Merge from develop

src/include/migraphx/functional.hpp

@@ -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)

src/include/migraphx/instruction.hpp

@@ -14,6 +14,7 @@ namespace migraphx {
 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

src/include/migraphx/iterator_for.hpp

@@ -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()

src/include/migraphx/literal.hpp

@@ -22,8 +22,8 @@ struct literal : raw_data<literal>
 {
     literal() {}
 
-    template <class U, class T = deduce<U>>
-    literal(U x) : buffer(make_shared_array<char>(sizeof(T))), m_shape(shape::get_type<T>{})
+    template <class U, class T = deduce<U>, shape::type_t ShapeType = shape::get_type<T>{}>
+    literal(U x) : buffer(make_shared_array<char>(sizeof(T))), m_shape(ShapeType)
     {
         static_assert(std::is_trivially_copyable<T>{}, "Literals can only be trivial types");
         *(reinterpret_cast<T*>(buffer.get())) = x;

src/include/migraphx/make_shared_array.hpp

@@ -10,7 +10,7 @@ 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 MIGRAPHX_INLINE_NS

src/include/migraphx/matcher.hpp

@@ -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());

src/include/migraphx/onnx.hpp

@@ -7,6 +7,24 @@
 namespace migraphx {
 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);
 

src/include/migraphx/operation.hpp

@@ -7,17 +7,17 @@
 #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 MIGRAPHX_INLINE_NS {
 
+struct context;
+
 #ifdef DOXYGEN
 
 /// The operation interface represents an action an instruction will perform. All
@@ -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,
@@ -99,6 +106,14 @@ 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>&)
 {
@@ -110,7 +125,53 @@ 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<<;
@@ -385,6 +543,22 @@ 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 MIGRAPHX_INLINE_NS

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

src/include/migraphx/par_for.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_PAR_FOR_HPP
+#define MIGRAPHX_GUARD_RTGLIB_PAR_FOR_HPP
+
+#include <thread>
+#include <cmath>
+#include <algorithm>
+#include <vector>
+#include <cassert>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+struct joinable_thread : std::thread
+{
+    template <class... Xs>
+    joinable_thread(Xs&&... xs) : std::thread(std::forward<Xs>(xs)...) // NOLINT
+    {
+    }
+
+    joinable_thread& operator=(joinable_thread&& other) = default;
+    joinable_thread(joinable_thread&& other)            = default;
+
+    ~joinable_thread()
+    {
+        if(this->joinable())
+            this->join();
+    }
+};
+
+template <class F>
+void par_for_impl(std::size_t n, std::size_t threadsize, F f)
+{
+    if(threadsize <= 1)
+    {
+        for(std::size_t i = 0; i < n; i++)
+            f(i);
+    }
+    else
+    {
+        std::vector<joinable_thread> threads(threadsize);
+// Using const here causes gcc 5 to ICE
+#if(!defined(__GNUC__) || __GNUC__ != 5)
+        const
+#endif
+            std::size_t grainsize = std::ceil(static_cast<double>(n) / threads.size());
+
+        std::size_t work = 0;
+        std::generate(threads.begin(), threads.end(), [=, &work] {
+            auto result = joinable_thread([=] {
+                std::size_t start = work;
+                std::size_t last  = std::min(n, work + grainsize);
+                for(std::size_t i = start; i < last; i++)
+                {
+                    f(i);
+                }
+            });
+            work += grainsize;
+            return result;
+        });
+        assert(work >= n);
+    }
+}
+
+template <class F>
+void par_for(std::size_t n, std::size_t min_grain, F f)
+{
+    const auto threadsize =
+        std::min<std::size_t>(std::thread::hardware_concurrency(), n / min_grain);
+    par_for_impl(n, threadsize, f);
+}
+
+template <class F>
+void par_for(std::size_t n, F f)
+{
+    const int min_grain = 8;
+    par_for(n, min_grain, f);
+}
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/pass.hpp

@@ -105,7 +105,13 @@ struct pass
     void apply(program& p) const
     {
         assert((*this).private_detail_te_handle_mem_var);
-        return (*this).private_detail_te_get_handle().apply(p);
+        (*this).private_detail_te_get_handle().apply(p);
+    }
+
+    friend bool is_shared(const pass& private_detail_x, const pass& private_detail_y)
+    {
+        return private_detail_x.private_detail_te_handle_mem_var ==
+               private_detail_y.private_detail_te_handle_mem_var;
     }
 
     private:
@@ -149,7 +155,7 @@ struct pass
 
         std::string name() const override { return private_detail_te_value.name(); }
 
-        void apply(program& p) const override { return private_detail_te_value.apply(p); }
+        void apply(program& p) const override { private_detail_te_value.apply(p); }
 
         PrivateDetailTypeErasedT private_detail_te_value;
     };

src/include/migraphx/program.hpp

@@ -91,16 +91,22 @@ struct program
 
     shape get_shape() const;
 
+    context& get_context() const;
+
     instruction_ref validate() const;
 
     void compile(const target& t, tracer trace = tracer{});
 
+    void finalize();
+
     void perf_report(std::ostream& os, std::size_t n, parameter_map params) const;
 
     void debug_print() const;
     void debug_print(instruction_ref ins) const;
     void debug_print(const std::vector<instruction_ref>& inss) const;
 
+    void dry_run(parameter_map params) const;
+
     friend std::ostream& operator<<(std::ostream& os, const program& p);
     friend bool operator==(const program& x, const program& y);
     friend bool operator!=(const program& x, const program& y) { return !(x == y); }

src/include/migraphx/rewrite_rnn.hpp

+#ifndef MIGRAPHX_GUARD_RTGLIB_REWRITE_RNN_HPP
+#define MIGRAPHX_GUARD_RTGLIB_REWRITE_RNN_HPP
+
+#include <string>
+#include <vector>
+#include <migraphx/instruction_ref.hpp>
+#include <migraphx/operators.hpp>
+#include <migraphx/config.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+struct program;
+
+/**
+ * Rewrite rnn to gemm and add.
+ */
+struct rewrite_rnn
+{
+    std::string name() const { return "rewrite_rnn"; }
+    void apply(program& prog) const;
+
+    private:
+    // for vanilla rnn operators
+    void apply_vanilla_rnn(program& prog, instruction_ref ins) const;
+    std::vector<instruction_ref> vanilla_rnn_cell(bool is_forward,
+                                                  program& prog,
+                                                  instruction_ref ins,
+                                                  instruction_ref input,
+                                                  instruction_ref w,
+                                                  instruction_ref r,
+                                                  instruction_ref bias,
+                                                  instruction_ref ih,
+                                                  operation& actv_func) const;
+    std::vector<operation> vanilla_rnn_actv_funcs(instruction_ref ins) const;
+
+    // for gru operators
+    void apply_gru(program& prog, instruction_ref ins) const;
+    std::vector<instruction_ref> gru_cell(bool is_forward,
+                                          program& prog,
+                                          instruction_ref ins,
+                                          std::vector<instruction_ref> inputs,
+                                          int linear_before_reset,
+                                          const operation& actv_func1,
+                                          const operation& actv_func2) const;
+
+    std::vector<operation> gru_actv_funcs(instruction_ref ins) const;
+
+    // for lstm operators
+    void apply_lstm(program& prog, instruction_ref ins) const;
+    std::vector<instruction_ref> lstm_cell(bool is_forward,
+                                           program& prog,
+                                           instruction_ref ins,
+                                           std::vector<instruction_ref> inputs,
+                                           const operation& actv_func1,
+                                           const operation& actv_func2,
+                                           const operation& actv_func3) const;
+
+    std::vector<operation> lstm_actv_funcs(instruction_ref ins) const;
+};
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/shape.hpp

@@ -35,22 +35,22 @@ struct shape
     m(uint64_type, uint64_t)
 // clang-format on
 
-#define MIGRAPHX_SHAPE_ENUM_TYPES(x, t) x,
+#define MIGRAPHX_SHAPE_GENERATE_ENUM_TYPES(x, t) x,
     enum type_t
     {
-        MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_ENUM_TYPES)
+        MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_GENERATE_ENUM_TYPES)
     };
-#undef MIGRAPHX_SHAPE_ENUM_TYPES
+#undef MIGRAPHX_SHAPE_GENERATE_ENUM_TYPES
 
     template <class T, class = void>
     struct get_type;
-#define MIGRAPHX_SHAPE_GET_TYPE(x, t)                         \
+#define MIGRAPHX_SHAPE_GENERATE_GET_TYPE(x, t)                \
     template <class T>                                        \
     struct get_type<t, T> : std::integral_constant<type_t, x> \
     {                                                         \
     };
-    MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_GET_TYPE)
-#undef MIGRAPHX_SHAPE_GET_TYPE
+    MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_GENERATE_GET_TYPE)
+#undef MIGRAPHX_SHAPE_GENERATE_GET_TYPE
 
     template <class T>
     struct get_type<const T> : get_type<T>
@@ -62,6 +62,19 @@ struct shape
     shape(type_t t, std::vector<std::size_t> l);
     shape(type_t t, std::vector<std::size_t> l, std::vector<std::size_t> s);
 
+    template <class Range>
+    shape(type_t t, const Range& l) : shape(t, std::vector<std::size_t>(l.begin(), l.end()))
+    {
+    }
+
+    template <class Range1, class Range2>
+    shape(type_t t, const Range1& l, const Range2& s)
+        : shape(t,
+                std::vector<std::size_t>(l.begin(), l.end()),
+                std::vector<std::size_t>(s.begin(), s.end()))
+    {
+    }
+
     type_t type() const;
     const std::vector<std::size_t>& lens() const;
     const std::vector<std::size_t>& strides() const;
@@ -141,6 +154,8 @@ struct shape
         {
             return reinterpret_cast<const T*>(buffer) + n;
         }
+
+        type_t type_enum() const { return get_type<T>{}; }
     };
 
     template <class Visitor>
@@ -148,14 +163,22 @@ struct shape
     {
         switch(this->type())
         {
-#define MIGRAPHX_SHAPE_VISITOR_CASE(x, t) \
+#define MIGRAPHX_SHAPE_GENERATE_VISITOR_CASE(x, t) \
     case x: v(as<t>()); return;
-            MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_VISITOR_CASE)
-#undef MIGRAPHX_SHAPE_VISITOR_CASE
+            MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_GENERATE_VISITOR_CASE)
+#undef MIGRAPHX_SHAPE_GENERATE_VISITOR_CASE
         }
         MIGRAPHX_THROW("Unknown type");
     }
 
+    template <class Visitor>
+    static void visit_types(Visitor v)
+    {
+#define MIGRAPHX_SHAPE_GENERATE_VISITOR_ALL(x, t) v(as<t>());
+        MIGRAPHX_SHAPE_VISIT_TYPES(MIGRAPHX_SHAPE_GENERATE_VISITOR_ALL)
+#undef MIGRAPHX_SHAPE_GENERATE_VISITOR_ALL
+    }
+
     private:
     std::shared_ptr<const shape_impl> impl;
 

src/include/migraphx/target.hpp

@@ -127,6 +127,12 @@ struct target
         return (*this).private_detail_te_get_handle().get_context();
     }
 
+    friend bool is_shared(const target& private_detail_x, const target& 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
     {

src/include/migraphx/tensor_view.hpp

@@ -124,6 +124,8 @@ struct tensor_view
             return m_data + this->size();
     }
 
+    std::vector<T> to_vector() const { return std::vector<T>(this->begin(), this->end()); }
+
     friend std::ostream& operator<<(std::ostream& os, const tensor_view<T>& x)
     {
         if(!x.empty())
@@ -164,7 +166,7 @@ bool operator!=(const tensor_view<T>& x, const tensor_view<U>& y)
 }
 
 template <class T>
-tensor_view<T> make_view(shape s, T* data)
+tensor_view<T> make_view(const shape& s, T* data)
 {
     return {s, data};
 }

src/include/migraphx/type_name.hpp

@@ -18,7 +18,7 @@ const std::string& get_type_name()
         name = typeid(PrivateMigraphTypeNameProbe).name();
         name = name.substr(7);
 #else
-        const char parameter_name[] = "PrivateMigraphTypeNameProbe =";
+        const char parameter_name[] = "PrivateMigraphTypeNameProbe ="; // NOLINT
 
         name = __PRETTY_FUNCTION__;
 

src/instruction.cpp

@@ -97,7 +97,7 @@ const std::vector<instruction_ref>& instruction::outputs() const { return output
 
 bool operator==(const instruction& x, const instruction& y)
 {
-    if(not(x.result == y.result and x.op == y.op and x.arguments == y.arguments))
+    if(std::tie(x.result, x.op, x.arguments) != std::tie(y.result, y.op, y.arguments))
         return false;
     if(x.name() == "@literal")
         return x.lit == y.lit;
@@ -162,25 +162,54 @@ void instruction::replace_argument(instruction_ref old, instruction_ref new_ins)
     old->remove_output(*this);
 }
 
-std::vector<shape> compute_shapes(const std::vector<instruction_ref>& args)
+argument instruction::eval() const
 {
-    std::vector<shape> shapes(args.size());
-    std::transform(
-        args.begin(), args.end(), shapes.begin(), [](instruction_ref i) { return i->get_shape(); });
-    return shapes;
+    if(op.name() == "@literal")
+    {
+        return this->get_literal().get_argument();
+    }
+    if(is_context_free(op))
+    {
+        std::vector<argument> args;
+        for(auto&& arg : this->inputs())
+        {
+            argument a = arg->eval();
+            if(a.empty())
+                return {};
+            args.push_back(a);
+        }
+        return op.compute(result, args);
+    }
+    return {};
 }
 
-instruction_ref instruction::get_output_alias(instruction_ref ins)
+void instruction::finalize(context& ctx)
 {
-    auto i = ins->get_operator().output_alias(compute_shapes(ins->inputs()));
+    if(has_finalize(this->op))
+        this->op.finalize(ctx, this->get_shape(), to_shapes(this->inputs()));
+}
+
+instruction_ref instruction::get_output_alias(instruction_ref ins, bool shallow)
+{
+    auto i = ins->get_operator().output_alias(to_shapes(ins->inputs()));
     if(i < 0)
         return ins;
+    if(shallow)
+        return ins->inputs().at(i);
     return get_output_alias(ins->inputs().at(i));
 }
 
+std::vector<shape> to_shapes(const std::vector<instruction_ref>& args)
+{
+    std::vector<shape> shapes(args.size());
+    std::transform(
+        args.begin(), args.end(), shapes.begin(), [](instruction_ref i) { return i->get_shape(); });
+    return shapes;
+}
+
 shape compute_shape(const operation& op, const std::vector<instruction_ref>& args)
 {
-    return op.compute_shape(compute_shapes(args));
+    return op.compute_shape(to_shapes(args));
 }
 
 } // namespace MIGRAPHX_INLINE_NS

src/onnx/mnist.cpp

@@ -14,7 +14,10 @@
 
 auto reverse_int(unsigned int i)
 {
-    unsigned char c1, c2, c3, c4;
+    unsigned char c1;
+    unsigned char c2;
+    unsigned char c3;
+    unsigned char c4;
     c1 = i & 255u;
     c2 = (i >> 8u) & 255u;
     c3 = (i >> 16u) & 255u;
@@ -32,7 +35,9 @@ read_mnist_images(const std::string& full_path, int& number_of_images, int& imag
 
     if(file.is_open())
     {
-        int magic_number = 0, n_rows = 0, n_cols = 0;
+        int magic_number = 0;
+        int n_rows       = 0;
+        int n_cols       = 0;
 
         file.read(reinterpret_cast<char*>(&magic_number), sizeof(magic_number));
         magic_number = reverse_int(magic_number);