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Commit 13ea6f19 authored by Brian Pickrell's avatar Brian Pickrell
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Merge branch 'dyn_unsqueeze' of... 

Merge branch 'dyn_unsqueeze' of https://github.com/ROCmSoftwarePlatform/AMDMIGraphX into dynamic_reduce.
Required because squeeze is added in parsing of onnx reduce op.
parents 980cfd49 c3e62f5f
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.github/workflows/ci.yaml
View file @ 13ea6f19
......@@ -7,7 +7,7 @@ jobs:
runs-on: ubuntu-latest
steps:
- name: Cancel Previous Runs
uses: styfle/cancel-workflow-action@0.6.0
uses: styfle/cancel-workflow-action@0.11.0
with:
access_token: ${{ github.token }}
tidy:
......@@ -15,9 +15,19 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: |
sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
du . --max-depth=1 -h
ls -la
cd /usr/local
du . --max-depth=1 -h
ls -la
cd /usr/local/lib
echo $(pwd)
du . --max-depth=1 -h
ls -la
- uses: actions/checkout@v3
# In this step, this action saves a list of existing images,
# the cache is created without them in the post run.
......@@ -34,7 +44,7 @@ jobs:
message("::set-output name=timestamp::${current_date}")
- name: Cache files for tidy
uses: pat-s/always-upload-cache@v2.1.3
uses: pat-s/always-upload-cache@v3.0.11
with:
path: tidy-cache
key: tidy-cache-${{ steps.cache_timestamp.outputs.timestamp }}
......@@ -65,8 +75,8 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
- uses: actions/checkout@v3
# In this step, this action saves a list of existing images,
# the cache is created without them in the post run.
......@@ -110,8 +120,8 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
- uses: actions/checkout@v3
# In this step, this action saves a list of existing images,
# the cache is created without them in the post run.
......@@ -146,10 +156,10 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v2
uses: actions/setup-python@v4
with:
python-version: 3.8
- name: Install pyflakes
......@@ -167,10 +177,10 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v2
uses: actions/setup-python@v4
with:
python-version: 3.8
- name: run License Check
......@@ -198,16 +208,16 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v2
uses: actions/setup-python@v4
with:
python-version: 3.7
- name: Cache dependencies
# Ignore the failure of a step and avoid terminating the job.
continue-on-error: true
uses: actions/cache@v2
uses: actions/cache@v3
with:
# This path is specific to Ubuntu
path: ${{ github.workspace }}/cget
......@@ -294,16 +304,16 @@ jobs:
steps:
- name: Free space
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android
- uses: actions/checkout@v2
run: sudo rm -rf /usr/local/android /usr/share/dotnet /usr/local/share/boost /opt/ghc /usr/local/share/chrom* /usr/share/swift /usr/local/julia* /usr/local/lib/android /usr/local/graalvm /usr/local/aws* /usr/local/lib/heroku
- uses: actions/checkout@v3
- name: Set up Python
uses: actions/setup-python@v2
uses: actions/setup-python@v4
with:
python-version: 3.7
- name: Cache dependencies
# Ignore the failure of a step and avoid terminating the job.
continue-on-error: true
uses: actions/cache@v2
uses: actions/cache@v3
with:
# This path is specific to Ubuntu
path: ${{ github.workspace }}/cget
......
Dockerfile
View file @ 13ea6f19
......@@ -74,7 +74,8 @@ RUN cget -p $PREFIX install facebook/zstd@v1.4.5 -X subdir -DCMAKE_DIR=build/cma
RUN cget -p $PREFIX install ccache@v4.1 -DENABLE_TESTING=OFF
# Install newer cmake for onnx runtime
RUN cget -p /opt/cmake install kitware/cmake@v3.13.4
ARG CMAKE_VERSION=3.24.2
RUN cget -p /opt/cmake install -X binary https://github.com/Kitware/CMake/releases/download/v${CMAKE_VERSION}/cmake-${CMAKE_VERSION}-Linux-x86_64.tar.gz
ARG ONNXRUNTIME_REPO=https://github.com/Microsoft/onnxruntime
ARG ONNXRUNTIME_BRANCH=main
......
src/CMakeLists.txt
View file @ 13ea6f19
......@@ -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
View file @ 13ea6f19
......@@ -32,6 +32,7 @@
#include <memory>
#include <numeric>
#include <exception>
#include <array>
#include <vector>
#include <cassert>
#include <iostream>
......
src/auto_contiguous.cpp
View file @ 13ea6f19
......@@ -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/common.cpp
View file @ 13ea6f19
......@@ -27,6 +27,7 @@
#include <migraphx/algorithm.hpp>
#include <migraphx/stringutils.hpp>
#include <migraphx/instruction.hpp>
#include <migraphx/ranges.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -43,6 +44,7 @@ inline namespace MIGRAPHX_INLINE_NS {
// In this case we need to broadcast the (:,:,1:,:) axis
// of s0 plus the 1st dimension of s1 giving
// output_lens = (3,2,7,5)
//
std::vector<std::size_t> compute_broadcasted_lens(std::vector<std::size_t> s0,
std::vector<std::size_t> s1)
{
......@@ -50,25 +52,63 @@ std::vector<std::size_t> compute_broadcasted_lens(std::vector<std::size_t> s0,
return s0;
if(s0.size() > s1.size())
s0.swap(s1);
std::vector<std::size_t> out_lens(s1);
auto offset = s1.size() - s0.size();
std::transform(
s0.begin(), s0.end(), s1.begin() + offset, out_lens.begin() + offset, [&](auto a, auto b) {
if(a != b and a != 1 and b != 1)
{
MIGRAPHX_THROW("COMPUTE_BROADCASTLEN: shape {" + to_string_range(s0) + "} and {" +
to_string_range(s1) + "} mismatch!");
MIGRAPHX_THROW("COMPUTE_BROADCASTLEN: shape {" + migraphx::to_string_range(s0) +
"} and {" + migraphx::to_string_range(s1) + "} mismatch!");
}
return std::max(a, b);
});
return out_lens;
}
std::vector<shape::dynamic_dimension> compute_broadcasted_dyn_dims(shape s0, shape s1)
{
// change both shapes to dynamic_dimension representation
s0 = s0.to_dynamic();
s1 = s1.to_dynamic();
if(s0.ndim() > s1.ndim())
{
std::swap(s0, s1);
}
auto offset = s1.ndim() - s0.ndim();
std::vector<shape::dynamic_dimension> out_dims(s1.dyn_dims());
shape::dynamic_dimension one_dyn_dim{1, 1, 0};
std::transform(
s0.dyn_dims().cbegin(),
s0.dyn_dims().cend(),
s1.dyn_dims().cbegin() + offset,
out_dims.begin() + offset,
[&](auto a, auto b) {
if(a == b)
{
return a;
}
else if(a == one_dyn_dim or b == one_dyn_dim)
{
// setting opt to 0, may need to be changed
return shape::dynamic_dimension{std::max(a.min, b.min), std::max(a.max, b.max), 0};
}
else
{
MIGRAPHX_THROW("COMPUTE_BROADCASTED_DYN_DIMS: dynamic shapes {" +
migraphx::to_string_range(s0.dyn_dims()) + "} and {" +
migraphx::to_string_range(s1.dyn_dims()) + "} mismatch!");
}
});
return out_dims;
}
// Compute the common (broadcasted) dimensions of a list of fixed shapes
std::vector<std::size_t> compute_common_lens(const std::vector<shape>& shapes)
{
assert(not shapes.empty());
assert(
std::none_of(shapes.cbegin(), shapes.cend(), [](auto shape) { return shape.dynamic(); }));
return transform_accumulate(shapes.begin() + 1,
shapes.end(),
shapes.front().lens(),
......@@ -114,20 +154,63 @@ instruction_ref insert_common_op(module& m,
const operation& op,
std::vector<instruction_ref> inputs)
{
auto common = common_shape(to_shapes(inputs));
std::transform(inputs.begin(), inputs.end(), inputs.begin(), [&](auto input) {
if(input->get_shape().lens() != common.lens())
if(std::any_of(
inputs.cbegin(), inputs.cend(), [](auto input) { return input->get_shape().dynamic(); }))
{
// currently only handles the binary case
if(inputs.size() != 2)
{
input = m.insert_instruction(
ins, make_op("multibroadcast", {{"out_lens", common.lens()}}), input);
MIGRAPHX_THROW("INSERT_COMMON_OP: not handled; " + migraphx::to_string(inputs.size()) +
"inputs, only handle two inputs if any are dynamic shape");
}
if(input->get_shape().type() != common.type())
auto c_type = compute_common_types(to_shapes(inputs));
auto c_dyn_dims =
compute_broadcasted_dyn_dims(inputs[0]->get_shape(), inputs[1]->get_shape());
// following should work for a static or dynamic shape
if(inputs[0]->get_shape().dyn_dims() != c_dyn_dims)
{
input = m.insert_instruction(
ins, make_op("convert", {{"target_type", common.type()}}), input);
inputs[0] = m.insert_instruction(
ins,
make_op("multibroadcast", {{"out_dyn_dims", to_value(c_dyn_dims)}}),
inputs[0],
inputs[1]);
}
return input;
});
if(inputs[1]->get_shape().dyn_dims() != c_dyn_dims)
{
inputs[1] = m.insert_instruction(
ins,
make_op("multibroadcast", {{"out_dyn_dims", to_value(c_dyn_dims)}}),
inputs[1],
inputs[0]);
}
std::transform(inputs.begin(), inputs.end(), inputs.begin(), [&](auto input) {
if(input->get_shape().type() != c_type)
{
input =
m.insert_instruction(ins, make_op("convert", {{"target_type", c_type}}), input);
}
return input;
});
}
else
{
auto common = common_shape(to_shapes(inputs));
std::transform(inputs.begin(), inputs.end(), inputs.begin(), [&](auto input) {
if(input->get_shape().lens() != common.lens())
{
input = m.insert_instruction(
ins, make_op("multibroadcast", {{"out_lens", common.lens()}}), input);
}
if(input->get_shape().type() != common.type())
{
input = m.insert_instruction(
ins, make_op("convert", {{"target_type", common.type()}}), input);
}
return input;
});
}
return m.insert_instruction(ins, op, inputs);
}
......
src/eliminate_contiguous.cpp
View file @ 13ea6f19
......@@ -42,6 +42,13 @@ static bool try_compute_shape(instruction_ref ins,
try
{
shape new_shape = ins->get_operator().compute_shape(inputs, mods);
// Cannot tell if a dynamic shape will need to be made contiguous
if(new_shape.dynamic())
{
return false;
}
// If the output shape is a standard shape, no need to try its output
if(new_shape.standard())
{
......@@ -133,14 +140,20 @@ static void remove_contiguous(const std::string& op_name, module& m, F f)
}
}
// Perform evaluations in parallel
// Perform static contiguous evaluations in parallel
std::vector<argument> literals(const_instructions.size());
par_for(const_instructions.size(), 1, [&](const auto i) {
auto c = op::contiguous{};
auto prev = const_instructions[i]->inputs().front();
literals[i] = c.compute(c.compute_shape({prev->get_shape()}), {prev->eval()});
auto c = op::contiguous{};
auto prev = const_instructions[i]->inputs().front();
// compute the output contiguous shape from the previous instruction shape
shape computed_shape = c.compute_shape({prev->get_shape()});
const std::vector<argument>& prev_eval = {prev->eval()};
// prev_eval should not be used in make_compute_output_shape() as computed_shape is static
auto co_shape = make_compute_output_shape(pack(c, computed_shape, prev_eval));
literals[i] = c.compute(co_shape, prev_eval);
});
// Replace static contiguous operations with a literal
for(size_t i = 0; i < const_instructions.size(); i++)
{
auto l = m.add_literal(literals[i].get_shape(), literals[i].data());
......
src/fuse_pointwise.cpp
View file @ 13ea6f19
......@@ -45,7 +45,16 @@ static literal get_scalar(instruction_ref ins)
return {};
auto e = ins->eval();
literal r{};
e.visit_at([&](auto x) { r = literal{x}; });
// needed for bool as visit_at invokes as() which promotes bool to int8
// Without this we'll break type checks for logical ops that are fused.
if(e.get_shape().type() == shape::bool_type)
{
r = literal{e.at<bool>()};
}
else
{
e.visit_at([&](auto x) { r = literal{x}; });
}
return r;
}
......@@ -56,6 +65,8 @@ 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
View file @ 13ea6f19
......@@ -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/common.hpp
View file @ 13ea6f19
......@@ -36,6 +36,9 @@ struct operation;
std::vector<std::size_t> compute_broadcasted_lens(std::vector<std::size_t> s0,
std::vector<std::size_t> s1);
std::vector<shape::dynamic_dimension> compute_broadcasted_dyn_dims(shape s0, shape s1);
shape common_shape(const std::vector<shape>& shapes);
instruction_ref insert_common_op(module& m,
......
src/include/migraphx/layout_nhwc.hpp 0 → 100644
View file @ 13ea6f19
/*
* 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/binary.hpp
View file @ 13ea6f19
......@@ -28,6 +28,7 @@
#include <migraphx/check_shapes.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/value.hpp>
#include <migraphx/dyn_output.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -60,10 +61,19 @@ struct binary : 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(2).same_type().same_dims();
check_shapes{inputs, static_cast<const Derived&>(*this), true}
.has(2)
.same_type()
.same_dims();
auto s0 = inputs.at(0);
auto s1 = inputs.at(1);
if(s0 == s1 and s0.packed())
if(s0.dynamic() or s1.dynamic())
{
if(s0 == s1)
return s0;
MIGRAPHX_THROW("BINARY: " + point_function() + ": fixed-dyn shape for inputs");
}
else if(s0 == s1 and s0.packed())
{
return s0;
}
......@@ -81,9 +91,9 @@ struct binary : 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};
visit_all(result, args[0], args[1])([&](auto output, auto input1, auto input2) {
std::transform(input1.begin(),
input1.end(),
......
src/include/migraphx/op/broadcast.hpp
View file @ 13ea6f19
......@@ -27,23 +27,30 @@
#include <migraphx/check_shapes.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/config.hpp>
#include <migraphx/dyn_output.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {
/// The broadcast operator performs the numpy-style broadcasting of an axis of a given tensor. This
/// is achieved primarily by setting the stride of the broadcasted axis to zero. Linear indicies are
/// computed from multi-indicies by computing the inner product on the multi-index with the strides.
/// For example, if we have a tensor A(2,3) it has lengths of (2,3) and strides of (3,1). If we want
/// to compute the linear offset that corresponds to the element on the 2nd row (i = 1) and 3rd
/// column (j = 2), we compute the following inner product (1,2) dot (3, 1) = 1*3 + 2*1 = 5. It is
/// obvious from there that we can negate the effects of a given axis by setting the stride of that
/// axis to zero.
/**
* 1 input version:
* Broadcasts a tensor from the original shape to the broadcast_lens by setting the stride of
* broadcasted dimensions to zero. `axis` attribute for a 1D input shape is the output dimension
* that stays the same. ex: broadcasting shape [1024] -> [4, 1024, 3] has axis = 1 For higher rank
* input shapes, axis is an offset parameter for the broadcasting. Such that this operator would
* work in the opposite direction of NumPy broadcasting. ex: broadcasting shape [2, 2] -> [2, 2, 3]
* with axis = 0
*
* 2 input version:
* Broadcast the first input 1D shape into the second input shape based on the axis parameter.
* Handles broadcasting a 1D static shape into a higher rank dynamic shape.
* broadcast_lens is not used
*/
struct broadcast
{
uint64_t axis = 0;
std::vector<std::size_t> broadcast_lens;
uint64_t axis = 0;
std::vector<std::size_t> broadcast_lens = {};
template <class Self, class F>
static auto reflect(Self& self, F f)
......@@ -54,36 +61,86 @@ struct broadcast
std::string name() const { return "broadcast"; }
shape compute_shape(std::vector<shape> inputs) const
{
auto input = inputs.at(0);
auto t = input.type();
std::vector<size_t> bcast_strides(broadcast_lens.size(), 0);
// the broacast op is deprecated now, so not handling the negative
// value of axis anymore
if(axis >= broadcast_lens.size())
check_shapes{inputs, *this, true}.has(1, 2);
auto s0 = inputs.at(0);
auto t = s0.type();
if(inputs.size() == 1)
{
MIGRAPHX_THROW("BROADCAST : axis is out of range");
}
// the ONNX broadcast op is deprecated now, so not handling the negative
// value of axis anymore
if(axis >= broadcast_lens.size())
{
MIGRAPHX_THROW("BROADCAST : axis " + migraphx::to_string(axis) +
" is out of range");
}
if(broadcast_lens.size() - axis < s0.lens().size())
{
MIGRAPHX_THROW("BROADCAST: (broadcast ndims - axis) is less than s0 ndims");
}
if(not std::equal(s0.lens().begin(), s0.lens().end(), broadcast_lens.begin() + axis))
{
MIGRAPHX_THROW("BROADCAST: when broadcasting, succeeding sizes must match");
}
if(broadcast_lens.size() - axis < input.lens().size())
{
MIGRAPHX_THROW("BROADCAST: (broadcast ndims - axis) is less than input ndims");
std::vector<size_t> bcast_strides(broadcast_lens.size(), 0);
std::copy(s0.strides().begin(), s0.strides().end(), bcast_strides.begin() + axis);
shape output{t, broadcast_lens, std::move(bcast_strides)};
if(output.elements() < s0.elements())
{
// don't think this can occur?
MIGRAPHX_THROW("BROADCAST: output size must be greater than or equal to s0 size");
}
return output;
}
if(not std::equal(input.lens().begin(), input.lens().end(), broadcast_lens.begin() + axis))
else
{
MIGRAPHX_THROW("BROADCAST: when broadcasting, succeeding sizes must match");
}
std::copy(input.strides().begin(), input.strides().end(), bcast_strides.begin() + axis);
// two inputs
auto s1 = inputs.at(1);
if(s0.dynamic())
{
MIGRAPHX_THROW("BROADCAST_2in: s0 is a dynamic shape, does not handle broadcasting "
"a dynamic shape");
}
if(s0.ndim() != 1)
{
MIGRAPHX_THROW("BROADCAST_2in: s0 has ndim " + migraphx::to_string(s0.ndim()) +
", only handle ndim = 1");
}
if(axis >= s1.ndim())
{
MIGRAPHX_THROW("BROADCAST_2in: axis " + migraphx::to_string(axis) +
" is out of range");
}
if(s1.dynamic())
{
s0 = s0.to_dynamic();
if(s0.dyn_dims()[0] != s1.dyn_dims()[axis])
{
MIGRAPHX_THROW("BROADCAST_2in: s0 length doesn't match with dynamic s1 axis "
"dimension length (" +
migraphx::to_string(s0.dyn_dims()[0]) +
" != " + migraphx::to_string(s1.dyn_dims()[axis]) + ")");
}
return s1;
}
shape output{t, broadcast_lens, std::move(bcast_strides)};
if(output.elements() < input.elements())
MIGRAPHX_THROW("BROADCAST: output size must be greater than or equal to input size");
return output;
if(s0.lens()[0] != s1.lens()[axis])
{
MIGRAPHX_THROW("BROADCAST_2in: s0 length doesn't match with static s1 axis "
"dimension length (" +
migraphx::to_string(s0.lens()[0]) +
" != " + migraphx::to_string(s1.lens()[axis]) + ")");
}
std::vector<size_t> bcast_strides(s1.ndim(), 0);
std::copy(s0.strides().begin(), s0.strides().end(), bcast_strides.begin() + axis);
shape output{t, s1.lens(), std::move(bcast_strides)};
return output;
}
}
argument compute(shape output_shape, std::vector<argument> args) const
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
return args[0].reshape(output_shape);
return args[0].reshape(dyn_out.computed_shape);
}
std::ptrdiff_t output_alias(const std::vector<shape>&) const { return 0; }
};
......
src/include/migraphx/op/contiguous.hpp
View file @ 13ea6f19
......@@ -28,6 +28,7 @@
#include <migraphx/argument.hpp>
#include <migraphx/shape_for_each.hpp>
#include <migraphx/config.hpp>
#include <migraphx/dyn_output.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -42,19 +43,27 @@ namespace op {
struct contiguous
{
std::string name() const { return "contiguous"; }
shape compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this}.has(1);
if(inputs.front().standard())
return inputs.front();
auto lens = inputs.at(0).lens();
auto t = inputs.at(0).type();
return {t, lens};
check_shapes{inputs, *this, true}.has(1);
auto s0 = inputs.front();
if(s0.dynamic() or s0.standard())
{
return s0;
}
else
{
const auto& lens = s0.lens();
auto t = s0.type();
return {t, lens};
}
}
argument compute(const shape& output_shape, std::vector<argument> args) const
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
assert(output_shape.standard());
argument result{output_shape};
assert(dyn_out.computed_shape.standard());
argument result{dyn_out.computed_shape};
visit_all(result, args[0])([&](auto output, auto input) {
shape_for_each(output.get_shape(), [&](const auto& idx) {
output(idx.begin(), idx.end()) = input(idx.begin(), idx.end());
......
src/include/migraphx/op/layout.hpp 0 → 100644
View file @ 13ea6f19
/*
* 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/include/migraphx/op/multibroadcast.hpp
View file @ 13ea6f19
......@@ -26,64 +26,105 @@
#include <migraphx/check_shapes.hpp>
#include <migraphx/argument.hpp>
#include <migraphx/dyn_output.hpp>
#include <migraphx/common.hpp>
#include <migraphx/config.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {
/**
* Broadcast multiple dimensions between two tensors.
* Two versions of this operator: one input and two inputs.
* One input version uses output_lens attribute and broadcasts to it.
* Two inputs version broadcasts both inputs to the common shape at evaluation time.
*/
struct multibroadcast
{
std::vector<std::size_t> output_lens;
std::vector<std::size_t> output_lens = {};
// optional attribute
std::vector<shape::dynamic_dimension> output_dyn_dims = {};
template <class Self, class F>
static auto reflect(Self& self, F f)
{
return pack(f(self.output_lens, "out_lens"));
return pack(f(self.output_lens, "out_lens"), f(self.output_dyn_dims, "out_dyn_dims"));
}
std::string name() const { return "multibroadcast"; }
shape compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this}.has(1);
auto t = inputs.at(0).type();
auto input = inputs.at(0);
check_shapes{inputs, *this, true}.has(1, 2);
if(input.lens().empty())
{
MIGRAPHX_THROW("MULTIBROADCAST: inputs dimensions should be > 0");
}
auto t = inputs.at(0).type();
auto s0 = inputs.at(0);
if(input.lens().size() > output_lens.size())
if(s0.max_lens().empty())
{
MIGRAPHX_THROW("MULTIBROADCAST: inputs dimensions should <= output size");
MIGRAPHX_THROW("MULTIBROADCAST: input dimensions should be > 0");
}
auto offset = output_lens.size() - input.lens().size();
for(std::ptrdiff_t i = input.lens().size() - 1; i >= 0; i--)
auto make_bcast_strides = [&](std::vector<std::size_t> bcast_lens, std::size_t offset) {
std::vector<size_t> bcast_strides(bcast_lens.size(), 0);
for(std::ptrdiff_t i = s0.lens().size() - 1; i >= 0; i--)
{
if(bcast_lens[i + offset] == s0.lens()[i])
{
bcast_strides[i + offset] = s0.strides()[i];
}
}
return bcast_strides;
};
if(inputs.size() == 1)
{
if(output_lens[i + offset] != input.lens()[i] and input.lens()[i] != 1)
if(s0.lens().size() > output_lens.size())
{
MIGRAPHX_THROW("MULTIBROADCAST: input shape {" + to_string_range(input.lens()) +
"} cannot be broadcasted to {" + to_string_range(output_lens) +
"}!");
MIGRAPHX_THROW("MULTIBROADCAST: input dimensions should <= output size");
}
}
std::vector<size_t> bcast_strides(output_lens.size(), 0);
for(std::ptrdiff_t i = input.lens().size() - 1; i >= 0; i--)
auto offset = output_lens.size() - s0.lens().size();
for(std::ptrdiff_t i = s0.lens().size() - 1; i >= 0; i--)
{
if(output_lens[i + offset] != s0.lens()[i] and s0.lens()[i] != 1)
{
MIGRAPHX_THROW("MULTIBROADCAST: input shape {" + to_string_range(s0.lens()) +
"} cannot be broadcasted to {" + to_string_range(output_lens) +
"}!");
}
}
auto bcast_strides = make_bcast_strides(output_lens, offset);
return {t, output_lens, std::move(bcast_strides)};
}
else
{
if(output_lens[i + offset] == input.lens()[i])
// two inputs
auto s1 = inputs.at(1);
if(s0.dynamic() or s1.dynamic())
{
bcast_strides[i + offset] = input.strides()[i];
if(not output_dyn_dims.empty())
{
return {t, output_dyn_dims};
}
return {t, compute_broadcasted_dyn_dims(s0, s1)};
}
else
{
auto bcast_lens = compute_broadcasted_lens(s0.lens(), s1.lens());
auto offset = bcast_lens.size() - s0.lens().size();
auto bcast_strides = make_bcast_strides(bcast_lens, offset);
return {t, std::move(bcast_lens), std::move(bcast_strides)};
}
}
return {t, output_lens, bcast_strides};
}
argument compute(shape output_shape, std::vector<argument> args) const
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
return args[0].reshape(output_shape);
return args[0].reshape(dyn_out.computed_shape);
}
std::ptrdiff_t output_alias(const std::vector<shape>&) const { return 0; }
};
......
src/include/migraphx/op/squeeze.hpp
View file @ 13ea6f19
......@@ -29,6 +29,7 @@
#include <migraphx/config.hpp>
#include <migraphx/value.hpp>
#include <migraphx/op/normalize_attribute.hpp>
#include <migraphx/dyn_output.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
......@@ -54,52 +55,90 @@ struct squeeze
std::string name() const { return "squeeze"; }
shape normalize_compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this}.has(1);
check_shapes{inputs, *this, true}.has(1);
auto input_shape = inputs[0];
auto type = input_shape.type();
auto old_lens = input_shape.lens();
auto old_strides = input_shape.strides();
if(std::any_of(axes.begin(), axes.end(), [&](auto axis) { return old_lens[axis] != 1; }))
if(input_shape.dynamic())
{
MIGRAPHX_THROW("squeeze axis dimension should be equal to 1");
}
std::vector<std::size_t> new_lens;
std::vector<std::size_t> new_strides;
if(axes.empty())
{
for(auto i : range(old_lens.size()))
shape::dynamic_dimension one_dyn_dim{1, 1, 0};
if(std::any_of(axes.begin(), axes.end(), [&](auto axis) {
return input_shape.dyn_dims()[axis] != one_dyn_dim;
}))
{
MIGRAPHX_THROW(
"SQUEEZE: dynamic axis dimension should be equal to {1, 1, 0} or {1, 1, 1}");
}
std::vector<shape::dynamic_dimension> dyn_dims = {};
if(axes.empty())
{
if(old_lens[i] != 1)
for(auto i : range(input_shape.ndim()))
{
new_lens.push_back(old_lens[i]);
new_strides.push_back(old_strides[i]);
auto dd = input_shape.dyn_dims()[i];
if(dd != one_dyn_dim)
{
dyn_dims.push_back(dd);
}
}
}
}
else
{
for(auto i : range(old_lens.size()))
else
{
if(std::find(axes.begin(), axes.end(), i) == axes.end())
for(auto i : range(input_shape.ndim()))
{
new_lens.push_back(old_lens[i]);
new_strides.push_back(old_strides[i]);
if(std::find(axes.begin(), axes.end(), i) == axes.end())
{
dyn_dims.push_back(input_shape.dyn_dims()[i]);
}
}
}
}
if(new_lens.empty())
{
return shape{type};
return {input_shape.type(), dyn_dims};
}
else
{
return shape{type, new_lens, new_strides};
auto type = input_shape.type();
auto old_lens = input_shape.lens();
auto old_strides = input_shape.strides();
if(std::any_of(
axes.begin(), axes.end(), [&](auto axis) { return old_lens[axis] != 1; }))
{
MIGRAPHX_THROW("SQUEEZE: static axis dimension should be equal to 1");
}
std::vector<std::size_t> new_lens;
std::vector<std::size_t> new_strides;
if(axes.empty())
{
for(auto i : range(old_lens.size()))
{
if(old_lens[i] != 1)
{
new_lens.push_back(old_lens[i]);
new_strides.push_back(old_strides[i]);
}
}
}
else
{
for(auto i : range(old_lens.size()))
{
if(std::find(axes.begin(), axes.end(), i) == axes.end())
{
new_lens.push_back(old_lens[i]);
new_strides.push_back(old_strides[i]);
}
}
}
if(new_lens.empty())
{
return shape{type};
}
else
{
return shape{type, new_lens, new_strides};
}
}
}
argument compute(shape output_shape, std::vector<argument> args) const
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
return args[0].reshape(output_shape);
return args[0].reshape(dyn_out.computed_shape);
}
std::ptrdiff_t output_alias(const std::vector<shape>&) const { return 0; }
};
......
src/include/migraphx/op/unsqueeze.hpp
View file @ 13ea6f19
......@@ -29,11 +29,20 @@
#include <migraphx/config.hpp>
#include <migraphx/value.hpp>
#include <migraphx/op/normalize_attribute.hpp>
#include <migraphx/dyn_output.hpp>
namespace migraphx {
inline namespace MIGRAPHX_INLINE_NS {
namespace op {
/**
* Adds dimensions to a tensor based on the axes attribute.
* `axes` are based on the number of output shape dimensions and should not contain duplicates.
* `steps` are for modifying dimensions added to the middle of the original shape.
* Each step must be a factor of the original dimension.
* ex: unsqueeze(shape = [3, 4, 10], axes = [2, 4, 5], steps = [2]) -> shape = [3, 4, 2, 5, 1, 1]
* Dynamic shape version does not handle `steps`.
*/
struct unsqueeze
{
std::vector<int64_t> axes;
......@@ -56,63 +65,89 @@ struct unsqueeze
std::string name() const { return "unsqueeze"; }
shape normalize_compute_shape(std::vector<shape> inputs) const
{
check_shapes{inputs, *this}.has(1);
check_shapes{inputs, *this, true}.has(1);
auto input_shape = inputs[0];
auto type = input_shape.type();
auto old_lens = input_shape.lens();
auto old_strides = input_shape.strides();
if(input_shape.scalar())
if(input_shape.dynamic())
{
if(old_lens.size() == 1 and old_lens.front() == 1)
return shape{type, old_lens};
else
MIGRAPHX_THROW("UNSQUEEZE: Input must be a scalar");
if(not steps.empty())
{
MIGRAPHX_THROW("UNSQUEEZE_dyn: nonempty steps attribute");
}
std::vector<shape::dynamic_dimension> dyn_dims = {};
auto new_ndim = input_shape.ndim() + axes.size();
std::size_t k = 0;
for(auto i : range(new_ndim))
{
if(std::find(axes.begin(), axes.end(), i) != axes.end())
{
dyn_dims.push_back({1, 1, 0});
}
else
{
dyn_dims.push_back(input_shape.dyn_dims().at(k++));
}
}
return {input_shape.type(), dyn_dims};
}
else
{
auto type = input_shape.type();
auto old_lens = input_shape.lens();
auto old_strides = input_shape.strides();
if(input_shape.scalar())
{
if(old_lens.size() == 1 and old_lens.front() == 1)
return shape{type, old_lens};
else
MIGRAPHX_THROW("UNSQUEEZE: Input must be a scalar");
}
if(steps.size() > axes.size())
MIGRAPHX_THROW("UNSQUEEZE: Steps provided with no axis");
if(steps.size() > axes.size())
MIGRAPHX_THROW("UNSQUEEZE: Steps provided with no axis");
std::size_t new_size = old_lens.size() + axes.size();
std::size_t new_size = old_lens.size() + axes.size();
std::vector<std::size_t> new_lens(new_size);
std::vector<std::size_t> new_strides(new_size);
std::size_t p = 0;
for(auto i : range(new_size))
{
auto axis_idx = std::find(axes.begin(), axes.end(), i) - axes.begin();
if(axis_idx < axes.size())
std::vector<std::size_t> new_lens(new_size);
std::vector<std::size_t> new_strides(new_size);
std::size_t p = 0;
for(auto i : range(new_size))
{
std::int64_t step = 1;
if(axis_idx < steps.size())
step = steps[axis_idx];
if(step == 0)
MIGRAPHX_THROW("UNSQUEEZE: step must be non-zero");
new_lens[i] = step;
if(p < old_strides.size())
auto axis_idx = std::find(axes.begin(), axes.end(), i) - axes.begin();
if(axis_idx < axes.size())
{
if((old_lens[p] % step) != 0)
MIGRAPHX_THROW("UNSQUEEZE: Axis dimenstion is not divisible by step");
old_lens[p] /= step;
new_strides[i] = old_strides[p] * old_lens[p];
std::int64_t step = 1;
if(axis_idx < steps.size())
step = steps[axis_idx];
if(step == 0)
MIGRAPHX_THROW("UNSQUEEZE: step must be non-zero");
new_lens[i] = step;
if(p < old_strides.size())
{
if((old_lens[p] % step) != 0)
MIGRAPHX_THROW("UNSQUEEZE: Axis dimenstion is not divisible by step");
old_lens[p] /= step;
new_strides[i] = old_strides[p] * old_lens[p];
}
else
{
if(step != 1)
MIGRAPHX_THROW("UNSQUEEZE: Step must be 1 for extra axes");
new_strides[i] = 1;
}
}
else
{
if(step != 1)
MIGRAPHX_THROW("UNSQUEEZE: Step must be 1 for extra axes");
new_strides[i] = 1;
new_lens[i] = old_lens[p];
new_strides[i] = old_strides[p++];
}
}
else
{
new_lens[i] = old_lens[p];
new_strides[i] = old_strides[p++];
}
return shape{type, new_lens, new_strides};
}
return shape{type, new_lens, new_strides};
}
argument compute(shape output_shape, std::vector<argument> args) const
argument compute(const dyn_output& dyn_out, std::vector<argument> args) const
{
return args[0].reshape(output_shape);
return args[0].reshape(dyn_out.computed_shape);
}
std::ptrdiff_t output_alias(const std::vector<shape>&) const { return 0; }
};
......
src/include/migraphx/shape.hpp
View file @ 13ea6f19
......@@ -30,6 +30,7 @@
#include <numeric>
#include <memory>
#include <migraphx/functional.hpp>
#include <migraphx/errors.hpp>
#include <migraphx/half.hpp>
#include <migraphx/config.hpp>
......@@ -89,7 +90,10 @@ struct shape
std::size_t opt = 0;
template <class Self, class F>
static auto reflect(Self& self, F f);
static auto reflect(Self& self, F f)
{
return pack(f(self.min, "min"), f(self.max, "max"), f(self.opt, "opt"));
}
bool is_fixed() const;
bool has_optimal() const;
......@@ -115,6 +119,12 @@ struct shape
shape(type_t t, std::vector<dynamic_dimension> dims);
// Construct a dynamic shape from three sets of lengths (of the same rank)
shape(type_t t,
std::vector<std::size_t> mins,
std::vector<std::size_t> maxes,
std::vector<std::size_t> opts);
template <class Range>
shape(type_t t, const Range& l) : shape(t, std::vector<std::size_t>(l.begin(), l.end()))
{
......@@ -227,6 +237,9 @@ struct shape
shape with_type(type_t t) const;
// convert the shape to an equivalent dynamic shape
shape to_dynamic() const;
friend bool operator==(const shape& x, const shape& y);
friend bool operator!=(const shape& x, const shape& y);
friend std::ostream& operator<<(std::ostream& os, const shape& x);
......
src/instruction.cpp 100644 → 100755
View file @ 13ea6f19
File mode changed from 100644 to 100755
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