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-rw-r--r--arm_compute/core/utils/misc/ShapeCalculator.h32
1 files changed, 32 insertions, 0 deletions
diff --git a/arm_compute/core/utils/misc/ShapeCalculator.h b/arm_compute/core/utils/misc/ShapeCalculator.h
index d72547ed07..cb04182c21 100644
--- a/arm_compute/core/utils/misc/ShapeCalculator.h
+++ b/arm_compute/core/utils/misc/ShapeCalculator.h
@@ -275,6 +275,38 @@ inline TensorShape compute_flatten_shape(const ITensorInfo *input)
return output_shape;
}
+inline TensorShape compute_softmax_shape(const ITensorInfo *input, size_t axis = 1)
+{
+ // The output shape will be a 2D version of the input. For instance:
+ // - [x,y,z] and axis 1 will return [x, y*z]
+ // - [x,y,z,w] and axis 2 will return [x*y, w*z]
+ // - [x,y,z,w] and axis 3 will return [x*y*z, w]
+ TensorShape shape2D = input->tensor_shape();
+
+ if(axis < input->num_dimensions())
+ {
+ // Collapse from axis onward (this changes the shape)
+ shape2D.collapse_from(axis);
+
+ // Collapse the rest (collapse is inclusive)
+ shape2D.collapse(shape2D.num_dimensions() - 1);
+ }
+ else
+ {
+ // Collapse everything
+ shape2D.collapse(shape2D.num_dimensions());
+ }
+
+ if(axis == 0)
+ {
+ // If axis is zero the first dim should be one. Since
+ // collapse is an inclusive operation we need to shift
+ shape2D.shift_right(1);
+ }
+
+ return shape2D;
+}
+
inline TensorShape compute_interleave_custom_shape(const TensorShape &input, const int x_interleave, const int y_interleave)
{
TensorShape output_shape{ input };