Merge branch 'main' into experiments/minif2f

experiments/dsp/.gitignore

@@ -0,0 +1 @@
+/result

experiments/dsp/main.py

@@ -183,7 +183,20 @@ def prove(
     # If this throws index out of bound errors it means the source doesn't contain walled off Lean sections.
     print(colored("Sketch:", "yellow"), fl_sketch)
     lean_code, = [extract_lean_code(sketch)[0] for sketch in fl_sketch]
-    state, = server.load_sorry(lean_code)
+    print(colored("Lean code:", "light_grey"), lean_code)
+    states = server.load_sorry(lean_code)
+
+    if len(states) != 1:
+        print(colored("Model must output one compilation unit", "red"))
+        raise NotImplemented
+
+    state = states[0]
+
+    if isinstance(state, list) and len(state) > 0:
+        print(colored("Sketch failed:", "red"), "\n".join(state))
+        # what should we do?
+        raise NotImplemented
+
     agent = HammerAgent()
     result = agent.search(server, state)
     print(colored(f"Result: {result}", "blue"))
@@ -213,13 +226,16 @@ def full_proof_search_dsp_lean(
         eng: Engine,
         server: Server,
         data: list[Datum],
+        path_output: Path,
     ):
     print(colored(f"DSP on {len(data)} points", "blue", attrs=["bold", "underline"]))
     # -- Proof search by DSP over all eval data
-    for datum in tqdm(data, total=len(data), desc='DSP proof loop per data point in benchmark.'):
+    for i, datum in tqdm(enumerate(data), total=len(data), desc='DSP proof loop per data point in benchmark.'):
-        print("Problem:", colored(datum.id, "cyan"))
+        print(f"Problem {i}:", colored(str(datum), "cyan"))
         result = single_proof_search_dsp_lean(eng, server, datum)
-        print(result)
+        file_name = path_output / f"{i:03}.json"
+        with open(file_name, 'w') as f:
+            json.dump({ 'name': str(datum), 'success': result.success, 'steps': result.steps  }, f)
         #server.gc()
     return
 
@@ -253,9 +269,13 @@ def load_data(args) -> list[Datum]:
 # -- Main
 
 def main(args):
-    import time
+    import time, datetime
     start_time = time.time()
+
+    # Setup paths and data
     data_eval = load_data(args)
+    path_output = Path(args.output)
+    path_output.mkdir(exist_ok=True, parents=True)
 
     # Start server
     project_path, lean_path = get_project_and_lean_path()
@@ -302,9 +322,10 @@ def main(args):
     )
 
     # - Full proof search with DSP
-    full_proof_search_dsp_lean(eng, server, data_eval)
+    full_proof_search_dsp_lean(eng, server, data_eval, path_output)
-    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"
+
-    print(colored(msg, "magenta"))
+    dt = datetime.timedelta(seconds=time.time() - start_time)
+    print(colored(f"Time elapsed: {dt}", "magenta"))
 
     # - End run
     # wandb.config.update(config)
@@ -329,6 +350,11 @@ if __name__ == "__main__":
         help="Evaluation dataset path",
         default=experiment_dir / 'debug/toy_example1_dsp/dsp_debug5_sf/dsp_debug5_sf_train.json',
     )
+    parser.add_argument(
+        "--output",
+        help="Result directory",
+        default=experiment_dir / 'result',
+    )
     parser.add_argument(
         "--model",
         help="Model",

experiments/dsp/solve/data.py

@@ -20,7 +20,7 @@ class Datum:
     def __str__(self):
         if self.id:
             return self.id
-        return str(self.nl_problem)
+        return self.nl_problem_str
 
     @property
     def nl_problem_str(self) -> Optional[str]:

experiments/dsp/solve/prompts.py

@@ -100,7 +100,7 @@ SYSTEM_PROMPT_SKETCH_V0 = 'You are an expert mathematician and an expert in the
 STOP_TOKENS_SKETCH_V0: list[str] = ['Informal:', '(*### Problem', '###Solution', 'Formal:']
 prompt_sketch_template_lean4_v0 = ("Translate the informal solution into a sketch in the "
 f"formal Lean 4 proof. Add {TOKEN_PLACEHOLDER} in the formal sketch whenever possible. "
-f"{TOKEN_PLACEHOLDER} will be used to call a automated theorem prover or tactic in Lean 4. "
+f"{TOKEN_PLACEHOLDER} will be used to call a automated theorem prover or tactic in Lean 4. Do not use any lemmas."
 "Here are some examples:\n"
 )
 def get_prompt_sketch_template_4_lean_v0(

experiments/dsp/solve/prove.py

@@ -11,6 +11,8 @@ class HammerAgent(Agent):
         self.goal_tactic_id_map = collections.defaultdict(lambda : 0)
         self.tactics = [
             "aesop",
+            "simp",
+            "linarith",
         ]
 
     def next_tactic(

pantograph/server.py

@@ -180,12 +180,22 @@ class Server:
 
         with open(file_name, 'rb') as f:
             content = f.read()
-            units = [content[begin:end].decode('utf-8') for begin,end in result['units']]
+            units = [
-
+                content[unit["bounary"][0]:unit["boundary"][1]].decode('utf-8')
-        invocations = [TacticInvocation.parse(i) for i in result['invocations']]
+                for unit in result['units']
+            ]
+            invocations = [
+                invocation
+                for unit in result['units']
+                for invocation in [TacticInvocation.parse(i) for i in unit['invocations']]
+            ]
         return units, invocations
 
-    def load_sorry(self, command: str) -> list[GoalState]:
+    def load_sorry(self, command: str) -> list[GoalState | list[str]]:
+        """
+        Executes the compiler on a Lean file. For each compilation unit, either
+        return the gathered `sorry`s, or a list of messages indicating error.
+        """
         result = self.run('frontend.process', {
             'file': command,
             'invocations': False,
@@ -193,9 +203,17 @@ class Server:
         })
         if "error" in result:
             raise ServerError(result["desc"])
+
+        def parse_unit(unit: dict):
+            state_id = unit.get("goalStateId")
+            if state_id is None:
+                # NOTE: `state_id` maybe 0.
+                # Maybe error has occurred
+                return unit["messages"]
+            state = GoalState.parse_inner(state_id, unit["goals"], self.to_remove_goal_states)
+            return state
         states = [
-            GoalState.parse_inner(state_id, goals, self.to_remove_goal_states)
+            parse_unit(unit) for unit in result['units']
-            for (state_id, goals) in result['goalStates']
         ]
         return states
 
@@ -346,6 +364,8 @@ class TestServer(unittest.TestCase):
     def test_load_sorry(self):
         server = Server()
         state0, = server.load_sorry("example (p: Prop): p → p := sorry")
+        if isinstance(state0, list):
+            print(state0)
         self.assertEqual(state0.goals, [
             Goal(
                 [Variable(name="p", t="Prop")],

src

@@ -1 +1 @@
-Subproject commit 10cb32e03f43e9306203d1c4a3852573ec55c4f2
+Subproject commit d0321e72ddb477a5eea1ebee346c5ee00512d22e