mirror of
https://github.com/SikongJueluo/Mini-Nav.git
synced 2026-07-13 04:25:32 +08:00
SikongJueluo
e4cbb5e30d
- add TOPK_K, FIFO_DEPTH, RESULT_SERIAL parameters to cam_params - add candidate_fifo: synchronous ready/valid FIFO for (row, score) candidates - add topk_tracker: tracks top-K candidates with clear/ready handshake - add result_serializer: serializes packed Top-K array into rank-ordered stream - refactor match_engine_pipeline from 4-state to 8-state Top-K pipeline - extend cam_top with serial Top-K interface (result_rank/row/score/last) - add backward-compatible top1_index/top1_score aliases from rank-0 beat - add comprehensive tests for all new modules
134 lines
4.4 KiB
Python
134 lines
4.4 KiB
Python
from __future__ import annotations
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import cocotb
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from cocotb.clock import Clock
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from cocotb.triggers import RisingEdge
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# ── Parameter defaults (matching cam_params.svh with NUM_ROWS=4096, HASH_BITS=512) ──
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K = 4
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ROW_BITS = 12
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SCORE_BITS = 10 # $clog2(512 + 1)
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ROW_SENTINEL = (1 << ROW_BITS) - 1 # all-ones
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def golden(candidates, k=K):
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"""Return top-k candidates sorted by score desc, then row asc (higher score wins; lower row breaks ties)."""
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return sorted(candidates, key=lambda item: (-item[1], item[0]))[:k]
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def unpack(dut, k=K):
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"""Read packed topk_rows_o and topk_scores_o; return list of (row, score) tuples ordered by rank."""
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rows_packed = int(dut.topk_rows_o.value)
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scores_packed = int(dut.topk_scores_o.value)
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result = []
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for i in range(k):
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row = (rows_packed >> (i * ROW_BITS)) & ((1 << ROW_BITS) - 1)
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score = (scores_packed >> (i * SCORE_BITS)) & ((1 << SCORE_BITS) - 1)
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result.append((row, score))
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return result
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# ── Helpers ──────────────────────────────────────────────────────────────────────
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async def reset_tracker(dut):
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"""Assert reset for 5 cycles, release, then wait 2 cycles."""
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dut.rst_n.value = 0
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dut.clear_i.value = 0
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dut.candidate_valid_i.value = 0
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for _ in range(5):
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await RisingEdge(dut.clk)
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dut.rst_n.value = 1
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for _ in range(2):
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await RisingEdge(dut.clk)
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async def push_candidate(dut, row: int, score: int):
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"""Drive one candidate handshake (candidate_ready_o is always 1)."""
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dut.candidate_valid_i.value = 1
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dut.candidate_row_i.value = row
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dut.candidate_score_i.value = score
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await RisingEdge(dut.clk)
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dut.candidate_valid_i.value = 0
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# ── Test 1: Basic ordering ───────────────────────────────────────────────────────
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@cocotb.test()
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async def tracker_orders_by_score_then_lower_row(dut):
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"""
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Push candidates [(5,10), (3,11), (2,11), (9,7), (1,11), (0,3)] and verify
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the tracker's Top-4 matches golden: [(1,11), (2,11), (3,11), (5,10)].
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"""
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cocotb.start_soon(Clock(dut.clk, 10, unit="ns").start())
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await reset_tracker(dut)
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candidates = [(5, 10), (3, 11), (2, 11), (9, 7), (1, 11), (0, 3)]
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for row, score in candidates:
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await push_candidate(dut, row, score)
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result = unpack(dut)
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expected = golden(candidates)
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assert result == expected, f"Expected {expected}, got {result}"
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assert dut.update_pending_o.value == 0, "update_pending_o should be 0"
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# ── Test 2: Clear restarts query ─────────────────────────────────────────────────
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@cocotb.test()
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async def tracker_clear_starts_new_query(dut):
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"""
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After candidate (7,60), pulse clear_i, send candidate (4,12).
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Expect rank 0 = (4,12), remaining slots = sentinel rows, score 0.
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"""
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cocotb.start_soon(Clock(dut.clk, 10, unit="ns").start())
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await reset_tracker(dut)
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# Push (7, 60)
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await push_candidate(dut, 7, 60)
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# Pulse clear
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dut.clear_i.value = 1
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await RisingEdge(dut.clk)
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dut.clear_i.value = 0
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# Push (4, 12)
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await push_candidate(dut, 4, 12)
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result = unpack(dut)
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expected = [(4, 12)] + [(ROW_SENTINEL, 0)] * (K - 1)
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assert result == expected, f"Expected {expected}, got {result}"
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# ── Test 3: Random validation against golden ─────────────────────────────────────
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@cocotb.test()
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async def tracker_matches_random_python_golden(dut):
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"""
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Push 100 candidates (row in [0,63], score in [0,127]) seeded at 42.
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Verify final Top-4 matches Python golden model.
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"""
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import random
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random.seed(42)
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cocotb.start_soon(Clock(dut.clk, 10, unit="ns").start())
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await reset_tracker(dut)
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max_row = 64
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max_score = 128
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candidates = []
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for _ in range(100):
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row = random.randint(0, max_row - 1)
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score = random.randint(0, max_score - 1)
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candidates.append((row, score))
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await push_candidate(dut, row, score)
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result = unpack(dut)
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expected = golden(candidates)
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assert result == expected, f"Expected {expected}, got {result}"
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