");
+        }
+
+        std::size_t num_directions = 1;
+        if(direction == rnn_direction::bidirectional)
+        {
+            num_directions = 2;
+        }
+
+        if(num_directions != hidden_dims[0])
+        {
+            MIGRAPHX_THROW("RNN: num_direction mismatch in attribute and input");
+        }
+
+        std::vector<std::size_t> out_dims(in_dims);
+        out_dims.insert(out_dims.begin() + 1, num_directions);
+        out_dims.back() = hidden_size;
+
+        return {inputs[0].type(), out_dims};
     }
 };
 
+struct rnn_last_output
+{
+    std::string name() const { return "rnn_last_output"; }
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(1);
+        auto dims = inputs[0].lens();
+
+        // remove the first dimension, remaing are output shape
+        dims.erase(dims.begin());
+        return {inputs[0].type(), dims};
+    }
+};
+
+struct gru
+{
+    std::size_t hidden_size = 1;
+    std::vector<operation> actv_funcs{sigmoid{}, tanh{}};
+    rnn_direction direction = rnn_direction::forward;
+    float clip              = 0.0f;
+    int linear_before_reset = 0;
+
+    std::string name() const { return "gru"; }
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        auto in_dims     = inputs[0].lens();
+        auto hidden_dims = inputs[2].lens();
+        if(hidden_size != hidden_dims[2])
+        {
+            MIGRAPHX_THROW("GRU: hidden size mismatch in attribute and input");
+        }
+
+        std::size_t num_directions = 1;
+        if(direction == rnn_direction::bidirectional)
+        {
+            num_directions = 2;
+        }
+
+        if(num_directions != hidden_dims[0])
+        {
+            MIGRAPHX_THROW("GRU: num_direction does not match the direction attribute");
+        }
+
+        std::vector<std::size_t> out_dims(in_dims);
+        out_dims.insert(out_dims.begin() + 1, num_directions);
+        out_dims.back() = hidden_size;
+
+        return {inputs[0].type(), out_dims};
+    }
+};
+
+struct undefined
+{
+    std::string name() const { return "undefined"; }
+    shape compute_shape(const std::vector<shape>& inputs) const
+    {
+        check_shapes{inputs, *this}.has(0);
+        return {};
+    }
+
+    argument compute(const shape&, const std::vector<argument>&) const { return {{}, nullptr}; }
+};
+
 } // namespace op
-} // namespace MIGRAPH_INLINE_NS
+} // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
 
 #endif

src/include/migraphx/par_dfor.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_PAR_DFOR_HPP
+#define MIGRAPHX_GUARD_RTGLIB_PAR_DFOR_HPP
+
+#include <migraphx/par_for.hpp>
+#include <migraphx/functional.hpp>
+#include <array>
+#include <numeric>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+template <class... Ts>
+auto par_dfor(Ts... xs)
+{
+    return [=](auto f) {
+        using array_type = std::array<std::size_t, sizeof...(Ts)>;
+        array_type lens  = {{static_cast<std::size_t>(xs)...}};
+        auto n = std::accumulate(lens.begin(), lens.end(), 1, std::multiplies<std::size_t>{});
+        const std::size_t min_grain = 8;
+        if(n > 2 * min_grain)
+        {
+            array_type strides;
+            strides.fill(1);
+            std::partial_sum(lens.rbegin(),
+                             lens.rend() - 1,
+                             strides.rbegin() + 1,
+                             std::multiplies<std::size_t>());
+            auto size =
+                std::accumulate(lens.begin(), lens.end(), 1, std::multiplies<std::size_t>());
+            par_for(size, min_grain, [&](std::size_t i) {
+                array_type indices;
+                std::transform(strides.begin(),
+                               strides.end(),
+                               lens.begin(),
+                               indices.begin(),
+                               [&](size_t stride, size_t len) { return (i / stride) % len; });
+                migraphx::unpack(f, indices);
+            });
+        }
+        else
+        {
+            dfor(xs...)(f);
+        }
+
+    };
+}
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif