Incorrect output aliases

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The program fails with an error if the last op is slice.

terminate called after throwing an instance of 'migraphx::version_1::exception'
what(): /AMDMIGraphX/src/program.cpp:270: operator(): Incorrect shape {float_type, {1, 63, 672, 672}, {28901376, 451584, 672, 1}} for parameter: main:#output_1

Code example

#include <iostream>
#include <map>
#include <memory>
#include <string>
#include <vector>

#include <migraphx/argument.hpp>
#include <migraphx/generate.hpp>
#include <migraphx/gpu/hip.hpp>
#include <migraphx/gpu/target.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/make_op.hpp>
#include <migraphx/program.hpp>
#include <migraphx/ref/target.hpp>
#include <migraphx/target.hpp>

int main() {
  auto target = migraphx::target(migraphx::gpu::target{});
  migraphx::module *network_;
  migraphx::program program_;

  network_ = program_.get_main_module();

  const size_t W = 672;
  const size_t H = 672;
  const size_t K = 64;
  const size_t C = 3;
  const size_t R = 3;
  const size_t S = 3;

  const migraphx::shape input_shape{migraphx::shape::float_type, {1, C, W, H}};
  const migraphx::shape filter_shape{migraphx::shape::float_type, {K, C, R, S}};
  const auto input = network_->add_parameter("data", input_shape);

  std::vector<float> weights(filter_shape.elements(), 1);

  const auto filter =
      network_->add_literal(migraphx::literal(filter_shape, weights));

  auto out = network_->add_instruction(
      migraphx::make_op("convolution", {{"padding", {1, 1}},
                                        {"stride", {1, 1}},
                                        {"dilation", {1, 1}},
                                        {"group", 1}}),
      input, filter);

  auto slice_out_0 = network_->add_instruction(
      migraphx::make_op("slice",
                        {{"axes", {1}}, {"starts", {0}}, {"ends", {1}}}),
      out);

  auto slice_out_1 = network_->add_instruction(
      migraphx::make_op("slice",
                        {{"axes", {1}}, {"starts", {1}}, {"ends", {K}}}),
      out);

  const auto out0 =
      network_->add_parameter("main:#output_0", slice_out_0->get_shape());
  const auto out1 =
      network_->add_parameter("main:#output_1", slice_out_1->get_shape());

  network_->add_return({slice_out_0, slice_out_1});
  program_.compile(target);

  auto param_shapes = program_.get_parameter_shapes();
  for (auto &p : param_shapes) {
    std::cout << p.first << " " << p.second << '\n';
  }

  auto output_shapes = program_.get_output_shapes();
  for (auto &o : output_shapes) {
    std::cout << o << '\n';
  }

  std::vector<float> input_data;
  input_data.resize(input_shape.elements());

  std::vector<float> out0_data;
  std::vector<float> out1_data;
  out0_data.resize(output_shapes[0].elements());
  out1_data.resize(output_shapes[1].elements());

  migraphx::parameter_map pm;
  pm["data"] =
      migraphx::gpu::to_gpu(migraphx::argument(input_shape, input_data.data()));
  pm["main:#output_0"] = migraphx::gpu::to_gpu(
      migraphx::argument(output_shapes[0], out0_data.data()));
  pm["main:#output_1"] = migraphx::gpu::to_gpu(
      migraphx::argument(output_shapes[1], out1_data.data()));

  auto output = program_.eval(pm);
  for (auto &o : output) {
    std::cout << o.get_shape() << " ";
  }
}

Local configuration

latest develop (c99be32c013a21c41f6ad31154fc12c03eac1124)
gpu target
gfx1030

Root cause

instruction.cpp:get_output_alias returns the input tensor as the slice op defines the next output alias:

https://github.com/ROCmSoftwarePlatform/AMDMIGraphX/blob/c99be32c013a21c41f6ad31154fc12c03eac1124/src/include/migraphx/op/slice.hpp#L114

And then replace_allocate.cpp:create_output_names creates incorrect output_names with tensor from the previous layer instead of sliced tensor.

Solution

I tried the same test program with default output_alias for slice operation and it works correctly. I suppose that other operations like reshape transpose broadcast also may throw an error.

Start with instruction.cpp:get_output_alias and op/slice.hpp, then inspect replace_allocate.cpp:create_output_names. Reproduce the provided C++ program on the GPU target and compare the reported parameter and output shapes. Done means sliced outputs retain the correct aliases and the example evaluates without the incorrect-shape error; check whether the same behavior affects reshape, transpose, or broadcast.

Written by the indexing model from the issue text.

Description

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Root cause

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Incorrect output aliases

Description

Code example

Local configuration

Root cause

Solution

Contributor guide

First steps

Research direction

Assessment

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