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authorGian Marco Iodice <gianmarco.iodice@arm.com>2018-07-26 11:44:03 +0100
committerAnthony Barbier <anthony.barbier@arm.com>2018-11-02 16:54:54 +0000
commit68a3f56627b04acdefebe67d645727dd83889766 (patch)
tree4a3f4dc0facfda861a5ba7afa29d84d82d0829c2 /src/runtime/CL/functions/CLGEMM.cpp
parent4e0d3819be6c61cc00c7e0fa9b4b740738c703b7 (diff)
downloadComputeLibrary-68a3f56627b04acdefebe67d645727dd83889766.tar.gz
COMPMID-1276 - Allow GEMM to work with 3D input tensor
Skipped im2col in CLGEMMConvolutionLayer for 1x1 convolutions with NHWC data layout Change-Id: I894e6b952ed8605e8f3ffc0ffc25c24730d4664c Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/141909 Tested-by: Jenkins <bsgcomp@arm.com> Reviewed-by: Anthony Barbier <anthony.barbier@arm.com> Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Diffstat (limited to 'src/runtime/CL/functions/CLGEMM.cpp')
-rw-r--r--src/runtime/CL/functions/CLGEMM.cpp32
1 files changed, 24 insertions, 8 deletions
diff --git a/src/runtime/CL/functions/CLGEMM.cpp b/src/runtime/CL/functions/CLGEMM.cpp
index 1f4df4f1a9..1d1b17bbf1 100644
--- a/src/runtime/CL/functions/CLGEMM.cpp
+++ b/src/runtime/CL/functions/CLGEMM.cpp
@@ -102,7 +102,8 @@ void CLGEMM::configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *
// Arguments used by GEMMReshapeInfo
// If we pass the matrix A and matrix B reshaped to CLGEMMMatrixMultiplyKernel, we need to pass m, n, k, mult_transpose1xW_width and mult_interleave4x4_height to CLGEMMReshapeInfo
// in order to know how the matrices have been reshaped
- const int m = a->info()->dimension(1);
+ bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
+ const int m = reinterpret_input_as_3d ? (a->info()->dimension(1) * a->info()->dimension(2)) : a->info()->dimension(1);
const int n = b->info()->dimension(0);
const int k = a->info()->dimension(0);
const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
@@ -118,6 +119,12 @@ void CLGEMM::configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *
// Check if we need to reshape the matrix A and matrix B
_is_interleaved_transposed = is_interleaved_transposed(m, n, k, a->info()->data_type(), _reshape_b_only_on_first_run, gpu_target);
+ // if _is_interleaved_transposed is set, force reinterpret_input_as_3d to be false as the output of CLGEMMInterleaveKernel will be 2D
+ if(_is_interleaved_transposed)
+ {
+ reinterpret_input_as_3d = false;
+ }
+
if(_is_interleaved_transposed)
{
matrix_a = &_tmp_a;
@@ -132,14 +139,15 @@ void CLGEMM::configure(const ICLTensor *a, const ICLTensor *b, const ICLTensor *
// _tmp_a and _tmp_b will be auto configured in _interleave_kernel and in _transpose_kernel
// Configure interleave kernel
- _interleave_kernel.configure(a, &_tmp_a, mult_interleave4x4_height);
+ _interleave_kernel.configure(a, &_tmp_a, mult_interleave4x4_height, gemm_info.reinterpret_input_as_3d());
// Configure transpose kernel
_transpose_kernel.configure(b, &_tmp_b, mult_transpose1xW_width);
}
// Configure and tune matrix multiply kernel
- _mm_kernel.configure(matrix_a, matrix_b, output, alpha, _is_interleaved_transposed, GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height, depth_output_gemm3d));
+ _mm_kernel.configure(matrix_a, matrix_b, output, alpha, _is_interleaved_transposed, GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height, depth_output_gemm3d,
+ reinterpret_input_as_3d));
CLScheduler::get().tune_kernel_static(_mm_kernel);
if(_is_interleaved_transposed)
@@ -180,11 +188,13 @@ Status CLGEMM::validate(const ITensorInfo *a, const ITensorInfo *b, const ITenso
// Arguments used by GEMMReshapeInfo
// If we pass the matrix A and matrix B reshaped to CLGEMMMatrixMultiplyKernel, we need to pass m, n, k, mult_transpose1xW_width and mult_interleave4x4_height to CLGEMMReshapeInfo
// in order to know how the matrices have been reshaped
- const int m = a->dimension(1);
+ bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
+ const int m = reinterpret_input_as_3d ? (a->dimension(1) * a->dimension(2)) : a->dimension(1);
const int n = b->dimension(0);
const int k = a->dimension(0);
int mult_transpose1xW_width = 1;
int mult_interleave4x4_height = 1;
+ const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
if(get_arch_from_target(gpu_target) == GPUTarget::BIFROST)
{
@@ -192,19 +202,25 @@ Status CLGEMM::validate(const ITensorInfo *a, const ITensorInfo *b, const ITenso
mult_interleave4x4_height = 2;
}
- const GEMMReshapeInfo reshape_info = GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height, gemm_info.depth_output_gemm3d());
-
// Check if we need to reshape the matrix A and matrix B
const bool run_interleave_transpose = is_interleaved_transposed(m, n, k, a->data_type(), reshape_b_only_on_first_run, gpu_target);
+ // if _is_interleaved_transposed is set, force reinterpret_input_as_3d to be false as the output of CLGEMMInterleaveKernel will be 2D
+ if(run_interleave_transpose)
+ {
+ reinterpret_input_as_3d = false;
+ }
+
+ const GEMMReshapeInfo reshape_info = GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height, depth_output_gemm3d, reinterpret_input_as_3d);
+
if(run_interleave_transpose)
{
matrix_a_info = &tmp_a_info;
matrix_b_info = &tmp_b_info;
// Validate interleave kernel
- auto_init_if_empty(tmp_a_info, a->clone()->set_tensor_shape(compute_interleaved_shape(*a, mult_interleave4x4_height)));
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMInterleave4x4Kernel::validate(a, &tmp_a_info, mult_interleave4x4_height));
+ auto_init_if_empty(tmp_a_info, a->clone()->set_tensor_shape(compute_interleaved_shape(*a, mult_interleave4x4_height, gemm_info.reinterpret_input_as_3d())));
+ ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMInterleave4x4Kernel::validate(a, &tmp_a_info, mult_interleave4x4_height, gemm_info.reinterpret_input_as_3d()));
// Validate transpose kernel
auto_init_if_empty(tmp_b_info, b->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(*b, mult_transpose1xW_width)));