COMPMID-3574: add logarithm to LogSoftmaxLayer

Missed logarithm for the summation is added to NEON, CL and reference
backends. To avoid complex changes, log softmax layer on CL backend
doesn't support quantized data types. Tests and doxygen comments
are modified accordingly.

Change-Id: Iafd29291be8b81345cb4999b2668dbc3ae0c3345
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/ml/ComputeLibrary/+/3517
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Michele Di Giorgio <michele.digiorgio@arm.com>
Reviewed-by: SiCong Li <sicong.li@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>

3 files changed, 9 insertions, 9 deletions

diff --git a/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h b/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
index b174f493b5..bd544e1537 100644
--- a/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
@@ -203,7 +203,7 @@ public:
     CLLogits1DNormKernel &operator=(CLLogits1DNormKernel &&) = default;
     /** Set the input and output tensors.
      *
-     * @param[in]  input  Source tensor. Data types supported: S32/F16/F32
+     * @param[in]  input  Source tensor. Data types supported: S32/F16/F32. If this kernel is used for log softmax, only F32/F16 is supported.
      * @param[in]  sum    Sum tensor. Dimensions should be dim(input)-1. Data types supported: same as @p input
      * @param[out] output Destination tensor. Data types supported: QASYMM8 for S32 @p input, or same as @p input
      * @param[in]  info   Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
@@ -212,7 +212,7 @@ public:
     /** Set the input and output tensors.
      *
      * @param[in]  compile_context The compile context to be used.
-     * @param[in]  input           Source tensor. Data types supported: S32/F16/F32
+     * @param[in]  input           Source tensor. Data types supported: S32/F16/F32. If this kernel is used for log softmax, only F32/F16 is supported.
      * @param[in]  sum             Sum tensor. Dimensions should be dim(input)-1. Data types supported: same as @p input
      * @param[out] output          Destination tensor. Data types supported: QASYMM8 for S32 @p input, or same as @p input
      * @param[in]  info            Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
@@ -220,7 +220,7 @@ public:
     void configure(const CLCompileContext &compile_context, const ICLTensor *input, const ICLTensor *sum, ICLTensor *output, const SoftmaxKernelInfo &info);
     /** Static function to check if given info will lead to a valid configuration of @ref CLLogits1DNormKernel
      *
-     * @param[in] input  Source tensor. Data types supported: S32/F16/F32
+     * @param[in] input  Source tensor. Data types supported: S32/F16/F32. If this kernel is used for log softmax, only F32/F16 is supported.
      * @param[in] sum    Sum tensor. Dimensions should be dim(input)-1. Data types supported: same as @p input
      * @param[in] output Destination tensor. Data types supported: QASYMM8 for S32 @p input, or same as @p input
      * @param[in] info   Contains information consumed by kernels for softmax described in @ref SoftmaxKernelInfo.
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
index f0ef15acd7..40b6743031 100644
--- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
+++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
@@ -44,7 +44,7 @@ class ICLTensor;
  * @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f]
  *
  * Log Softmax is calculated by :
- * @f[ out = (x - max(x) * beta) - \sum{e^{x - max(x) * beta}} @f]
+ * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
  *
  * This function runs the following kernels:
  * -# @ref CLLogits1DMaxKernel
@@ -63,7 +63,7 @@ public:
     CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager = nullptr);
     /** Set the input and output tensors.
      *
-     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax
      * @param[out] output          Destination tensor. Data types supported: same as @p input
      * @param[in]  beta            (Optional) A scaling factor for the exponent. Defaults to 1.f
      * @param[in]  reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
@@ -75,7 +75,7 @@ public:
     /** Set the input and output tensors.
      *
      * @param[in]  compile_context The compile context to be used.
-     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32
+     * @param[in]  input           Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax
      * @param[out] output          Destination tensor. Data types supported: same as @p input
      * @param[in]  beta            (Optional) A scaling factor for the exponent. Defaults to 1.f
      * @param[in]  reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
@@ -86,7 +86,7 @@ public:
     void configure(const CLCompileContext &compile_context, const ICLTensor *input, ICLTensor *output, float beta = 1.0f, size_t reduce_end_axis = 0);
     /** Static function to check if given info will lead to a valid configuration of @ref CLSoftmaxLayer
      *
-     * @param[in] input           Source tensor. Data types supported: QASYMM8/F16/F32
+     * @param[in] input           Source tensor. Data types supported: QASYMM8/F16/F32 for Softmax and F16/F32 for Log Softmax
      * @param[in] output          Destination tensor. Data types supported: same as @p input
      * @param[in] beta            (Optional) A scaling factor for the exponent. Defaults to 1.f
      * @param[in] reduce_end_axis (Optional) The last axis of the first n dimensions (inclusive)to reduce. Defaults to 0.
diff --git a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
index 51d981de44..fc1316d33c 100644
--- a/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
+++ b/arm_compute/runtime/NEON/functions/NESoftmaxLayer.h
@@ -39,10 +39,10 @@ class ITensor;
 /** Basic function to compute a SoftmaxLayer and a Log SoftmaxLayer.
  *
  * Softmax is calculated by :
- * @f[ out = \frac{e^{x - max(x)}}{\sum{e^{x - max(x)}}} @f]
+ * @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f]
  *
  * Log Softmax is calculated by :
- * @f[ out = (x - max(x)) - \sum{e^{x - max(x)}} @f]
+ * @f[ out = (x - max(x) * beta) - log(\sum{e^{x - max(x) * beta}}) @f]
  *
  * This function runs the following kernels:
  * -# @ref NEFillBorderKernel