File size: 8,033 Bytes
d814291
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fe1f842
 
 
 
 
 
 
d814291
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fe1f842
 
 
d814291
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fe1f842
 
 
 
 
 
d814291
 
 
 
 
 
 
 
fe1f842
 
 
d814291
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
fe1f842
 
 
d814291
 
 
 
 
 
 
 
 
 
 
 
fe1f842
 
 
 
 
 
d814291
 
 
 
 
 
 
fe1f842
 
 
d814291
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
from pathlib import Path
import json

from osint_env.training.config import load_self_play_config


def test_self_play_config_defaults_when_missing():
    cfg = load_self_play_config("/tmp/does_not_exist_for_self_play_config.json")
    assert cfg.rounds >= 1
    assert cfg.pipeline_mode in {"legacy", "swarm_v2"}
    assert cfg.model_topology in {"dual", "shared"}
    assert cfg.phase_schedule in {"generator_answerer", "answerer_generator_answerer"}
    assert cfg.tuning_mode in {"full", "lora"}
    assert cfg.generator_phase.max_steps >= 1
    assert cfg.answerer_phase.max_steps >= 1
    assert cfg.generator_reward_weights.hardness > 0.0
    assert cfg.generated_task_max_new_tokens >= 32
    assert cfg.post_training_eval_questions >= 1
    assert cfg.generator_phase.optim == "adamw_torch_fused"
    assert cfg.generator_phase.bf16 is True
    assert cfg.generator_phase.tf32 is True
    assert cfg.generator_phase.generation_batch_size >= 1
    assert cfg.generator_phase.max_prompt_length >= 32
    assert cfg.swarm_v2.generator_swarm.shared_context is True
    assert cfg.swarm_v2.validation.max_support_edges >= 1
    assert cfg.wandb_enabled is False
    assert cfg.wandb_project == "osint-self-play"
    assert cfg.canonical_graph_mode == "generate"


def test_self_play_config_parses_overrides(tmp_path: Path):
    cfg_path = tmp_path / "self_play.json"
    cfg_path.write_text(
        json.dumps(
            {
                "rounds": 5,
                "output_dir": "artifacts/custom_self_play",
                "dry_run": False,
                "pipeline_mode": "swarm_v2",
                "wandb_enabled": True,
                "wandb_project": "osint-train-tests",
                "wandb_entity": "example-team",
                "wandb_run_name_prefix": "ci-self-play",
                "canonical_graph_mode": "fixed",
                "model_topology": "shared",
                "phase_schedule": "answerer_generator_answerer",
                "tuning_mode": "lora",
                "shared_model_name_or_path": "/models/local-base",
                "seed_tasks_per_round": 12,
                "generated_tasks_per_round": 18,
                "generated_task_max_new_tokens": 640,
                "post_training_eval_questions": 9,
                "post_training_eval_answer_max_new_tokens": 96,
                "swarm_v2": {
                    "generator_swarm": {
                        "shared_context": True,
                        "max_agents": 5,
                        "max_breadth": 4,
                        "max_depth": 3,
                        "planner_rounds": 3,
                        "tools_per_agent": 2,
                    },
                    "answerer_swarm": {
                        "shared_context": True,
                        "max_agents": 4,
                        "max_breadth": 3,
                        "max_depth": 2,
                        "planner_rounds": 2,
                        "tools_per_agent": 2,
                    },
                    "validation": {
                        "max_support_edges": 6,
                        "max_path_hops": 3,
                        "max_context_nodes": 10,
                        "max_context_edges": 6,
                        "duplicate_similarity_threshold": 0.75,
                    },
                    "shared_context": {
                        "shared_by_default": True,
                        "max_nodes": 10,
                        "max_edges": 6,
                        "target_pressure": 0.9,
                    },
                },
                "generator_reward_weights": {
                    "validity": 0.2,
                    "hardness": 0.6,
                    "diversity": 0.1,
                    "consistency": 0.1,
                },
                "lora": {
                    "r": 32,
                    "alpha": 64,
                    "dropout": 0.1,
                    "target_modules": ["q_proj", "v_proj"],
                    "bias": "none",
                    "task_type": "CAUSAL_LM",
                },
                "generator_phase": {
                    "model_name_or_path": "Qwen/Qwen2.5-3B-Instruct",
                    "max_steps": 77,
                    "num_generations": 6,
                    "optim": "adamw_torch",
                    "bf16": False,
                    "tf32": False,
                    "generation_batch_size": 12,
                    "max_prompt_length": 768,
                    "save_total_limit": 3,
                    "loss_type": "grpo",
                    "scale_rewards": "group",
                    "output_subdir": "gen_phase",
                },
                "answerer_phase": {
                    "model_name_or_path": "Qwen/Qwen2.5-1.5B-Instruct",
                    "max_steps": 55,
                    "num_generations": 5,
                    "dataloader_num_workers": 6,
                    "dataloader_persistent_workers": False,
                    "dataloader_prefetch_factor": 6,
                    "output_subdir": "ans_phase",
                },
            }
        ),
        encoding="utf-8",
    )

    cfg = load_self_play_config(cfg_path)
    assert cfg.rounds == 5
    assert cfg.output_dir == "artifacts/custom_self_play"
    assert cfg.dry_run is False
    assert cfg.pipeline_mode == "swarm_v2"
    assert cfg.wandb_enabled is True
    assert cfg.wandb_project == "osint-train-tests"
    assert cfg.wandb_entity == "example-team"
    assert cfg.wandb_run_name_prefix == "ci-self-play"
    assert cfg.canonical_graph_mode == "fixed"
    assert cfg.model_topology == "shared"
    assert cfg.phase_schedule == "answerer_generator_answerer"
    assert cfg.tuning_mode == "lora"
    assert cfg.shared_model_name_or_path == "/models/local-base"
    assert cfg.seed_tasks_per_round == 12
    assert cfg.generated_tasks_per_round == 18
    assert cfg.generated_task_max_new_tokens == 640
    assert cfg.post_training_eval_questions == 9
    assert cfg.post_training_eval_answer_max_new_tokens == 96
    assert cfg.swarm_v2.generator_swarm.max_agents == 5
    assert cfg.swarm_v2.answerer_swarm.max_agents == 4
    assert cfg.swarm_v2.validation.max_support_edges == 6
    assert cfg.swarm_v2.shared_context.target_pressure == 0.9
    assert cfg.generator_reward_weights.hardness == 0.6
    assert cfg.lora.r == 32
    assert cfg.lora.alpha == 64
    assert cfg.lora.target_modules == ["q_proj", "v_proj"]

    assert cfg.generator_phase.model_name_or_path == "Qwen/Qwen2.5-3B-Instruct"
    assert cfg.generator_phase.max_steps == 77
    assert cfg.generator_phase.num_generations == 6
    assert cfg.generator_phase.optim == "adamw_torch"
    assert cfg.generator_phase.bf16 is False
    assert cfg.generator_phase.tf32 is False
    assert cfg.generator_phase.generation_batch_size == 12
    assert cfg.generator_phase.max_prompt_length == 768
    assert cfg.generator_phase.save_total_limit == 3
    assert cfg.generator_phase.loss_type == "grpo"
    assert cfg.generator_phase.scale_rewards == "group"
    assert cfg.generator_phase.output_subdir == "gen_phase"

    assert cfg.answerer_phase.model_name_or_path == "Qwen/Qwen2.5-1.5B-Instruct"
    assert cfg.answerer_phase.max_steps == 55
    assert cfg.answerer_phase.num_generations == 5
    assert cfg.answerer_phase.dataloader_num_workers == 6
    assert cfg.answerer_phase.dataloader_persistent_workers is False
    assert cfg.answerer_phase.dataloader_prefetch_factor == 6
    assert cfg.answerer_phase.output_subdir == "ans_phase"


def test_self_play_config_keeps_legacy_mode_when_not_set(tmp_path: Path):
    cfg_path = tmp_path / "legacy_self_play.json"
    cfg_path.write_text(
        json.dumps(
            {
                "rounds": 2,
                "max_support_edges": 11,
            }
        ),
        encoding="utf-8",
    )

    cfg = load_self_play_config(cfg_path)
    assert cfg.pipeline_mode == "legacy"
    assert cfg.max_support_edges == 11
    assert cfg.swarm_v2.validation.max_support_edges == 11