Merge branch 'develop' into fix_parse_if

src/CMakeLists.txt

@@ -55,6 +55,7 @@ add_library(migraphx
     insert_pad.cpp
     instruction.cpp
     json.cpp
+    layout_nhwc.cpp
     load_save.cpp
     make_op.cpp
     module.cpp
@@ -144,6 +145,7 @@ register_migraphx_ops(
     if_op
     im2col
     isnan
+    layout
     leaky_relu
     less
     load

src/api/include/migraphx/migraphx.hpp

@@ -32,6 +32,7 @@
 #include <memory>
 #include <numeric>
 #include <exception>
+#include <array>
 #include <vector>
 #include <cassert>
 #include <iostream>

src/auto_contiguous.cpp

@@ -59,6 +59,8 @@ void auto_contiguous::apply(module& m) const
     auto last = std::prev(m.end());
     for(auto ins : iterator_for(m))
     {
+        if(ins->name() == "layout")
+            continue;
         // for last instruction that is NOT a return
         if(ins->outputs().empty() and ins != last)
             continue;

src/fuse_pointwise.cpp

@@ -56,6 +56,8 @@ static void create_pointwise_modules(module_pass_manager& mpm)
     {
         if(not ins->get_operator().attributes().get("pointwise", false))
             continue;
+        if(ins->get_operator().name() == "layout")
+            continue;
         assert(ins->get_operator().attributes().contains("point_op"));
         auto* pm = mpm.create_module(mpm.get_module().name() + ":pointwise" + std::to_string(n++));
         pm->set_bypass();

src/include/migraphx/check_shapes.hpp

@@ -24,6 +24,7 @@
 #ifndef MIGRAPHX_GUARD_RTGLIB_CHECK_SHAPES_HPP
 #define MIGRAPHX_GUARD_RTGLIB_CHECK_SHAPES_HPP
 
+#include <migraphx/permutation.hpp>
 #include <migraphx/shape.hpp>
 #include <migraphx/ranges.hpp>
 #include <migraphx/stringutils.hpp>
@@ -232,6 +233,19 @@ struct check_shapes
         return *this;
     }
 
+    /*!
+     * Check all shapes are packed with certain layouts
+     */
+    const check_shapes&
+    packed_layouts(const std::initializer_list<std::vector<int64_t>>& layouts) const
+    {
+        if(not this->all_of([&](const shape& s) {
+               return s.packed() and contains(layouts, find_permutation(s));
+           }))
+            MIGRAPHX_THROW(prefix() + "Shapes are not packed with correct layout");
+        return *this;
+    }
+
     /*!
      * Check all shapes are packed or broadcasted.
      */

src/include/migraphx/layout_nhwc.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_MIGRAPHX_LAYOUT_NHWC_HPP
+#define MIGRAPHX_GUARD_MIGRAPHX_LAYOUT_NHWC_HPP
+
+#include <string>
+#include <migraphx/instruction_ref.hpp>
+#include <migraphx/config.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+struct module_pass_manager;
+
+/**
+ * Transform convolutions to nhwc
+ */
+struct layout_nhwc
+{
+    std::string name() const { return "layout_nhwc"; }
+    void apply(module_pass_manager& mpm) const;
+};
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#endif // MIGRAPHX_GUARD_MIGRAPHX_LAYOUT_NHWC_HPP

src/include/migraphx/op/layout.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_OP_LAYOUT_HPP
+#define MIGRAPHX_GUARD_OP_LAYOUT_HPP
+
+#include <migraphx/config.hpp>
+#include <array>
+#include <migraphx/check_shapes.hpp>
+#include <migraphx/stringutils.hpp>
+#include <migraphx/streamutils.hpp>
+#include <migraphx/literal.hpp>
+#include <migraphx/op/unary.hpp>
+#include <cmath>
+#include <utility>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+struct layout : unary<layout>
+{
+    std::vector<int64_t> permutation;
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.permutation, "permutation"));
+    }
+
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        check_shapes{inputs, *this}.has(1).only_dims(permutation.size());
+        auto lens = inputs.at(0).lens();
+        auto t    = inputs.at(0).type();
+        return shape::from_permutation(t, lens, permutation);
+    }
+
+    auto apply() const
+    {
+        return [](auto x) { return x; };
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+#endif // MIGRAPHX_GUARD_OP_LAYOUT_HPP

src/layout_nhwc.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/layout_nhwc.hpp>
+#include <migraphx/module.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/iterator_for.hpp>
+#include <migraphx/permutation.hpp>
+#include <migraphx/functional.hpp>
+#include <migraphx/ranges.hpp>
+#include <migraphx/make_op.hpp>
+#include <migraphx/eliminate_contiguous.hpp>
+#include <migraphx/dead_code_elimination.hpp>
+#include <migraphx/pass_manager.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+
+template <class Predicate>
+std::vector<instruction_ref> find_lasts(const module& m, Predicate pred)
+{
+    std::vector<instruction_ref> result;
+    fix([&](auto self, auto ins) {
+        if(pred(ins))
+        {
+            result.push_back(ins);
+            return;
+        }
+        for(auto input : ins->inputs())
+            self(input);
+    })(std::prev(m.end()));
+    return result;
+}
+
+std::unordered_set<instruction_ref> preserve_output_layout(module& m)
+{
+    std::unordered_set<instruction_ref> result;
+    std::vector<instruction_ref> outputs = find_lasts(m, [](auto ins) {
+        return ins->name() == "convolution" and ins->get_shape().lens().size() == 4;
+    });
+    for(auto output : outputs)
+    {
+        auto permutation = find_permutation(output->get_shape());
+        auto layout      = m.insert_instruction(
+            std::next(output), make_op("layout", {{"permutation", permutation}}), output);
+        result.insert(m.replace_instruction(output, layout));
+    }
+    return result;
+}
+
+void transform_convolutions(module& m)
+{
+    for(auto ins : iterator_for(m))
+    {
+        if(ins->name() != "convolution")
+            continue;
+        if(ins->get_shape().lens().size() != 4)
+            continue;
+        auto v = ins->get_operator().to_value();
+        if(v.at("group").to<int>() > 1)
+            continue;
+        auto args = ins->inputs();
+        std::transform(args.begin(), args.end(), args.begin(), [&](const auto& i) {
+            return m.insert_instruction(ins, make_op("layout", {{"permutation", {0, 2, 3, 1}}}), i);
+        });
+        auto conv = m.insert_instruction(ins, ins->get_operator(), args);
+        auto c    = m.insert_instruction(ins, make_op("contiguous"), conv);
+        m.replace_instruction(ins, c);
+    }
+}
+
+void remove_layout(module& m, const std::unordered_set<instruction_ref>& output_layouts)
+{
+    for(auto ins : iterator_for(m))
+    {
+        if(ins->name() != "layout")
+            continue;
+        if(ins->get_shape() != ins->inputs().front()->get_shape())
+            continue;
+        if(contains(output_layouts, ins))
+            continue;
+        m.replace_instruction(ins, ins->inputs().front());
+    }
+}
+
+void layout_nhwc::apply(module_pass_manager& mpm) const
+{
+    std::unordered_set<instruction_ref> output_layouts = preserve_output_layout(mpm.get_module());
+    transform_convolutions(mpm.get_module());
+    mpm.run_pass(dead_code_elimination{});
+    mpm.run_pass(eliminate_contiguous{"contiguous"});
+    mpm.run_pass(dead_code_elimination{});
+    remove_layout(mpm.get_module(), output_layouts);
+    mpm.run_pass(dead_code_elimination{});
+}
+
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/onnx/parse_split.cpp

@@ -26,6 +26,9 @@
 #include <migraphx/ranges.hpp>
 #include <migraphx/make_op.hpp>
 #include <migraphx/tune_axis.hpp>
+#include <migraphx/onnx/checks.hpp>
+
+#include <migraphx/stringutils.hpp>
 
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
@@ -59,6 +62,8 @@ struct parse_split : op_parser<parse_split>
         else if(args.size() == 2)
         {
             auto s = args[1]->eval();
+
+            check_arg_empty(s, "Split: dynamic shape is not supported");
             s.visit([&](auto v) { vec_splits.assign(v.begin(), v.end()); });
         }
         // no split attribute, input is equally divided
@@ -76,18 +81,10 @@ struct parse_split : op_parser<parse_split>
         if(std::accumulate(vec_splits.begin(), vec_splits.end(), int64_t(0)) !=
            static_cast<int64_t>(lens[tuned_axis]))
         {
-            std::string output;
-            for(const auto& index : vec_splits)
-                output += std::to_string(index) + ",";
-
-            std::string len_output;
-            for(const auto& len_vec : lens)
-                len_output += std::to_string(len_vec) + ",";
-
             MIGRAPHX_THROW(
                 "PARSE_SPLIT: sum of split attribute unequal to dim size of axis! tuned axis:" +
-                std::to_string(lens[tuned_axis]) + " Output " + output + " Rank " +
-                std::to_string(n_rank) + " Len outs " + len_output);
+                std::to_string(lens[tuned_axis]) + " Output " + to_string_range(vec_splits) +
+                " Rank " + std::to_string(n_rank) + " Len outs " + to_string_range(lens));
         }
 
         std::vector<instruction_ref> ret_ins;

src/targets/cpu/binary.cpp

@@ -51,7 +51,18 @@ struct dnnl_binary : dnnl_op<dnnl_binary, dnnl::binary>
         auto r  = s0;
         if(s0 != s1 or not s0.packed())
         {
-            r = shape{s0.type(), s0.lens()};
+            if(s0.packed() != s1.packed())
+            {
+                r = s0.packed() ? s0 : s1;
+            }
+            else if(s0.broadcasted() != s1.broadcasted())
+            {
+                r = s0.broadcasted() ? s1.with_lens(s0.lens()) : s0.with_lens(s0.lens());
+            }
+            else
+            {
+                r = {s0.type(), s0.lens()};
+            }
         }
         // Call to get_primitive to make sure an algo is available
         this->get_primitive(this->to_memory_desc(r, inputs));

src/targets/cpu/convolution.cpp

@@ -43,9 +43,9 @@ struct dnnl_convolution
         return {MIGRAPHX_DNNL_PREFIX(ARG_SRC), MIGRAPHX_DNNL_PREFIX(ARG_WEIGHTS)};
     }
 
-    shape adjust_shape(const shape& x, int i) const
+    shape adjust_shape(const shape& x, int i, const shape& output) const
     {
-        auto s = base_adjust_shape(x);
+        auto s = base_adjust_shape(x, output);
         if(i == 1 and op.group > 1)
         {
             // TODO: Add support for transposed weights

src/targets/cpu/deconvolution.cpp

@@ -37,9 +37,9 @@ struct dnnl_deconvolution
         return {MIGRAPHX_DNNL_PREFIX(ARG_SRC), MIGRAPHX_DNNL_PREFIX(ARG_WEIGHTS)};
     }
 
-    shape adjust_shape(const shape& x, int i) const
+    shape adjust_shape(const shape& x, int i, const shape& output) const
     {
-        auto s = base_adjust_shape(x);
+        auto s = base_adjust_shape(x, output);
         if(i == 1)
         {
             // The input and output channels are flipped for dnnl

src/targets/cpu/include/migraphx/cpu/dnnl.hpp

@@ -167,7 +167,7 @@ struct dnnl_op : auto_register_op<Derived>
         std::iota(result.begin(), result.end(), MIGRAPHX_DNNL_PREFIX(ARG_SRC_0));
         return result;
     }
-    shape base_adjust_shape(const shape& s) const
+    shape base_adjust_shape(const shape& s, const shape& output) const
     {
         if(s.broadcasted())
         {
@@ -183,7 +183,8 @@ struct dnnl_op : auto_register_op<Derived>
                                else
                                    return len;
                            });
-            return shape{s.type(), lens};
+            // Use the permutation of the output
+            return output.with_lens(s.type(), lens);
         }
         return s;
     }
@@ -204,7 +205,10 @@ struct dnnl_op : auto_register_op<Derived>
             i++;
         }
     }
-    shape adjust_shape(const shape& s, int) const { return base_adjust_shape(s); }
+    shape adjust_shape(const shape& s, int, const shape& output) const
+    {
+        return base_adjust_shape(s, output);
+    }
     std::vector<int> create_arg_map(std::size_t input_size) const
     {
         const auto& self     = static_cast<const Derived&>(*this);
@@ -224,12 +228,12 @@ struct dnnl_op : auto_register_op<Derived>
         const auto& self = static_cast<const Derived&>(*this);
         std::unordered_map<int, dnnl::memory::desc> result;
         result[MIGRAPHX_DNNL_PREFIX(ARG_DST)] =
-            to_dnnl_memory_desc(self.adjust_shape(output_shape, inputs.size()));
+            to_dnnl_memory_desc(self.adjust_shape(output_shape, inputs.size(), output_shape));
         auto m = create_arg_map(inputs.size());
         assert(m.size() >= inputs.size());
         for(int i = 0; i < inputs.size(); i++)
         {
-            result[m[i]] = to_dnnl_memory_desc(self.adjust_shape(inputs[i], i));
+            result[m[i]] = to_dnnl_memory_desc(self.adjust_shape(inputs[i], i, output_shape));
         }
         return result;
     }

src/targets/cpu/reorder.cpp

@@ -32,7 +32,7 @@ struct dnnl_reorder : dnnl_op<dnnl_reorder, dnnl::reorder>
 {
     std::string name() const { return "dnnl::reorder"; }
 
-    shape adjust_shape(const shape& x, int) const { return x; }
+    shape adjust_shape(const shape& x, int, const shape&) const { return x; }
 
     shape compute_shape(const std::vector<shape>& inputs) const
     {

src/targets/cpu/target.cpp

@@ -33,6 +33,7 @@
 #include <migraphx/eliminate_data_type.hpp>
 #include <migraphx/eliminate_identity.hpp>
 #include <migraphx/eliminate_pad.hpp>
+#include <migraphx/layout_nhwc.hpp>
 #include <migraphx/memory_coloring.hpp>
 #include <migraphx/propagate_constant.hpp>
 #include <migraphx/register_target.hpp>
@@ -82,6 +83,9 @@ std::vector<pass> target::get_passes(migraphx::context& gctx, const compile_opti
             dead_code_elimination{},
             simplify_algebra{},
             simplify_reshapes{},
+            layout_nhwc{},
+            dead_code_elimination{},
+            simplify_reshapes{},
             simplify_algebra{},
             auto_contiguous{},
             simplify_reshapes{},

src/targets/gpu/CMakeLists.txt

@@ -83,6 +83,7 @@ add_library(migraphx_gpu
     compile_gen.cpp
     compile_hip.cpp
     compile_hip_code_object.cpp
+    compile_miopen.cpp
     compiler.cpp
     device_name.cpp
     fuse_mlir.cpp

src/targets/gpu/compile_hip_code_object.cpp

@@ -144,9 +144,8 @@ compute_global_for(context& ctx, std::size_t n, std::size_t over)
 
 std::size_t compute_block_size(std::size_t n, std::size_t max_block_size)
 {
-    const std::size_t min_block_size  = 64;
-    const std::size_t base_block_size = 32;
-    auto block_size                   = (((n - 1) / base_block_size + 1)) * base_block_size;
+    const std::size_t min_block_size = 64;
+    auto block_size                  = (((n - 1) / min_block_size + 1)) * min_block_size;
     return std::min(std::max(min_block_size, block_size), max_block_size);
 }
 

src/targets/gpu/compile_miopen.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/compile_miopen.hpp>
+#include <migraphx/gpu/context.hpp>
+#include <migraphx/module.hpp>
+#include <migraphx/iterator_for.hpp>
+#include <migraphx/instruction.hpp>
+#include <migraphx/make_op.hpp>
+#include <migraphx/register_op.hpp>
+#include <migraphx/op/identity.hpp>
+#include <migraphx/gpu/rocblas.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace gpu {
+
+struct miopen_op
+{
+    operation op = op::identity{};
+
+    template <class Self, class F>
+    static auto reflect(Self& self, F f)
+    {
+        return pack(f(self.op, "op"));
+    }
+
+    std::string name() const { return "gpu::miopen_op"; }
+
+    shape compute_shape(std::vector<shape> inputs) const
+    {
+        inputs.push_back(inputs.back());
+        return op.compute_shape(inputs);
+    }
+
+    std::ptrdiff_t output_alias(const std::vector<shape>& shapes) const
+    {
+        return shapes.size() - 1;
+    }
+};
+MIGRAPHX_REGISTER_OP(miopen_op);
+
+std::size_t compile_miopen::compile(operation& op, instruction_ref ins, bool format) const
+{
+    op.from_value({{"int8_x4_format", format}});
+    auto v = op.compile(*ctx, ins->get_shape(), to_shapes(ins->inputs()));
+    return v.get("workspace", 0);
+}
+
+void compile_miopen::apply(module& m) const
+{
+    assert(ctx);
+    const bool int8_x4_format = get_int8_x4_format(any_cast<migraphx::gpu::context>(*ctx));
+    for(auto ins : iterator_for(m))
+    {
+        if(ins->name() != "gpu::miopen_op")
+            continue;
+        auto op        = any_cast<miopen_op>(ins->get_operator()).op;
+        std::size_t ws = 0;
+        try
+        {
+            // for the regular convolution and deconvolution, this try would always succeed
+            ws = compile(op, ins, int8_x4_format);
+        }
+        catch(migraphx::exception&)
+        {
+            // In case no solver supports the default format, retry using the other format.
+            ws = compile(op, ins, not int8_x4_format);
+        }
+        auto inputs = ins->inputs();
+        auto alloc  = m.insert_instruction(
+            ins, make_op("allocate", {{"shape", to_value(shape{shape::int8_type, {ws}})}}));
+        inputs.insert(std::prev(inputs.end()), alloc);
+
+        m.replace_instruction(ins, op, inputs);
+    }
+}
+
+} // namespace gpu
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx

src/targets/gpu/compile_ops.cpp

@@ -39,19 +39,26 @@ MIGRAPHX_DECLARE_ENV_VAR(MIGRAPHX_GPU_COMPILE_PARALLEL);
 
 struct precompile_op
 {
-    operation op = op::identity{};
+    operation op                = op::identity{};
+    std::size_t additional_args = 1;
+    bool ignore_modules         = false;
 
     template <class Self, class F>
     static auto reflect(Self& self, F f)
     {
-        return pack(f(self.op, "op"));
+        return pack(f(self.op, "op"),
+                    f(self.additional_args, "additional_args"),
+                    f(self.ignore_modules, "ignore_modules"));
     }
 
     std::string name() const { return "gpu::precompile_op"; }
 
     shape compute_shape(std::vector<shape> inputs, const std::vector<module_ref>& mods) const
     {
-        inputs.pop_back();
+        // Pop off additional args
+        inputs.resize(inputs.size() - additional_args);
+        if(ignore_modules)
+            return op.compute_shape(inputs);
         return op.compute_shape(inputs, mods);
     }