Merge branch 'main' into experiments/minif2f
This commit is contained in:
commit
159da09c9d
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@ -0,0 +1 @@
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/result
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@ -183,7 +183,20 @@ def prove(
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# If this throws index out of bound errors it means the source doesn't contain walled off Lean sections.
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print(colored("Sketch:", "yellow"), fl_sketch)
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lean_code, = [extract_lean_code(sketch)[0] for sketch in fl_sketch]
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state, = server.load_sorry(lean_code)
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print(colored("Lean code:", "light_grey"), lean_code)
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states = server.load_sorry(lean_code)
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if len(states) != 1:
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print(colored("Model must output one compilation unit", "red"))
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raise NotImplemented
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state = states[0]
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if isinstance(state, list) and len(state) > 0:
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print(colored("Sketch failed:", "red"), "\n".join(state))
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# what should we do?
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raise NotImplemented
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agent = HammerAgent()
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result = agent.search(server, state)
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print(colored(f"Result: {result}", "blue"))
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@ -213,13 +226,16 @@ def full_proof_search_dsp_lean(
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eng: Engine,
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server: Server,
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data: list[Datum],
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path_output: Path,
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):
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print(colored(f"DSP on {len(data)} points", "blue", attrs=["bold", "underline"]))
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# -- Proof search by DSP over all eval data
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for datum in tqdm(data, total=len(data), desc='DSP proof loop per data point in benchmark.'):
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print("Problem:", colored(datum.id, "cyan"))
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for i, datum in tqdm(enumerate(data), total=len(data), desc='DSP proof loop per data point in benchmark.'):
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print(f"Problem {i}:", colored(str(datum), "cyan"))
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result = single_proof_search_dsp_lean(eng, server, datum)
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print(result)
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file_name = path_output / f"{i:03}.json"
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with open(file_name, 'w') as f:
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json.dump({ 'name': str(datum), 'success': result.success, 'steps': result.steps }, f)
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#server.gc()
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return
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@ -253,9 +269,13 @@ def load_data(args) -> list[Datum]:
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# -- Main
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def main(args):
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import time
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import time, datetime
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start_time = time.time()
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# Setup paths and data
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data_eval = load_data(args)
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path_output = Path(args.output)
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path_output.mkdir(exist_ok=True, parents=True)
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# Start server
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project_path, lean_path = get_project_and_lean_path()
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@ -302,9 +322,10 @@ def main(args):
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)
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# - Full proof search with DSP
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full_proof_search_dsp_lean(eng, server, data_eval)
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msg = f"Time taken: {time.time() - start_time:.2f} seconds, or {(time.time() - start_time) / 60:.2f} minutes, or {(time.time() - start_time) / 3600:.2f} hours.\a"
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print(colored(msg, "magenta"))
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full_proof_search_dsp_lean(eng, server, data_eval, path_output)
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dt = datetime.timedelta(seconds=time.time() - start_time)
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print(colored(f"Time elapsed: {dt}", "magenta"))
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# - End run
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# wandb.config.update(config)
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@ -329,6 +350,11 @@ if __name__ == "__main__":
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help="Evaluation dataset path",
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default=experiment_dir / 'debug/toy_example1_dsp/dsp_debug5_sf/dsp_debug5_sf_train.json',
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)
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parser.add_argument(
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"--output",
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help="Result directory",
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default=experiment_dir / 'result',
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)
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parser.add_argument(
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"--model",
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help="Model",
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@ -20,7 +20,7 @@ class Datum:
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def __str__(self):
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if self.id:
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return self.id
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return str(self.nl_problem)
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return self.nl_problem_str
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@property
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def nl_problem_str(self) -> Optional[str]:
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@ -100,7 +100,7 @@ SYSTEM_PROMPT_SKETCH_V0 = 'You are an expert mathematician and an expert in the
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STOP_TOKENS_SKETCH_V0: list[str] = ['Informal:', '(*### Problem', '###Solution', 'Formal:']
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prompt_sketch_template_lean4_v0 = ("Translate the informal solution into a sketch in the "
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f"formal Lean 4 proof. Add {TOKEN_PLACEHOLDER} in the formal sketch whenever possible. "
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f"{TOKEN_PLACEHOLDER} will be used to call a automated theorem prover or tactic in Lean 4. "
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f"{TOKEN_PLACEHOLDER} will be used to call a automated theorem prover or tactic in Lean 4. Do not use any lemmas."
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"Here are some examples:\n"
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)
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def get_prompt_sketch_template_4_lean_v0(
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@ -11,6 +11,8 @@ class HammerAgent(Agent):
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self.goal_tactic_id_map = collections.defaultdict(lambda : 0)
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self.tactics = [
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"aesop",
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"simp",
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"linarith",
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]
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def next_tactic(
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@ -180,12 +180,22 @@ class Server:
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with open(file_name, 'rb') as f:
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content = f.read()
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units = [content[begin:end].decode('utf-8') for begin,end in result['units']]
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invocations = [TacticInvocation.parse(i) for i in result['invocations']]
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units = [
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content[unit["bounary"][0]:unit["boundary"][1]].decode('utf-8')
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for unit in result['units']
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]
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invocations = [
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invocation
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for unit in result['units']
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for invocation in [TacticInvocation.parse(i) for i in unit['invocations']]
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]
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return units, invocations
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def load_sorry(self, command: str) -> list[GoalState]:
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def load_sorry(self, command: str) -> list[GoalState | list[str]]:
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"""
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Executes the compiler on a Lean file. For each compilation unit, either
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return the gathered `sorry`s, or a list of messages indicating error.
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"""
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result = self.run('frontend.process', {
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'file': command,
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'invocations': False,
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@ -193,9 +203,17 @@ class Server:
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})
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if "error" in result:
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raise ServerError(result["desc"])
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def parse_unit(unit: dict):
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state_id = unit.get("goalStateId")
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if state_id is None:
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# NOTE: `state_id` maybe 0.
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# Maybe error has occurred
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return unit["messages"]
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state = GoalState.parse_inner(state_id, unit["goals"], self.to_remove_goal_states)
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return state
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states = [
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GoalState.parse_inner(state_id, goals, self.to_remove_goal_states)
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for (state_id, goals) in result['goalStates']
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parse_unit(unit) for unit in result['units']
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]
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return states
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@ -346,6 +364,8 @@ class TestServer(unittest.TestCase):
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def test_load_sorry(self):
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server = Server()
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state0, = server.load_sorry("example (p: Prop): p → p := sorry")
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if isinstance(state0, list):
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print(state0)
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self.assertEqual(state0.goals, [
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Goal(
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[Variable(name="p", t="Prop")],
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2
src
2
src
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@ -1 +1 @@
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Subproject commit 10cb32e03f43e9306203d1c4a3852573ec55c4f2
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Subproject commit d0321e72ddb477a5eea1ebee346c5ee00512d22e
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