"""End-to-end pipeline tests (ADR-0020 + ADR-0021).

Verifies:
  1. Actual benchmark kernel → greenlet mode → op_log → DataExecutor → accuracy
  2. CompositeCmd → _feed_loop → DMA → FETCH_STORE → GEMM → STORE → DMA_WB chain
  3. Latency regression: new builtin produces reasonable latency
"""
from __future__ import annotations

from pathlib import Path

import numpy as np

from kernbench.sim_engine.engine import GraphEngine
from kernbench.sim_engine.transaction import Transaction
from kernbench.topology.builder import load_topology
from kernbench.triton_emu.registry import clear_registry, register_kernel

TOPOLOGY_PATH = Path(__file__).parent.parent / "topology.yaml"


def _graph():
    return load_topology(TOPOLOGY_PATH)


def _engine(enable_data=False):
    return GraphEngine(_graph(), enable_data=enable_data)


def _hbm_pa(sip=0, cube=0, pe_id=0):
    from kernbench.policy.address.phyaddr import PhysAddr
    slice_bytes = 48 * (1 << 30) // 8
    pa = PhysAddr.pe_hbm_addr(
        rack_id=0, sip_id=sip, cube_id=cube, pe_id=pe_id,
        pe_local_hbm_offset=0x1000, slice_size_bytes=slice_bytes,
    )
    return pa.encode()


def _inject_kernel(engine, kernel_name, kernel_fn, *, args=(), enable_data=False):
    """Inject a kernel directly into PE_CPU inbox and run."""
    from kernbench.runtime_api.kernel import KernelLaunchMsg, KernelRef

    pe_cpu_id = "sip0.cube0.pe0.pe_cpu"
    done = engine._env.event()
    txn = Transaction(
        request=KernelLaunchMsg(
            correlation_id="test", request_id=kernel_name,
            kernel_ref=KernelRef(name=kernel_name, kind="builtin"),
            args=args,
        ),
        path=[pe_cpu_id], step=0, nbytes=0, done=done,
    )

    def inject():
        yield engine._components[pe_cpu_id]._inbox.put(txn)
        yield done

    engine._env.process(inject())
    engine._env.run()
    return engine._env.now, txn


# ── 1. CompositeCmd GEMM pipeline E2E ────────────────────────────────


def test_composite_gemm_pipeline_completes():
    """CompositeCmd(gemm) runs through full pipeline: scheduler → DMA → fetch → GEMM → store → DMA."""
    clear_registry()
    pa = _hbm_pa()

    def kernel(tl):
        a = tl.load(pa, shape=(32, 64), dtype="f16")
        b = tl.ref(pa, shape=(64, 32), dtype="f16")
        h = tl.composite(op="gemm", a=a, b=b, out_ptr=pa)
        tl.wait(h)

    register_kernel("e2e_gemm", kernel)
    engine = _engine()
    latency_ns, _ = _inject_kernel(engine, "e2e_gemm", kernel)
    assert latency_ns > 0, "Pipeline should take non-zero time"


def test_composite_math_pipeline_completes():
    """CompositeCmd(math) runs through full pipeline."""
    clear_registry()
    pa = _hbm_pa()

    def kernel(tl):
        a = tl.load(pa, shape=(32, 32), dtype="f16")
        h = tl.composite(op="math", a=a, out_ptr=pa, math_op="exp")
        tl.wait(h)

    register_kernel("e2e_math", kernel)
    engine = _engine()
    latency_ns, _ = _inject_kernel(engine, "e2e_math", kernel)
    assert latency_ns > 0


# ── 2. Greenlet mode + op_log generation ─────────────────────────────


def test_greenlet_mode_generates_op_log():
    """enable_data=True → greenlet mode → op_log records generated."""
    clear_registry()
    pa = _hbm_pa()

    def kernel(tl):
        a = tl.load(pa, shape=(32, 64), dtype="f16")
        b = tl.ref(pa, shape=(64, 32), dtype="f16")
        h = tl.composite(op="gemm", a=a, b=b, out_ptr=pa)
        tl.wait(h)

    register_kernel("e2e_oplog", kernel)
    engine = _engine(enable_data=True)
    latency_ns, _ = _inject_kernel(engine, "e2e_oplog", kernel)

    assert latency_ns > 0
    records = engine.op_log
    # Should have DMA read + composite/GEMM records
    assert len(records) > 0
    op_kinds = {r.op_kind for r in records}
    assert "memory" in op_kinds, f"Expected memory ops, got {op_kinds}"


# ── 3. Phase 1 → Phase 2 accuracy (GEMM) ────────────────────────────


def test_phase1_phase2_gemm_accuracy():
    """Full pipeline: greenlet + MemoryStore → op_log → DataExecutor → verify."""
    from kernbench.sim_engine.data_executor import DataExecutor

    clear_registry()
    pa_a = _hbm_pa(pe_id=0)
    pa_b = _hbm_pa(pe_id=1)  # different PE offset for distinct address
    pa_out = _hbm_pa(pe_id=2)

    # Prepare input data in MemoryStore
    a_data = np.random.randn(32, 64).astype(np.float16)
    b_data = np.random.randn(64, 32).astype(np.float16)

    def kernel(tl):
        a = tl.load(pa_a, shape=(32, 64), dtype="f16")
        b = tl.ref(pa_b, shape=(64, 32), dtype="f16")
        h = tl.composite(op="gemm", a=a, b=b, out_ptr=pa_out)
        tl.wait(h)

    register_kernel("e2e_accuracy", kernel)
    engine = _engine(enable_data=True)

    # Seed MemoryStore with actual data
    engine.memory_store.write("hbm", pa_a, a_data)
    engine.memory_store.write("hbm", pa_b, b_data)

    latency_ns, _ = _inject_kernel(engine, "e2e_accuracy", kernel)
    assert latency_ns > 0

    # Phase 2: execute GEMM ops from op_log
    gemm_records = [r for r in engine.op_log if r.op_kind == "gemm"]
    if len(gemm_records) > 0:
        snap = engine.memory_store.snapshot()
        executor = DataExecutor(gemm_records, snap)
        executor.run()

        # Verify: check that GEMM produced correct result
        expected = (a_data.astype(np.float32) @ b_data.astype(np.float32)).astype(np.float16)
        # The result address depends on tiling, check any gemm output
        for r in gemm_records:
            if "dst_addr" in r.params:
                try:
                    result = snap.read("tcm", r.params["dst_addr"])
                    assert np.allclose(result, expected[:result.shape[0], :result.shape[1]],
                                       rtol=1e-2, atol=1e-2), \
                        f"GEMM result mismatch at addr {r.params['dst_addr']}"
                except KeyError:
                    pass  # Address not in store (intermediate tile)


# ── 4. Latency regression ────────────────────────────────────────────


def test_latency_positive_and_consistent():
    """Multiple runs of same kernel produce same latency (deterministic)."""
    clear_registry()
    pa = _hbm_pa()

    def kernel(tl):
        a = tl.load(pa, shape=(32, 64), dtype="f16")
        b = tl.ref(pa, shape=(64, 32), dtype="f16")
        h = tl.composite(op="gemm", a=a, b=b, out_ptr=pa)
        tl.wait(h)

    register_kernel("e2e_latency", kernel)

    engine1 = _engine()
    ns1, _ = _inject_kernel(engine1, "e2e_latency", kernel)

    clear_registry()
    register_kernel("e2e_latency", kernel)
    engine2 = _engine()
    ns2, _ = _inject_kernel(engine2, "e2e_latency", kernel)

    assert ns1 > 0
    assert ns1 == ns2, f"Non-deterministic latency: {ns1} vs {ns2}"


def test_multi_tile_latency_greater_than_single():
    """Multi-tile GEMM (K=128) takes longer than single-tile (K=64)."""
    clear_registry()
    pa = _hbm_pa()

    def single_kernel(tl):
        a = tl.load(pa, shape=(32, 64), dtype="f16")
        b = tl.ref(pa, shape=(64, 32), dtype="f16")
        h = tl.composite(op="gemm", a=a, b=b, out_ptr=pa)
        tl.wait(h)

    register_kernel("e2e_single", single_kernel)
    engine1 = _engine()
    ns_single, _ = _inject_kernel(engine1, "e2e_single", single_kernel)

    clear_registry()

    def multi_kernel(tl):
        a = tl.load(pa, shape=(32, 128), dtype="f16")
        b = tl.ref(pa, shape=(128, 32), dtype="f16")
        h = tl.composite(op="gemm", a=a, b=b, out_ptr=pa)
        tl.wait(h)

    register_kernel("e2e_multi", multi_kernel)
    engine2 = _engine()
    ns_multi, _ = _inject_kernel(engine2, "e2e_multi", multi_kernel)

    assert ns_multi > ns_single, \
        f"Multi-tile ({ns_multi:.1f}ns) should be > single-tile ({ns_single:.1f}ns)"