COMPMID-415: Move SoftmaxLayer to new validation

Change-Id: I68bb359021256e67892e4fc00d436f9027a3bd07
Reviewed-on: http://mpd-gerrit.cambridge.arm.com/80942
Reviewed-by: Anthony Barbier <anthony.barbier@arm.com>
Tested-by: Kaizen <jeremy.johnson+kaizengerrit@arm.com>

1 files changed, 0 insertions, 79 deletions

diff --git a/tests/validation/TensorOperations.h b/tests/validation/TensorOperations.h
index 359dfe8d03..5018bfdb2b 100644
--- a/tests/validation/TensorOperations.h
+++ b/tests/validation/TensorOperations.h
@@ -1606,85 +1606,6 @@ void roi_pooling_layer(const Tensor<T> &in, Tensor<T> &out, const std::vector<RO
     }
 }
 
-// Softmax Layer
-template <typename T, typename std::enable_if<is_floating_point<T>::value, int>::type * = nullptr>
-void softmax_layer(const Tensor<T> &in, Tensor<T> &out)
-{
-    const int cols       = static_cast<int>(in.shape()[0]);
-    const int upper_dims = in.shape().total_size() / cols;
-    for(int r = 0; r < upper_dims; ++r)
-    {
-        // Find max
-        T max = std::numeric_limits<T>::lowest();
-        for(int c = 0; c < cols; ++c)
-        {
-            const T x = in[r * cols + c];
-            if(x > max)
-            {
-                max = x;
-            }
-        }
-
-        // Regularize
-        T sum(0);
-        for(int c = 0; c < cols; ++c)
-        {
-            const T res       = exp(in[r * cols + c] - max);
-            out[r * cols + c] = res;
-            sum += res;
-        }
-
-        // Normalize
-        const T norm_val = static_cast<T>(1) / sum;
-        for(int c = 0; c < cols; ++c)
-        {
-            out[r * cols + c] *= norm_val;
-        }
-    }
-}
-template <typename T, typename std::enable_if<std::is_integral<T>::value, int>::type * = nullptr>
-void softmax_layer(const Tensor<T> &in, Tensor<T> &out)
-{
-    using namespace fixed_point_arithmetic;
-    using promoted_T = typename test::traits::promote<T>::type;
-
-    const int fixed_point_position = in.fixed_point_position();
-    const int cols                 = static_cast<int>(in.shape()[0]);
-    const int upper_dims           = in.shape().total_size() / cols;
-
-    for(int r = 0; r < upper_dims; ++r)
-    {
-        // Find max
-        fixed_point<T> max(std::numeric_limits<T>::lowest(), fixed_point_position, true);
-        for(int c = 0; c < cols; ++c)
-        {
-            const fixed_point<T> x(in[r * cols + c], fixed_point_position, true);
-            if(x > max)
-            {
-                max = x;
-            }
-        }
-
-        // Regularize
-        fixed_point<promoted_T> sum(0, fixed_point_position);
-        for(int c = 0; c < cols; ++c)
-        {
-            const fixed_point<T> x(in[r * cols + c], fixed_point_position, true);
-            fixed_point<T>       res = exp(x - max);
-            out[r * cols + c]        = res.raw();
-            sum                      = add(sum, static_cast<fixed_point<promoted_T>>(res));
-        }
-
-        // Normalize
-        fixed_point<T> sat_sum(sum);
-        for(int c = 0; c < cols; ++c)
-        {
-            const fixed_point<T> x(out[r * cols + c], fixed_point_position, true);
-            out[r * cols + c] = div(x, sat_sum).raw();
-        }
-    }
-}
-
 // Fixed point operations
 template <typename T>
 void fixed_point_operation(const Tensor<T> &in, Tensor<T> &out, FixedPointOp op)