From 62eeb53a5eee9d388a6074553175909fd1b441b5 Mon Sep 17 00:00:00 2001
From: Sang-Hoon Park <sang-hoon.park@arm.com>
Date: Tue, 29 Oct 2019 13:13:19 +0000
Subject: COMPMID-2266: [CL] add support for Log Softmax

Change-Id: I4a8f3519328553e24cbb4fe45a8ca4d47c90975d
Signed-off-by: Sang-Hoon Park <sang-hoon.park@arm.com>
Reviewed-on: https://review.mlplatform.org/c/2182
Tested-by: Arm Jenkins <bsgcomp@arm.com>
Reviewed-by: Georgios Pinitas <georgios.pinitas@arm.com>
Comments-Addressed: Arm Jenkins <bsgcomp@arm.com>
---
 src/runtime/CL/functions/CLSoftmaxLayer.cpp | 30 ++++++++++++++++++++---------
 1 file changed, 21 insertions(+), 9 deletions(-)

(limited to 'src/runtime/CL')

diff --git a/src/runtime/CL/functions/CLSoftmaxLayer.cpp b/src/runtime/CL/functions/CLSoftmaxLayer.cpp
index 73add97ef1..32d7f4423d 100644
--- a/src/runtime/CL/functions/CLSoftmaxLayer.cpp
+++ b/src/runtime/CL/functions/CLSoftmaxLayer.cpp
@@ -34,13 +34,15 @@
 
 namespace arm_compute
 {
-CLSoftmaxLayer::CLSoftmaxLayer(std::shared_ptr<IMemoryManager> memory_manager)
+template <bool IS_LOG>
+CLSoftmaxLayerGeneric<IS_LOG>::CLSoftmaxLayerGeneric(std::shared_ptr<IMemoryManager> memory_manager)
     : _memory_group(std::move(memory_manager)), _max_shift_exp_sum_kernel(), _norm_kernel(), _flatten_kernel_ptr(), _reshape_kernel(), _max(), _sum(), _tmp(), _input_flattened(), _output_flattened(),
       _needs_flattening(false)
 {
 }
 
-void CLSoftmaxLayer::configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t axis)
+template <bool IS_LOG>
+void CLSoftmaxLayerGeneric<IS_LOG>::configure_reshape_input_kernel(const ICLTensor *input, const ICLTensor *output, size_t axis)
 {
     // Flatten the input
     const TensorShape shape_flatten = misc::shape_calculator::compute_softmax_shape(input->info(), axis);
@@ -69,11 +71,12 @@ void CLSoftmaxLayer::configure_reshape_input_kernel(const ICLTensor *input, cons
     auto_init_if_empty(*output->info(), *input->info()->clone());
 }
 
-void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output, float beta, size_t axis)
+template <bool IS_LOG>
+void CLSoftmaxLayerGeneric<IS_LOG>::configure(const ICLTensor *input, ICLTensor *output, float beta, size_t axis)
 {
     // Perform validation step
     ARM_COMPUTE_ERROR_ON_NULLPTR(input, output);
-    ARM_COMPUTE_ERROR_THROW_ON(CLSoftmaxLayer::validate(input->info(), output->info(), beta, axis));
+    ARM_COMPUTE_ERROR_THROW_ON(CLSoftmaxLayerGeneric<IS_LOG>::validate(input->info(), output->info(), beta, axis));
 
     // We don't need flattening only in the case the input is 2D and axis is 1
     _needs_flattening = axis != 1;
@@ -114,8 +117,12 @@ void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output, float
     _memory_group.manage(&_max);
     _memory_group.manage(&_sum);
 
+    SoftmaxKernelInfo softmax_info;
+    softmax_info.beta   = beta;
+    softmax_info.is_log = IS_LOG;
+
     // Configure kernels
-    _max_shift_exp_sum_kernel.configure(input_2D, &_max, &_tmp, &_sum, beta);
+    _max_shift_exp_sum_kernel.configure(input_2D, &_max, &_tmp, &_sum, softmax_info);
 
     if(_needs_flattening)
     {
@@ -123,7 +130,7 @@ void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output, float
         _memory_group.manage(&_output_flattened);
 
         // The normalization kernel stores the result in a flat output tensor
-        _norm_kernel.configure(&_tmp, &_sum, &_output_flattened, beta);
+        _norm_kernel.configure(&_tmp, &_sum, &_output_flattened, softmax_info);
 
         // Reshape the flat output into a the requested (4D) output
         _reshape_kernel.configure(&_output_flattened, output);
@@ -135,7 +142,7 @@ void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output, float
     else
     {
         // Softmax 2D case
-        _norm_kernel.configure(&_tmp, &_sum, output, beta);
+        _norm_kernel.configure(&_tmp, &_sum, output, softmax_info);
     }
 
     // Allocate intermediate buffers
@@ -144,7 +151,8 @@ void CLSoftmaxLayer::configure(const ICLTensor *input, ICLTensor *output, float
     _sum.allocator()->allocate();
 }
 
-Status CLSoftmaxLayer::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, size_t axis)
+template <bool IS_LOG>
+Status CLSoftmaxLayerGeneric<IS_LOG>::validate(const ITensorInfo *input, const ITensorInfo *output, float beta, size_t axis)
 {
     ARM_COMPUTE_RETURN_ERROR_ON_NULLPTR(input, output);
     ARM_COMPUTE_RETURN_ERROR_ON_MSG(input->num_dimensions() > 4, "Only up to 4 dimensions are supported");
@@ -188,7 +196,8 @@ Status CLSoftmaxLayer::validate(const ITensorInfo *input, const ITensorInfo *out
     return Status{};
 }
 
-void CLSoftmaxLayer::run()
+template <bool IS_LOG>
+void CLSoftmaxLayerGeneric<IS_LOG>::run()
 {
     MemoryGroupResourceScope scope_mg(_memory_group);
 
@@ -206,4 +215,7 @@ void CLSoftmaxLayer::run()
     }
 }
 
+template class CLSoftmaxLayerGeneric<false>;
+template class CLSoftmaxLayerGeneric<true>;
+
 } // namespace arm_compute
-- 
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