Optimize CpuSoftmaxKernel for axis=0
Implement a single kernel instead of having two consecutive ones. In the previous setup, one kernel was calculating the maximum value in the axis, and this maximum was being subtracted from each data while calculating the softmax, i.e.
softmax(x_i) = exp(x_i - max) / sum_i( exp(x_i - max) )
This patch integrates these two stages into a single kernel for Neon™ for all data types. This will save some memory because we don't need to hold the max values in a separate auxiliary tensor.
It also introduces some other optimizations that will ease memory pressure when the data type is float/half, by using the dst tensor as temporary storage for already exponentiated inputs.
It removes the references to SVE and SVE2 implementations, and most of the associated files; but, it leaves the implementations as these may be used in the future.
Resolves: COMPMID-6500
Signed-off-by: Gunes Bayir <gunes.bayir@arm.com>
Change-Id: Icff9976d1214c4c6cbe15a62ca60b8a77d3784cc
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/10688
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Benchmark: Arm Jenkins <bsgcomp@arm.com>
diff --git a/src/cpu/kernels/softmax/generic/neon/fp16.cpp b/src/cpu/kernels/softmax/generic/neon/fp16.cpp
index 2e2adf3..db8f881 100644
--- a/src/cpu/kernels/softmax/generic/neon/fp16.cpp
+++ b/src/cpu/kernels/softmax/generic/neon/fp16.cpp
@@ -31,21 +31,18 @@
{
namespace cpu
{
-void neon_fp16_softmax(const ITensor *in,
- const ITensor *max,
- void *const tmp,
- ITensor *out,
- const float beta,
- bool is_log,
- const Window &window)
+
+template <bool IS_LOG>
+void neon_fp16_softmax(const ITensor *in, void *const tmp, ITensor *out, const float beta, const Window &window)
{
- return neon_softmax_logits_1d_float<float16_t>(in, max, tmp, out, beta, is_log, window);
+ return neon_softmax_float<float16_t, IS_LOG>(in, tmp, out, beta, window);
}
-void neon_fp16_logits(const ITensor *in, ITensor *out, const Window &window)
-{
- return neon_logits_1d_max<float16_t>(in, out, window);
-}
+template void
+neon_fp16_softmax<true>(const ITensor *in, void *const tmp, ITensor *out, const float beta, const Window &window);
+template void
+neon_fp16_softmax<false>(const ITensor *in, void *const tmp, ITensor *out, const float beta, const Window &window);
+
} // namespace cpu
} // namespace arm_compute
#endif //defined(__ARM_FEATURE_FP16_VECTOR_ARITHMETIC)