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

Jump to bottom

[CHERRY-PICK] Fix for matmul_v2 oneDNN op broadcasting when inputs dims have different lengths #38733

Merged
merged 2 commits into from
Jan 6, 2022
Merged

[CHERRY-PICK] Fix for matmul_v2 oneDNN op broadcasting when inputs dims have different lengths #38733

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a840ef7
fix for matmul_v2 broadcasting
jakpiase Jan 3, 2022
bcadf96
resolved conflicts
jakpiase Jan 4, 2022
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
68 changes: 44 additions & 24 deletions paddle/fluid/operators/mkldnn/matmul_v2_mkldnn_op.cc
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -152,7 +152,7 @@ class MatMulV2MKLDNNKernel
x_bd_dims[x_bd_dims.size() - 2] = x_dims[0];
} else {
for (size_t i = 0; i < x_dims.size(); ++i) {
x_bd_dims[i] = x_dims[i];
x_bd_dims[x_bd_dims.size() - x_dims.size() + i] = x_dims[i];
}
}
if (y_dims.size() == 1) {
Expand All @@ -162,20 +162,21 @@ class MatMulV2MKLDNNKernel
y_bd_dims[y_bd_dims.size() - 2] = y_dims[0];
} else {
for (size_t i = 0; i < y_dims.size(); ++i) {
y_bd_dims[i] = y_dims[i];
y_bd_dims[y_bd_dims.size() - y_dims.size() + i] = y_dims[i];
}
}

if ((y_dims.size() == x_dims.size()) && y_dims.size() > 2) {
for (size_t i = 0; i < x_dims.size() - 2; ++i) {
if (x_dims.size() > 2 && y_dims.size() > 2) {
for (size_t i = 0; i < x_bd_dims.size() - 2; ++i) {
PADDLE_ENFORCE_EQ(
x_dims[i] == y_dims[i] || x_dims[i] == 1 || y_dims[i] == 1, true,
paddle::platform::errors::InvalidArgument(
"Tensor dimensions are incorrect for broadcasting."
"Dimensions in X and Y must be same or equal to 1, but "
"received x_dim[%d]=%d and y_dims[%d]= %d",
i, x_dims[i], i, y_dims[i]));
out_dims[i] = std::max(x_dims[i], y_dims[i]);
x_bd_dims[i] == y_bd_dims[i] || x_bd_dims[i] == 1 ||
y_bd_dims[i] == 1,
true, paddle::platform::errors::InvalidArgument(
"Tensor dimensions are incorrect for broadcasting."
"Dimensions in X and Y must be same or equal to 1, but "
"received x_dim[%d]=%d and y_dims[%d]= %d",
i, x_bd_dims[i], i, y_bd_dims[i]));
out_dims[i] = std::max(x_bd_dims[i], y_bd_dims[i]);
}
out->Resize(make_ddim(out_dims));
}
Expand Down Expand Up @@ -237,11 +238,11 @@ class MatMulV2GradMKLDNNKernel : public MatMulV2MKLDNNKernel<T> {
dy_tmp->mutable_data<T>(ctx.GetPlace());
}

void ReduceSumForMatmulGradOutput(const ExecutionContext& ctx,
const MKLDNNDeviceContext& dev_ctx,
const mkldnn::engine onednn_engine,
const Tensor* dx_tmp, Tensor* dx,
std::vector<int64_t> dx_dims) const {
void ReduceSumForMatmulGradOutput(
const ExecutionContext& ctx, const MKLDNNDeviceContext& dev_ctx,
const dnnl::engine onednn_engine, const Tensor* dx_tmp, Tensor* dx,
std::vector<int64_t>& dx_dims,
const std::vector<int64_t>& squeezed_dims) const {
paddle::platform::ReductionMKLDNNHandler<T> handler(
dnnl::algorithm::reduction_sum, 0.0f, 0.0f, onednn_engine,
ctx.GetPlace(), dx_tmp, dx, dx_dims);
Expand All @@ -257,6 +258,19 @@ class MatMulV2GradMKLDNNKernel : public MatMulV2MKLDNNKernel<T> {

reduction_p->execute(astream, reduction_args);
astream.wait();

dx->set_format(paddle::platform::GetMKLDNNFormat(
dst_memory_p->get_desc().reshape(squeezed_dims)));
}

std::vector<int64_t> ExtendDimsWithOnes(const std::vector<int64_t>& dims,
int new_size) const {
std::vector<int64_t> new_dims(new_size, 1);
for (size_t i = 0; i < dims.size(); ++i) {
new_dims[new_size - dims.size() + i] = dims[i];
}

return new_dims;
}

void RunKernel(const ExecutionContext& ctx) const {
Expand Down Expand Up @@ -295,8 +309,14 @@ class MatMulV2GradMKLDNNKernel : public MatMulV2MKLDNNKernel<T> {
bool trans_y = ctx.Attr<bool>("trans_y");
auto dout_dims = vectorize(dout->dims());

int ndims = std::max(x->dims().size(), y->dims().size());
ndims = std::max(ndims, 3);
size_t ndims = std::max(x->dims().size(), y->dims().size());
ndims = std::max<size_t>(ndims, 3);

if (x_dims.size() != ndims) {
x_dims = ExtendDimsWithOnes(x_dims, ndims);
} else if (y_dims.size() != ndims) {
y_dims = ExtendDimsWithOnes(y_dims, ndims);
}

// in broadcasting scenario new memory is required because
// reduce sum must be calculated upon broadcasted dims
Expand Down Expand Up @@ -340,21 +360,21 @@ class MatMulV2GradMKLDNNKernel : public MatMulV2MKLDNNKernel<T> {

if (x_dims != dx_bd_dims) {
ReduceSumForMatmulGradOutput(ctx, dev_ctx, onednn_engine, &dx_tmp, dx,
x_dims);
x_dims,
paddle::framework::vectorize(x->dims()));
} else {
*dx = std::move(dx_tmp);
}
if (y_dims != dy_bd_dims) {
ReduceSumForMatmulGradOutput(ctx, dev_ctx, onednn_engine, &dy_tmp, dy,
y_dims);
y_dims,
paddle::framework::vectorize(y->dims()));
} else {
*dy = std::move(dy_tmp);
}

dx->set_layout(paddle::framework::DataLayout::kMKLDNN);
dx->set_format(x->format());
dy->set_layout(paddle::framework::DataLayout::kMKLDNN);
dy->set_format(y->format());
dx->Resize(x->dims());
dy->Resize(y->dims());
}
};
} // anonymous namespace
Expand Down
35 changes: 35 additions & 0 deletions python/paddle/fluid/tests/unittests/mkldnn/test_matmul_v2_mkldnn_op.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -251,6 +251,41 @@ def config(self):
self.trans_y = False


class TestMatMulV2MatrixXMatrix4Dx3DTransposeXOneDNNOp(
TestMatMulV2VectorXVectorOneDNNOp):
def config(self):
self.x_shape = (5, 4, 15, 10)
self.y_shape = (1, 15, 20)
self.trans_x = True
self.trans_y = False


class TestMatMulV2MatrixXMatrix3Dx4DTransposeYOneDNNOp(
TestMatMulV2VectorXVectorOneDNNOp):
def config(self):
self.x_shape = (2, 10, 15)
self.y_shape = (4, 2, 20, 15)
self.trans_x = False
self.trans_y = True


class TestMatMulV2MatrixXMatrix5Dx3DTransposeXTransposeYOneDNNOp(
TestMatMulV2VectorXVectorOneDNNOp):
def config(self):
self.x_shape = (4, 3, 2, 15, 10)
self.y_shape = (1, 20, 15)
self.trans_x = True
self.trans_y = True


class TestMatMulV2MatrixXMatrix3Dx4DOneDNNOp(TestMatMulV2VectorXVectorOneDNNOp):
def config(self):
self.x_shape = (1, 1, 32, 16)
self.y_shape = (16, 16, 16)
self.trans_x = False
self.trans_y = False


# BF16 TESTS
def create_bf16_test_class(parent):
@OpTestTool.skip_if_not_cpu_bf16()
Expand Down