Merge branch 'develop' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX into mlir-attention

src/driver/argument_parser.hpp

@@ -105,6 +105,8 @@ inline std::ostream& operator<<(std::ostream& os, const color& c)
     static const bool use_color = isatty(STDOUT_FILENO) != 0;
     if(use_color)
         return os << "\033[" << static_cast<std::size_t>(c) << "m";
+#else
+    (void)c;
 #endif
     return os;
 }

src/driver/main.cpp

@@ -59,6 +59,13 @@ namespace migraphx {
 namespace driver {
 inline namespace MIGRAPHX_INLINE_NS {
 
+inline std::string get_version()
+{
+    return "MIGraphX Version: " + std::to_string(MIGRAPHX_VERSION_MAJOR) + "." +
+           std::to_string(MIGRAPHX_VERSION_MINOR) + "." + std::to_string(MIGRAPHX_VERSION_PATCH) +
+           "." MIGRAPHX_VERSION_TWEAK;
+}
+
 struct loader
 {
     std::string model;
@@ -597,17 +604,6 @@ struct verify : command<verify>
     }
 };
 
-struct version : command<version>
-{
-    void parse(const argument_parser&) {}
-    void run() const
-    {
-        std::cout << "MIGraphX Version: " << MIGRAPHX_VERSION_MAJOR << "." << MIGRAPHX_VERSION_MINOR
-                  << "." << MIGRAPHX_VERSION_PATCH << "."
-                  << MIGRAPHX_STRINGIZE(MIGRAPHX_VERSION_TWEAK) << std::endl;
-    }
-};
-
 struct compile : command<compile>
 {
     compiler c;
@@ -760,16 +756,14 @@ struct main_command
     }
     void parse(argument_parser& ap)
     {
-        std::string version_str = "MIGraphX Version: " + std::to_string(MIGRAPHX_VERSION_MAJOR) +
-                                  "." + std::to_string(MIGRAPHX_VERSION_MINOR) + "." +
-                                  std::to_string(MIGRAPHX_VERSION_PATCH) + "." +
-                                  MIGRAPHX_STRINGIZE(MIGRAPHX_VERSION_TWEAK);
+        std::string version_str = get_version();
         ap(wrong_commands, {}, ap.metavar("<command>"), ap.append());
         ap(nullptr, {"-h", "--help"}, ap.help("Show help"), ap.show_help(get_command_help()));
         ap(nullptr,
            {"-v", "--version"},
            ap.help("Show MIGraphX version"),
            ap.show_help(version_str));
+        ap(nullptr, {"--ort-sha"}, ap.help("Show MIGraphX onnx runtime SHA"));
 
         // Trim command off of exe name
         ap.set_exe_name(ap.get_exe_name().substr(0, ap.get_exe_name().size() - 5));
@@ -812,7 +806,6 @@ using namespace migraphx::driver; // NOLINT
 int main(int argc, const char* argv[])
 {
     std::vector<std::string> args(argv + 1, argv + argc);
-
     // no argument, print the help infomration by default
     if(args.empty())
     {
@@ -822,15 +815,27 @@ int main(int argc, const char* argv[])
     auto&& m = get_commands();
     auto cmd = args.front();
 
-    if(cmd == "ort-sha")
+    if(cmd == "--ort-sha")
     {
         std::cout << MIGRAPHX_ORT_SHA1 << std::endl;
         return 0;
     }
+    if(cmd == "-v" or cmd == "--version")
+    {
+        std::cout << get_version() << std::endl;
+        return 0;
+    }
 
     if(m.count(cmd) > 0)
     {
-        m.at(cmd)(argv[0], {args.begin() + 1, args.end()});
+        std::string driver_invocation =
+            std::string(argv[0]) + " " + migraphx::to_string_range(args, " ");
+        std::cout << "Running [ " << get_version() << " ]: " << driver_invocation << std::endl;
+
+        m.at(cmd)(argv[0],
+                  {args.begin() + 1, args.end()}); // run driver command found in commands map
+
+        std::cout << "[ " << get_version() << " ] Complete: " << driver_invocation << std::endl;
     }
     else
     {

src/driver/verify.cpp

@@ -119,6 +119,7 @@ void verify_program(const std::string& name,
     auto target_outs = run_target(p, t, options, quantize, inputs);
 
     std::size_t output_num = ref_outs.size();
+    bool passed            = true;
     for(std::size_t i = 0; i < output_num; ++i)
     {
         if(ref_outs[i].get_shape().type() != target_outs[i].get_shape().type() or
@@ -130,9 +131,11 @@ void verify_program(const std::string& name,
         }
         else
         {
-            verify_args(name, target_outs[i], verify::expected{ref_outs[i]}, tols);
+            passed &= verify_args(name, target_outs[i], verify::expected{ref_outs[i]}, tols);
         }
     }
+    if(passed)
+        std::cout << "MIGraphX verification passed successfully." << std::endl;
 }
 
 void verify_instructions(const program& prog,

src/dynamic_loader.cpp

@@ -130,6 +130,30 @@ struct dynamic_loader_impl
     tmp_dir temp;
 };
 
+fs::path dynamic_loader::path(void* address)
+{
+    HMODULE module = nullptr;
+    if(GetModuleHandleEx(GET_MODULE_HANDLE_EX_FLAG_FROM_ADDRESS |
+                             GET_MODULE_HANDLE_EX_FLAG_UNCHANGED_REFCOUNT,
+                         static_cast<LPCSTR>(address),
+                         &module) == 0)
+    {
+        auto err = GetLastError();
+        MIGRAPHX_THROW("Unable to obtain module handle, error = " + std::to_string(err));
+    }
+    TCHAR buffer[MAX_PATH];
+    if(GetModuleFileName(module, buffer, sizeof(buffer)) == 0)
+    {
+        auto err = GetLastError();
+        MIGRAPHX_THROW("Unable to read module file path, error = " + std::to_string(err));
+    }
+    if(GetLastError() == ERROR_INSUFFICIENT_BUFFER)
+    {
+        MIGRAPHX_THROW("Buffer too small (" + std::to_string(MAX_PATH) + ") to hold the path");
+    }
+    return {buffer};
+}
+
 #endif
 
 optional<dynamic_loader> dynamic_loader::try_load(const fs::path& p)

src/fuse_pointwise.cpp

@@ -219,9 +219,8 @@ struct find_pointwise_reshape_pointwise
 
         auto reshape_input = [&](const auto& ins_to_insert) {
             return [&](auto input) {
-                auto c = m.insert_instruction(ins_to_insert, make_op("contiguous"), input);
                 return m.insert_instruction(
-                    ins_to_insert, make_op("reshape", {{"dims", cd.dims}}), c);
+                    ins_to_insert, make_op("reshape", {{"dims", cd.dims}}), input);
             };
         };
         auto x_inputs = x_ins->inputs();

src/include/migraphx/bit_cast.hpp

+/* ************************************************************************
+ * Copyright (C) 2016-2023 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell cop-
+ * ies of the Software, and to permit persons to whom the Software is furnished
+ * to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IM-
+ * PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+ * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+ * COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+ * IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE-
+ * CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ *
+ * ************************************************************************ */
+#ifndef MIGRAPHX_GUARD_RTGLIB_BITCAST_HPP
+#define MIGRAPHX_GUARD_RTGLIB_BITCAST_HPP
+#if defined(__GNUC__) && !defined(__clang__)
+#pragma GCC diagnostic push
+#pragma GCC diagnostic ignored "-Wstrict-aliasing"
+#endif
+#include <migraphx/config.hpp>
+
+// NOLINTNEXTLINE(cppcoreguidelines-macro-usage)
+#define MIGRAPHX_CONST_FOLD(x) (__builtin_constant_p(x) ? (x) : (x))
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+template <typename To, typename From>
+inline constexpr To bit_cast(From fr) noexcept
+{
+    static_assert(sizeof(To) == sizeof(From));
+#if defined(__GNUC__) and !defined(__clang__)
+    return MIGRAPHX_CONST_FOLD(*reinterpret_cast<To*>(&fr));
+#else
+    return __builtin_bit_cast(To, fr);
+#endif
+}
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#if defined(__GNUC__) && !defined(__clang__)
+#pragma GCC diagnostic pop
+#endif
+#endif // MIGRAPHX_GUARD_RTGLIB_BITCAST_HPP

src/include/migraphx/dynamic_loader.hpp

@@ -38,15 +38,12 @@ struct dynamic_loader_impl;
 
 struct MIGRAPHX_EXPORT dynamic_loader
 {
-#ifndef _WIN32
     template <class T>
     static fs::path path(T* address)
     {
         return path(reinterpret_cast<void*>(address));
     }
     static fs::path path(void* address);
-#endif
-
     static optional<dynamic_loader> try_load(const fs::path& p);
 
     dynamic_loader() = default;

src/include/migraphx/float8.hpp

+/* ************************************************************************
+ * Copyright (C) 2016-2023 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell cop-
+ * ies of the Software, and to permit persons to whom the Software is furnished
+ * to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IM-
+ * PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+ * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+ * COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+ * IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE-
+ * CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ *
+ * ************************************************************************ */
+
+#ifndef MIGRAPHX_GUARD_RTGLIB_FLOAT8_HPP
+#define MIGRAPHX_GUARD_RTGLIB_FLOAT8_HPP
+
+// We are clipping/saturation in down conversion by default. Unclipped version is not tested and
+// shouldn't be used without having enough tests.
+// logic is based on clipping table from here : https://onnx.ai/onnx/technical/float8.html#cast
+// NOLINTNEXTLINE
+#define MIGRAPHX_F8_DOWNCAST_CLIPPING 1
+
+#include <cmath>
+#include <cstdint>
+#include <climits>
+#include <cstring>
+#include <iosfwd>
+#include <limits>
+#include <sstream>
+#include <iostream>
+#include <string>
+#include <utility>
+#include <migraphx/config.hpp>
+#include <migraphx/float8_impl.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace fp8 {
+
+enum class rounding_mode
+{
+    standard, // standard rounding is doing RNE -- round to nearest even
+    stochastic
+};
+
+enum class f8_type
+{
+    bf8 = 0, // s1e5m2
+    fp8 = 1  // s1e4m3
+};
+
+template <typename T, bool FNUZ = true>
+class numeric_limits;
+
+template <migraphx::fp8::f8_type T = migraphx::fp8::f8_type::fp8, bool FNUZ = true>
+struct float8
+{
+    uint8_t data = 0x00;
+    // default constructor
+    constexpr float8() = default;
+    // default copy constructor
+    constexpr float8(const float8& y) = default;
+    struct from_bits_t
+    {
+    };
+    static constexpr from_bits_t from_bits() { return from_bits_t(); }
+
+    explicit constexpr float8(uint8_t bits, from_bits_t) : data(bits) {}
+
+    explicit constexpr float8(
+        float v,
+        migraphx::fp8::rounding_mode rm = migraphx::fp8::rounding_mode::standard,
+        uint32_t rng                    = 0)
+    {
+        if constexpr(T == migraphx::fp8::f8_type::fp8)
+        {
+#ifdef MIGRAPHX_F8_DOWNCAST_CLIPPING
+            data = migraphx::fp8::impl::
+                cast_to_f8<3, 4, float, FNUZ /*negative_zero_nan*/, true /*clip*/>(
+                    v, (rm == migraphx::fp8::rounding_mode::stochastic), rng);
+#else  // MIGRAPHX_F8_DOWNCAST_CLIPPING
+            data = migraphx::fp8::impl::
+                cast_to_f8<3, 4, float, FNUZ /*negative_zero_nan*/, false /*clip*/>(
+                    v, (rm == migraphx::fp8::rounding_mode::stochastic), rng);
+#endif // MIGRAPHX_F8_DOWNCAST_CLIPPING
+        }
+        else
+        {
+#ifdef MIGRAPHX_F8_DOWNCAST_CLIPPING
+            data = migraphx::fp8::impl::
+                cast_to_f8<2, 5, float, FNUZ /*negative_zero_nan*/, true /*clip*/>(
+                    v, (rm == migraphx::fp8::rounding_mode::stochastic), rng);
+#else  // MIGRAPHX_F8_DOWNCAST_CLIPPING
+            data = migraphx::fp8::impl::
+                cast_to_f8<2, 5, float, FNUZ /*negative_zero_nan*/, false /*clip*/>(
+                    v, (rm == migraphx::fp8::rounding_mode::stochastic), rng);
+#endif // rocblas_F8_downcast_clipping}
+        }
+    }
+
+    inline constexpr operator float() const
+    {
+        if constexpr(T == migraphx::fp8::f8_type::fp8)
+        {
+            return migraphx::fp8::impl::cast_from_f8<3, 4, float, FNUZ /*negative_zero_nan*/>(data);
+        } // else
+        return migraphx::fp8::impl::cast_from_f8<2, 5, float, FNUZ /*negative_zero_nan*/>(data);
+    }
+
+    inline constexpr bool is_zero() const
+    {
+        if constexpr(FNUZ)
+        {
+            return data == 0x00;
+        }
+        else
+        {
+            return (data == 0x00) or (data == 0x80);
+        }
+    }
+
+    inline constexpr bool is_nan() const
+    {
+        if constexpr(FNUZ)
+        {
+            return data == 0x80;
+        }
+        else
+        {
+            if(T == migraphx::fp8::f8_type::bf8)
+            {
+                return (data == 0x7D) or (data == 0x7E) or (data == 0x7F) or (data == 0xFD) or
+                       (data == 0xFE) or (data == 0xFF);
+            }
+            else
+            {
+                return (data == 0x7F) or (data == 0xFF);
+            }
+        }
+    }
+
+    inline constexpr bool is_inf() const
+    {
+        if constexpr(FNUZ)
+        {
+            return data == 0x80;
+        }
+        else
+        {
+            if(T == migraphx::fp8::f8_type::bf8)
+            {
+                return (data == 0x7C) or (data == 0xFC);
+            }
+            else
+            {
+                // no infinities in e4m3fn, represent them as NaNs
+                return (data == 0x7F) or (data == 0xFF);
+            }
+        }
+    }
+
+// NOLINTNEXTLINE
+#define MIGRAPHX_FP8_UNARY_OP(unary_op, binary_op)                                    \
+    constexpr float8& operator unary_op(const float8& rhs)                            \
+    {                                                                                 \
+        const auto tmp = static_cast<float>(*this) binary_op static_cast<float>(rhs); \
+        *this          = static_cast<float8>(tmp);                                    \
+        return *this;                                                                 \
+    }                                                                                 \
+    constexpr float8& operator unary_op(const float& rhs)                             \
+    {                                                                                 \
+        const auto tmp = static_cast<float>(*this) binary_op static_cast<float>(rhs); \
+        *this          = static_cast<float8>(tmp);                                    \
+        return *this;                                                                 \
+    }
+
+    MIGRAPHX_FP8_UNARY_OP(*=, *)
+    MIGRAPHX_FP8_UNARY_OP(-=, -)
+    MIGRAPHX_FP8_UNARY_OP(+=, +)
+    MIGRAPHX_FP8_UNARY_OP(/=, /)
+
+    inline constexpr float8& operator=(const float8& rhs)     = default;
+    inline constexpr float8& operator=(float8&& rhs) noexcept = default;
+
+    inline constexpr float8& operator=(float rhs)
+    {
+        *this = static_cast<float8>(rhs);
+        return *this;
+    }
+
+    inline constexpr bool operator==(const float8& rhs) const
+    {
+        if(rhs.is_nan() or rhs.is_inf() or this->is_nan() or this->is_inf())
+            return false;
+        else if((rhs.is_zero() and this->is_zero()) or (this->data == rhs.data))
+            return true;
+        return false;
+    }
+
+    inline constexpr bool operator<(const float8& rhs) const
+    {
+        const auto we   = static_cast<float>(*this);
+        const auto them = static_cast<float>(rhs);
+        return we < them;
+    }
+
+    inline constexpr bool operator>(const float8& rhs) const
+    {
+        const auto we   = static_cast<float>(*this);
+        const auto them = static_cast<float>(rhs);
+        return we > them;
+    }
+};
+
+// https://onnx.ai/onnx/technical/float8.html
+using fp8e4m3fn   = float8<migraphx::fp8::f8_type::fp8, false>;
+using fp8e5m2     = float8<migraphx::fp8::f8_type::bf8, false>;
+using fp8e4m3fnuz = float8<migraphx::fp8::f8_type::fp8, true>;
+using fp8e5m2fnuz = float8<migraphx::fp8::f8_type::bf8, true>;
+/*
+// NOLINTNEXTLINE
+#define MIGRAPHX_FP8_BINARY_OP(binary_op, T, U)                                     \
+    inline constexpr U operator binary_op(const T& lhs, const T& rhs)               \
+    {                                                                               \
+        return U(static_cast<float>(lhs) binary_op static_cast<float>(rhs)); \
+    }
+
+// TODO: these should return floats for binary ops
+// NOLINTNEXTLINE
+#define MIGRAPHX_FP8_BINARY_OP_GEN_FOR(T) \
+    MIGRAPHX_FP8_BINARY_OP(*, T, T)       \
+    MIGRAPHX_FP8_BINARY_OP(-, T, T)       \
+    MIGRAPHX_FP8_BINARY_OP(/, T, T)       \
+    MIGRAPHX_FP8_BINARY_OP(+, T, T)       \
+    MIGRAPHX_FP8_BINARY_OP(==, T, bool)   \
+    MIGRAPHX_FP8_BINARY_OP(>=, T, bool)   \
+    MIGRAPHX_FP8_BINARY_OP(<=, T, bool)   \
+    MIGRAPHX_FP8_BINARY_OP(>, T, bool)    \
+    MIGRAPHX_FP8_BINARY_OP(<, T, bool)    \
+    MIGRAPHX_FP8_BINARY_OP(!=, T, bool)
+
+MIGRAPHX_FP8_BINARY_OP_GEN_FOR(fp8e5m2)
+MIGRAPHX_FP8_BINARY_OP_GEN_FOR(fp8e4m3fn)
+MIGRAPHX_FP8_BINARY_OP_GEN_FOR(fp8e5m2fnuz)
+MIGRAPHX_FP8_BINARY_OP_GEN_FOR(fp8e4m3fnuz)
+*/
+
+// Special operator overloading
+inline std::ostream& operator<<(std::ostream& os, const fp8e4m3fnuz& rhs)
+{
+    return os << static_cast<float>(rhs);
+}
+
+inline fp8e4m3fnuz fabs(fp8e4m3fnuz v)
+{
+    v.data = v.data & 0x7F; // NOLINT
+    return v;
+}
+
+// Special operator overloading
+inline std::ostream& operator<<(std::ostream& os, const fp8e4m3fn& rhs)
+{
+    return os << static_cast<float>(rhs);
+}
+
+inline fp8e4m3fn fabs(fp8e4m3fn v)
+{
+    v.data = v.data & 0x7F; // NOLINT
+    return v;
+}
+
+// Special operator overloading
+inline std::ostream& operator<<(std::ostream& os, const fp8e5m2fnuz& rhs)
+{
+    return os << static_cast<float>(rhs);
+}
+
+inline fp8e5m2fnuz fabs(fp8e5m2fnuz v)
+{
+    v.data = v.data & 0x7F; // NOLINT
+    return v;
+}
+// Special operator overloading
+inline std::ostream& operator<<(std::ostream& os, const fp8e5m2& rhs)
+{
+    return os << static_cast<float>(rhs);
+}
+
+inline fp8e5m2 fabs(fp8e5m2 v)
+{
+    v.data = v.data & 0x7F; // NOLINT
+    return v;
+}
+template <>
+class numeric_limits<fp8e4m3fnuz>
+{
+    public:
+    static constexpr bool has_infinity = false;
+    static constexpr fp8e4m3fnuz epsilon() { return fp8e4m3fnuz(0x28, fp8e4m3fnuz::from_bits()); }
+    // NOLINTNEXTLINE
+    static constexpr fp8e4m3fnuz quiet_NaN() { return fp8e4m3fnuz(0x80, fp8e4m3fnuz::from_bits()); }
+
+    static constexpr fp8e4m3fnuz max() { return fp8e4m3fnuz(0x7F, fp8e4m3fnuz::from_bits()); }
+    // this is min value that is not DeNorm. DeNorm min is 0x01
+    static constexpr fp8e4m3fnuz min() { return fp8e4m3fnuz(0x08, fp8e4m3fnuz::from_bits()); }
+
+    static constexpr fp8e4m3fnuz lowest() { return fp8e4m3fnuz(0xFF, fp8e4m3fnuz::from_bits()); }
+};
+
+template <>
+class numeric_limits<fp8e4m3fn>
+{
+    public:
+    static constexpr bool has_infinity = false;
+    static constexpr fp8e4m3fn epsilon() { return fp8e4m3fn(0x20, fp8e4m3fn::from_bits()); }
+    // NOLINTNEXTLINE
+    static constexpr fp8e4m3fn quiet_NaN() { return fp8e4m3fn(0x7F, fp8e4m3fn::from_bits()); }
+
+    static constexpr fp8e4m3fn max() { return fp8e4m3fn(0x7E, fp8e4m3fn::from_bits()); }
+    // this is min value that is not DeNorm. DeNorm min is 0x01
+    static constexpr fp8e4m3fn min() { return fp8e4m3fn(0x08, fp8e4m3fn::from_bits()); }
+
+    static constexpr fp8e4m3fn lowest() { return fp8e4m3fn(0xFE, fp8e4m3fn::from_bits()); }
+};
+
+template <>
+class numeric_limits<fp8e5m2fnuz>
+{
+    public:
+    static constexpr bool has_infinity = false;
+    static constexpr fp8e5m2fnuz epsilon() { return fp8e5m2fnuz(0x34, fp8e5m2fnuz::from_bits()); }
+
+    static constexpr fp8e5m2fnuz quiet_NaN() // NOLINT
+    {
+        return fp8e5m2fnuz(0x80, fp8e5m2fnuz::from_bits());
+    }
+
+    static constexpr fp8e5m2fnuz max() { return fp8e5m2fnuz(0x7F, fp8e5m2fnuz::from_bits()); }
+    // this is min value that is not DeNorm. DeNorm min is 0x01. I am not sure if we want to make
+    // this distinction. For the floating points we would end up using lowest most of the times.
+    static constexpr fp8e5m2fnuz min() { return fp8e5m2fnuz(0x4, fp8e5m2fnuz::from_bits()); }
+
+    static constexpr fp8e5m2fnuz lowest() { return fp8e5m2fnuz(0xFF, fp8e5m2fnuz::from_bits()); }
+};
+
+template <>
+class numeric_limits<fp8e5m2>
+{
+    public:
+    static constexpr bool has_infinity = true;
+    static constexpr fp8e5m2 epsilon() { return fp8e5m2(0x34, fp8e5m2::from_bits()); }
+    // 7D, 7E, 7F are positive NaNs and FD, FE, FF are negative NaNs
+    static constexpr fp8e5m2 quiet_NaN() { return fp8e5m2(0xFF, fp8e5m2::from_bits()); } // NOLINT
+
+    static constexpr fp8e5m2 max() { return fp8e5m2(0x7B, fp8e5m2::from_bits()); }
+    // this is min value that is not DeNorm. DeNorm min is 0x01. I am not sure if we want to make
+    // this distinction. For the floating points we would end up using lowest most of the times.
+    static constexpr fp8e5m2 min() { return fp8e5m2(0x4, fp8e5m2::from_bits()); }
+
+    static constexpr fp8e5m2 lowest() { return fp8e5m2(0xFB, fp8e5m2::from_bits()); }
+    // 7C and FC both are infinity
+    static constexpr fp8e5m2 infinity() { return fp8e5m2(0x7C, fp8e5m2::from_bits()); }
+};
+} // namespace fp8
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+// =================================================================================================
+// define numeric limits for the new data type
+// NOLINTBEGIN
+namespace std {
+#define MIGRAPHX_FP8_STD_OVERLOADS(T)                                       \
+    inline bool isfinite(T x) { return not x.is_inf() and not x.is_nan(); } \
+    inline bool isnan(T x) { return x.is_nan(); }                           \
+    template <>                                                             \
+    class numeric_limits<T> : public migraphx::fp8::numeric_limits<T>       \
+    {                                                                       \
+    };                                                                      \
+    template <class U>                                                      \
+    struct common_type<T, U> : std::common_type<float, U>                   \
+    {                                                                       \
+    };                                                                      \
+    template <class U>                                                      \
+    struct common_type<U, T> : std::common_type<float, U>                   \
+    {                                                                       \
+    };                                                                      \
+    template <>                                                             \
+    struct common_type<T, T>                                                \
+    {                                                                       \
+        using type = T;                                                     \
+    };
+
+MIGRAPHX_FP8_STD_OVERLOADS(migraphx::fp8::fp8e4m3fn)
+MIGRAPHX_FP8_STD_OVERLOADS(migraphx::fp8::fp8e5m2)
+MIGRAPHX_FP8_STD_OVERLOADS(migraphx::fp8::fp8e4m3fnuz)
+MIGRAPHX_FP8_STD_OVERLOADS(migraphx::fp8::fp8e5m2fnuz)
+} // namespace std
+// NOLINTEND
+// =================================================================================================
+#endif // MIGRAPHX_GUARD_RTGLIB_FLOAT8_HPP

src/include/migraphx/float8_impl.hpp

+/* ************************************************************************
+ * Copyright (C) 2016-2023 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell cop-
+ * ies of the Software, and to permit persons to whom the Software is furnished
+ * to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in all
+ * copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IM-
+ * PLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS
+ * FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
+ * COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER
+ * IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNE-
+ * CTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
+ *
+ * ************************************************************************ */
+
+#ifndef MIGRAPHX_GUARD_RTGLIB_FLOAT8_IMPL_HPP
+#define MIGRAPHX_GUARD_RTGLIB_FLOAT8_IMPL_HPP
+#include <algorithm>
+#include <cstdint>
+#include <type_traits>
+#include <migraphx/config.hpp>
+#include <migraphx/bit_cast.hpp>
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace fp8 {
+namespace impl {
+
+// NOLINTBEGIN
+template <uint32_t Wm, uint32_t We, typename T, bool NegativeZeroNan, bool Clip>
+constexpr uint8_t cast_to_f8(T f_x, bool stoch = false, uint32_t rng = 0)
+{
+    constexpr bool is_float = std::is_same<T, float>::value;
+    // half is not supported for now
+    constexpr bool is_half = false;
+    static_assert(Wm + We == 7, "Wm+We==7");
+    static_assert(is_float or is_half, "Only float can be cast to f8");
+
+    const uint32_t mfmt = (sizeof(T) == 4) ? 23 : 10;
+    typename std::conditional<sizeof(T) == 2, uint16_t, uint32_t>::type x;
+
+    if constexpr(sizeof(T) == 4)
+        x = migraphx::bit_cast<uint32_t>(f_x);
+    else
+        x = migraphx::bit_cast<uint16_t>(f_x);
+
+    uint32_t head     = 0;
+    uint32_t mantissa = 0;
+    int exponent      = 0;
+    uint32_t bias     = 0;
+    uint32_t sign     = 0;
+    if constexpr(sizeof(T) == 4)
+    {
+        head     = x & 0xFF800000;
+        mantissa = x & 0x7FFFFF;
+        exponent = (head >> 23) & 0xFF;
+        sign     = head >> 31;
+        bias     = 127;
+    }
+    else
+    {
+        head     = x & 0xFC00;
+        mantissa = x & 0x3FF;
+        exponent = (head >> 10) & 0x1F;
+        sign     = head >> 15;
+        bias     = 15;
+    }
+
+    uint32_t signed_inf      = (sign << 7) + (((1 << We) - 1) << Wm);
+    uint32_t signed_all_ones = (sign << 7) + ((((1 << We) - 1) << Wm) + ((1 << Wm) - 1));
+
+    // Calcualte maximum singed value FLT_MAX, FLT_MIN
+    uint32_t signed_max = signed_all_ones;
+    if(not NegativeZeroNan)
+        signed_max = (Wm == 2) ? (signed_max - 4) : (signed_max - 1);
+
+    // Deal with inf and NaNs
+    if(NegativeZeroNan) // For the FNUZ cases, it is simple just return NaNs
+    {
+        if((sizeof(T) == 4 and ((x & 0x7F800000) == 0x7F800000)) or
+           (sizeof(T) == 2 and ((x & 0x7C00) == 0x7C00)))
+            return 0x80;
+    }
+    else
+    {
+        // calculate most common NaN mantissa for FP8, which is all Ones in binary
+        uint32_t nan_mantissa = 1;
+        for(auto i = 1; i < Wm; ++i)
+        {
+            nan_mantissa |= (nan_mantissa << 1);
+        }
+        if((sizeof(T) == 4 and ((x & 0x7F800000) == 0x7F800000)) or
+           (sizeof(T) == 2 and ((x & 0x7C00) == 0x7C00)))
+        {
+            // infinity
+            if(mantissa == 0)
+            {
+                if(sign == 0)
+                    return (Wm == 2) ? 0x7B : 0x7E;
+                else
+                    return (Wm == 2) ? 0xFB : 0xFE;
+            }
+            else // NaNs
+                return signed_inf + nan_mantissa;
+        }
+    }
+    // handle positive zero
+    if(x == 0)
+        return 0;
+    // handle negative zero
+    else if((sizeof(T) == 4 and x == 0x80000000) or (sizeof(T) == 2 and x == 0x8000))
+    {
+        return NegativeZeroNan ? 0 : 0x80; // For FNUZ types neg zero is just positive zero
+    }
+
+    /* First need to check if it is normal or denorm as there is a difference of implict 1
+    Then need to adjust the exponent to align with the F8 exponent, in the meanwhile, shift
+    The mantissa. Then for stochastic rounding, add rng to mantissa and truncate. And for
+    RNE, no need to add rng. Then probably need to check whether there is carry and adjust
+    exponent and mantissa again*/
+
+    // For IEEE bias mode, the bias is 2^(k-1) -1 where k is the width of exponent bits
+    const int f8_bias                  = (1 << (We - 1u)) - 1 + (NegativeZeroNan ? 1 : 0);
+    const int f8_denormal_act_exponent = 1 - f8_bias; // actual exponent of f8 denormal
+    /* act_exponent is the actual exponent of fp32/fp16 (after subtracting bias)
+    f8_exponent is the converted f8 exponent with bias encoding
+    exponent_diff is the diff between fp32/fp16 exponent and f8 exponent,
+    the difference needs to be adjusted and mantissa shifted*/
+    int act_exponent  = 0;
+    int f8_exponent   = 0;
+    int exponent_diff = 0;
+
+    if(exponent == 0 and mantissa != 0)
+    { // fp32/fp16 is in denormal.
+        /* fp32 denormal is below 2^-127 so it is usually not a concern here, we mostly concern fp16
+        here. In this case, f8 is usually in denormal. But there could be exceptions. fp16 denormal
+        has exponent bias 15 while bf8 with FNUZ has exponent bias 16. It means that there are some
+        numbers in fp16 denormal but they are bf8 (FNUZ) normals - smallest bf8 (FNUZ) normal is
+        2^-15. fp16 numbers where exponent==0 (actual exponent -14) and highest bit of mantissa is 1
+        are bf8 (FNUZ) normal. In this case, the fp16 mantissa should be shift left by 1  */
+        act_exponent  = 1 - bias;
+        exponent_diff = f8_denormal_act_exponent -
+                        act_exponent; // actual exponent is exponent-bias+1 as it is denormal
+    }
+    else
+    { // fp32/fp16 is normal with implicit 1
+        act_exponent = exponent - bias;
+        if(act_exponent <= f8_denormal_act_exponent)
+        {
+            /* This is the case where fp32/fp16 is normal but it is in f8 denormal range.
+            For example fp8 FNUZ mode, denormal exponent is -7, but if the fp32/fp16
+            actual exponent is -7, it is actually larger due to the implict 1,
+            Therefore it needs to be adjust to -6 and mantissa shift right by 1.
+            So for fp32/fp16, exponent -8 is the cut point to convert to fp8 FNUZ */
+            exponent_diff = f8_denormal_act_exponent - act_exponent;
+        }
+        else
+        {          // both fp32/fp16 and f8 are in normal range
+            exponent_diff =
+                0; // exponent_diff=0 does not mean there is no difference for this case,
+            // act_exponent could be larger. Just that it does not need shift mantissa
+        }
+        mantissa += (1u << mfmt); // Add the implicit 1 into mantissa
+    }
+
+    // need to know whether the number is right in the middle of two adjacent fp8 numbers. use  max
+    // value of 31 to avoid undefined behaviour
+    bool midpoint = (mantissa & ((1u << std::min(31u, mfmt - Wm + exponent_diff)) - 1)) ==
+                    (1u << std::min(31u, mfmt - Wm + exponent_diff - 1));
+    /* This part is a bit tricky. The judgment of whether it is a tie needs to be done before we
+    shift right as shift right could rip off some residual part and make something not midpoint look
+    like midpoint. For example, the fp16 number 0x1002 (0 00100 0000000010), it is larger than
+    midpoint, but after shift right by 4 bits, it would look like midpoint.
+    */
+
+    if(exponent_diff > 0)
+        mantissa >>= std::min(31u, uint32_t(exponent_diff));
+    else if(exponent_diff == -1)
+        mantissa <<= -exponent_diff;
+    bool implicit_one = mantissa & (1 << mfmt);
+    // if there is no implict 1, it  means the f8 is denormal and need to adjust to denorm exponent
+    f8_exponent =
+        (act_exponent + exponent_diff) /*actual f8 exponent*/ + f8_bias - (implicit_one ? 0 : 1);
+
+    // Now we have the exponent and mantissa adjusted
+    uint32_t drop_mask = (1u << (mfmt - Wm)) - 1;
+    bool odd =
+        mantissa & (1u << (mfmt - Wm)); // if the least significant bit that is not truncated is 1
+    /*
+    This part is doing rounding by adding mantissa part that is going to get dropped.
+    e.g. if the dropped part for less than 0.5 than it would round down.
+    if the dropped part is more than 0.5 then it would round up by rolling carry to LSB of retained
+    mantissa.
+    For the mid point when bit pattern is like this for Odd: `xy1:10000000` for Odd and
+    `xy0:10000000` for the Even.  where `:` is delimiter for dropped v/s retained part.
+    For the odd case :
+    this will add xy1:10000000 + 000:10000000 which would roll over carry to LSB of retained
+    part making it RNE.
+    For the even case : this will add xy0:10000000 + 000:01111111 which would
+    round down and keep number Even
+    */
+    mantissa += (stoch ? rng : (midpoint ? (odd ? mantissa : mantissa - 1) : mantissa)) & drop_mask;
+
+    // Now we deal with overflow
+    if(f8_exponent == 0 and ((1 << mfmt) & mantissa))
+    {
+        f8_exponent = 1; // denormal overflow to become normal, promote exponent
+    }
+    else if((1 << (mfmt + 1)) & mantissa)
+    {
+        mantissa >>= 1;
+        f8_exponent++;
+    }
+
+    mantissa >>= (mfmt - Wm);
+
+    // above range: quantize to maximum possible float of the same sign
+    // for e5m2 case, max_exp is 14, since exp = 15 is reserved for Infs and Nans
+    const int max_exp = (1 << We) - ((NegativeZeroNan or Wm == 3) ? 1 : 2);
+    if(f8_exponent > max_exp)
+    {
+        if(Clip)
+            return signed_max;
+        else
+        {
+            // https://onnx.ai/onnx/technical/float8.html#cast
+            if(NegativeZeroNan)
+                return 0x80;
+            else
+                return (Wm == 2) ? signed_inf : signed_all_ones;
+        }
+    }
+
+    if(f8_exponent == 0 and mantissa == 0)
+        return NegativeZeroNan ? 0 : (sign << 7);
+    mantissa &= (1 << Wm) - 1;
+    return (sign << 7) | (f8_exponent << Wm) | mantissa;
+}
+// NOLINTEND
+
+template <uint32_t Wm, uint32_t We, typename T, bool NegativeZeroNan>
+constexpr T cast_from_f8(uint8_t x)
+{
+    // half is not supported for now
+    constexpr bool is_half  = false;
+    constexpr bool is_float = std::is_same<T, float>::value;
+    static_assert(is_float or is_half, "Only float are supported");
+
+    constexpr int weo = is_half ? 5 : 8;
+    constexpr int wmo = is_half ? 10 : (is_float ? 23 : 7);
+    // NOLINTNEXTLINE
+    T f_inf, f_neg_inf, f_nan, f_neg0;
+
+    if constexpr(is_float)
+    {
+        const uint32_t if_inf     = 0x7F800000;
+        const uint32_t if_neg_inf = 0xFF800000;
+        const uint32_t if_nan     = 0x7F800001;
+        const uint32_t if_neg0    = 0x80000000;
+        f_inf                     = migraphx::bit_cast<float>(if_inf);
+        f_neg_inf                 = migraphx::bit_cast<float>(if_neg_inf);
+        f_nan                     = migraphx::bit_cast<float>(if_nan);
+        f_neg0                    = migraphx::bit_cast<float>(if_neg0);
+    }
+
+    if(x == 0)
+        return 0;
+
+    uint32_t sign     = x >> 7;              // NOLINT
+    uint32_t mantissa = x & ((1 << Wm) - 1); // NOLINT
+    int exponent      = (x & 0x7F) >> Wm;    // NOLINT
+    if(NegativeZeroNan)
+    {
+        if(x == 0x80)
+            return f_nan;
+    }
+    else
+    {
+        if(x == 0x80)
+            return f_neg0;
+        if(exponent == ((1 << We) - 1) and Wm == 2) // NOLINT
+            return (mantissa == 0) ? (sign ? f_neg_inf : f_inf) : f_nan;
+        else if(Wm == 3 and (x == 0x7F or x == 0xFF))
+            return f_nan;
+    }
+    typename std::conditional<sizeof(T) == 2, uint16_t, uint32_t>::type retval;
+
+    const int exp_low_cutoff =
+        (1 << (weo - 1)) - (1 << (We - 1)) + 1 - (NegativeZeroNan ? 1 : 0); // NOLINT
+
+    // subnormal input
+    if(exponent == 0)
+    {
+        // guaranteed mantissa!=0 since cases 0x0 and 0x80 are handled above
+        int sh = 1 + __builtin_clz(mantissa) - (32 - Wm);
+        mantissa <<= sh;             // NOLINT
+        exponent += 1 - sh;
+        mantissa &= ((1 << Wm) - 1); // NOLINT
+    }
+    exponent += exp_low_cutoff - 1;
+    mantissa <<= wmo - Wm; // NOLINT
+
+    // subnormal output (occurs when T=half, We=5, negative_zero_nan=true)
+    if(exponent <= 0)
+    {
+        mantissa |= 1 << wmo;      // NOLINT
+        mantissa >>= 1 - exponent; // NOLINT
+        exponent = 0;
+    }
+
+    if(sizeof(T) == 2)
+        retval = (sign << 15) | (exponent << 10) | mantissa; // NOLINT
+    else
+        retval = (sign << 31) | (exponent << 23) | mantissa; // NOLINT
+    return migraphx::bit_cast<T>(retval);
+}
+
+} // namespace impl
+} // namespace fp8
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#endif // MIGRAPHX_GUARD_RTGLIB_FLOAT8_IMPL

src/include/migraphx/half.hpp

@@ -27,6 +27,7 @@
 
 #include <half/half.hpp>
 #include <migraphx/config.hpp>
+#include <migraphx/float8.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -67,6 +68,18 @@ struct common_type<T, migraphx::half> : std::common_type<float, T> // NOLINT
 {
 };
 
+template <>
+struct common_type<migraphx::fp8::fp8e4m3fnuz, migraphx::half>
+{
+    using type = float;
+};
+
+template <>
+struct common_type<migraphx::half, migraphx::fp8::fp8e4m3fnuz>
+{
+    using type = float;
+};
+
 template <>
 struct common_type<migraphx::half, migraphx::half>
 {

src/include/migraphx/matcher.hpp

@@ -591,6 +591,19 @@ MIGRAPHX_PRED_MATCHER(same_input_shapes, instruction_ref ins)
         ins->inputs().begin(), ins->inputs().end(), [&](auto x) { return x->get_shape() == s; });
 }
 
+MIGRAPHX_PRED_MATCHER(has_same_value, instruction_ref ins)
+{
+    if(ins->name() != "@literal")
+        return false;
+    bool all_same = false;
+    ins->get_literal().visit([&](auto s) {
+        all_same = std::all_of(s.begin() + 1, s.end(), [&](const auto& scale) {
+            return float_equal(scale, s.front());
+        });
+    });
+    return all_same;
+}
+
 MIGRAPHX_BASIC_MATCHER(output, const matcher_context&, instruction_ref ins)
 {
     if(ins->outputs().size() == 1)
@@ -844,6 +857,12 @@ auto skip_broadcasts_converts(Ms... ms)
     return skip(name("broadcast", "multibroadcast", "contiguous", "convert"))(ms...);
 }
 
+template <class... Ms>
+auto skip_broadcasts_transposes_contiguous(Ms... ms)
+{
+    return skip(name("broadcast", "multibroadcast", "contiguous", "transpose"))(ms...);
+}
+
 template <class T>
 inline auto has_value(T x, float tolerance = 1e-6)
 {

src/include/migraphx/module.hpp

@@ -42,6 +42,7 @@
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 
+MIGRAPHX_EXPORT
 const operation& get_operation(instruction_ref ins);
 
 struct module_impl;

src/include/migraphx/onnx.hpp

@@ -48,8 +48,12 @@ struct onnx_options
     bool skip_unknown_operators = false;
     /// Print program if an error occurs
     bool print_program_on_error = false;
-    /// Max iter num for the loop operator
+    /// Max iter num for the loop operator if trip count is not set
     int64_t max_loop_iterations = 10;
+    /// Max iter limit for the loop operator.
+    /// Since loop will become a tensor of max iter size a huge number can cause overflow during
+    /// shape computations.
+    int64_t limit_max_iterations = std::numeric_limits<uint16_t>::max();
     /// Use dynamic output for operators when available
     bool use_dyn_output = false;
 };

src/include/migraphx/op/isinf.hpp

+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
+ *
+ * Permission is hereby granted, free of charge, to any person obtaining a copy
+ * of this software and associated documentation files (the "Software"), to deal
+ * in the Software without restriction, including without limitation the rights
+ * to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+ * copies of the Software, and to permit persons to whom the Software is
+ * furnished to do so, subject to the following conditions:
+ *
+ * The above copyright notice and this permission notice shall be included in
+ * all copies or substantial portions of the Software.
+ *
+ * THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+ * IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+ * FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT.  IN NO EVENT SHALL THE
+ * AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+ * LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+ * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+ * THE SOFTWARE.
+ */
+#ifndef MIGRAPHX_GUARD_OPERATORS_ISINF_HPP
+#define MIGRAPHX_GUARD_OPERATORS_ISINF_HPP
+
+#include <migraphx/op/unary.hpp>
+#include <migraphx/config.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct isinf : unary<isinf>
+{
+    auto apply() const
+    {
+        return [&](auto x) { return std::isinf(static_cast<double>(x)); };
+    }
+
+    std::string name() const { return "isinf"; }
+
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        return unary<isinf>::compute_shape(std::move(inputs)).with_type(shape::bool_type);
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/include/migraphx/op/multinomial.hpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to deal
@@ -21,11 +21,52 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
+
+/**
+ *  * Multinomial or categorical distribution.  Performs a sampling of random input
+ *         and returns a count of
+ *         each category, or bucket.  This does not require the standard multinomial
+ *         distribution but instead takes a probability distribution, i.e. cumulative
+ *         distribution function (CDF) as its first input.
+ *
+ *      Inputs:   args[0] - a tensor of probabilities for each category.  Values are
+ *                          cumulative density function
+ *                          totals as provided by operation prefix_scan_sum.  Values are
+ *                          cumulative probabilities (i.e. start with any set of numbers > 0
+ *                          and then apply prefix_scan_sum).  Values do not need to be
+ *                          normalized to sum to 1; this is done in runtime computation.
+ *
+ *                          This input has Rank 2.  Dimension 0 is batch #, so that there can be
+ *                          a different CDF for each iteration in the batch.  The size of dimension
+ *                          1 is the number of categories.
+ *
+ *                args[1] - a tensor of random numbers.  The last dimension is the sample
+ *                          size, i.e. the number of
+ *                          random samples in each iteration of the batch.  Nominally
+ *                          has two dimensions where the first dimension is batch size, but
+ *                          any reshaping such that the total
+ *                          number of elements is (batch_size * sample_size) is legal.
+ *
+ *                          Values as created by a std::mt19937 like this:
+ *
+ *                           size_t sample_size = 100000;
+ *                           float seed         = 0.0f;
+ *                           std::mt19937 gen(seed);
+ *                           std::uniform_real_distribution<> dis(0.0, 1.0);
+ *                           std::vector<float> rand_samples(sample_size);
+ *                           std::generate(rand_samples.begin(), rand_samples.end(), [&]() { return
+ *                                dis(gen); });
+ *
+ *        Output:   A 2D vector of category each input.  Dimensions are (Input 1[first], Input
+ 2[last]).
+ *
+*/
 #ifndef MIGRAPHX_GUARD_OPERATORS_MULTINOMIAL_HPP
 #define MIGRAPHX_GUARD_OPERATORS_MULTINOMIAL_HPP
 
-#include <migraphx/check_shapes.hpp>
 #include <migraphx/argument.hpp>
+#include <migraphx/check_shapes.hpp>
+#include <migraphx/dyn_output.hpp>
 #include <migraphx/par_for.hpp>
 #include <migraphx/reflect.hpp>
 #include <random>
@@ -47,22 +88,35 @@ struct multinomial
     std::string name() const { return "multinomial"; }
     shape compute_shape(std::vector<shape> inputs) const
     {
-        check_shapes{inputs, *this}.has(2).only_dims(2);
-        size_t sample_size = inputs.back().lens().back();
+        check_shapes{inputs, *this, true}.has(2).only_dims(2);
 
-        if(not contains({shape::int32_type, shape::int64_type}, dtype))
-            MIGRAPHX_THROW(
-                "Multinomial: Invalid output type. Valid types are int32_type and int64_type.");
+        if(inputs.back().ndim() < 1)
+            MIGRAPHX_THROW("Multinomial: Second input shape (sample) has no dimensions");
+        if(dtype == shape::bool_type)
+            MIGRAPHX_THROW("Multinomial: boolean output type invalid.");
 
-        return {dtype, {inputs.front().lens().front(), sample_size}};
+        // Output takes one dimension from each of the two input shapes.  If they are both fixed,
+        // return a static shape
+        if((not inputs.front().dynamic()) or (inputs.front().dyn_dims().front().is_fixed()))
+        {
+            if((not inputs.back().dynamic()) or (inputs.back().dyn_dims().back().is_fixed()))
+            {
+                size_t batch = {inputs.front().max_lens().front()};
+                size_t sample_size{inputs.back().max_lens().back()};
+                return {dtype, {batch, sample_size}};
+            }
+        }
+        return {dtype,
+                {inputs.front().to_dynamic().dyn_dims().front(),
+                 inputs.back().to_dynamic().dyn_dims().back()}};
     }
 
-    argument compute(const shape& output_shape, std::vector<argument> args) const
+    argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
     {
-        argument result{output_shape};
-        size_t batch_size  = output_shape.lens().front();
+        argument result{dyn_out.computed_shape};
+        size_t batch_size  = dyn_out.computed_shape.lens().front();
         size_t class_size  = args[0].get_shape().lens().back();
-        size_t sample_size = output_shape.lens().back();
+        size_t sample_size = dyn_out.computed_shape.lens().back();
 
         visit_all(args[0], args[1])([&](auto cdf, auto dist) {
             result.visit([&](auto output) {
@@ -70,13 +124,16 @@ struct multinomial
                     auto idx       = args[1].get_shape().multi(i);
                     auto cdf_begin = cdf.begin() + (idx[0] * class_size);
                     auto cdf_end   = cdf_begin + class_size;
+
+                    // std::upper_bound returns an iterator to the bucket the value belongs in,
+                    // when normalized by the probability distribution dist
                     auto sample_iter =
                         std::upper_bound(cdf_begin, cdf_end, dist[i] * *(std::prev(cdf_end)));
+                    // convert iterator to an integer index
                     output[i] = std::distance(cdf_begin, sample_iter);
                 });
             });
         });
-
         return result;
     }
 };

src/include/migraphx/op/round.hpp → src/include/migraphx/op/nearbyint.hpp

 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
  *
  * Permission is hereby granted, free of charge, to any person obtaining a copy
  * of this software and associated documentation files (the "Software"), to deal
@@ -21,24 +21,28 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#ifndef MIGRAPHX_GUARD_OPERATORS_ROUND_HPP
-#define MIGRAPHX_GUARD_OPERATORS_ROUND_HPP
+#ifndef MIGRAPHX_GUARD_OPERATORS_NEARBYINT_HPP
+#define MIGRAPHX_GUARD_OPERATORS_NEARBYINT_HPP
 
 #include <migraphx/op/unary.hpp>
 #include <migraphx/config.hpp>
+#include <fenv.h>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace op {
-
-struct round : unary<round>
+struct nearbyint : unary<nearbyint>
 {
     auto apply() const
     {
-        return [](auto x) { return std::round(x); };
+        return [](auto x) {
+            auto rounding_mode = fegetround();
+            fesetround(FE_TONEAREST);
+            return std::nearbyint(x);
+            fesetround(rounding_mode);
+        };
     }
 };
-
 } // namespace op
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/include/migraphx/op/normalize_attribute.hpp

@@ -40,6 +40,8 @@ namespace op {
  * 2. use_rank (default) vs use_len:
  *  `use_rank` sets the max value/index of the attribute as the rank of lens.
  *  `use_lens` sets the max value/index as the corresponding value in lens at the axes index.
+ *      Uses the dynamic_dimension.max value for dynamic shapes. Returns the original vector
+ *      (no normalization) if any of dynamic_dimension[axes] are not fixed.
  * 3. `clip_min` vs. `not_clip_min` (default):
  *  Clip values less than the minimum to the minimum or not.
  * 4. `include_min` vs. `exclude_min` (default):

src/include/migraphx/op/prefix_scan_op.hpp

@@ -22,6 +22,12 @@
  * THE SOFTWARE.
  */
 
+/**
+ * Parent struct for prefix scan ops.  A prefix scan is a mathematical entity useful
+ * in parallelizing various computations.  Given a list of numbers, a prefix scan
+ * op returns an equal size list of running totals of the values.  Other operations
+ * besides addition can be supported by child ops.
+ */
 #ifndef MIGRAPHX_GUARD_OPERATORS_SCAN_OP_HPP
 #define MIGRAPHX_GUARD_OPERATORS_SCAN_OP_HPP
 

src/include/migraphx/op/quantizelinear.hpp

@@ -30,11 +30,11 @@
 #include <migraphx/par_for.hpp>
 #include <migraphx/value.hpp>
 #include <cmath>
+#include <fenv.h>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace op {
-
 struct quantizelinear
 {
     std::string name() const { return "quantizelinear"; }
@@ -71,26 +71,26 @@ struct quantizelinear
         {
             y_zero_point = args.at(2);
         }
-
         argument result{output_shape};
+        auto rounding_mode = fegetround();
+        fesetround(FE_TONEAREST);
         visit_all(result, y_zero_point)([&](auto output, auto zero_pts) {
             visit_all(x, y_scale)([&](auto input, auto scales) {
                 using quant_type = typename decltype(output)::value_type;
                 auto min_value   = std::numeric_limits<quant_type>::min();
                 auto max_value   = std::numeric_limits<quant_type>::max();
                 par_for(output_shape.elements(), [&](auto i) {
-                    int64_t quantized = static_cast<int64_t>(std::round(input[i] / scales[i])) +
+                    int64_t quantized = static_cast<int64_t>(std::nearbyint(input[i] / scales[i])) +
                                         static_cast<int64_t>(zero_pts[i]);
                     output[i] = std::max(static_cast<int64_t>(min_value),
                                          std::min(static_cast<int64_t>(max_value), quantized));
                 });
             });
         });
-
+        fesetround(rounding_mode);
         return result;
     }
 };
-
 } // namespace op
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx

src/include/migraphx/op/random_uniform.hpp

@@ -65,11 +65,10 @@ struct random_uniform
         return inputs.at(1);
     }
 
-    argument compute(const shape&, std::vector<argument> args) const
+    argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
     {
         // Output goes into the passed buffer, not the shape output.
-        auto result = args[1];
-
+        argument result{dyn_out.computed_shape};
         uint64_t local_seed = args[0].at<uint64_t>(0);
         std::mt19937 gen(local_seed);