Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Rework split_reshape simplification to handle multiple reshapes from same slice #2146

Merged
merged 13 commits into from
Sep 19, 2023
Merged

Rework split_reshape simplification to handle multiple reshapes from same slice #2146

Show file tree
Hide file tree
Changes from 9 commits
Commits
Show all changes
13 commits
Select commit Hold shift + click to select a range
7b68324
split_reshape bug fix
shivadbhavsar Aug 31, 2023
47ebed5
Merge branch 'develop' into fix_split_reshape
shivadbhavsar Aug 31, 2023
d103134
allow slice reshape simplification for multiple reshapes from single …
shivadbhavsar Sep 6, 2023
4b286e5
use elements() to get arg size
shivadbhavsar Sep 6, 2023
f3ccae3
Merge branch 'develop' into fix_split_reshape
shivadbhavsar Sep 6, 2023
6f5ade4
Merge branch 'develop' into fix_split_reshape
shivadbhavsar Sep 7, 2023
a349cf0
handle edge case where dimension is not a multiple of the split sizes
shivadbhavsar Sep 7, 2023
dfe9465
add test case for invalid reshape axis len
shivadbhavsar Sep 8, 2023
50cccbe
Merge branch 'develop' into fix_split_reshape
shivadbhavsar Sep 8, 2023
0849f48
add check for single axis when performing split reshape simplification
shivadbhavsar Sep 18, 2023
2ebb711
add comments with examples for clarity
shivadbhavsar Sep 19, 2023
01f35e5
add additional test case for slice_reshape
shivadbhavsar Sep 19, 2023
3400122
Merge branch 'develop' into fix_split_reshape
shivadbhavsar Sep 19, 2023
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
84 changes: 55 additions & 29 deletions src/simplify_algebra.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1330,34 +1330,36 @@ struct find_split_reshape

auto input = slc->inputs().front();
auto split_outputs = get_splits(input);

if(split_outputs.empty())
{
return;
}

// Only want to apply this optimization if each split output is followed by
// a contiguous op and a reshape
if(std::any_of(split_outputs.begin(), split_outputs.end(), [](auto i) {
if(i->outputs().size() == 1)
{
auto cont = i->outputs().front();
return cont->outputs().size() != 1;
}
return false;
}))
// Find all the reshapes (similar to rsp) that can be simplified
std::vector<instruction_ref> conts;
std::vector<instruction_ref> vec_rsp;

// Iterate through slice and contiguous outputs to allow simplifications when
// slice is followed by multiple reshapes
for(auto& i : split_outputs)
{
return;
std::copy_if(i->outputs().begin(),
i->outputs().end(),
std::back_inserter(conts),
[](auto j) { return j->name() == "contiguous"; });
}

std::vector<instruction_ref> vec_rsp(split_outputs.size());
std::transform(split_outputs.begin(), split_outputs.end(), vec_rsp.begin(), [](auto i) {
auto cont = i->outputs().front();
return cont->outputs().front();
});
for(auto& i : conts)
{
std::copy_if(i->outputs().begin(),
i->outputs().end(),
std::back_inserter(vec_rsp),
[&](auto j) { return j->get_operator() == rsp->get_operator(); });
}

// all outputs are reshape and of the same shape
auto dims = any_cast<op::reshape>(rsp->get_operator()).dims;
if(not same_ops(vec_rsp))
// No simplification needed if there is only one slice -> cont -> reshape
if(vec_rsp.size() <= 1)
{
return;
}
Expand All @@ -1367,6 +1369,9 @@ struct find_split_reshape
auto slc_lens = slc->get_shape().lens();
auto slc_dim_size = std::accumulate(
slc_lens.begin() + axis, slc_lens.end(), 1, std::multiplies<std::size_t>());
auto input_lens = input->get_shape().lens();
auto input_size = input->get_shape().elements();
auto slc_axis_len = input_lens[axis];
umangyadav marked this conversation as resolved.
Show resolved Hide resolved

// search the reshape output (standard shape) to decide which axis are
// in its output corresponding to the slc_dim_size
Expand All @@ -1393,16 +1398,39 @@ struct find_split_reshape
{
rsp_axis = std::distance(rsp_strides.begin(), ait);
}
// calculate reshape output shape
std::vector<int64_t> vec_dims(vec_rsp.size());

std::transform(vec_rsp.begin(), vec_rsp.end(), vec_dims.begin(), [&](auto is) {
return is->get_shape().lens()[rsp_axis];
});

// calculate reshape output shape
std::vector<int64_t> rsp_out_lens(rsp_lens.begin(), rsp_lens.end());
rsp_out_lens[rsp_axis] = 1;
auto rsp_fixed_size = std::accumulate(
rsp_out_lens.begin(), rsp_out_lens.end(), 1, std::multiplies<std::size_t>());
// cannot create a valid reshape for simplification
if(input_size % rsp_fixed_size != 0)
{
return;
Copy link
Collaborator

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

Is it possible to add a unit test for this case?

Copy link
Contributor Author

Choose a reason for hiding this comment

The reason will be displayed to describe this comment to others. Learn more.

added

}
auto rsp_axis_len = input_size / rsp_fixed_size;
rsp_out_lens[rsp_axis] = rsp_axis_len;

// calculate new slice start and end indices
// indices are scaled using the new reshape axis and the original slice axis
// eg. slice with size [1, 2, 4, 30] can be reshaped to [8, 30] and vice-versa

std::vector<int64_t> new_starts(vec_rsp.size());
std::transform(vec_rsp.begin(), vec_rsp.end(), new_starts.begin(), [&](auto is) {
auto cont = is->inputs().front();
auto og_slc = cont->inputs().front();
return any_cast<op::slice>(og_slc->get_operator()).starts[0] * rsp_axis_len /
slc_axis_len;
umangyadav marked this conversation as resolved.
Show resolved Hide resolved
});

rsp_out_lens[rsp_axis] = std::accumulate(vec_dims.begin(), vec_dims.end(), std::int64_t{0});
std::vector<int64_t> new_ends(vec_rsp.size());
std::transform(vec_rsp.begin(), vec_rsp.end(), new_ends.begin(), [&](auto is) {
auto cont = is->inputs().front();
auto og_slc = cont->inputs().front();
return any_cast<op::slice>(og_slc->get_operator()).ends[0] * rsp_axis_len /
slc_axis_len;
});

// insert the reshape instruction and add contiguous if needed
if(not input->get_shape().standard())
Expand All @@ -1413,16 +1441,14 @@ struct find_split_reshape
std::next(input), make_op("reshape", {{"dims", rsp_out_lens}}), input);

// replace the original reshape with slice
int64_t start = 0;
for(std::size_t i = 0; i < vec_rsp.size(); ++i)
{
m.replace_instruction(
vec_rsp[i],
make_op(
"slice",
{{"axes", {rsp_axis}}, {"starts", {start}}, {"ends", {start + vec_dims[i]}}}),
{{"axes", {rsp_axis}}, {"starts", {new_starts[i]}}, {"ends", {new_ends[i]}}}),
rsp_ins);
start += vec_dims[i];
}
}
};
Expand Down
145 changes: 142 additions & 3 deletions test/simplify_algebra_test.cpp
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2910,6 +2910,126 @@ TEST_CASE(reorder_reshape_slice_not_apply)
EXPECT(m1.sort() == m2.sort());
}

TEST_CASE(reorder_reshape_slice_multi_rsp)
{
migraphx::module m1;
{
migraphx::shape s{migraphx::shape::float_type, {4, 128, 3, 32, 80}};
auto input = m1.add_parameter("input", s);
auto t1 = m1.add_instruction(
migraphx::make_op("transpose", {{"permutation", {2, 0, 3, 1, 4}}}), input);
auto slc0 = m1.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {1}}}), t1);
auto slc1 = m1.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {1}}, {"ends", {2}}}), t1);
auto slc2 = m1.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {2}}, {"ends", {3}}}), t1);

auto c1_1 = m1.add_instruction(migraphx::make_op("contiguous"), slc1);
auto c2_1 = m1.add_instruction(migraphx::make_op("contiguous"), slc2);

auto c1 = m1.add_instruction(migraphx::make_op("contiguous"), slc1);
auto r1 =
m1.add_instruction(migraphx::make_op("reshape", {{"dims", {4, 32, 128, 80}}}), c1);

auto c2 = m1.add_instruction(migraphx::make_op("contiguous"), slc2);
auto r2 =
m1.add_instruction(migraphx::make_op("reshape", {{"dims", {4, 32, 128, 80}}}), c2);

auto r1_1 =
m1.add_instruction(migraphx::make_op("reshape", {{"dims", {128, 128, 80}}}), c1_1);
auto r2_1 =
m1.add_instruction(migraphx::make_op("reshape", {{"dims", {128, 128, 80}}}), c2_1);

auto c0 = m1.add_instruction(migraphx::make_op("contiguous"), slc0);
auto r0 = m1.add_instruction(migraphx::make_op("reshape", {{"dims", {128, 128, 80}}}), c0);

auto t2 =
m1.add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 2, 1}}}), r1_1);
auto c_t2 = m1.add_instruction(migraphx::make_op("contiguous"), t2);

auto dot = m1.add_instruction(migraphx::make_op("dot"), r0, c_t2);

m1.add_return({r1, r2, dot, r2_1});
};

migraphx::module m2;
{
migraphx::shape s{migraphx::shape::float_type, {4, 128, 3, 32, 80}};
auto input = m2.add_parameter("input", s);
auto t1 = m2.add_instruction(
migraphx::make_op("transpose", {{"permutation", {2, 0, 3, 1, 4}}}), input);
auto c_t1 = m2.add_instruction(migraphx::make_op("contiguous"), t1);
auto rsp1 =
m2.add_instruction(migraphx::make_op("reshape", {{"dims", {384, 128, 80}}}), c_t1);
auto slc0 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {256}}, {"ends", {384}}}), rsp1);
auto slc1 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {128}}, {"ends", {256}}}), rsp1);

auto t_slc1 =
m2.add_instruction(migraphx::make_op("transpose", {{"permutation", {0, 2, 1}}}), slc1);
auto c_t_slc1 = m2.add_instruction(migraphx::make_op("contiguous"), t_slc1);

auto slc2 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {128}}}), rsp1);

auto dot = m2.add_instruction(migraphx::make_op("dot"), slc2, c_t_slc1);

auto c_t1_1 = m2.add_instruction(migraphx::make_op("contiguous"), t1);
auto rsp2 =
m2.add_instruction(migraphx::make_op("reshape", {{"dims", {12, 32, 128, 80}}}), c_t1_1);

auto slc2_1 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {4}}, {"ends", {8}}}), rsp2);

auto slc2_2 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {8}}, {"ends", {12}}}), rsp2);

m2.add_return({slc2_1, slc2_2, dot, slc0});
};

run_pass(m1);
EXPECT(m1.sort() == m2.sort());
}

TEST_CASE(reorder_reshape_slice_uneven_slice)
{
auto create_p = [] {
migraphx::module m;
migraphx::shape s{migraphx::shape::float_type, {128, 96}};
auto input = m.add_parameter("input", s);
auto slc0 = m.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {0}}, {"ends", {31}}}), input);
auto slc1 = m.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {31}}, {"ends", {62}}}), input);
auto slc2 = m.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {62}}, {"ends", {93}}}), input);
auto slc3 = m.add_instruction(
migraphx::make_op("slice", {{"axes", {0}}, {"starts", {93}}, {"ends", {128}}}), input);

auto c0 = m.add_instruction(migraphx::make_op("contiguous"), slc0);
auto c1 = m.add_instruction(migraphx::make_op("contiguous"), slc1);
auto c2 = m.add_instruction(migraphx::make_op("contiguous"), slc2);

std::vector<int64_t> lens = {1, 31, 96};
auto r0 = m.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), c0);
auto r1 = m.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), c1);
auto r2 = m.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), c2);

auto sum = m.add_instruction(migraphx::make_op("add"), r0, r1);
auto ret = m.add_instruction(migraphx::make_op("mul"), sum, r2);
m.add_return({ret, slc3});

return m;
};

auto m1 = create_p();
auto m2 = m1;
run_pass(m1);
EXPECT(m1.sort() == m2.sort());
}

template <std::size_t BS>
void reorder_reshape_slice_diff_dims()
{
Expand All @@ -2931,13 +3051,32 @@ void reorder_reshape_slice_diff_dims()
std::vector<int64_t> lens = {static_cast<int64_t>(BS), 32, 3, 32};
std::vector<int64_t> lens1 = {static_cast<int64_t>(BS), 48, 2, 32};
auto r0 = m1.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), c0);
auto r1 = m1.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), c1);
auto r2 = m1.add_instruction(migraphx::make_op("reshape", {{"dims", lens1}}), c2);
auto r1 = m1.add_instruction(migraphx::make_op("reshape", {{"dims", lens1}}), c1);
auto r2 = m1.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), c2);

m1.add_return({r0, r1, r2});
};

auto m2 = m1;
migraphx::module m2;
{
auto s = migraphx::shape{migraphx::shape::float_type, {BS, 96, 96}};
auto input = m2.add_parameter("input", s);
auto slc1 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {2}}, {"starts", {32}}, {"ends", {64}}}), input);
auto c1 = m2.add_instruction(migraphx::make_op("contiguous"), slc1);
std::vector<int64_t> lens1 = {static_cast<int64_t>(BS), 48, 2, 32};
auto r1 = m2.add_instruction(migraphx::make_op("reshape", {{"dims", lens1}}), c1);

std::vector<int64_t> lens = {static_cast<int64_t>(BS), 32, 3, 96};
auto r_new = m2.add_instruction(migraphx::make_op("reshape", {{"dims", lens}}), input);
auto slc0 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {3}}, {"starts", {0}}, {"ends", {32}}}), r_new);
auto slc2 = m2.add_instruction(
migraphx::make_op("slice", {{"axes", {3}}, {"starts", {64}}, {"ends", {96}}}), r_new);

m2.add_return({slc0, r1, slc2});
};

run_pass(m1);
EXPECT(m1.sort() == m2.sort());
}
Expand Down
Loading