Function arm_minimum_f32

Function Documentation

arm_cmsis_nn_status arm_minimum_f32(const cmsis_nn_context *ctx, const float32_t *input_1_data, const cmsis_nn_dims *input_1_dims, const float32_t *input_2_data, const cmsis_nn_dims *input_2_dims, float32_t *output_data, const cmsis_nn_dims *output_dims)

Elementwise minimum with TensorFlow Lite NHWC broadcasting: each dimension of the two inputs must be equal or 1, and output_dims must be their broadcast shape.

The result for a tie between zeros of opposite sign, and for any non-finite input, is unspecified. The Helium leg is VMAXNM / VMINNM, which implement IEEE maxNum / minNum: they break a zero tie by sign - maximum returns +0.0, minimum returns -0.0 - and they suppress NaN, returning the non-NaN operand and a default quiet NaN when both operands are NaN. The scalar leg breaks the tie by operand position instead, and which position wins is not fixed either: the shipped -Ofast (CMSIS_OPTIMIZATION_LEVEL in the top-level CMakeLists.txt) implies -fno-signed-zeros and -ffinite-math-only, which license the compiler to answer a zero tie or a NaN either way, and the answer measurably differs between build targets, between optimization levels, and between the contiguous and the broadcast-scalar loop of the same build. Both zero answers compare equal to zero, so the difference is invisible to anything that is not bit-exact; a caller that cares about the sign of a zero, or about NaN, must screen its inputs rather than rely on either leg. See issue #316, and #333 for the same -ffinite-math-only caveat on the elementwise family.

Returns:

ARM_CMSIS_NN_SUCCESS on success, or ARM_CMSIS_NN_ARG_ERROR when a pointer is NULL, a dimension is not positive, the shapes are not broadcast-compatible, or the output shape is not their broadcast shape. ctx is unused and may be NULL.