Files
nvfp4-megamoe-kernel/dsv4/_archive/model/layer_schedule.py
biondizzle f3b551956d Cleanup Step 2: Archive Lineage P code, fix broken imports
- Move dead dsv4/ modules to dsv4/_archive/ (52 files)
  - model/{dsv4,mtp,layer,layer_schedule}
  - layers/{embedding,attention,ffn,norm} (kept linear,mhc,router,moe,shared_expert,grouped_linear - live)
  - cache/*, kernels/cache/*, kernels/indexer/{csa_indexer,score_topk,compute_valid_lens}
  - kernels/router/{nvfp4_fused_router,dense_router_decode_kernel,dense_router_prefill}
  - ops/{topk,topk_select,rope,router}, loader/{hf_checkpoint,layout_convert}
  - reference/{attention,compressor,csa_attention,moe_pipeline}
  - kernels/compressor/{compress_tail,csa_hca}
- Restore dsv4/ops/{router,custom_ops}.py (needed by live layers)
- Fix dsv4/kernels/{indexer,compressor,attention}/__init__.py (removed broken imports)
- Remove preload_all() from loader.py (dead, referenced nonexistent .cu file)
- Fix loader.py docstring (fused_amax_quantize_nvfp4 → quantize_nvfp4_from_buffer)
- Move broken tests to tests/e2e_archive/
  - test_fused_router, production_values_test, e2e/{one_layer,model_construction,csa_hca}
- vLLM has 0 imports of dsv4 (Step 0 confirmed)
2026-06-02 19:27:07 +00:00

103 lines
3.7 KiB
Python

"""Per-layer-index architecture schedule for DSV4.
Encodes the attention / FFN / routing pattern from the paper. Kept
separate from layer.py so the KV cache allocator can query it without
instantiating any layers.
"""
from __future__ import annotations
from enum import Enum
from dataclasses import dataclass
from typing import List
from dsv4.model.config import DSV4Config
class AttentionType(Enum):
SWA = "swa" # Sliding window only (Flash layers 0-1)
HCA = "hca" # Heavily Compressed Attention (Pro layers 0-1, alternating later)
CSA = "csa" # Compressed Sparse Attention (alternating from layer 2)
class FFNType(Enum):
MOE = "moe" # DeepSeekMoE — both variants use MoE in every layer
class RouterMode(Enum):
HASH = "hash" # Layers 0-2: deterministic by token ID
DENSE = "dense" # Layers 3+: sqrt(softplus) + top-k
@dataclass(frozen=True)
class LayerSpec:
"""The complete architectural type of a single transformer layer."""
layer_idx: int
attn: AttentionType
ffn: FFNType
router_mode: RouterMode
def build_schedule(config: DSV4Config) -> List[LayerSpec]:
"""Produce the full per-layer schedule for a given config.
Paper §4.2.1:
Flash: first 2 layers = pure SWA, then alternating CSA / HCA.
Pro: first 2 layers = HCA, then alternating CSA / HCA.
Both: first 3 MoE layers use hash routing.
'Alternating CSA / HCA' starts with CSA at layer 2 in both variants.
"""
schedule: List[LayerSpec] = []
first_special = config.num_special_first_layers # 2
for i in range(config.num_layers):
# Attention type
if i < first_special:
if config.variant == "flash":
attn = AttentionType.SWA
else: # pro
attn = AttentionType.HCA
else:
# Layer 2 is CSA, layer 3 is HCA, layer 4 is CSA, ...
attn = AttentionType.CSA if (i - first_special) % 2 == 0 else AttentionType.HCA
# FFN type — DSV4 is MoE in every layer.
ffn = FFNType.MOE
# Router mode — hash for the first N MoE layers.
router = RouterMode.HASH if i < config.num_hash_routing_layers else RouterMode.DENSE
schedule.append(LayerSpec(layer_idx=i, attn=attn, ffn=ffn, router_mode=router))
return schedule
def validate_schedule(schedule: List[LayerSpec], config: DSV4Config) -> None:
"""Sanity checks. Wrong schedule = silent garbage, so be loud here."""
assert len(schedule) == config.num_layers, \
f"schedule has {len(schedule)} layers, config says {config.num_layers}"
# First N hash routing layers
for i in range(config.num_hash_routing_layers):
assert schedule[i].router_mode == RouterMode.HASH, \
f"layer {i} should be HASH-routed"
for i in range(config.num_hash_routing_layers, config.num_layers):
assert schedule[i].router_mode == RouterMode.DENSE, \
f"layer {i} should be DENSE-routed"
# First two layers are special
expected_first = AttentionType.SWA if config.variant == "flash" else AttentionType.HCA
for i in range(config.num_special_first_layers):
assert schedule[i].attn == expected_first, \
f"layer {i} should be {expected_first} for {config.variant}"
# Alternation from layer 2
for i in range(config.num_special_first_layers, config.num_layers):
expected = AttentionType.CSA if (i - config.num_special_first_layers) % 2 == 0 \
else AttentionType.HCA
assert schedule[i].attn == expected, \
f"layer {i} should be {expected}, got {schedule[i].attn}"
# Every layer is MoE
for i, spec in enumerate(schedule):
assert spec.ffn == FFNType.MOE, f"layer {i} should be MOE"