COMPMID-1451: Reverting changes for CLGEMM and CLGEMMLowp previuosly done (384496)
Mirroring CLGEMM behaviour to CLGEMMLowp
Change-Id: I308b54e2c0de131a5322b77e83e7454db498d692
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/153175
Reviewed-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Tested-by: bsgcomp <bsgcomp@arm.com>
diff --git a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
index 56f318d..99e1840 100644
--- a/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMLowpMatrixMultiplyKernel.cpp
@@ -57,6 +57,7 @@
Status validate_arguments(const ITensorInfo *input0, const ITensorInfo *input1, const ITensorInfo *output, bool is_interleaved_transposed, const GEMMReshapeInfo &reshape_info)
{
+ ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input0, input1, output);
ARM_COMPUTE_RETURN_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input0, 1, DataType::QASYMM8);
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_DATA_TYPES(input0, input1);
ARM_COMPUTE_RETURN_ERROR_ON_MSG(input0->num_dimensions() > 4, "The number of dimensions for the matrix A must be <= 4");
@@ -87,7 +88,7 @@
const TensorInfo tensor_info0 = input0->clone()->set_tensor_shape(tensor_shape0);
const TensorInfo tensor_info1 = input1->clone()->set_tensor_shape(tensor_shape1);
- const TensorInfo tensor_info_reshaped0 = input0->clone()->set_tensor_shape(compute_interleaved_shape(tensor_info0, mult_interleave4x4_height, reshape_info.reinterpret_input_as_3d()));
+ const TensorInfo tensor_info_reshaped0 = input0->clone()->set_tensor_shape(compute_interleaved_shape(tensor_info0, mult_interleave4x4_height));
const TensorInfo tensor_info_reshaped1 = input1->clone()->set_tensor_shape(compute_transpose1xW_with_element_size_shape(tensor_info1, mult_transpose1xW_width));
ARM_COMPUTE_RETURN_ERROR_ON_MISMATCHING_SHAPES(input0, &tensor_info_reshaped0);
@@ -124,11 +125,8 @@
reinterpret_output_as_3d = false;
}
- GEMMReshapeInfo reshape_info_to_use = GEMMReshapeInfo(reshape_info.m(), reshape_info.n(), reshape_info.k(), reshape_info.mult_transpose1xW_width(), reshape_info.mult_interleave4x4_height(),
- reinterpret_output_as_3d ? reshape_info.depth_output_gemm3d() : 1, reinterpret_input_as_3d);
-
// Output tensor auto inizialitation if not yet initialized
- auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info_to_use)));
+ auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info)));
TensorInfo tmp_info(*output);
@@ -145,7 +143,7 @@
if(is_interleaved_transposed)
{
// reinterpret_input_as_3d is not supported if is_interleaved_transposed is set
- ARM_COMPUTE_ERROR_ON(reinterpret_input_as_3d);
+ ARM_COMPUTE_ERROR_ON(reshape_info.reinterpret_input_as_3d());
// Configure kernel window
num_elems_processed_per_iteration_x = 4;
@@ -198,7 +196,7 @@
Coordinates coord;
coord.set_num_dimensions(output->num_dimensions());
- output_access.set_valid_region(win, ValidRegion(coord, output->tensor_shape()));
+ output_access.set_valid_region(win_out, ValidRegion(coord, output->tensor_shape()));
}
// Collapse along the Z direction
diff --git a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
index c8bcb37..715edae 100644
--- a/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
+++ b/src/core/CL/kernels/CLGEMMMatrixMultiplyKernel.cpp
@@ -120,12 +120,8 @@
reinterpret_output_as_3d = false;
}
- const GEMMReshapeInfo reshape_info_to_use(reshape_info.m(), reshape_info.n(), reshape_info.k(), reshape_info.mult_transpose1xW_width(),
- reshape_info.mult_interleave4x4_height(), reinterpret_output_as_3d ? reshape_info.depth_output_gemm3d() : 1, reinterpret_input_as_3d);
-
// Output tensor auto inizialitation if not yet initialized
- auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed,
- reshape_info_to_use)));
+ auto_init_if_empty(*output, input0->clone()->set_tensor_shape(compute_mm_shape(*input0, *input1, is_interleaved_transposed, reshape_info)));
TensorInfo tmp_info(*output);
@@ -141,7 +137,7 @@
if(is_interleaved_transposed)
{
// reinterpret_input_as_3d is not supported if is_interleaved_transposed is set
- ARM_COMPUTE_ERROR_ON(reinterpret_input_as_3d);
+ ARM_COMPUTE_ERROR_ON(reshape_info.reinterpret_input_as_3d());
// Configure kernel window
num_elems_processed_per_iteration_x = max_cl_vector_width / data_size_from_type(data_type);
diff --git a/src/runtime/CL/functions/CLGEMM.cpp b/src/runtime/CL/functions/CLGEMM.cpp
index 0c82e6d..6adbdc0 100644
--- a/src/runtime/CL/functions/CLGEMM.cpp
+++ b/src/runtime/CL/functions/CLGEMM.cpp
@@ -133,10 +133,7 @@
if(_is_interleaved_transposed)
{
reinterpret_input_as_3d = false;
- }
- if(_is_interleaved_transposed)
- {
matrix_a = &_tmp_a;
matrix_b = &_tmp_b;
@@ -200,8 +197,7 @@
// 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();
- bool reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 1);
- const int m = a->dimension(1);
+ 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;
@@ -217,21 +213,13 @@
// 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);
- // In case both input and output have to be reinterpreted as 3D tensors,
- // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
- if(reinterpret_input_as_3d == reinterpret_output_as_3d)
- {
- reinterpret_input_as_3d = false;
- reinterpret_output_as_3d = false;
- }
-
// 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, reinterpret_output_as_3d ? depth_output_gemm3d : 1, reinterpret_input_as_3d);
+ 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)
{
@@ -239,8 +227,8 @@
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, reinterpret_input_as_3d)));
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMInterleave4x4Kernel::validate(a, &tmp_a_info, mult_interleave4x4_height, reinterpret_input_as_3d));
+ 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)));
diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
index 7aeade1..509b668 100644
--- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
@@ -108,22 +108,13 @@
// 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();
- bool reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 1);
- int m = reinterpret_input_as_3d ? (a->info()->dimension(1) * a->info()->dimension(2)) : a->info()->dimension(1);
+ 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();
constexpr int mult_transpose1xW_width = 1;
constexpr int mult_interleave4x4_height = 1;
- // In case both input and output have to be reinterpreted as 3D tensors,
- // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
- if(reinterpret_input_as_3d == reinterpret_output_as_3d)
- {
- reinterpret_input_as_3d = false;
- reinterpret_output_as_3d = false;
- }
-
// 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);
@@ -131,7 +122,6 @@
{
// if _is_interleaved_transposed is set, force reinterpret_input_as_3d to be false as the output of CLGEMMInterleaveKernel will be 2D
reinterpret_input_as_3d = false;
- m = a->info()->dimension(1);
matrix_a = &_tmp_a;
matrix_b = &_tmp_b;
@@ -143,7 +133,7 @@
}
// Configure interleave kernel
- _mtx_a_reshape_kernel.configure(a, &_tmp_a, mult_interleave4x4_height, reinterpret_input_as_3d);
+ _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);
@@ -151,7 +141,7 @@
// 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,
- reinterpret_output_as_3d ? depth_output_gemm3d : 1, reinterpret_input_as_3d));
+ 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)
@@ -213,23 +203,20 @@
int32_t a_offset = a->quantization_info().offset;
int32_t b_offset = b->quantization_info().offset;
+ const ITensorInfo *matrix_a_info = a;
+ const ITensorInfo *matrix_b_info = b;
+
+ TensorInfo tmp_a_info{};
+ TensorInfo tmp_b_info{};
+
bool reinterpret_input_as_3d = gemm_info.reinterpret_input_as_3d();
- bool reinterpret_output_as_3d = (gemm_info.depth_output_gemm3d() != 1);
- int m = a->dimension(1);
+ 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);
constexpr int mult_transpose1xW_width = 1;
constexpr int mult_interleave4x4_height = 1;
const int depth_output_gemm3d = gemm_info.depth_output_gemm3d();
- // In case both input and output have to be reinterpreted as 3D tensors,
- // force reinterpret_input_as_3d and reinterpret_output_as_3d to be false.
- if(reinterpret_input_as_3d == reinterpret_output_as_3d)
- {
- reinterpret_input_as_3d = false;
- reinterpret_output_as_3d = false;
- }
-
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
@@ -238,21 +225,23 @@
reinterpret_input_as_3d = false;
}
- const GEMMReshapeInfo reshape_info = GEMMReshapeInfo(m, n, k, mult_transpose1xW_width, mult_interleave4x4_height, reinterpret_output_as_3d ? depth_output_gemm3d : 1, reinterpret_input_as_3d);
+ 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, reinterpret_input_as_3d), 1, a->data_type());
- TensorInfo info_b(compute_transpose1xW_with_element_size_shape(*b, mult_transpose1xW_width), 1, b->data_type());
+ matrix_a_info = &tmp_a_info;
+ matrix_b_info = &tmp_b_info;
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMInterleave4x4Kernel::validate(a, &info_a, mult_interleave4x4_height, reinterpret_input_as_3d));
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMTranspose1xWKernel::validate(b, &info_b, mult_transpose1xW_width));
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(&info_a, &info_b, output, reshape_matrices, reshape_info));
+ // Validate interleave kernel
+ 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)));
}
- else
- {
- ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(a, b, output, reshape_matrices, reshape_info));
- }
+
+ // Validate matrix multiply
+ ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(matrix_a_info, matrix_b_info, output, reshape_matrices, reshape_info));
TensorInfo info_vector_sum_col, info_vector_sum_row;