Refactor dynamic compute; Dynamic ref unary functions (#1407)

Refactor dynamic compute
- add a compute_output_shape object that implicitly converts to a new dyn_output or shape object
- dyn_output object can handle computing the static output shape of an operator given the input arguments shapes
  change an operator's compute function to argument compute(const dyn_output& dyn_out, std::vector<argument> args) to 
  use dyn_output object

Dynamic ref unary functions
-  Included these changes to have an example of the refactored dynamic compute being used
-  Changes to unary base class to handle dynamic shapes
-  Changed elu and leaky_relu to use unary base class and pointwise JIT

src/include/migraphx/argument.hpp

@@ -107,6 +107,7 @@ struct argument : raw_data<argument>
     data_t m_data{};
 };
 
+std::vector<shape> to_shapes(const std::vector<argument>& args);
 void migraphx_to_value(value& v, const argument& a);
 void migraphx_from_value(const value& v, argument& a);
 

src/targets/gpu/include/migraphx/gpu/elu.hpp → src/include/migraphx/dyn_output.hpp

@@ -21,44 +21,55 @@
  * OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
  * THE SOFTWARE.
  */
-#ifndef MIGRAPHX_GUARD_RTGLIB_ELU_HPP
-#define MIGRAPHX_GUARD_RTGLIB_ELU_HPP
+#ifndef MIGRAPHX_GUARD_MIGRAPHLIB_DYN_OUTPUT_HPP
+#define MIGRAPHX_GUARD_MIGRAPHLIB_DYN_OUTPUT_HPP
 
-#include <migraphx/op/elu.hpp>
 #include <migraphx/shape.hpp>
-#include <migraphx/reflect.hpp>
-#include <migraphx/gpu/miopen.hpp>
+#include <migraphx/argument.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
 
-struct context;
+struct dyn_output
+{
+    // original shape from the instruction
+    shape ins_shape;
+    // shape computed at eval time using input arguments
+    shape computed_shape;
+};
 
-struct miopen_elu
+/**
+ * Handle dynamic and static shape at evaluation time.
+ * If converted to shape type, returns original ins_shape.
+ * If converted to dyn_output type, will compute an output shape using the input arguments.
+ */
+template <class F>
+struct compute_output_shape
 {
-    op::elu op;
-    shared<activation_descriptor> ad;
+    F ins_inputs;
 
-    template <class Self, class F>
-    static auto reflect(Self& self, F f)
+    operator dyn_output() const
     {
-        return migraphx::reflect(self.op, f);
+        return ins_inputs([](const auto& x, shape ins_shape, const std::vector<argument>& inputs) {
+            if(ins_shape.dynamic())
+                return dyn_output{ins_shape, compute_shape(x, to_shapes(inputs))};
+            return dyn_output{ins_shape, ins_shape};
+        });
     }
 
-    std::string name() const { return "gpu::elu"; }
-    shape compute_shape(const std::vector<shape>& inputs) const;
-    argument
-    compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
-    void finalize(context&, const shape&, const std::vector<shape>&);
-    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
+    operator shape() const
     {
-        return shapes.size() - 1;
+        return ins_inputs(
+            [](const auto&, shape ins_shape, const std::vector<argument>&) { return ins_shape; });
     }
 };
 
-} // namespace gpu
+template <class F>
+compute_output_shape<F> make_compute_output_shape(F f)
+{
+    return {f};
+}
+
 } // namespace MIGRAPHX_INLINE_NS
 } // namespace migraphx
-
 #endif

src/include/migraphx/op/convert.hpp

@@ -44,7 +44,7 @@ struct convert : unary<convert>
 
     shape compute_shape(std::vector<shape> inputs) const
     {
-        check_shapes{inputs, *this}.has(1);
+        check_shapes{inputs, *this, true}.has(1);
         auto input = inputs.at(0);
         if(input.dynamic())
         {

src/include/migraphx/op/elu.hpp

@@ -32,14 +32,13 @@ namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace op {
 
-struct elu
+struct elu : unary<elu>
 {
-    std::string name() const { return "elu"; }
     float alpha = 1;
-    shape compute_shape(std::vector<shape> inputs) const
+
+    std::string point_op() const
     {
-        check_shapes{inputs, *this}.has(1);
-        return inputs.front();
+        return "${function:where}(${0} > 0, ${0}, ${alpha} * (${function:exp}(${0}) - 1))";
     }
 
     template <class Self, class F>
@@ -47,6 +46,11 @@ struct elu
     {
         return pack(f(self.alpha, "alpha"));
     }
+
+    auto apply() const
+    {
+        return [&](auto x) { return x > 0 ? x : alpha * std::expm1(x); };
+    }
 };
 
 } // namespace op

src/include/migraphx/op/leaky_relu.hpp

@@ -26,12 +26,13 @@
 
 #include <migraphx/check_shapes.hpp>
 #include <migraphx/config.hpp>
+#include <migraphx/op/unary.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 namespace op {
 
-struct leaky_relu
+struct leaky_relu : unary<leaky_relu>
 {
     float alpha = 0.01;
 
@@ -41,11 +42,13 @@ struct leaky_relu
         return pack(f(self.alpha, "alpha"));
     }
 
+    std::string point_op() const { return "${function:where}(${0} > 0, ${0}, ${alpha} * ${0})"; }
+
     std::string name() const { return "leaky_relu"; }
-    shape compute_shape(std::vector<shape> inputs) const
+
+    auto apply() const
     {
-        check_shapes{inputs, *this}.has(1);
-        return inputs.front();
+        return [&](auto x) { return x > 0 ? x : x * alpha; };
     }
 };
 

src/include/migraphx/op/unary.hpp

@@ -30,6 +30,7 @@
 #include <migraphx/argument.hpp>
 #include <migraphx/stringutils.hpp>
 #include <migraphx/value.hpp>
+#include <migraphx/dyn_output.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -62,9 +63,9 @@ struct unary : op_name<Derived>
     value attributes() const { return base_attributes(); }
     shape compute_shape(std::vector<shape> inputs) const
     {
-        check_shapes{inputs, static_cast<const Derived&>(*this)}.has(1);
+        check_shapes{inputs, static_cast<const Derived&>(*this), true}.has(1);
         auto s = inputs.at(0);
-        if(s.scalar())
+        if(s.dynamic() or s.scalar())
         {
             return s;
         }
@@ -78,9 +79,9 @@ struct unary : op_name<Derived>
         }
     }
 
-    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};
+        argument result{dyn_out.computed_shape};
         result.visit([&](auto output) {
             args[0].visit([&](auto input) {
                 std::transform(input.begin(),

src/include/migraphx/operation.hpp

@@ -32,6 +32,8 @@
 #include <utility>
 #include <unordered_map>
 #include <migraphx/reflect.hpp>
+#include <migraphx/dyn_output.hpp>
+#include <migraphx/functional.hpp>
 #include <migraphx/streamutils.hpp>
 #include <migraphx/normalize_attributes.hpp>
 #include <migraphx/argument.hpp>
@@ -199,9 +201,12 @@ auto compute_op(rank<1>,
                 context& ctx,
                 const shape& output_shape,
                 const std::vector<argument>& input)
-    -> decltype(x.compute(auto_any_cast(ctx), output_shape, input))
+    -> decltype(x.compute(auto_any_cast(ctx),
+                          make_compute_output_shape(pack(x, output_shape, input)),
+                          input))
 {
-    return x.compute(auto_any_cast(ctx), output_shape, input);
+    return x.compute(
+        auto_any_cast(ctx), make_compute_output_shape(pack(x, output_shape, input)), input);
 }
 
 template <class T>
@@ -220,9 +225,9 @@ compute_op(const T& x, context& ctx, const shape& output_shape, const std::vecto
 
 template <class T>
 auto compute_op(rank<1>, const T& x, const shape& output_shape, const std::vector<argument>& input)
-    -> decltype(x.compute(output_shape, input))
+    -> decltype(x.compute(make_compute_output_shape(pack(x, output_shape, input)), input))
 {
-    return x.compute(output_shape, input);
+    return x.compute(make_compute_output_shape(pack(x, output_shape, input)), input);
 }
 
 template <class T>
@@ -244,9 +249,11 @@ auto compute_op(rank<1>,
                 const shape& output,
                 const std::vector<argument>& inputs,
                 const std::vector<module_ref>& module_args,
-                F f) -> decltype(x.compute(output, inputs, module_args, f))
+                F f)
+    -> decltype(
+        x.compute(make_compute_output_shape(pack(x, output, inputs)), inputs, module_args, f))
 {
-    return x.compute(output, inputs, module_args, f);
+    return x.compute(make_compute_output_shape(pack(x, output, inputs)), inputs, module_args, f);
 }
 
 template <class T, class F>
@@ -278,9 +285,17 @@ auto compute_op(rank<4>,
                 const shape& output,
                 const std::vector<argument>& inputs,
                 const std::vector<module_ref>& module_args,
-                F f) -> decltype(x.compute(auto_any_cast(ctx), output, inputs, module_args, f))
+                F f) -> decltype(x.compute(auto_any_cast(ctx),
+                                           make_compute_output_shape(pack(x, output, inputs)),
+                                           inputs,
+                                           module_args,
+                                           f))
 {
-    return x.compute(auto_any_cast(ctx), output, inputs, module_args, f);
+    return x.compute(auto_any_cast(ctx),
+                     make_compute_output_shape(pack(x, output, inputs)),
+                     inputs,
+                     module_args,
+                     f);
 }
 
 template <class T, class F>
@@ -290,9 +305,11 @@ auto compute_op(rank<3>,
                 const shape& output,
                 const std::vector<argument>& inputs,
                 const std::vector<module_ref>& module_args,
-                F f) -> decltype(x.compute(output, inputs, module_args, f))
+                F f)
+    -> decltype(
+        x.compute(make_compute_output_shape(pack(x, output, inputs)), inputs, module_args, f))
 {
-    return x.compute(output, inputs, module_args, f);
+    return x.compute(make_compute_output_shape(pack(x, output, inputs)), inputs, module_args, f);
 }
 
 template <class T, class F>
@@ -302,9 +319,10 @@ auto compute_op(rank<2>,
                 const shape& output,
                 const std::vector<argument>& inputs,
                 const std::vector<module_ref>&,
-                F) -> decltype(x.compute(output, inputs))
+                F)
+    -> decltype(x.compute(make_compute_output_shape(pack(x, output, inputs)), inputs))
 {
-    return x.compute(output, inputs);
+    return x.compute(make_compute_output_shape(pack(x, output, inputs)), inputs);
 }
 
 template <class T, class F>
@@ -314,9 +332,12 @@ auto compute_op(rank<1>,
                 const shape& output,
                 const std::vector<argument>& inputs,
                 const std::vector<module_ref>&,
-                F) -> decltype(x.compute(auto_any_cast(ctx), output, inputs))
+                F) -> decltype(x.compute(auto_any_cast(ctx),
+                                         make_compute_output_shape(pack(x, output, inputs)),
+                                         inputs))
 {
-    return x.compute(auto_any_cast(ctx), output, inputs);
+    return x.compute(
+        auto_any_cast(ctx), make_compute_output_shape(pack(x, output, inputs)), inputs);
 }
 
 template <class T, class F>
@@ -348,7 +369,8 @@ 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{});
+    -> decltype(x.compute(make_compute_output_shape(pack(x, output_shape, input)), input),
+                std::true_type{});
 
 template <class T>
 auto is_context_free_op(rank<0>, const T&, const shape&, const std::vector<argument>&)

src/targets/cpu/lowering.cpp

@@ -215,55 +215,6 @@ struct cpu_pad
 };
 MIGRAPHX_REGISTER_OP(cpu_pad)
 
-struct leaky_relu_op
-{
-    op::leaky_relu op;
-    std::string name() const { return "cpu::leaky_relu"; }
-    auto fcn() const
-    {
-        auto a = op.alpha;
-        return [a](auto x) { return x > 0 ? x : x * a; };
-    }
-};
-
-template <typename Op>
-struct cpu_unary2 : auto_register_op<cpu_unary2<Op>>
-{
-    cpu_unary2() = default;
-
-    template <class T>
-    cpu_unary2(T pop) : op(Op{std::move(pop)})
-    {
-    }
-
-    Op op;
-
-    template <class Self, class F>
-    static auto reflect(Self& self, F f)
-    {
-        return migraphx::reflect(self.op.op, f);
-    }
-    std::string name() const { return op.name(); }
-    shape compute_shape(const std::vector<shape>& inputs) const
-    {
-        check_shapes{inputs, *this}.has(1);
-        const auto& s = inputs.at(0);
-        return {s.type(), s.lens()};
-    }
-
-    argument compute(context&, const shape& output_shape, std::vector<argument> args) const
-    {
-        argument result{output_shape};
-        visit_all(result, args[0])([&](auto output, auto input) {
-            assert(input.get_shape().standard());
-            std::transform(input.begin(), input.end(), output.begin(), op.fcn());
-        });
-
-        return result;
-    }
-};
-template struct cpu_unary2<leaky_relu_op>;
-
 struct cpu_rnn_var_sl_last_output
 {
     op::rnn_var_sl_last_output op;

src/targets/gpu/CMakeLists.txt

@@ -85,7 +85,6 @@ add_library(migraphx_gpu
     compile_hip_code_object.cpp
     compiler.cpp
     device_name.cpp
-    elu.cpp
     fuse_mlir.cpp
     fuse_ops.cpp
     gather.cpp
@@ -98,7 +97,6 @@ add_library(migraphx_gpu
     logsoftmax.cpp
     loop.cpp
     lrn.cpp
-    leaky_relu.cpp
     mlir.cpp
     multinomial.cpp
     nonzero.cpp
@@ -143,9 +141,7 @@ register_migraphx_gpu_ops(hip_
 register_migraphx_gpu_ops(miopen_
     abs
     contiguous
-    elu
     int8_conv_pack
-    leaky_relu
     lrn
     pooling
 )

src/targets/gpu/elu.cpp

-/*
- * The MIT License (MIT)
- *
- * Copyright (c) 2015-2022 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.
- */
-#include <migraphx/gpu/elu.hpp>
-#include <migraphx/gpu/context.hpp>
-
-namespace migraphx {
-inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
-
-shape miopen_elu::compute_shape(const std::vector<shape>& inputs) const
-{
-    check_shapes{inputs, *this}.has(2).not_broadcasted();
-    return inputs.at(1);
-}
-
-argument miopen_elu::compute(context& ctx,
-                             const shape& output_shape,
-                             const std::vector<argument>& args) const
-{
-    float alpha = 1;
-    float beta  = 0;
-    auto x_desc = make_tensor(args[0].get_shape());
-    auto y_desc = make_tensor(output_shape);
-    miopenActivationForward(ctx.get_stream().get_miopen(),
-                            ad.get(),
-                            &alpha,
-                            x_desc.get(),
-                            args[0].implicit(),
-                            &beta,
-                            y_desc.get(),
-                            args[1].implicit());
-
-    return args[1];
-}
-
-void miopen_elu::finalize(context&, const shape&, const std::vector<shape>&)
-{
-    ad = make_elu(op.alpha);
-}
-
-} // namespace gpu
-} // namespace MIGRAPHX_INLINE_NS
-} // namespace migraphx

src/targets/gpu/include/migraphx/gpu/leaky_relu.hpp

-/*
- * The MIT License (MIT)
- *
- * Copyright (c) 2015-2022 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_RTGLIB_LEAKY_RELU_HPP
-#define MIGRAPHX_GUARD_RTGLIB_LEAKY_RELU_HPP
-
-#include <migraphx/op/leaky_relu.hpp>
-#include <migraphx/shape.hpp>
-#include <migraphx/reflect.hpp>
-#include <migraphx/gpu/miopen.hpp>
-
-namespace migraphx {
-inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
-
-struct context;
-
-struct miopen_leaky_relu
-{
-    op::leaky_relu op;
-    shared<activation_descriptor> ad;
-
-    template <class Self, class F>
-    static auto reflect(Self& self, F f)
-    {
-        return migraphx::reflect(self.op, f);
-    }
-
-    std::string name() const { return "gpu::leaky_relu"; }
-    shape compute_shape(const std::vector<shape>& inputs) const;
-    argument
-    compute(context& ctx, const shape& output_shape, const std::vector<argument>& args) const;
-    void finalize(context&, const shape&, const std::vector<shape>&);
-    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
-    {
-        return shapes.size() - 1;
-    }
-};
-
-} // namespace gpu
-} // namespace MIGRAPHX_INLINE_NS
-} // namespace migraphx
-
-#endif

src/targets/gpu/jit/scatternd.cpp

@@ -79,9 +79,10 @@ struct scatternd_compiler : compiler<scatternd_compiler>
     {
         assert(starts_with(op.name(), "scatternd_"));
         auto reduction = op.name().substr(10);
-        return insert(compile_op(ctx,
-                                 to_shapes({ins->inputs().begin() + 1, ins->inputs().end()}),
-                                 {{"reduction", reduction}}));
+        return insert(compile_op(
+            ctx,
+            to_shapes(std::vector<instruction_ref>{ins->inputs().begin() + 1, ins->inputs().end()}),
+            {{"reduction", reduction}}));
     }
 
     compiler_replace insert(const operation& op) const

src/targets/gpu/leaky_relu.cpp

-/*
- * The MIT License (MIT)
- *
- * Copyright (c) 2015-2022 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.
- */
-#include <migraphx/gpu/leaky_relu.hpp>
-#include <migraphx/gpu/context.hpp>
-#include <migraphx/gpu/miopen.hpp>
-
-namespace migraphx {
-inline namespace MIGRAPHX_INLINE_NS {
-namespace gpu {
-
-shape miopen_leaky_relu::compute_shape(const std::vector<shape>& inputs) const
-{
-    check_shapes{inputs, *this}.has(2).not_broadcasted();
-    return inputs.at(1);
-}
-
-argument miopen_leaky_relu::compute(context& ctx,
-                                    const shape& output_shape,
-                                    const std::vector<argument>& args) const
-{
-    float alpha = 1;
-    float beta  = 0;
-    auto x_desc = make_tensor(args[0].get_shape());
-    auto y_desc = make_tensor(output_shape);
-    miopenActivationForward(ctx.get_stream().get_miopen(),
-                            ad.get(),
-                            &alpha,
-                            x_desc.get(),
-                            args[0].implicit(),
-                            &beta,
-                            y_desc.get(),
-                            args[1].implicit());
-
-    return args[1];
-}
-
-void miopen_leaky_relu::finalize(context&, const shape&, const std::vector<shape>&)
-{
-    ad = make_leaky_relu(op.alpha);
-}
-
-} // namespace gpu
-} // namespace MIGRAPHX_INLINE_NS
-} // namespace migraphx

src/targets/gpu/lowering.cpp

@@ -95,9 +95,7 @@ struct miopen_apply
 
         add_extend_op("argmax");
         add_extend_op("argmin");
-        add_extend_op("elu");
         add_extend_op("gather");
-        add_extend_op("leaky_relu");
         add_extend_op("logsoftmax");
         add_extend_op("lrn");
         add_extend_op("multinomial");

src/targets/ref/lowering.cpp

@@ -31,9 +31,7 @@
 #include <migraphx/op/quant_convolution.hpp>
 #include <migraphx/op/dot.hpp>
 #include <migraphx/op/quant_dot.hpp>
-#include <migraphx/op/elu.hpp>
 #include <migraphx/op/im2col.hpp>
-#include <migraphx/op/leaky_relu.hpp>
 #include <migraphx/op/logsoftmax.hpp>
 #include <migraphx/op/loop.hpp>
 #include <migraphx/op/lrn.hpp>
@@ -431,65 +429,6 @@ struct ref_quant_gemm
 };
 MIGRAPHX_REGISTER_OP(ref_gemm)
 
-struct leaky_relu_op
-{
-    op::leaky_relu op;
-    std::string name() const { return "ref::leaky_relu"; }
-    auto fcn() const
-    {
-        auto a = op.alpha;
-        return [a](auto x) { return x > 0 ? x : x * a; };
-    }
-};
-
-struct elu_op
-{
-    op::elu op;
-    std::string name() const { return "ref::elu"; }
-    auto fcn() const
-    {
-        auto a = op.alpha;
-        return [a](auto x) { return x > 0 ? x : a * std::expm1(x); };
-    }
-};
-
-template <typename Op>
-struct ref_unary : auto_register_op<ref_unary<Op>>
-{
-    ref_unary() = default;
-
-    template <class T>
-    ref_unary(T pop) : op(Op{std::move(pop)})
-    {
-    }
-
-    Op op;
-
-    template <class Self, class F>
-    static auto reflect(Self& self, F f)
-    {
-        return migraphx::reflect(self.op.op, f);
-    }
-    std::string name() const { return op.name(); }
-    shape compute_shape(const std::vector<shape>& inputs) const
-    {
-        check_shapes{inputs, *this}.has(1);
-        const auto& s = inputs.at(0);
-        return {s.type(), s.lens()};
-    }
-
-    argument compute(context&, const shape& output_shape, std::vector<argument> args) const
-    {
-        argument result{output_shape};
-        visit_all(result, args[0])([&](auto output, auto input) {
-            assert(input.get_shape().standard());
-            std::transform(input.begin(), input.end(), output.begin(), op.fcn());
-        });
-
-        return result;
-    }
-};
-
 template <class Op>
 struct ref_softmax : auto_register_op<ref_softmax<Op>>
 {
@@ -630,9 +569,7 @@ struct ref_apply
         apply_map["quant_dot"]   = extend_op<ref_quant_gemm, op::quant_dot>();
         apply_map["quant_convolution"] =
             extend_op<ref_convolution<op::quant_convolution>, op::quant_convolution>();
-        apply_map["elu"]        = extend_op<ref_unary<elu_op>, op::elu>();
         apply_map["im2col"]     = extend_op<ref_im2col, op::im2col>();
-        apply_map["leaky_relu"] = extend_op<ref_unary<leaky_relu_op>, op::leaky_relu>();
         apply_map["logsoftmax"] = extend_op<ref_softmax<op::logsoftmax>, op::logsoftmax>();
         apply_map["lrn"]        = extend_op<ref_lrn, op::lrn>();
         apply_map["pad"]        = extend_op<ref_pad, op::pad>();

test/onnx/gen_onnx.py

@@ -3648,6 +3648,16 @@ def neg_test():
     return ([node], [x], [y])
 
 
+@onnx_test
+def neg_dynamic_test():
+    x = helper.make_tensor_value_info('0', TensorProto.INT64, [None, 3])
+    y = helper.make_tensor_value_info('1', TensorProto.INT64, [None, 3])
+
+    node = onnx.helper.make_node('Neg', inputs=['0'], outputs=['1'])
+
+    return ([node], [x], [y])
+
+
 @onnx_test
 def nms_test():
     b = helper.make_tensor_value_info('boxes', TensorProto.FLOAT, [1, 6, 4])
@@ -5281,6 +5291,20 @@ def sinh_test():
     return ([node], [x], [y])
 
 
+@onnx_test
+def sinh_dynamic_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [None])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [None])
+
+    node = onnx.helper.make_node(
+        'Sinh',
+        inputs=['x'],
+        outputs=['y'],
+    )
+
+    return ([node], [x], [y])
+
+
 @onnx_test
 def size_float_test():
     x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [2, 3, 4])

test/onnx/onnx_test.cpp

@@ -3501,6 +3501,21 @@ TEST_CASE(neg_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(neg_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::int64_type, {{1, 10, 0}, {3, 3, 0}}};
+    auto input = mm->add_parameter("0", s);
+    auto ret   = mm->add_instruction(migraphx::make_op("neg"), input);
+    mm->add_return({ret});
+
+    migraphx::onnx_options options;
+    options.default_dyn_dim_value = {1, 10, 0};
+    auto prog                     = migraphx::parse_onnx("neg_dynamic_test.onnx", options);
+    EXPECT(p == prog);
+}
+
 TEST_CASE(nms_test)
 {
     migraphx::program p;
@@ -5224,6 +5239,24 @@ TEST_CASE(sinh_test)
     EXPECT(p == prog);
 }
 
+TEST_CASE(sinh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{1, 10, 0};
+    std::vector<migraphx::shape::dynamic_dimension> dyn_dims;
+    dyn_dims.push_back(dd);
+    auto input = mm->add_parameter("x", migraphx::shape{migraphx::shape::float_type, dyn_dims});
+    auto ret   = mm->add_instruction(migraphx::make_op("sinh"), input);
+    mm->add_return({ret});
+
+    migraphx::onnx_options options;
+    options.default_dyn_dim_value = dd;
+    auto prog                     = parse_onnx("sinh_dynamic_test.onnx", options);
+
+    EXPECT(p == prog);
+}
+
 TEST_CASE(size_float_test)
 {
     migraphx::program p;

test/ref_ops_test.cpp

@@ -61,6 +61,25 @@ TEST_CASE(abs_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(abs_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm             = p.get_main_module();
+    std::vector<float> a = {-1, 2, -3, 4};
+    migraphx::shape s{migraphx::shape::float_type, {{2, 8, 0}, {2, 2, 0}}};
+    auto input = mm->add_parameter("X", s);
+    mm->add_instruction(migraphx::make_op("abs"), input);
+    p.compile(migraphx::ref::target{});
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {2, 2}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, a.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold{1, 2, 3, 4};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(acos_test)
 {
     migraphx::program p;
@@ -79,6 +98,29 @@ TEST_CASE(acos_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(acos_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-0.8f, 0.0f, 1.0f};
+    mm->add_instruction(migraphx::make_op("acos"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return acosf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(acosh_test)
 {
     migraphx::program p;
@@ -97,6 +139,29 @@ TEST_CASE(acosh_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(acosh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{1.1f, 1.2f, 2.0f};
+    mm->add_instruction(migraphx::make_op("acosh"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return acoshf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(add_broadcast_test)
 {
     {
@@ -331,6 +396,29 @@ TEST_CASE(asin_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(asin_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-0.5f, 0.0f, 0.9f};
+    mm->add_instruction(migraphx::make_op("asin"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return asinf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(asinh_test)
 {
     migraphx::program p;
@@ -349,6 +437,29 @@ TEST_CASE(asinh_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(asinh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-0.5f, 0.0f, 0.9f};
+    mm->add_instruction(migraphx::make_op("asinh"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return asinhf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(atan_test)
 {
     migraphx::program p;
@@ -367,6 +478,29 @@ TEST_CASE(atan_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(atan_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1.0f, 0.0f, 1.0f};
+    mm->add_instruction(migraphx::make_op("atan"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return atanf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(atanh_test)
 {
     migraphx::program p;
@@ -385,6 +519,29 @@ TEST_CASE(atanh_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(atanh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{0.4435683f, 0.6223626f, 0.316958f};
+    mm->add_instruction(migraphx::make_op("atanh"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return atanhf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(avgpool_test)
 {
     // 1D case 1, input is 3D
@@ -532,6 +689,29 @@ TEST_CASE(ceil_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(ceil_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{4, 12, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input                    = mm->add_parameter("X", s);
+    std::vector<float> input_data = {1.1, 1.5, 1.6, -1.1, -1.5, -1.6, 0.0, 2.0, -2.0};
+    mm->add_instruction(migraphx::make_op("ceil"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {9}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return std::ceil(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(clip_test)
 {
     migraphx::program p;
@@ -1449,6 +1629,29 @@ TEST_CASE(cos_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(cos_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1, 0, 1};
+    mm->add_instruction(migraphx::make_op("cos"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return cosf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(cosh_test)
 {
     migraphx::program p;
@@ -1467,6 +1670,29 @@ TEST_CASE(cosh_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(cosh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input                    = mm->add_parameter("X", s);
+    std::vector<float> input_data = {-1.0, 2.0, -3.0, 4.0};
+    mm->add_instruction(migraphx::make_op("cosh"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {4}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return coshf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(deconv_1d_test)
 {
     migraphx::shape s{migraphx::shape::float_type, {1, 1, 3}};
@@ -1651,6 +1877,28 @@ TEST_CASE(elu_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(elu_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1.0, 2.0, -3.0, 4.0};
+    float alpha = 0.5;
+    mm->add_instruction(migraphx::make_op("elu", {{"alpha", alpha}}), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {4}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold{elu(alpha, -1), elu(alpha, 2), elu(alpha, -3), elu(alpha, 4)};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(equal_brcst_test)
 {
     migraphx::program p;
@@ -1718,6 +1966,29 @@ TEST_CASE(erf_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(erf_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input                    = mm->add_parameter("X", s);
+    std::vector<float> input_data = {0.73785057, 1.58165966, -0.43597795, -0.01677432};
+    mm->add_instruction(migraphx::make_op("erf"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {4}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return erff(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(exp_test)
 {
     migraphx::program p;
@@ -1736,6 +2007,29 @@ TEST_CASE(exp_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(exp_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1, 0, 1};
+    mm->add_instruction(migraphx::make_op("exp"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return expf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(floor_test)
 {
     migraphx::program p;
@@ -1754,6 +2048,29 @@ TEST_CASE(floor_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(floor_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{5, 12, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input                    = mm->add_parameter("X", s);
+    std::vector<float> input_data = {1.1, 1.5, 0.6, -1.1, -1.5, -0.6, 0.0, 2.0, -2.0};
+    mm->add_instruction(migraphx::make_op("floor"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {9}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return floor(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(fp16_test)
 {
     migraphx::program p;
@@ -2306,6 +2623,25 @@ TEST_CASE(identity_test)
     EXPECT(std::equal(data.begin(), data.end(), results_vector.begin()));
 }
 
+TEST_CASE(identity_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::float_type, {{2, 4, 0}, {2, 4, 0}}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<int> input_data{1, 2, 3, 4};
+    mm->add_instruction(migraphx::make_op("identity"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::int32_type, {2, 2}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<int> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    EXPECT(std::equal(input_data.begin(), input_data.end(), results_vector.begin()));
+}
+
 TEST_CASE(if_literal_test)
 {
     auto create_program = [] {
@@ -2533,6 +2869,27 @@ TEST_CASE(isnan_test)
     }
 }
 
+TEST_CASE(isnan_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::float_type, {{2, 2, 0}, {3, 8, 0}}};
+    auto input                    = mm->add_parameter("X", s);
+    auto nan_val                  = std::numeric_limits<float>::quiet_NaN();
+    std::vector<float> input_data = {1.2, 5.2, nan_val, nan_val, 0., 100.};
+    mm->add_instruction(migraphx::make_op("isnan"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {2, 3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> correct = {0, 0, 1, 1, 0, 0};
+    EXPECT(migraphx::verify_range(results_vector, correct));
+}
+
 TEST_CASE(im2col_3x3_no_pad_identity_test)
 {
     std::size_t f[2]    = {3, 3};
@@ -2849,6 +3206,29 @@ TEST_CASE(log_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(log_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input                    = mm->add_parameter("X", s);
+    std::vector<float> input_data = {1, 2, 3};
+    mm->add_instruction(migraphx::make_op("log"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return logf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(logical_and_test)
 {
     migraphx::program p;
@@ -3499,6 +3879,27 @@ TEST_CASE(neg_test)
     EXPECT(migraphx::verify_range(result_vector, gold));
 }
 
+TEST_CASE(neg_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::float_type, {{2, 4, 0}, {3, 3, 0}}};
+    std::vector<float> a = {1.0f, 1.3f, -1.2f, 0.0f, -100.f, 200.f};
+    auto input           = mm->add_parameter("X", s);
+    auto ret             = mm->add_instruction(migraphx::make_op("neg"), input);
+    mm->add_return({ret});
+    p.compile(migraphx::ref::target{});
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {2, 3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, a.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> result_vector;
+    result.visit([&](auto output) { result_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = a;
+    std::transform(gold.begin(), gold.end(), gold.begin(), std::negate<float>());
+    EXPECT(migraphx::verify_range(result_vector, gold));
+}
+
 TEST_CASE(nms_dynamic_out_test)
 {
     migraphx::program p;
@@ -3869,6 +4270,27 @@ TEST_CASE(not_test)
     }
 }
 
+TEST_CASE(not_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{0, 8, 1, -32};
+    mm->add_instruction(migraphx::make_op("not"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {4}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<char> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<char> gold{1, 0, 0, 0};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(pad_test)
 {
     migraphx::program p;
@@ -4519,6 +4941,27 @@ TEST_CASE(recip_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(recip_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-0.5f, 0.1f, 0.5f};
+    mm->add_instruction(migraphx::make_op("recip"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {-2.0f, 10.0f, 2.0f};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(reduce_max_axis0)
 {
     migraphx::program p;
@@ -4806,6 +5249,27 @@ TEST_CASE(relu_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(relu_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1.f, 0.f, 1.f};
+    mm->add_instruction(migraphx::make_op("relu"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {0.f, 0.f, 1.f};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(reshape_test)
 {
     migraphx::shape a_shape{migraphx::shape::float_type, {24, 1, 1, 1}};
@@ -5090,6 +5554,27 @@ TEST_CASE(round_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(round_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{4, 10, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{1.1, 1.5, 1.6, -1.1, -1.5, -1.6, 0.0, 2.0, -2.0};
+    mm->add_instruction(migraphx::make_op("round"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {9}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {1.0, 2.0, 2.0, -1.0, -2.0, -2.0, 0.0, 2.0, -2.0};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(rsqrt_test)
 {
     migraphx::program p;
@@ -5105,6 +5590,27 @@ TEST_CASE(rsqrt_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(rsqrt_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{4.0, 16.0, 64.0};
+    mm->add_instruction(migraphx::make_op("rsqrt"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {0.5, 0.25, 0.125};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 // reduction_mode: "scatter_none", "scatter_add", "scatter_mul"
 migraphx::program create_scatter_program(const std::string& reduction_mode, int axis)
 {
@@ -5653,6 +6159,26 @@ TEST_CASE(sigmoid_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(sigmoid_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::float_type, {{2, 4, 0}, {2, 2, 0}}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1, 2, -3, 4};
+    mm->add_instruction(migraphx::make_op("sigmoid"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {2, 2}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold{sigmoid(-1), sigmoid(2), sigmoid(-3), sigmoid(4)};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(sign_test)
 {
     migraphx::program p;
@@ -5669,6 +6195,27 @@ TEST_CASE(sign_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(sign_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{1.02481645, 0.85643062, -0.03404123, -0.92791926, 0.0};
+    mm->add_instruction(migraphx::make_op("sign"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {5}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = {1.0, 1.0, -1.0, -1.0, 0.0};
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(sin_test)
 {
     migraphx::program p;
@@ -5687,6 +6234,29 @@ TEST_CASE(sin_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(sin_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input                    = mm->add_parameter("X", s);
+    std::vector<float> input_data = {-1, 0, 1};
+    mm->add_instruction(migraphx::make_op("sin"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return sinf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(sinh_test)
 {
     migraphx::program p;
@@ -5705,6 +6275,28 @@ TEST_CASE(sinh_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(sinh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s{migraphx::shape::float_type, {{2, 4, 0}, {2, 4, 0}}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1.0, 2.0, -3.0, 4.0};
+    mm->add_instruction(migraphx::make_op("sinh"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {4}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return sinhf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(slice_test)
 {
     {
@@ -5861,6 +6453,29 @@ TEST_CASE(sqrt_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(sqrt_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{1.02481645, 0.85643062, 0.03404123, 0.92791926, 0.10569184};
+    mm->add_instruction(migraphx::make_op("sqrt"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {5}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector;
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return sqrtf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(squeeze_test)
 {
     {
@@ -5973,6 +6588,29 @@ TEST_CASE(tan_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(tan_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1, 0, 1};
+    mm->add_instruction(migraphx::make_op("tan"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {3}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(3);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return tanf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(tanh_test)
 {
     migraphx::program p;
@@ -5991,6 +6629,29 @@ TEST_CASE(tanh_test)
     EXPECT(migraphx::verify_range(results_vector, gold));
 }
 
+TEST_CASE(tanh_dynamic_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape::dynamic_dimension dd{3, 8, 0};
+    migraphx::shape s{migraphx::shape::float_type, {dd}};
+    auto input = mm->add_parameter("X", s);
+    std::vector<float> input_data{-1.0, 2.0, -3.0, 4.0};
+    mm->add_instruction(migraphx::make_op("tanh"), input);
+    p.compile(migraphx::ref::target{});
+
+    migraphx::parameter_map params0;
+    migraphx::shape input_fixed_shape0{migraphx::shape::float_type, {4}};
+    params0["X"] = migraphx::argument(input_fixed_shape0, input_data.data());
+    auto result  = p.eval(params0).back();
+    std::vector<float> results_vector(4);
+    result.visit([&](auto output) { results_vector.assign(output.begin(), output.end()); });
+    std::vector<float> gold = input_data;
+    std::transform(
+        gold.begin(), gold.end(), gold.begin(), [](float n) -> float { return tanhf(n); });
+    EXPECT(migraphx::verify_range(results_vector, gold));
+}
+
 TEST_CASE(topk_test)
 {
     auto create_program = [](int64_t k, int64_t axis, int largest) {