COMPMID-617: Adds CLFullyConnectionLayer validation support

Change-Id: I4d2eb9872a3165fdcaa7784596e441cbe563dbc2
Reviewed-on: https://eu-gerrit-1.euhpc.arm.com/112577
Tested-by: Jenkins <bsgcomp@arm.com>
Reviewed-by: Ioan-Cristian Szabo <ioan-cristian.szabo@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>

1 files changed, 70 insertions, 34 deletions

diff --git a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
index 5c6f5b4ed0..ddcab6a256 100644
--- a/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
+++ b/src/runtime/CL/functions/CLGEMMLowpMatrixMultiplyCore.cpp
@@ -29,9 +29,11 @@
 #include "arm_compute/core/TensorInfo.h"
 #include "arm_compute/core/Types.h"
 #include "arm_compute/core/Validate.h"
+#include "arm_compute/core/utils/misc/ShapeCalculator.h"
 #include "arm_compute/runtime/CL/CLScheduler.h"
 
 using namespace arm_compute;
+using namespace arm_compute::misc::shape_calculator;
 
 CLGEMMLowpMatrixMultiplyCore::CLGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemoryManager> memory_manager)
     : _memory_group(std::move(memory_manager)), _mm_kernel(), _mtx_a_reshape_kernel(), _mtx_b_reshape_kernel(), _mtx_a_reduction_kernel(), _mtx_b_reduction_kernel(), _offset_contribution_kernel(),
@@ -41,14 +43,9 @@ CLGEMMLowpMatrixMultiplyCore::CLGEMMLowpMatrixMultiplyCore(std::shared_ptr<IMemo
 
 void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor *b, ICLTensor *output, const GEMMInfo &gemm_info)
 {
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(a, 1, DataType::QASYMM8);
-    ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(output, 1, DataType::S32);
-    ARM_COMPUTE_ERROR_ON_MISMATCHING_DATA_TYPES(a, b);
-    ARM_COMPUTE_ERROR_ON_MSG((a)->info()->dimension(0) != (b)->info()->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_ERROR_ON_MSG((a)->info()->dimension(1) != (output)->info()->dimension(1), "The output matrix must have the same number of rows as the matrix A");
-    ARM_COMPUTE_ERROR_ON_MSG((b)->info()->dimension(0) != (output)->info()->dimension(0), "The output matrix must have the same number of columns as the matrix B");
-    ARM_COMPUTE_ERROR_ON_MSG(gemm_info.is_a_reshaped(), "Matrix A already reshaped is not supported");
-    ARM_COMPUTE_ERROR_ON_MSG(gemm_info.is_b_reshaped(), "Matrix B already reshaped is not supported");
+    ARM_COMPUTE_ERROR_ON_NULLPTR(a, b, output);
+    ARM_COMPUTE_UNUSED(gemm_info);
+    ARM_COMPUTE_ERROR_THROW_ON(CLGEMMLowpMatrixMultiplyCore::validate(a->info(), b->info(), output->info(), gemm_info));
 
     _reshape_b_only_on_first_run = gemm_info.reshape_b_only_on_first_run();
     _a_offset                    = a->info()->quantization_info().offset;
@@ -65,18 +62,8 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor
         matrix_a = &_tmp_a;
         matrix_b = &_tmp_b;
 
-        // The interleaved output matrix will have the following shape: [ a_height * 4, ceil(a_width / 4.0f) ]
-        TensorShape shape_tmp_a = a->info()->tensor_shape();
-        shape_tmp_a.set(0, a->info()->dimension(0) * 4);
-        shape_tmp_a.set(1, std::ceil(a->info()->dimension(1) / 4.f));
-
-        // The transpose1xW output matrix will have the following shape: [ b_height * 16, ceil(b_width / 16.0f) ]
-        TensorShape shape_tmp_b = b->info()->tensor_shape();
-        shape_tmp_b.set(0, b->info()->dimension(1) * 16);
-        shape_tmp_b.set(1, std::ceil(b->info()->dimension(0) / 16.f));
-
-        TensorInfo info_a(shape_tmp_a, 1, a->info()->data_type());
-        TensorInfo info_b(shape_tmp_b, 1, b->info()->data_type());
+        TensorInfo info_a(compute_interleaved_shape(*a->info()), 1, a->info()->data_type());
+        TensorInfo info_b(compute_transpose1xW_shape(*b->info()), 1, b->info()->data_type());
         _tmp_a.allocator()->init(info_a);
         _tmp_b.allocator()->init(info_b);
         _memory_group.manage(&_tmp_a);
@@ -95,13 +82,7 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor
     // Initialize matrix B reduction kernel only if _a_offset is not equal to 0
     if(_a_offset != 0)
     {
-        TensorShape shape_vector_sum_col = b->info()->tensor_shape();
-
-        if(shape_vector_sum_col.num_dimensions() > 1)
-        {
-            shape_vector_sum_col.remove_dimension(1);
-        }
-        TensorInfo info_vector_sum_col(shape_vector_sum_col, 1, DataType::S32);
+        TensorInfo info_vector_sum_col(compute_reductionA_shape(*b->info()), 1, DataType::S32);
         _vector_sum_col.allocator()->init(info_vector_sum_col);
         _memory_group.manage(&_vector_sum_col);
 
@@ -112,13 +93,7 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor
     // Initialize Matrix A reduction kernel only if _b_offset is not equal to 0
     if(_b_offset != 0)
     {
-        TensorShape shape_vector_sum_row = a->info()->tensor_shape();
-        shape_vector_sum_row.set(Window::DimX, a->info()->dimension(1));
-        if(a->info()->num_dimensions() > 1)
-        {
-            shape_vector_sum_row.remove_dimension(1);
-        }
-        TensorInfo info_vector_sum_row(shape_vector_sum_row, 1, DataType::S32);
+        TensorInfo info_vector_sum_row(compute_reductionB_shape(*a->info()), 1, DataType::S32);
         _vector_sum_row.allocator()->init(info_vector_sum_row);
         _memory_group.manage(&_vector_sum_row);
 
@@ -147,6 +122,67 @@ void CLGEMMLowpMatrixMultiplyCore::configure(const ICLTensor *a, const ICLTensor
     }
 }
 
+Status CLGEMMLowpMatrixMultiplyCore::validate(const ITensorInfo *a, const ITensorInfo *b, const ITensorInfo *output, const GEMMInfo &gemm_info)
+{
+    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;
+    bool    is_interleaved_transposed = a->dimension(1) > 16;
+
+    if(is_interleaved_transposed)
+    {
+        TensorInfo info_a(compute_interleaved_shape(*a), 1, a->data_type());
+        TensorInfo info_b(compute_transpose1xW_shape(*b), 1, b->data_type());
+
+        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMInterleave4x4Kernel::validate(a, &info_a));
+        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMTranspose1xWKernel::validate(b, &info_b));
+        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(&info_a, &info_b, output));
+    }
+    else
+    {
+        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixMultiplyKernel::validate(a, b, output));
+    }
+
+    TensorInfo info_vector_sum_col, info_vector_sum_row;
+
+    // Validate matrix B reduction kernel only if _a_offset is not equal to 0
+    if(a_offset != 0)
+    {
+        info_vector_sum_col = TensorInfo(compute_reductionA_shape(*b), 1, DataType::S32);
+
+        // Configure Matrix B reduction kernel
+        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixBReductionKernel::validate(b, &info_vector_sum_col));
+    }
+
+    // Validate Matrix A reduction kernel only if _b_offset is not equal to 0
+    if(b_offset != 0)
+    {
+        info_vector_sum_row = TensorInfo(compute_reductionB_shape(*a), 1, DataType::S32);
+
+        // Configure matrix A reduction kernel
+        ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpMatrixAReductionKernel::validate(a, &info_vector_sum_row));
+    }
+
+    // Validate offset contribution kernel
+    ARM_COMPUTE_RETURN_ON_ERROR(CLGEMMLowpOffsetContributionKernel::validate(output,
+                                                                             a_offset == 0 ? nullptr : &info_vector_sum_col,
+                                                                             b_offset == 0 ? nullptr : &info_vector_sum_row,
+                                                                             a_offset, b_offset));
+
+    return Status{};
+}
+
 void CLGEMMLowpMatrixMultiplyCore::run()
 {
     _memory_group.acquire();