COMPMID-3925: Dispatch CLGEMM with no padding y requirement
- Add has_pad_y flag in GEMMKernelInfo
- Skip reinterpret as 3D in CLGEMMMatrixMultiplyReshapedOnlyRHSKernel if
has_pad_y = false
- Add test to validate CLGEMMMatrixMultiplyReshapedOnlyRHSkernel with
had_pad_y = false/true
- Configure two variants of CLGEMMMatrixMultiplyReshapedOnlyRHSKernel to
run with has_pad_y = false/true in CLGEMM
- Check if the lhs/dst tensors have pad y. If not, run
CLGEMMMatrixMultiplyReshapedOnlyRHSKernel without padding requirement
Change-Id: I68bb43389789736d676b899ac7c77fd9138babaf
Signed-off-by: Gian Marco Iodice <gianmarco.iodice@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/4248
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
diff --git a/tests/validation/fixtures/GEMMFixture.h b/tests/validation/fixtures/GEMMFixture.h
index 0a964a7..6288b6b 100644
--- a/tests/validation/fixtures/GEMMFixture.h
+++ b/tests/validation/fixtures/GEMMFixture.h
@@ -1125,7 +1125,7 @@
public:
template <typename...>
void setup(unsigned int m_w, unsigned int m_h, unsigned int n, unsigned int k, unsigned int batch_size, unsigned int m0, unsigned int n0, unsigned int k0, unsigned int h0,
- bool interleave_rhs, bool transpose_rhs, bool export_to_cl_image, DataType data_type, float alpha, float beta, const ActivationLayerInfo &act_info)
+ bool interleave_rhs, bool transpose_rhs, bool export_to_cl_image, bool has_pad_y, DataType data_type, float alpha, float beta, const ActivationLayerInfo &act_info)
{
GEMMLHSMatrixInfo lhs_info;
lhs_info.m0 = m0;
@@ -1147,7 +1147,7 @@
const TensorShape rhs_shape(n, k, batch_size);
const TensorShape bias_shape(n, 1, 1);
- _target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info);
+ _target = compute_target(lhs_shape, rhs_shape, bias_shape, lhs_info, rhs_info, data_type, alpha, beta, m_h, act_info, has_pad_y);
_reference = compute_reference(lhs_shape, rhs_shape, data_type, alpha, beta, m_h, act_info);
}
@@ -1161,7 +1161,7 @@
TensorType compute_target(const TensorShape &lhs_shape, const TensorShape &rhs_shape, const TensorShape &bias_shape, const GEMMLHSMatrixInfo &lhs_info, const GEMMRHSMatrixInfo &rhs_info,
DataType data_type, float alpha, float beta,
- unsigned int m_h, const ActivationLayerInfo &act_info)
+ unsigned int m_h, const ActivationLayerInfo &act_info, bool has_pad_y)
{
// Create tensors
TensorType lhs = create_tensor<TensorType>(lhs_shape, data_type, 1);
@@ -1181,15 +1181,22 @@
kernel_info.reinterpret_input_as_3d = false;
kernel_info.broadcast_bias = true;
kernel_info.activation_info = act_info;
+ kernel_info.has_pad_y = has_pad_y;
// The output tensor will be auto-initialized within the function
-
// Create and configure function
ReshapeRHSFunctionType reshape_rhs;
GEMMFunctionType gemm;
reshape_rhs.configure(&rhs, &rhs_reshaped, rhs_info);
gemm.configure(&lhs, &rhs_reshaped, &bias, &dst, alpha, beta, lhs_info, rhs_info, kernel_info);
+ if(has_pad_y)
+ {
+ // Add dummy padding into lhs to validate has_pad_y path
+ lhs.info()->extend_padding(PaddingSize(2, 0, 2, 0));
+ dst.info()->extend_padding(PaddingSize(2, 0, 1, 0));
+ }
+
ARM_COMPUTE_EXPECT(lhs.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(rhs.info()->is_resizable(), framework::LogLevel::ERRORS);
ARM_COMPUTE_EXPECT(bias.info()->is_resizable(), framework::LogLevel::ERRORS);