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// Copyright 2020 Google LLC
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
$assert ELEMENTS_TILE >= 1
$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
#include <assert.h>
#include <xnnpack/common.h>
#include <xnnpack/raddstoreexpminusmax.h>
#include <fp16/bitcasts.h>
void xnn_f32_raddstoreexpminusmax_ukernel__scalar_p5_x${ELEMENTS_TILE}${"" if ACCUMULATORS == 1 else "_acc%d" % ACCUMULATORS}(
size_t elements,
const float* input,
float* output,
float* sum,
float vi_max)
{
assert(elements % sizeof(float) == 0);
const float vmagic_bias = 0x1.8000FEp23f;
// The smallest x for which expf(x) is normalized.
const float vdenorm_cutoff = -0x1.5D589Ep6f;
const float vlog2e = 0x1.715476p+0f;
// Last 7 bits are zeroes
const float vminus_ln2_hi = -0x1.62E400p-1f;
const float vminus_ln2_lo = -0x1.7F7D1Cp-20f;
const float vc1 = 0x1.FFFFF6p-1f;
const float vc2 = 0x1.FFFDC6p-2f;
const float vc3 = 0x1.555A80p-3f;
const float vc4 = 0x1.573A1Ap-5f;
const float vc5 = 0x1.0F9F9Cp-7f;
$if ELEMENTS_TILE > 1:
$for K in range(ACCUMULATORS):
float vacc${K} = 0.0f;
for (; elements >= ${ELEMENTS_TILE} * sizeof(float); elements -= ${ELEMENTS_TILE} * sizeof(float)) {
// Load ${ELEMENTS_TILE} inputs at a time.
$for N in range(ELEMENTS_TILE):
const float vi${N} = input[${N}];
input += ${ELEMENTS_TILE};
// Subtract maximum input x := i - i_max. This implies x <= 0.
$for N in range(ELEMENTS_TILE):
const float vx${N} = vi${N} - vi_max;
// Compute reduced argument n := round(x / log(2)).
// We do it by adding a large number (magic bias) to the product x * (1/log(2)), which cause rounding of the result
// to an integer, then subtracing the large number back. The trick with adding large number is valid only within
// certain bounds (|x| <= 2**22), but thats ok, because inputs outside of [-87.336540, 0.0] underflow expf(x)
// anyway. We fixup the result for such inputs at the very end of the algorithm.
$for N in range(ELEMENTS_TILE):
float vn${N} = vx${N} * vlog2e + vmagic_bias;
// Create a floating-point number s (scale) such that s == 2**n for inputs which don't cause underflow, i.e.
// -87.33642 <= x <= 0.0, and -126 <= n <= 0 accordingly.
$for N in range(ELEMENTS_TILE):
const float vs${N} = fp32_from_bits(fp32_to_bits(vn${N}) << 23);
// Subtract the large number back to get final n := round(x / log(2)).
$for N in range(ELEMENTS_TILE):
vn${N} -= vmagic_bias;
// Compute reduced argument t := x - n * log(2).
// Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
$for N in range(ELEMENTS_TILE):
float vt${N} = vn${N} * vminus_ln2_hi + vx${N};
$for N in range(ELEMENTS_TILE):
vt${N} = vn${N} * vminus_ln2_lo + vt${N};
// Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
$for N in range(ELEMENTS_TILE):
float vp${N} = vc5 * vt${N} + vc4;
$for N in range(ELEMENTS_TILE):
vp${N} = vp${N} * vt${N} + vc3;
$for N in range(ELEMENTS_TILE):
vp${N} = vp${N} * vt${N} + vc2;
$for N in range(ELEMENTS_TILE):
vp${N} = vp${N} * vt${N} + vc1;
// Reconstruct the final f value:
// f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
// = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
// = s + (t * s) * p
$for N in range(ELEMENTS_TILE):
vt${N} *= vs${N};
$for N in range(ELEMENTS_TILE):
float vf${N} = vt${N} * vp${N} + vs${N};
// For inputs below denormal cutoff, replace output with +0.0f.
// Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
$for N in range(ELEMENTS_TILE):
if XNN_UNPREDICTABLE(vx${N} < vdenorm_cutoff) {
vf${N} = 0.0f;
}
// Store ${ELEMENTS_TILE} outputs at a time.
$for N in range(ELEMENTS_TILE):
output[${N}] = vf${N};
output += ${ELEMENTS_TILE};
// Accumulate computed exponents.
$for N in range(ELEMENTS_TILE):
vacc${N % ACCUMULATORS} += vf${N};
}
$if ACCUMULATORS > 1:
// Add up all accumulators to vacc0
$ACC_SLICE = 1
$while ACC_SLICE < ACCUMULATORS:
$for A in range(0, ACCUMULATORS, ACC_SLICE * 2):
$if A + ACC_SLICE < ACCUMULATORS:
vacc${A} += vacc${A + ACC_SLICE};
$ACC_SLICE *= 2
float vacc = vacc0;
$else:
float vacc = 0.0f;
for (; elements >= sizeof(float); elements -= sizeof(float)) {
// Load 1 input at a time.
const float vi = *input++;
// Subtract maximum input x := i - i_max. This implies x <= 0.
const float vx = vi - vi_max;
// Compute reduced argument n := round(x / log(2)).
// We do it by adding a large number (magic bias) to the product x * (1/log(2)), which cause rounding of the result
// to an integer, then subtracing the large number back. The trick with adding large number is valid only within
// certain bounds (|x| <= 2**22), but thats ok, because inputs outside of [-87.336540, 0.0] underflow expf(x)
// anyway. We fixup the result for such inputs at the very end of the algorithm.
float vn = vx * vlog2e + vmagic_bias;
// Create a floating-point number s (scale) such that s == 2**n for inputs which don't cause underflow, i.e.
// -87.33642 <= x <= 0.0, and -126 <= n <= 0 accordingly.
const float vs = fp32_from_bits(fp32_to_bits(vn) << 23);
// Subtract the large number back to get final n := round(x / log(2)).
vn -= vmagic_bias;
// Compute reduced argument t := x - n * log(2).
// Use Cody-Waite range reduction method (note two constants to represent log(2)) to improve accuracy.
float vt = vn * vminus_ln2_hi + vx;
vt = vn * vminus_ln2_lo + vt;
// Compute degree-5 polynomial approxiatmion for exp(t) on [-log(2)/2, log(2)/2].
float vp = vc5 * vt + vc4;
vp = vp * vt + vc3;
vp = vp * vt + vc2;
vp = vp * vt + vc1;
// Reconstruct the final f value:
// f = s * (1 + t * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5)))))
// = s + (t * s) * (c1 + t * (c2 + t * (c3 + t * (c4 + t * c5))))
// = s + (t * s) * p
vt *= vs;
float vf = vt * vp + vs;
// For inputs below denormal cutoff, replace output with +0.0f.
// Note that for NaN inputs, comparison result is false, and outputs are left unchanged.
if XNN_UNPREDICTABLE(vx < vdenorm_cutoff) {
vf = 0.0f;
}
// Store 1 output at a time.
*output++ = vf;
// Accumulate computed exponents.
vacc += vf;
}
*sum = vacc;
}