mirror of
https://github.com/retroSoC/retroSoC.git
synced 2026-11-05 06:32:37 +00:00
maksyuki
10c9ed8942
- Introduced differential tests for the APU-P7 frontend profile-1 BAM to ensure consistency with ROM and generator outputs. - Implemented concurrent decode and continuous KWS smoke tests for APU-P7 to validate system stability under load. - Added accuracy qualification tests for APU-P7 to verify through-hardware performance against expected results. - Created contention tests for APU-P8 to assess USB2/SDIO0/APU Gateway A interactions. - Developed quiesced loader admission tests for APU-P8 to ensure proper handling of DMA operations. - Added post-fault visibility tests for APU-P8 HP interconnect to confirm fault handling capabilities. - Enhanced register parity tests to include ABI digest verification for consistency across implementations. - Updated publication register tests to reflect changes in capability constants for P5 and P7 profiles.
350 lines
13 KiB
Python
350 lines
13 KiB
Python
"""Bit-accurate model (BAM) of the frozen APU-P7 frontend numerical profile 1.
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Implements docs/ip/apu.md "P7 frontend numerical profile 1" (lines 2322-2398)
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exactly, mirroring the RTL arithmetic in rtl/ip/multimedia/apu_kws_engine.sv
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operation by operation:
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PCM 16000 x S16 -> positive peak P=max(1,max(x[0..15999]))
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-> 49 frames of 480 samples (hop 320; the last 160 samples only feed P)
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-> Hann Q2.30, real FFT input RNE(x*H/2^15), imaginary zero, zero-pad 512
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-> bit-reversed radix-2 DIT FFT (Q2.30 cos/-sin twiddles, one RNE/2^30 per
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complex multiply, RNE/2 per butterfly sum/diff; components = DFT*64,
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signed-32 with fault on overflow)
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-> bins 0..256, nearest-integer sqrt of the unsigned-64 component squares
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(ties even)
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-> 40 mel triangles Q2.30 (DC bin zeroed), M=RNE(sum/2^32) unsigned UQ28.4
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-> exact rational z=(1000000*M+16*P)/(16000000*P), exact 2^e*m
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normalization, log ROM interpolation with f=65536 allowed
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-> DCT Q2.30, C[j]=RNE(sum(log*D)/2^30) signed Q8.24
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-> q=TZ(C[j]/(2^24*S)+83) with the exact binary32 scale S=0x3f15af17
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(2^24*S == 9809687 == 0x95AF17), low-8-bit wrap to the INT8 feature byte.
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All arithmetic is exact Python integer arithmetic. ROM constants are imported
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from scripts/generate_apu_kws_rtl_constants.py (the same generators that emit
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rtl/ip/multimedia/apu_kws_rom.svh), never duplicated. Where the RTL faults
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(FFT signed-32 component overflow) or wraps (log output truncation to
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signed-32), this model does the same; :class:`FrontendFault` marks the fault
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cases, which valid S16 audio never reaches.
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"""
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from __future__ import annotations
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import math
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import struct
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import sys
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from dataclasses import dataclass
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from decimal import Decimal
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from functools import lru_cache
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from pathlib import Path
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from typing import Final
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sys.path.insert(0, str(Path(__file__).resolve().parent))
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import generate_apu_kws_rtl_constants as gen # noqa: E402
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WINDOW_SAMPLES: Final = 16000
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WINDOW_BYTES: Final = 32000
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FRAME_COUNT: Final = 49
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FRAME_SAMPLES: Final = 480
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FRAME_HOP: Final = 320
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FFT_POINTS: Final = 512
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FFT_BINS: Final = 257
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MEL_BANDS: Final = 40
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MFCC_COEFFICIENTS: Final = 10
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FEATURE_BYTES: Final = FRAME_COUNT * MFCC_COEFFICIENTS
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QUANT_SCALE_BITS: Final = 0x3F15AF17
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QUANT_DIVISOR: Final = 0x0095AF17
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QUANT_BIAS: Final = 83
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_S32_MIN: Final = -(1 << 31)
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_S32_MAX: Final = (1 << 31) - 1
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class FrontendFault(RuntimeError):
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"""The input drives an RTL checked-arithmetic fault range."""
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@lru_cache(maxsize=1)
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def hann_q30() -> tuple[int, ...]:
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"""Hann window coefficients H[n]=RNE(2^30*(1-cos(2*pi*n/480))/2)."""
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return tuple(gen._hann())
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@lru_cache(maxsize=1)
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def twiddle_q30() -> tuple[tuple[int, ...], tuple[int, ...]]:
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"""FFT twiddles: RNE-quantized Q2.30 cos and negative sin of 2*pi*k/512."""
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real, imag = gen._twiddle()
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return tuple(real), tuple(imag)
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@lru_cache(maxsize=1)
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def mel_q30() -> tuple[int, ...]:
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"""Forty mel triangle weight rows, 257 bins each, Q2.30, DC zeroed (flat)."""
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return tuple(gen._mel_weights())
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@lru_cache(maxsize=1)
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def dct_q30() -> tuple[int, ...]:
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"""DCT coefficients D[j,b]=RNE(2^30*sqrt(2/40)*cos(pi*(b+1/2)*j/40)) (flat)."""
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return tuple(gen._dct())
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@lru_cache(maxsize=1)
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def log_q24() -> tuple[int, ...]:
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"""Log ROM L[i]=RNE(2^24*ln(1+i/1024)) for i=0..1024, signed Q8.24."""
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return tuple(gen._log_rom())
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@lru_cache(maxsize=1)
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def ln2_q24() -> int:
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"""LN2=RNE(2^24*ln(2)) signed Q8.24, the ROM localparam ApuKwsLn2Q24."""
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return gen._rne(gen.TWO.ln() * Decimal(1 << 24))
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@lru_cache(maxsize=1)
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def _bit_reverse9() -> tuple[int, ...]:
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return tuple(int(f"{index:09b}"[::-1], 2) for index in range(FFT_POINTS))
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def _s32(value: int) -> int:
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"""Truncate to signed 32 bits, mirroring the RTL 32'(...) conversion."""
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value &= 0xFFFFFFFF
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return value - (1 << 32) if value > _S32_MAX else value
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def _trunc_div(numerator: int, denominator: int) -> int:
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"""TZ(numerator/denominator): truncation toward zero."""
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return numerator // denominator if numerator >= 0 else -((-numerator) // denominator)
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def rne_shift(value: int, shift: int) -> int:
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"""RNE(value / 2^shift) with ties to even, sign symmetric (RTL rne_shift)."""
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if shift == 0:
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return value
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magnitude = -value if value < 0 else value
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quotient = magnitude >> shift
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remainder = magnitude & ((1 << shift) - 1)
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half = 1 << (shift - 1)
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if remainder > half or (remainder == half and (quotient & 1) != 0):
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quotient += 1
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return -quotient if value < 0 else quotient
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def rne_uq32(value: int) -> int:
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"""Unsigned RNE(value / 2^32) with ties to even (RTL rne_uq32)."""
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if value < 0 or value >= 1 << 64:
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raise FrontendFault(f"mel reduction outside u64: {value}")
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quotient = value >> 32
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remainder = value & 0xFFFFFFFF
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if remainder > 0x80000000 or (remainder == 0x80000000 and (quotient & 1) != 0):
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quotient += 1
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return quotient
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def nearest_isqrt(value: int) -> int:
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"""Nearest-integer square root of an unsigned-64 value, ties even."""
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if value < 0 or value >= 1 << 64:
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raise FrontendFault(f"magnitude square outside u64: {value}")
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root = math.isqrt(value)
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lower = value - root * root
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upper = (root + 1) * (root + 1) - value
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if upper < lower or (upper == lower and (root & 1) != 0):
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root += 1
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return root
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def log_mel_q24(mel: int, peak: int) -> int:
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"""Exact rational log stage: Q8.24 ln(M/(16*P)+1e-6) (RTL log_mel_q24)."""
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if not 0 <= mel <= 0xFFFFFFFF:
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raise FrontendFault(f"mel value outside UQ28.4 word: {mel}")
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if not 1 <= peak <= 0xFFFF:
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raise FrontendFault(f"window peak outside u16: {peak}")
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numerator = 1_000_000 * mel + 16 * peak
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denominator = 16_000_000 * peak
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exponent = 0
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if numerator >= denominator:
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normalized = denominator
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while numerator >= normalized << 1:
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normalized <<= 1
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exponent += 1
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else:
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normalized = denominator
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while numerator < normalized:
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numerator <<= 1
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exponent -= 1
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scaled = (numerator - normalized) * 1024
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index = scaled // normalized
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remainder = scaled - index * normalized
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fraction_scaled = remainder * 65536
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fraction = fraction_scaled // normalized
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fraction_remainder = fraction_scaled - fraction * normalized
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if 2 * fraction_remainder > normalized or (
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2 * fraction_remainder == normalized and (fraction & 1) != 0
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):
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fraction += 1 # fraction may be 65536 (spec step 5)
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table = log_q24()
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interpolation = rne_shift((table[index + 1] - table[index]) * fraction, 16)
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return _s32(exponent * ln2_q24() + table[index] + interpolation)
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def quantize_coefficient(coefficient: int) -> int:
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"""Frozen step-7 quantizer: q=TZ(C/(2^24*S)+83) with S=0x3f15af17.
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C/(2^24*S)+83 == (C + 83*9809687)/9809687 as an exact rational; truncating
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the integer division matches both the frozen formula and the RTL
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expression (s_dct_coefficient + 64'sh3087_c475) / 64'sh0095_af17.
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"""
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return _trunc_div(coefficient + QUANT_BIAS * QUANT_DIVISOR, QUANT_DIVISOR)
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def wrap_int8(value: int) -> int:
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"""Low-8-bit wrap of a quantized coefficient, interpreted signed INT8."""
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wrapped = value & 0xFF
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return wrapped - 256 if wrapped >= 128 else wrapped
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def samples_from_pcm(pcm: bytes) -> tuple[int, ...]:
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"""Decode one 32000-byte little-endian S16 window into 16000 samples."""
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if len(pcm) != WINDOW_BYTES:
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raise ValueError(f"profile-1 window must be {WINDOW_BYTES} bytes, got {len(pcm)}")
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return struct.unpack(f"<{WINDOW_SAMPLES}h", pcm)
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def _fft_frame(windowed: list[int], real: list[int], imag: list[int]) -> None:
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"""One 512-point profile-1 FFT in place; windowed holds 480 FFT inputs."""
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twiddle_real, twiddle_imag = twiddle_q30()
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bit_reverse = _bit_reverse9()
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for index in range(FFT_POINTS):
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real[index] = 0
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imag[index] = 0
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for index in range(FRAME_SAMPLES):
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real[bit_reverse[index]] = windowed[index]
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length = 2
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while length <= FFT_POINTS:
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half = length // 2
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step = FFT_POINTS // length
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for group in range(0, FFT_POINTS, length):
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for j in range(half):
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left = group + j
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right = left + half
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wr = twiddle_real[step * j]
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wi = twiddle_imag[step * j]
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right_r = real[right]
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right_i = imag[right]
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tw_r = _s32(rne_shift(right_r * wr - right_i * wi, 30))
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tw_i = _s32(rne_shift(right_r * wi + right_i * wr, 30))
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left_r = real[left]
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left_i = imag[left]
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sum_r = rne_shift(left_r + tw_r, 1)
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sum_i = rne_shift(left_i + tw_i, 1)
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dif_r = rne_shift(left_r - tw_r, 1)
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dif_i = rne_shift(left_i - tw_i, 1)
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for component in (sum_r, sum_i, dif_r, dif_i):
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if component < _S32_MIN or component > _S32_MAX:
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raise FrontendFault(f"FFT component overflow: {component}")
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real[left] = sum_r
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imag[left] = sum_i
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real[right] = dif_r
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imag[right] = dif_i
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length *= 2
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@dataclass(frozen=True)
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class FrontendStages:
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"""Every observable profile-1 stage for one 16000-sample window."""
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samples: tuple[int, ...]
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peak: int
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windowed: tuple[tuple[int, ...], ...] # 49 x 480, RNE(x*H/2^15)
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fft_real: tuple[tuple[int, ...], ...] # 49 x 512 signed-32, unscaled DFT*64
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fft_imag: tuple[tuple[int, ...], ...]
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magnitude: tuple[tuple[int, ...], ...] # 49 x 257
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mel: tuple[tuple[int, ...], ...] # 49 x 40 unsigned UQ28.4
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logs: tuple[tuple[int, ...], ...] # 49 x 40 signed Q8.24
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coeffs: tuple[tuple[int, ...], ...] # 49 x 10 signed Q8.24
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quantized: tuple[tuple[int, ...], ...] # 49 x 10 pre-wrap q
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features: bytes # 490 wrapped INT8 feature bytes
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def frontend_stages(samples: tuple[int, ...] | list[int]) -> FrontendStages:
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"""Run profile 1 on one 16000-sample S16 window and return every stage."""
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if len(samples) != WINDOW_SAMPLES:
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raise ValueError(f"profile-1 window must be {WINDOW_SAMPLES} samples")
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samples = tuple(int(value) for value in samples)
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if any(value < -32768 or value > 32767 for value in samples):
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raise ValueError("profile-1 input must be signed S16")
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hann = hann_q30()
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mel_weights = mel_q30()
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dct = dct_q30()
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peak = max(1, max(samples))
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windowed_rows: list[tuple[int, ...]] = []
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fft_real_rows: list[tuple[int, ...]] = []
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fft_imag_rows: list[tuple[int, ...]] = []
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magnitude_rows: list[tuple[int, ...]] = []
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mel_rows: list[tuple[int, ...]] = []
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real = [0] * FFT_POINTS
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imag = [0] * FFT_POINTS
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for row in range(FRAME_COUNT):
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frame = samples[FRAME_HOP * row : FRAME_HOP * row + FRAME_SAMPLES]
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windowed = [rne_shift(value * coefficient, 15) for value, coefficient in zip(frame, hann)]
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_fft_frame(windowed, real, imag)
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windowed_rows.append(tuple(windowed))
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fft_real_rows.append(tuple(real))
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fft_imag_rows.append(tuple(imag))
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magnitude = tuple(
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nearest_isqrt(real[bin_index] * real[bin_index] + imag[bin_index] * imag[bin_index])
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for bin_index in range(FFT_BINS)
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)
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magnitude_rows.append(magnitude)
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mel_rows.append(
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tuple(
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rne_uq32(
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sum(
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magnitude[bin_index] * mel_weights[band * FFT_BINS + bin_index]
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for bin_index in range(FFT_BINS)
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)
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)
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for band in range(MEL_BANDS)
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)
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)
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logs_rows = tuple(
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tuple(log_mel_q24(mel_rows[row][band], peak) for band in range(MEL_BANDS))
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for row in range(FRAME_COUNT)
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)
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coeffs_rows: list[tuple[int, ...]] = []
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for row in range(FRAME_COUNT):
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coeffs = []
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for coefficient in range(MFCC_COEFFICIENTS):
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total = sum(
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logs_rows[row][band] * dct[coefficient * MEL_BANDS + band]
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for band in range(MEL_BANDS)
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)
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if total < -(1 << 63) or total >= 1 << 63:
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raise FrontendFault(f"DCT reduction outside s64: {total}")
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coeffs.append(rne_shift(total, 30))
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coeffs_rows.append(tuple(coeffs))
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quantized_rows = tuple(
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tuple(quantize_coefficient(coeffs_rows[row][j]) for j in range(MFCC_COEFFICIENTS))
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for row in range(FRAME_COUNT)
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)
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features = bytes(value & 0xFF for row in quantized_rows for value in row)
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return FrontendStages(
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samples=samples,
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peak=peak,
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windowed=tuple(windowed_rows),
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fft_real=tuple(fft_real_rows),
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fft_imag=tuple(fft_imag_rows),
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magnitude=tuple(magnitude_rows),
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mel=tuple(mel_rows),
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logs=logs_rows,
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coeffs=tuple(coeffs_rows),
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quantized=quantized_rows,
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features=features,
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)
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def mfcc_profile1(pcm: bytes) -> bytes:
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"""Map one 32000-byte padded PCM window to its 490 profile-1 MFCC bytes."""
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return frontend_stages(samples_from_pcm(pcm)).features
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