COMPMID-556: Support beta for all softmax data types.

Change-Id: I4c0ca033dc53829fb7ac3dd7c7469d143be74e73
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/94251
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
diff --git a/arm_compute/core/CL/CLKernelLibrary.h b/arm_compute/core/CL/CLKernelLibrary.h
index fc131cd..d433a74 100644
--- a/arm_compute/core/CL/CLKernelLibrary.h
+++ b/arm_compute/core/CL/CLKernelLibrary.h
@@ -33,6 +33,41 @@
 
 namespace arm_compute
 {
+/** Build options */
+class CLBuildOptions
+{
+    using StringSet = std::set<std::string>;
+
+public:
+    /** Default constructor. */
+    CLBuildOptions();
+    /** Adds option to the existing build option list
+     *
+     * @param[in] option Option to add
+     */
+    void add_option(std::string option);
+    /** Adds option if a given condition is true;
+     *
+     * @param[in] cond   Condition to check
+     * @param[in] option Option to add if condition is true
+     */
+    void add_option_if(bool cond, std::string option);
+    /** Adds first option if condition is true else the second one
+     *
+     * @param[in] cond         Condition to check
+     * @param[in] option_true  Option to add if condition is true
+     * @param[in] option_false Option to add if condition is false
+     */
+    void add_option_if_else(bool cond, std::string option_true, std::string option_false);
+    /** Gets the current options list set
+     *
+     * @return Build options set
+     */
+    StringSet options() const;
+
+private:
+    StringSet _build_opts; /**< Build options set */
+};
 /** Program class */
 class Program
 {
diff --git a/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h b/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
index 60d5550..1e079cb 100644
--- a/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
+++ b/arm_compute/core/CL/kernels/CLSoftmaxLayerKernel.h
@@ -60,7 +60,7 @@
      *
      * @param[in]  input  Source tensor. Data types supported: QS8/QS16/F16/F32
      * @param[in]  max    Max values tensor. Data types supported: same as @p input
-     * @param[in]  beta   A scaling factor for the exponent. QS8/QS16/F16 only support a beta value of 1.
+     * @param[in]  beta   A scaling factor for the exponent.
      * @param[out] output Destination tensor. Data types supported: same as @p input
      * @param[out] sum    Sum of 1D logits tensor. Data types supported: same as @p input
      */
diff --git a/arm_compute/core/Helpers.inl b/arm_compute/core/Helpers.inl
index 1a27684..acdb956 100644
--- a/arm_compute/core/Helpers.inl
+++ b/arm_compute/core/Helpers.inl
@@ -263,7 +263,7 @@
 
 inline bool set_quantization_info_if_empty(ITensorInfo &info, QuantizationInfo quantization_info)
 {
-    if(info.quantization_info().empty() && (is_data_type_assymetric(info.data_type())))
+    if(info.quantization_info().empty() && (is_data_type_quantized_assymetric(info.data_type())))
     {
         info.set_quantization_info(quantization_info);
         return true;
diff --git a/arm_compute/core/Utils.h b/arm_compute/core/Utils.h
index 8e15a0a..a77df03 100644
--- a/arm_compute/core/Utils.h
+++ b/arm_compute/core/Utils.h
@@ -755,7 +755,7 @@
  *
  * @return True if data type is of symmetric quantized type, else false.
  */
-inline bool is_data_type_assymetric(DataType dt)
+inline bool is_data_type_quantized_assymetric(DataType dt)
 {
     switch(dt)
     {
diff --git a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
index e87deb6..d84297e 100644
--- a/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
+++ b/arm_compute/runtime/CL/functions/CLSoftmaxLayer.h
@@ -39,7 +39,7 @@
 /** Basic function to compute a SoftmaxLayer.
  *
  * Softmax is calculated by :
- * @f[ out = exp(x - max(x)) / sum(exp(x - max(x))) @f]
+ * @f[ out = exp((x - max(x)) * beta) / sum(exp((x - max(x)) * beta)) @f]
  *
  * This function runs the following kernels:
  * -# @ref CLLogits1DMaxKernel
@@ -54,7 +54,7 @@
     /** Set the input and output tensors.
      *
      * @param[in]  input  Source tensor. Data types supported: QS8/QS16/F16/F32
-     * @param[in]  beta   A scaling factor for the exponent. QS8/QS16/F16 only support a beta value of 1.
+     * @param[in]  beta   A scaling factor for the exponent.
      * @param[out] output Destination tensor. Data types supported: same as @p input
      */
     void configure(const ICLTensor *input, ICLTensor *output, float beta = 1.0f);
diff --git a/src/core/CL/CLKernelLibrary.cpp b/src/core/CL/CLKernelLibrary.cpp
index 9e2b5bd..f9142f4 100644
--- a/src/core/CL/CLKernelLibrary.cpp
+++ b/src/core/CL/CLKernelLibrary.cpp
@@ -35,6 +35,34 @@
 
 using namespace arm_compute;
 
+CLBuildOptions::CLBuildOptions()
+    : _build_opts()
+{
+}
+
+void CLBuildOptions::add_option(std::string option)
+{
+    _build_opts.emplace(std::move(option));
+}
+
+void CLBuildOptions::add_option_if(bool cond, std::string option)
+{
+    if(cond)
+    {
+        add_option(std::move(option));
+    }
+}
+
+void CLBuildOptions::add_option_if_else(bool cond, std::string option_true, std::string option_false)
+{
+    (cond) ? add_option(std::move(option_true)) : add_option(std::move(option_false));
+}
+
+CLBuildOptions::StringSet CLBuildOptions::options() const
+{
+    return _build_opts;
+}
+
 Program::Program()
     : _context(), _device(), _is_binary(false), _name(), _source(), _binary()
 {
diff --git a/src/core/CL/kernels/CLActivationLayerKernel.cpp b/src/core/CL/kernels/CLActivationLayerKernel.cpp
index 42f577c..ca6760d 100644
--- a/src/core/CL/kernels/CLActivationLayerKernel.cpp
+++ b/src/core/CL/kernels/CLActivationLayerKernel.cpp
@@ -70,7 +70,7 @@
     }
 
     const unsigned int num_elems_processed_per_iteration = 16 / input->info()->element_size();
-    DataType           dt                                = input->info()->data_type();
+    const DataType     dt                                = input->info()->data_type();
     const int          fixed_point_position              = input->info()->fixed_point_position();
     float              a_const                           = act_info.a();
     float              b_const                           = act_info.b();
@@ -104,7 +104,7 @@
         build_opts.emplace(("-DB_VAL=" + support::cpp11::to_string(b_const_int)));
 
         // Set scale and offset of the input and output
-        if(is_data_type_assymetric(dt))
+        if(is_data_type_quantized_assymetric(dt))
         {
             float s1 = input->info()->quantization_info().scale;
             int   o1 = input->info()->quantization_info().offset;
@@ -130,7 +130,7 @@
     }
 
     // Create kernel
-    std::string kernel_name = is_data_type_assymetric(dt) ? std::string("activation_layer_qa8") : std::string("activation_layer");
+    std::string kernel_name = is_data_type_quantized_assymetric(dt) ? std::string("activation_layer_qa8") : std::string("activation_layer");
     _kernel                 = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel(kernel_name, build_opts));
 
     // Make sure _kernel is initialized before calling the parent's configure
diff --git a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
index fb066bc..1b89161 100644
--- a/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
+++ b/src/core/CL/kernels/CLSoftmaxLayerKernel.cpp
@@ -109,7 +109,6 @@
 {
     ARM_COMPUTE_ERROR_ON_DATA_TYPE_CHANNEL_NOT_IN(input, 1, DataType::QS8, DataType::QS16, DataType::F16, DataType::F32);
     ARM_COMPUTE_ERROR_ON_NULLPTR(max, sum, output);
-    ARM_COMPUTE_ERROR_ON(beta != 1.0f && input->info()->data_type() != DataType::F32);
 
     // Output auto initialization if not yet initialized
     auto_init_if_empty(*sum->info(), max->info()->tensor_shape(), 1, input->info()->data_type(), input->info()->fixed_point_position());
@@ -125,34 +124,25 @@
     _output = output;
     _sum    = sum;
 
+    const DataType dt       = input->info()->data_type();
+    auto           beta_int = static_cast<int>(lround(beta * (1 << input->info()->fixed_point_position())));
+
     // The kernel loops over all elements in steps of 16
     const unsigned int num_elems_processed_per_iteration = ceil_to_multiple(input->info()->dimension(0), 16);
 
     // Set build options
-    std::set<std::string> build_opts;
-    build_opts.emplace(("-DDATA_TYPE=" + get_cl_type_from_data_type(input->info()->data_type())));
-    if(is_data_type_fixed_point(input->info()->data_type()))
-    {
-        build_opts.emplace(("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())));
-    }
-    else if(input->info()->data_type() == DataType::F16)
-    {
-        build_opts.emplace("-DUSE_F16");
-    }
-
+    CLBuildOptions build_opts;
+    build_opts.add_option(std::string("-DDATA_TYPE=" + get_cl_type_from_data_type(dt)));
+    build_opts.add_option_if(is_data_type_fixed_point(dt),
+                             std::string("-DFIXED_POINT_POSITION=" + support::cpp11::to_string(input->info()->fixed_point_position())));
+    build_opts.add_option_if(dt == DataType::F16, std::string("-DUSE_F16"));
     // Tell the kernel that the width is not a multiple of 16
-    if((input->info()->dimension(0) % max_cl_vector_width) != 0)
-    {
-        build_opts.emplace("-DNON_MULTIPLE_OF_16");
-    }
-
-    if(beta != 1.0f)
-    {
-        build_opts.emplace(("-DBETA=" + float_to_string_with_full_precision(beta)));
-    }
+    build_opts.add_option_if((input->info()->dimension(0) % max_cl_vector_width) != 0, std::string("-DNON_MULTIPLE_OF_16"));
+    build_opts.add_option_if(is_data_type_fixed_point(dt) && (beta != 1.0f), std::string("-DBETA=" + support::cpp11::to_string(beta_int)));
+    build_opts.add_option_if(is_data_type_float(dt) && (beta != 1.0f), std::string("-DBETA=" + float_to_string_with_full_precision(beta)));
 
     // Create kernel
-    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts));
+    _kernel = static_cast<cl::Kernel>(CLKernelLibrary::get().create_kernel("softmax_layer_shift_exp_sum", build_opts.options()));
 
     // Set fixed arguments
     unsigned int idx = 4 * num_arguments_per_3D_tensor(); //Skip the input and output parameters