COMPMID-1518: Add support for GEMM3D in CLGEMMLowpMatrixMultiplyCore
Change-Id: Ib14ac821ee5d4aff80bd602cd3e76e7018abb5e6
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/150268
Tested-by: bsgcomp <bsgcomp@arm.com>
Reviewed-by: Isabella Gottardi <isabella.gottardi@arm.com>
Reviewed-by: Michele DiGiorgio <michele.digiorgio@arm.com>
diff --git a/src/runtime/CL/functions/CLGEMM.cpp b/src/runtime/CL/functions/CLGEMM.cpp
index 9dbfd3e..821464e 100644
--- a/src/runtime/CL/functions/CLGEMM.cpp
+++ b/src/runtime/CL/functions/CLGEMM.cpp
@@ -72,8 +72,18 @@
} // namespace
CLGEMM::CLGEMM(std::shared_ptr<IMemoryManager> memory_manager)
- : _memory_group(std::move(memory_manager)), _interleave_kernel(), _transpose_kernel(), _mm_kernel(), _ma_kernel(), _tmp_a(), _tmp_b(), _original_b(nullptr), _is_interleaved_transposed(false),
- _run_addition(false), _reshape_b_only_on_first_run(false), _is_prepared(false)
+ : _memory_group(std::move(memory_manager)),
+ _interleave_kernel(),
+ _transpose_kernel(),
+ _mm_kernel(),
+ _ma_kernel(),
+ _tmp_a(),
+ _tmp_b(),
+ _original_b(nullptr),
+ _is_interleaved_transposed(false),
+ _run_addition(false),
+ _reshape_b_only_on_first_run(false),
+ _is_prepared(false)
{
}
@@ -146,8 +156,9 @@
}
// 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,
- reinterpret_input_as_3d));
+ _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)
diff --git a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
index c9daea4..bd5e969 100644
--- a/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
+++ b/src/runtime/CL/functions/CLGEMMConvolutionLayer.cpp
@@ -130,9 +130,10 @@
{
const bool is_quantized = is_data_type_quantized_asymmetric(input->data_type());
- const GEMMInfo &gemm_info = GEMMInfo(false, false, true /* Reshape weights only for the first run */, gemm_3d_depth, skip_im2col /* Reinterpret the input as 3D if im2col is skipped */);
if(is_quantized)
{
+ const GEMMInfo &gemm_info = GEMMInfo(false, false, true /* Reshape weights only for the first run */);
+
// Since we need negative offsets for computing convolution, we need to change QuantizationInfo()
// Extract and negate input and weights offset
const QuantizationInfo input_quantization_info = input->quantization_info();
@@ -148,6 +149,8 @@
}
else
{
+ const GEMMInfo &gemm_info = GEMMInfo(false, false, true /* Reshape weights only for the first run */, gemm_3d_depth, skip_im2col /* Reinterpret the input as 3D if im2col is skipped */);
+
// Perform validation step on Matrix multiply function
return CLGEMM::validate(input, weights, nullptr, output, 1.0f, 0.0f, gemm_info);
}
diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
index 763ebce..1d6f343 100644
--- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
@@ -107,15 +107,23 @@
// 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
+ bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
const int m = 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();
constexpr int mult_transpose1xW_width = 1;
constexpr int mult_interleave4x4_height = 1;
// Check if we need to reshape the matrix A and matrix B
_is_interleaved_transposed = is_interleaved_transposed(m, n, k, _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;
@@ -128,14 +136,15 @@
}
// Configure interleave kernel
- _mtx_a_reshape_kernel.configure(a, &_tmp_a, mult_interleave4x4_height);
+ _mtx_a_reshape_kernel.configure(a, &_tmp_a, mult_interleave4x4_height, gemm_info.reinterpret_input_as_3d());
// Configure transpose kernel
_mtx_b_reshape_kernel.configure(b, &_tmp_b, mult_transpose1xW_width);
}
-
// Configure matrix multiply kernel
- _mm_kernel.configure(matrix_a, matrix_b, output, _is_interleaved_transposed, GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height));
+ _mm_kernel.configure(matrix_a, matrix_b, output, _is_interleaved_transposed, GEMMReshapeInfo(m, n, k,
+ mult_transpose1xW_width, mult_interleave4x4_height,
+ depth_output_gemm3d, reinterpret_input_as_3d));
// Initialize matrix B reduction kernel only if _a_offset is not equal to 0
if(_a_offset != 0)
@@ -191,28 +200,30 @@
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::QASYMM8);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(a, b);
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((a)->dimension(0) != (b)->dimension(1),
- "The product AB is defined only if the number of columns in A is equal to the number of rows in B");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((a)->dimension(1) != (output)->dimension(1),
- "The output matrix must have the same number of rows as the matrix A");
- ARM_COMPUTE_RETURN_ERROR_ON_MSG((b)->dimension(0) != (output)->dimension(0),
- "The output matrix must have the same number of columns as the matrix B");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.is_a_reshaped(), "Matrix A already reshaped is not supported");
ARM_COMPUTE_RETURN_ERROR_ON_MSG(gemm_info.is_b_reshaped(), "Matrix B already reshaped is not supported");
int32_t a_offset = a->quantization_info().offset;
int32_t b_offset = b->quantization_info().offset;
- const int m = a->dimension(1);
- const int n = b->dimension(0);
- const int k = a->dimension(0);
- constexpr int mult_transpose1xW_width = 1;
- constexpr int mult_interleave4x4_height = 1;
- const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
- const GEMMReshapeInfo reshape_info(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height, depth_output_gemm3d);
+ const int m = a->dimension(1);
+ const int n = b->dimension(0);
+ const int k = a->dimension(0);
+ constexpr int mult_transpose1xW_width = 1;
+ constexpr int mult_interleave4x4_height = 1;
+ bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
+ const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
bool reshape_matrices = is_interleaved_transposed(m, n, k, gemm_info.reshape_b_only_on_first_run(), CLScheduler::get().target());
+ // if reshape_matrices is set, force reinterpret_input_as_3d to be false as the output of CLGEMMInterleaveKernel will be 2D
+ if(reshape_matrices)
+ {
+ 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(reshape_matrices)
{
TensorInfo info_a(compute_interleaved_shape(*a, mult_interleave4x4_height, gemm_info.reinterpret_input_as_3d()), 1, a->data_type());