Merge branch 'master' of https://git.d-popov.com/popov/neuron-tai
This commit is contained in:
@@ -671,6 +671,42 @@ def test_tracker_rebalances_after_middle_range_node_timeout():
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tracker.stop()
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def test_tracker_rebalances_managed_hf_node_after_peer_timeout():
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"""HF nodes auto-assigned by the tracker receive LOAD_SHARD after a peer dies."""
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tracker = TrackerServer(heartbeat_timeout=0.15, rebalance_interval=10.0)
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tracker_port = tracker.start()
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try:
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managed = _post_json(
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f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
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{"endpoint": "http://127.0.0.1:9101", "model": "Qwen2.5-0.5B-Instruct",
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"hf_repo": "Qwen/Qwen2.5-0.5B-Instruct", "num_layers": 24,
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"shard_start": 0, "shard_end": 21, "managed_assignment": True,
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"vram_bytes": 1_000_000_000, "hardware_profile": {}, "score": 1.0},
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)
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expired = _post_json(
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f"http://127.0.0.1:{tracker_port}/v1/nodes/register",
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{"endpoint": "http://127.0.0.1:9102", "model": "Qwen2.5-0.5B-Instruct",
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"hf_repo": "Qwen/Qwen2.5-0.5B-Instruct", "num_layers": 24,
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"shard_start": 22, "shard_end": 23,
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"vram_bytes": 1_000_000_000, "hardware_profile": {}, "score": 1.0},
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)
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time.sleep(0.10)
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_post_json(f"http://127.0.0.1:{tracker_port}/v1/nodes/{managed['node_id']}/heartbeat", {})
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time.sleep(0.10)
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hb = _post_json(f"http://127.0.0.1:{tracker_port}/v1/nodes/{managed['node_id']}/heartbeat", {})
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assert expired["node_id"] not in tracker._registry
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load_directives = [d for d in hb.get("directives", []) if d["action"] == "LOAD_SHARD"]
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assert load_directives
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assert load_directives[-1]["model"] == "Qwen/Qwen2.5-0.5B-Instruct"
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assert load_directives[-1]["start_layer"] == 0
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assert load_directives[-1]["end_layer"] == 23
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finally:
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tracker.stop()
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def test_tracker_route_error_no_nodes():
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"""Tracker returns 503 with clear error when the registry is empty."""
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tracker = TrackerServer()
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@@ -1399,3 +1435,47 @@ def test_route_timeout_config_is_exposed_on_server():
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node = TorchNodeServer(backend=_MinimalBackend(), route_timeout=45.0)
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assert node.route_timeout == 45.0
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def test_torch_node_applies_tracker_load_shard_directive(monkeypatch):
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from meshnet_node import torch_server
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from meshnet_node.torch_server import TorchNodeServer
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class _MinimalBackend:
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def __init__(self, model_id="Qwen/Qwen2.5-0.5B-Instruct", shard_start=0, shard_end=21, quantization="bfloat16"):
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self.model_id = model_id
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self.shard_start = shard_start
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self.shard_end = shard_end
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self.quantization = quantization
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self.total_layers = 24
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self.is_head = shard_start == 0
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self.is_tail = shard_end == 23
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def generate_text(self, *a, **kw): return ""
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def count_prompt_tokens(self, *a): return 0
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def count_text_tokens(self, *a): return 0
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loaded = []
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def fake_load_backend(model_id, shard_start, shard_end, quantization):
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loaded.append((model_id, shard_start, shard_end, quantization))
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return _MinimalBackend(model_id, shard_start, shard_end, quantization)
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monkeypatch.setattr(torch_server, "_load_backend", fake_load_backend)
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node = TorchNodeServer(backend=_MinimalBackend())
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applied = node.apply_tracker_directives([
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{"action": "DROP_SHARD", "model": "Qwen/Qwen2.5-0.5B-Instruct", "shard_start": 0, "shard_end": 21},
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{"action": "LOAD_SHARD", "model": "Qwen/Qwen2.5-0.5B-Instruct", "shard_start": 0, "shard_end": 23,
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"quantization": "bfloat16"},
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])
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assert loaded == [("Qwen/Qwen2.5-0.5B-Instruct", 0, 23, "bfloat16")]
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assert applied == {
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"model": "Qwen/Qwen2.5-0.5B-Instruct",
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"shard_start": 0,
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"shard_end": 23,
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"quantization": "bfloat16",
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"tracker_mode": True,
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}
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assert node.backend.shard_end == 23
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