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$assert BATCH_TILE % 8 == 0 |
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$assert BATCH_TILE >= 8 |
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$ABC = "01234567456789ABCDEFGHIJKLMNOPQRSTUVWXYZ" |
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$assert OP in ["ADD", "DIV", "MAX", "MIN", "MUL", "SUB", "SQRDIFF"] |
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$assert ACTIVATION in ["LINEAR", "MINMAX"] |
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#include <assert.h> |
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#include <arm_neon.h> |
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#include <xnnpack/common.h> |
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#include <xnnpack/vbinary.h> |
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$VOPQ_F16 = { |
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$ "ADD": lambda x, y: "vaddq_f16(%s, %s)" % (x, y), |
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$ "DIV": lambda x, y: "vdivq_f16(%s, %s)" % (x, y), |
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$ "MAX": lambda x, y: "vmaxq_f16(%s, %s)" % (x, y), |
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$ "MIN": lambda x, y: "vminq_f16(%s, %s)" % (x, y), |
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$ "MUL": lambda x, y: "vmulq_f16(%s, %s)" % (x, y), |
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$ "SUB": lambda x, y: "vsubq_f16(%s, %s)" % (x, y), |
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$ "SQRDIFF": lambda x, y: "vsubq_f16(%s, %s)" % (x, y), |
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$}[OP] |
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$SUFFIX = {"LINEAR": "", "MINMAX": "_minmax"}[ACTIVATION] |
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$PARAMS = {"LINEAR": "xnn_f16_default_params", "MINMAX": "xnn_f16_minmax_params"}[ACTIVATION] |
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$ISA = "aarch64_neonfp16arith" if OP == "DIV" else "neonfp16arith" |
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void xnn_f16_v${OP.lower()}${SUFFIX}_ukernel__${ISA}_x${BATCH_TILE}( |
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size_t batch, |
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const void* restrict input_a, |
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const void* restrict input_b, |
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void* restrict output, |
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const union ${PARAMS} params[restrict XNN_MIN_ELEMENTS(1)]) XNN_OOB_READS |
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{ |
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assert(batch != 0); |
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assert(batch % sizeof(uint16_t) == 0); |
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assert(input_a != NULL); |
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assert(input_b != NULL); |
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assert(output != NULL); |
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const uint16_t* a = (const uint16_t*) input_a; |
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const uint16_t* b = (const uint16_t*) input_b; |
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uint16_t* o = (uint16_t*) output; |
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$if ACTIVATION == "MINMAX": |
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const float16x8_t vy_min = vreinterpretq_f16_u16(vld1q_dup_u16(¶ms->fp16arith.min)); |
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const float16x8_t vy_max = vreinterpretq_f16_u16(vld1q_dup_u16(¶ms->fp16arith.max)); |
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$if BATCH_TILE > 8: |
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for (; batch >= ${BATCH_TILE} * sizeof(uint16_t); batch -= ${BATCH_TILE} * sizeof(uint16_t)) { |
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$for N in range(0, BATCH_TILE, 8): |
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const float16x8_t va${ABC[N:N+8]} = vreinterpretq_f16_u16(vld1q_u16(a)); a += 8; |
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const float16x8_t vb${ABC[N:N+8]} = vreinterpretq_f16_u16(vld1q_u16(b)); b += 8; |
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$for N in range(0, BATCH_TILE, 8): |
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float16x8_t vy${ABC[N:N+8]} = ${VOPQ_F16("va" + ABC[N:N+8], "vb" + ABC[N:N+8])}; |
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$if OP == "SQRDIFF": |
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$for N in range(0, BATCH_TILE, 8): |
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vy${ABC[N:N+8]} = vmulq_f16(vy${ABC[N:N+8]}, vy${ABC[N:N+8]}); |
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$if ACTIVATION == "MINMAX": |
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$for N in range(0, BATCH_TILE, 8): |
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vy${ABC[N:N+8]} = vmaxq_f16(vy${ABC[N:N+8]}, vy_min); |
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$for N in range(0, BATCH_TILE, 8): |
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vy${ABC[N:N+8]} = vminq_f16(vy${ABC[N:N+8]}, vy_max); |
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$for N in range(0, BATCH_TILE, 8): |
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vst1q_u16(o, vreinterpretq_u16_f16(vy${ABC[N:N+8]})); o += 8; |
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} |
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for (; batch >= 8 * sizeof(uint16_t); batch -= 8 * sizeof(uint16_t)) { |
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const float16x8_t va01234567 = vreinterpretq_f16_u16(vld1q_u16(a)); a += 8; |
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const float16x8_t vb01234567 = vreinterpretq_f16_u16(vld1q_u16(b)); b += 8; |
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float16x8_t vy01234567 = ${VOPQ_F16("va01234567", "vb01234567")}; |
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$if OP == "SQRDIFF": |
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vy01234567 = vmulq_f16(vy01234567, vy01234567); |
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$if ACTIVATION == "MINMAX": |
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vy01234567 = vmaxq_f16(vy01234567, vy_min); |
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vy01234567 = vminq_f16(vy01234567, vy_max); |
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vst1q_u16(o, vreinterpretq_u16_f16(vy01234567)); o += 8; |
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} |
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if XNN_UNLIKELY(batch != 0) { |
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const float16x8_t va01234567 = vreinterpretq_f16_u16(vld1q_u16(a)); |
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const float16x8_t vb01234567 = vreinterpretq_f16_u16(vld1q_u16(b)); |
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float16x8_t vy01234567 = ${VOPQ_F16("va01234567", "vb01234567")}; |
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$if OP == "SQRDIFF": |
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vy01234567 = vmulq_f16(vy01234567, vy01234567); |
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$if ACTIVATION == "MINMAX": |
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vy01234567 = vmaxq_f16(vy01234567, vy_min); |
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vy01234567 = vminq_f16(vy01234567, vy_max); |
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float16x4_t vy0123 = vget_low_f16(vy01234567); |
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if (batch & (4 * sizeof(uint16_t))) { |
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vst1_u16(o, vreinterpret_u16_f16(vy0123)); o += 4; |
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vy0123 = vget_high_f16(vy01234567); |
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} |
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if (batch & (2 * sizeof(uint16_t))) { |
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vst1_lane_u32((void*) o, vreinterpret_u32_f16(vy0123), 0); o += 2; |
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vy0123 = vext_f16(vy0123, vy0123, 2); |
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} |
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if (batch & (1 * sizeof(uint16_t))) { |
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vst1_lane_u16(o, vreinterpret_u16_f16(vy0123), 0); |
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} |
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} |
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} |
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