Merge pull request #1552 from chenmoneygithub/fix-logging-warning

Fix misleading warning
stanfordnlp · Sep 27, 2024 · b1631ae · b1631ae
2 parents dac7030 + 87768c4
commit b1631ae
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Showing 2 changed files with 11 additions and 13 deletions.
diff --git a/dspy/evaluate/evaluate.py b/dspy/evaluate/evaluate.py
@@ -2,9 +2,9 @@
 import signal
 import sys
 import threading
+import traceback
 import types
 from typing import Any
-import traceback
 
 import pandas as pd
 import tqdm
@@ -69,11 +69,6 @@ def __init__(
         self.return_all_scores = return_all_scores
         self.return_outputs = return_outputs
         self.provide_traceback = provide_traceback
-        if "display" in _kwargs:
-            dspy.logger.warning(
-                "DeprecationWarning: 'display' has been deprecated. To see all information for debugging,"
-                " use 'dspy.set_log_level('debug')'. In the future this will raise an error.",
-            )
 
     def _execute_single_thread(self, wrapped_program, devset, display_progress):
         ncorrect = 0

diff --git a/dspy/teleprompt/copro_optimizer.py b/dspy/teleprompt/copro_optimizer.py
@@ -74,9 +74,6 @@ def __init__(
         self.prompt_model = prompt_model
         self.track_stats = track_stats
 
-        if "verbose" in _kwargs:
-            dspy.logger.warning("DeprecationWarning: 'verbose' has been deprecated. To see all information for debugging, use 'dspy.set_log_level('debug')'. In the future this will raise an error.")
-
     def _check_candidates_equal(self, candidate1, candidate2):
         for p1, p2 in zip(candidate1["program"].predictors(), candidate2["program"].predictors()):
             if self._get_signature(p1).instructions != self._get_signature(p2).instructions:
@@ -199,9 +196,11 @@ def compile(self, student, *, trainset, eval_kwargs):
             for p_i, (p_old, p_new) in enumerate(zip(module.predictors(), module_clone.predictors())):
                 candidates_ = latest_candidates[id(p_old)]  # Use the most recently generated candidates for evaluation
                 if len(module.predictors()) > 1:
+                    # Unless our program has multiple predictors, in which case we need to reevaluate all prompts with
+                    # the new prompt(s) for the other predictor(s).
                     candidates_ = all_candidates[
                         id(p_old)
-                    ]  # Unless our program has multiple predictors, in which case we need to reevaluate all prompts with the new prompt(s) for the other predictor(s)
+                    ]
 
                 # For each candidate
                 for c_i, c in enumerate(candidates_):
@@ -225,7 +224,8 @@ def compile(self, student, *, trainset, eval_kwargs):
                         dspy.logger.debug(f"Predictor {i+1}")
                         self._print_signature(predictor)
                     dspy.logger.info(
-                        f"At Depth {d+1}/{self.depth}, Evaluating Prompt Candidate #{c_i+1}/{len(candidates_)} for Predictor {p_i+1} of {len(module.predictors())}.",
+                        f"At Depth {d+1}/{self.depth}, Evaluating Prompt Candidate #{c_i+1}/{len(candidates_)} for "
+                        f"Predictor {p_i+1} of {len(module.predictors())}.",
                     )
                     score = evaluate(module_clone, devset=trainset, **eval_kwargs)
                     if self.prompt_model:
@@ -270,7 +270,8 @@ def compile(self, student, *, trainset, eval_kwargs):
                 self._set_signature(p_new, updated_signature)
 
                 dspy.logger.debug(
-                    f"Updating Predictor {id(p_old)} to:\ni: {best_candidate['instruction']}\np: {best_candidate['prefix']}",
+                    f"Updating Predictor {id(p_old)} to:\ni: {best_candidate['instruction']}\n"
+                    f"p: {best_candidate['prefix']}",
                 )
                 dspy.logger.debug("Full predictor with update: ")
                 for i, predictor in enumerate(module_clone.predictors()):
@@ -321,7 +322,9 @@ def compile(self, student, *, trainset, eval_kwargs):
                     )(attempted_instructions=attempts)
 
                 if self.prompt_model:
-                    dspy.logger.debug(f"(self.prompt_model.inspect_history(n=1)) {self.prompt_model.inspect_history(n=1)}")
+                    dspy.logger.debug(
+                        f"(self.prompt_model.inspect_history(n=1)) {self.prompt_model.inspect_history(n=1)}"
+                    )
                 # Get candidates for each predictor
                 new_candidates[id(p_base)] = instr.completions
                 all_candidates[id(p_base)].proposed_instruction.extend(instr.completions.proposed_instruction)