blob: 27a6705aad09562b4522e71ed2fcb3dde7d8a74b [file] [log] [blame]
// Copyright 2019 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 CHANNEL_TILE >= 1
$assert ROW_TILE >= 1
$ABC = "0123456789ABCDEFGHIJKLMNOPQRSTUVWXYZ"
#include <assert.h>
#include <xnnpack/math.h>
#include <xnnpack/vmulcaddc.h>
$MIN_F32 = "__builtin_wasm_min_f32" if WASM else "math_min_f32"
$MAX_F32 = "__builtin_wasm_max_f32" if WASM else "math_max_f32"
void xnn_f32_vmulcaddc_minmax_ukernel_c${CHANNEL_TILE}__${"wasm" if WASM else "scalar"}_${ROW_TILE}x(
size_t rows,
size_t channels,
const float*restrict input,
size_t input_stride,
const float*restrict weights,
float*restrict output,
size_t output_stride,
const union xnn_f32_minmax_params params[restrict XNN_MIN_ELEMENTS(1)])
{
assert(rows != 0);
assert(channels != 0);
assert(channels % sizeof(float) == 0);
const size_t input_increment = input_stride * ${ROW_TILE} - channels;
const size_t output_increment = output_stride * ${ROW_TILE} - channels;
const float* i0 = input;
float* o0 = output;
$for M in range(1, ROW_TILE):
const float* i${M} = (const float*) ((uintptr_t) i${M-1} + input_stride);
float* o${M} = (float*) ((uintptr_t) o${M-1} + output_stride);
$if M % 2 == 0:
if XNN_UNPREDICTABLE(rows <= ${M}) {
i${M} = i${M-1};
o${M} = o${M-1};
}
$else:
if XNN_UNPREDICTABLE(rows < ${M+1}) {
i${M} = i${M-1};
o${M} = o${M-1};
}
const float vmin = params->scalar.min;
const float vmax = params->scalar.max;
do {
const float* w = weights;
size_t c = channels;
$if CHANNEL_TILE > 1:
for (; c >= ${CHANNEL_TILE} * sizeof(float); c -= ${CHANNEL_TILE} * sizeof(float)) {
$for C in range(CHANNEL_TILE):
const float vscale${ABC[C]} = w[${C}];
$for M in range(ROW_TILE):
$for C in range(CHANNEL_TILE):
float vacc${M}x${ABC[C]} = i${M}[${C}];
i${M} += ${CHANNEL_TILE};
$for C in range(CHANNEL_TILE):
const float vbias${ABC[C]} = w[${C + CHANNEL_TILE}];
$for M in range(ROW_TILE):
$for C in range(CHANNEL_TILE):
vacc${M}x${ABC[C]} = vacc${M}x${ABC[C]} * vscale${ABC[C]} + vbias${ABC[C]};
$for M in range(ROW_TILE):
$for C in range(CHANNEL_TILE):
vacc${M}x${ABC[C]} = ${MAX_F32}(vacc${M}x${ABC[C]}, vmin);
$for M in range(ROW_TILE):
$for C in range(CHANNEL_TILE):
vacc${M}x${ABC[C]} = ${MIN_F32}(vacc${M}x${ABC[C]}, vmax);
$for M in range(ROW_TILE):
$for C in range(CHANNEL_TILE):
o${M}[${C}] = vacc${M}x${ABC[C]};
o${M} += ${CHANNEL_TILE};
w += ${CHANNEL_TILE * 2};
}
if XNN_UNLIKELY(c != 0) {
do {
const float vscale = *w++;
$for M in range(ROW_TILE):
float vacc${M} = *i${M}++;
const float vbias = w[${CHANNEL_TILE - 1}];
$for M in range(ROW_TILE):
vacc${M} = vacc${M} * vscale + vbias;
$for M in range(ROW_TILE):
vacc${M} = ${MAX_F32}(vacc${M}, vmin);
$for M in range(ROW_TILE):
vacc${M} = ${MIN_F32}(vacc${M}, vmax);
$for M in range(ROW_TILE):
*o${M}++ = vacc${M};
c -= sizeof(float);
} while (c != 0);
}
$else:
do {
const float vscale = w[0];
$for M in range(ROW_TILE):
float vacc${M} = *i${M}++;
const float vbias = w[1];
$for M in range(ROW_TILE):
vacc${M} = vacc${M} * vscale + vbias;
$for M in range(ROW_TILE):
vacc${M} = ${MAX_F32}(vacc${M}, vmin);
$for M in range(ROW_TILE):
vacc${M} = ${MIN_F32}(vacc${M}, vmax);
$for M in range(ROW_TILE):
*o${M}++ = vacc${M};
w += 2;
c -= sizeof(float);
} while (c != 0);
$for M in range(ROW_TILE):
i${M} = (const float*) ((uintptr_t) i${M} + input_increment);
o${M} = (float*) ((uintptr_t) o${M} + output_increment);
$if M % 2 == 1:
if XNN_UNPREDICTABLE(rows < ${ROW_TILE + M + 1}) {
i${M} = i${M-1};
o${M} = o${M-1};
}
$elif M != 0:
if XNN_UNPREDICTABLE(rows <= ${ROW_TILE + M}) {
i${M} = i${M-1};
o${M} = o${M-1};
}
rows = doz(rows, ${ROW_TILE});
} while (rows != 0);
}