Fixed CTS failures CLInstanceNorm
* Resolves COMPMID-4400
Change-Id: I54c33a017c735194fbf4437d1c7df465208bc0ca
Signed-off-by: Pablo Tello <pablo.tello@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/5505
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Sheri Zhang <sheri.zhang@arm.com>
diff --git a/src/core/CL/cl_kernels/instance_normalization.cl b/src/core/CL/cl_kernels/instance_normalization.cl
index d2507d9..adfbebd 100644
--- a/src/core/CL/cl_kernels/instance_normalization.cl
+++ b/src/core/CL/cl_kernels/instance_normalization.cl
@@ -23,7 +23,7 @@
*/
#include "helpers.h"
-#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z)
+#if defined(VEC_SIZE) && defined(DATA_TYPE) && defined(INTERNAL_DATA_TYPE) & defined(DIM_X) && defined(DIM_Y) && defined(DIM_Z)
/** This function computes the mean and variance of each plane of the input tensor and provides it as output.
*
* @attention Vector size should be given as a preprocessor argument using -DVEC_SIZE=size. e.g. -DVEC_SIZE=16
@@ -57,32 +57,37 @@
Tensor3D out = CONVERT_TO_TENSOR3D_STRUCT_NO_STEP(output);
#if defined(NHWC)
- const int ch = get_global_id(0); // Current channel
- const int batch = get_global_id(1); // Current batch
- const int elements_plane = DIM_Y * DIM_Z;
- float part_sum = 0.f;
- float part_sum_sq = 0.f;
- const int in_offset = input_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE);
- for(int i = 0; i < (DIM_Y * DIM_Z); ++i)
+ const int ch = get_global_id(0); // Current channel
+ const int batch = get_global_id(1); // Current batch
+ const int elements_plane = DIM_Y * DIM_Z;
+ INTERNAL_DATA_TYPE part_sum = 0.f;
+ INTERNAL_DATA_TYPE part_sum_sq = 0.f;
+ const int in_offset = input_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE);
+
+ for(int i_w = 0; i_w < DIM_Y; ++i_w)
{
- const float data = *((__global DATA_TYPE *)(input_ptr + in_offset + i * input_stride_y));
- part_sum += data;
- part_sum_sq += data * data;
+ for(int i_h = 0; i_h < DIM_Z; ++i_h)
+ {
+ INTERNAL_DATA_TYPE data = (INTERNAL_DATA_TYPE) * ((__global DATA_TYPE *)tensor4D_offset(&in, ch, i_w, i_h, batch));
+ part_sum += data;
+ part_sum_sq += data * data;
+ }
}
- float mean = (part_sum / elements_plane);
- float var = (part_sum_sq / elements_plane) - (mean * mean);
- __global DATA_TYPE *output_address0 = (__global DATA_TYPE *)tensor3D_offset(&out, ch, 0, batch);
- *output_address0 = mean;
- __global DATA_TYPE *output_address1 = (__global DATA_TYPE *)tensor3D_offset(&out, ch, 1, batch);
- *output_address1 = var;
+
+ INTERNAL_DATA_TYPE mean = (part_sum / elements_plane);
+ INTERNAL_DATA_TYPE var = (part_sum_sq / elements_plane) - (mean * mean);
+ __global INTERNAL_DATA_TYPE *output_address0 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 0, batch);
+ *output_address0 = mean;
+ __global INTERNAL_DATA_TYPE *output_address1 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 1, batch);
+ *output_address1 = var;
#else // !defined(NHWC)
const int ch = get_global_id(2) % DIM_Z; // Current channel
const int batch = get_global_id(2) / DIM_Z; // Current batch
const int elements_plane = DIM_X * DIM_Y;
- VEC_DATA_TYPE(float, VEC_SIZE)
+ VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)
part_sum = 0.f;
- VEC_DATA_TYPE(float, VEC_SIZE)
+ VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)
part_sum_sq = 0.f;
// Calculate partial sum
for(int y = 0; y < DIM_Y; ++y)
@@ -91,15 +96,15 @@
for(; x <= (DIM_X - VEC_SIZE); x += VEC_SIZE)
{
// Load data
- VEC_DATA_TYPE(float, VEC_SIZE)
- data = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)), VEC_DATA_TYPE(float, VEC_SIZE));
+ VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE)
+ data = CONVERT(VLOAD(VEC_SIZE)(0, (__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)), VEC_DATA_TYPE(INTERNAL_DATA_TYPE, VEC_SIZE));
part_sum += data;
part_sum_sq += data * data;
}
// Left-overs loop
for(; x < DIM_X; ++x)
{
- float data = (float)(*((__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)));
+ INTERNAL_DATA_TYPE data = (INTERNAL_DATA_TYPE)(*((__global DATA_TYPE *)tensor4D_offset(&in, x, y, ch, batch)));
part_sum.s0 += data;
part_sum_sq.s0 += data * data;
}
@@ -120,16 +125,16 @@
part_sum.s0 += part_sum.s1;
part_sum_sq.s0 += part_sum_sq.s1;
- float sum = (float)part_sum.s0;
- float sum_sq = (float)part_sum_sq.s0;
+ INTERNAL_DATA_TYPE sum = (INTERNAL_DATA_TYPE)part_sum.s0;
+ INTERNAL_DATA_TYPE sum_sq = (INTERNAL_DATA_TYPE)part_sum_sq.s0;
- const float mean = (sum / elements_plane);
- const float var = (sum_sq / elements_plane) - (mean * mean);
+ const INTERNAL_DATA_TYPE mean = (sum / elements_plane);
+ const INTERNAL_DATA_TYPE var = (sum_sq / elements_plane) - (mean * mean);
- __global DATA_TYPE *output_address0 = (__global DATA_TYPE *)tensor3D_offset(&out, ch, 0, batch);
- *output_address0 = mean;
- __global DATA_TYPE *output_address1 = (__global DATA_TYPE *)tensor3D_offset(&out, ch, 1, batch);
- *output_address1 = var;
+ __global INTERNAL_DATA_TYPE *output_address0 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 0, batch);
+ *output_address0 = mean;
+ __global INTERNAL_DATA_TYPE *output_address1 = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&out, ch, 1, batch);
+ *output_address1 = var;
#endif // defined(NHWC)
}
@@ -185,12 +190,12 @@
const int batch = get_global_id(2) / DIM_Z; // Current batch
#endif /* defined(NHWC) */
- const __global DATA_TYPE *mean_ptr = (__global DATA_TYPE *)tensor3D_offset(&mean_var, ch, 0, batch);
- const __global DATA_TYPE *var_ptr = (__global DATA_TYPE *)tensor3D_offset(&mean_var, ch, 1, batch);
- const INTERNAL_DATA_TYPE mean = (INTERNAL_DATA_TYPE) * mean_ptr;
- const INTERNAL_DATA_TYPE var = (INTERNAL_DATA_TYPE) * var_ptr;
- const INTERNAL_DATA_TYPE multip = GAMMA / sqrt(var + EPSILON);
- const INTERNAL_DATA_TYPE beta = (INTERNAL_DATA_TYPE)BETA;
+ const __global INTERNAL_DATA_TYPE *mean_ptr = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&mean_var, ch, 0, batch);
+ const __global INTERNAL_DATA_TYPE *var_ptr = (__global INTERNAL_DATA_TYPE *)tensor3D_offset(&mean_var, ch, 1, batch);
+ const INTERNAL_DATA_TYPE mean = (INTERNAL_DATA_TYPE) * mean_ptr;
+ const INTERNAL_DATA_TYPE var = (INTERNAL_DATA_TYPE) * var_ptr;
+ const INTERNAL_DATA_TYPE multip = GAMMA / sqrt(var + EPSILON);
+ const INTERNAL_DATA_TYPE beta = (INTERNAL_DATA_TYPE)BETA;
#if defined(NHWC)
const int in_offset = input_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE);
@@ -198,17 +203,19 @@
const int out_offset = output_offset_first_element_in_bytes + batch * input_stride_w + ch * sizeof(DATA_TYPE);
#endif /* IN_PLACE */
- for(int i = 0; i < (DIM_Y * DIM_Z); ++i)
+ for(int i_w = 0; i_w < DIM_Y; ++i_w)
{
- __global DATA_TYPE *input_address = (__global DATA_TYPE *)(input_ptr + in_offset + i * input_stride_y);
+ for(int i_h = 0; i_h < DIM_Z; ++i_h)
+ {
+ __global DATA_TYPE *input_address = (__global DATA_TYPE *)tensor4D_offset(&in, ch, i_w, i_h, batch);
#ifdef IN_PLACE
- __global DATA_TYPE *output_address = input_address;
+ __global DATA_TYPE *output_address = input_address;
#else /* !IN_PLACE */
- __global DATA_TYPE *output_address = (__global DATA_TYPE *)(output_ptr + out_offset + i * output_stride_y);
+ __global DATA_TYPE *output_address = (__global DATA_TYPE *)tensor4D_offset(&out, ch, i_w, i_h, batch);
#endif /* IN_PLACE */
- *(output_address) = (*(input_address) - mean) * multip + beta;
+ *(output_address) = (*(input_address) - mean) * multip + (INTERNAL_DATA_TYPE)BETA;
+ }
}
-
#else // !defined(NHWC)
for(int y = 0; y < DIM_Y; ++y)
{