Parse ONNX Expand to broadcast_with_dims

src/CMakeLists.txt

@@ -140,6 +140,7 @@ register_migraphx_ops(
     atan
     broadcast
     broadcast_for_dot
+    broadcast_with_dims
     capture
     ceil
     clip

src/include/migraphx/op/broadcast_with_dims.hpp

@@ -0,0 +1,84 @@
+/*
+ * The MIT License (MIT)
+ *
+ * Copyright (c) 2015-2024 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_BROADCAST_WITH_DIMS_HPP
+#define MIGRAPHX_GUARD_OPERATORS_BROADCAST_WITH_DIMS_HPP
+
+#include <migraphx/check_shapes.hpp>
+#include <migraphx/config.hpp>
+#include <migraphx/shape.hpp>
+#include <migraphx/argument.hpp>
+#include <migraphx/common.hpp>
+
+namespace migraphx {
+inline namespace MIGRAPHX_INLINE_NS {
+namespace op {
+
+/**
+ * Broadcast the input tensor to the shape defined by the values of the second input.
+ * Used as `broadcast_with_dims(input_tensor, dims)`, where dims is a vector of integer dimensions.
+ * `input_tensor` must be broadcastable with `dims`, otherwise this operator with throw at compute.
+ * This operator can be replaced with `multibroadcast(input_tensor)` if the `dims` vector is
+ * constant.
+ *
+ * Example:
+ *  input_tensor shape: lens = {2, 3}, strides = {3, 1}
+ *  dims = [4, 1, 3]
+ *  output shape: lens = {4, 2, 3}, strides = {0, 3, 1}
+ */
+struct broadcast_with_dims
+{
+    std::string name() const { return "broadcast_with_dims"; }
+
+    shape compute_shape(const std::vector<shape>& inputs) const
+    {
+        migraphx::check_shapes{inputs, *this, true}.has(2);
+        // check that second input has a static shape
+        (void)migraphx::check_shapes{inputs.begin() + 1, inputs.end(), *this, false};
+        // output tensor rank is greater of input_tensor rank or length of dims vector
+        const auto& input_tensor_shape = inputs.at(0);
+        const auto& dims_shape         = inputs.at(1);
+        size_t out_ndim     = std::max(input_tensor_shape.ndim(), dims_shape.lens().at(0));
+        std::size_t max_int = std::numeric_limits<std::size_t>::max();
+        std::vector<shape::dynamic_dimension> dyn_dims(out_ndim,
+                                                       shape::dynamic_dimension{0, max_int});
+        return {input_tensor_shape.type(), dyn_dims};
+    }
+
+    argument compute(const shape& output_shape, const std::vector<argument>& args) const
+    {
+        auto s0             = args.at(0).get_shape();
+        const auto& in_lens = s0.lens();
+        std::vector<std::size_t> dims_input(output_shape.ndim());
+        args.at(1).visit([&](auto a) { dims_input.assign(a.begin(), a.end()); });
+        auto out_lens  = compute_broadcasted_lens(in_lens, dims_input);
+        auto out_shape = make_bcast_shape(s0, out_lens);
+        return args[0].reshape(out_shape);
+    }
+};
+
+} // namespace op
+} // namespace MIGRAPHX_INLINE_NS
+} // namespace migraphx
+
+#endif

src/onnx/parse_expand.cpp

@@ -1,7 +1,7 @@
 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2022 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2024 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
@@ -43,11 +43,19 @@ struct parse_expand : op_parser<parse_expand>
     {
         auto in_lens             = args[0]->get_shape().lens();
         migraphx::argument arg_s = args[1]->eval();
-        check_arg_empty(arg_s, "Expand: dynamic shape is not supported");
-        std::vector<std::size_t> dims;
-        arg_s.visit([&](auto input) { dims.assign(input.begin(), input.end()); });
-        auto out_lens = compute_broadcasted_lens(in_lens, dims);
-        return info.add_instruction(make_op("multibroadcast", {{"out_lens", out_lens}}), args[0]);
+        if(arg_s.empty())
+        {
+            // variable dims input
+            return info.add_instruction(make_op("broadcast_with_dims"), args[0], args[1]);
+        }
+        else
+        {
+            std::vector<std::size_t> dims;
+            arg_s.visit([&](auto input) { dims.assign(input.begin(), input.end()); });
+            auto out_lens = compute_broadcasted_lens(in_lens, dims);
+            return info.add_instruction(make_op("multibroadcast", {{"out_lens", out_lens}}),
+                                        args[0]);
+        }
     }
 };
 

src/simplify_dyn_ops.cpp

@@ -33,6 +33,35 @@
 namespace migraphx {
 inline namespace MIGRAPHX_INLINE_NS {
 
+/**
+ *    Convert broadcast_with_dims operators with a static input tensor and a constant `dims` input
+ *    into multibroadcast op with a static output shape attribute.
+ *
+ */
+struct find_broadcast_with_dims_static
+{
+    auto matcher() const
+    {
+        return match::name("broadcast_with_dims")(match::nargs(2),
+                                                  match::arg(0)(match::static_shape()),
+                                                  match::arg(1)(match::is_constant()));
+    }
+
+    void apply(module& m, const match::matcher_result& mr) const
+    {
+        auto ins    = mr.result;
+        auto inputs = ins->inputs();
+
+        // read the values of arg(1) to create input to multibroadcast
+        std::vector<size_t> sizes_vec;
+        inputs.at(1)->eval().visit(
+            [&](auto output) { sizes_vec.assign(output.begin(), output.end()); });
+
+        m.replace_instruction(
+            ins, make_op("multibroadcast", {{"out_lens", sizes_vec}}), inputs.at(0));
+    }
+};
+
 /**
  * Convert a Resize op. with Nearest mode to an implementation using Gather op.
  * From:  resize[scales={...}/sizes={...},](static, constant)
@@ -586,6 +615,7 @@ struct simplify_select_module_output_shape
 void simplify_dyn_ops::apply(module& m) const
 {
     match::find_matches(m,
+                        find_broadcast_with_dims_static{},
                         find_resize_static{},
                         find_static_dimensions_of{},
                         find_const_alloc_reshapes{},

test/onnx/expand_dyn_test.onnx

@@ -0,0 +1,19 @@
+	expand_dyn_test:q
+
+
x
+dims
y"Expandexpand_dyn_testZ
+
x
+

+
+

+
Z
+dims
+
+
+b
+
y
+

+
+
+
+B

test/onnx/gen_onnx.py

@@ -2203,6 +2203,17 @@ def expand_test():
     return ([shape_const, node], [x], [y])
 
 
+@onnx_test()
+def expand_dyn_test():
+    x = helper.make_tensor_value_info('x', TensorProto.FLOAT, [3, 1, 1])
+    dims_in = helper.make_tensor_value_info('dims', TensorProto.INT64, [4])
+    y = helper.make_tensor_value_info('y', TensorProto.FLOAT, [2, 3, 4, 5])
+
+    node = onnx.helper.make_node('Expand', inputs=['x', 'dims'], outputs=['y'])
+
+    return ([node], [x, dims_in], [y])
+
+
 @onnx_test(True)
 def external_constant_test():
     x = np.array([0, 1, 2])

test/onnx/parse/expand_test.cpp

@@ -1,7 +1,7 @@
 /*
  * The MIT License (MIT)
  *
- * Copyright (c) 2015-2023 Advanced Micro Devices, Inc. All rights reserved.
+ * Copyright (c) 2015-2024 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
@@ -37,3 +37,17 @@ TEST_CASE(expand_test)
     auto prog = optimize_onnx("expand_test.onnx");
     EXPECT(p == prog);
 }
+
+TEST_CASE(expand_dyn_test)
+{
+    migraphx::program p;
+    auto* mm = p.get_main_module();
+    migraphx::shape s(migraphx::shape::float_type, {3, 1, 1});
+    auto param = mm->add_parameter("x", s);
+    migraphx::shape ss(migraphx::shape::int64_type, {4});
+    auto dims = mm->add_parameter("dims", ss);
+    mm->add_instruction(migraphx::make_op("broadcast_with_dims"), param, dims);
+
+    auto prog = optimize_onnx("expand_dyn_test.onnx");
+    EXPECT(p == prog);
+}

test/op_shape_test.cpp

@@ -942,6 +942,43 @@ TEST_CASE(broadcast_for_dot_dyn2)
         s0);
 }
 
+TEST_CASE(broadcast_with_dims0)
+{
+    using migraphx::shape;
+    shape s0{migraphx::shape::float_type, {2, 4}};
+    shape s1{migraphx::shape::int64_type, {4}};
+    std::size_t max_int = std::numeric_limits<std::size_t>::max();
+    std::vector<shape::dynamic_dimension> dyn_dims(4, shape::dynamic_dimension{0, max_int});
+    expect_shape(
+        shape{shape::float_type, dyn_dims}, migraphx::make_op("broadcast_with_dims"), s0, s1);
+}
+
+TEST_CASE(broadcast_with_dims1)
+{
+    using migraphx::shape;
+    shape s0{migraphx::shape::int32_type, {1, 2, 4}};
+    shape s1{migraphx::shape::int64_type, {1}};
+    std::size_t max_int = std::numeric_limits<std::size_t>::max();
+    std::vector<shape::dynamic_dimension> dyn_dims(3, shape::dynamic_dimension{0, max_int});
+    expect_shape(shape{migraphx::shape::int32_type, dyn_dims},
+                 migraphx::make_op("broadcast_with_dims"),
+                 s0,
+                 s1);
+}
+
+TEST_CASE(broadcast_with_dims2)
+{
+    using migraphx::shape;
+    shape s0{migraphx::shape::float_type, {{1, 4}, {2, 2}, {4, 4}}};
+    shape s1{migraphx::shape::int64_type, {4}};
+    std::size_t max_int = std::numeric_limits<std::size_t>::max();
+    std::vector<shape::dynamic_dimension> dyn_dims(4, shape::dynamic_dimension{0, max_int});
+    expect_shape(shape{migraphx::shape::float_type, dyn_dims},
+                 migraphx::make_op("broadcast_with_dims"),
+                 s0,
+                 s1);
+}
+
 TEST_CASE(flatten_shape)
 {
     migraphx::shape input{migraphx::shape::float_type, {2, 4, 6, 8}};