diff --git a/examples/imagenet/train_new.py b/examples/imagenet/train_new.py
index e3ebcc22..68c1ba4b 100644
--- a/examples/imagenet/train_new.py
+++ b/examples/imagenet/train_new.py
@@ -531,7 +531,9 @@ def main_worker(gpu, ngpus_per_node, args):
 
     if args.local_rank == 0 or args.gpu is not None:
         monitor = ZeusMonitor(
-            gpu_indices=list(range(args.local_world_size)) if args.gpu is None else [args.gpu],
+            gpu_indices=list(range(args.local_world_size))
+            if args.gpu is None
+            else [args.gpu],
         )
         plo = GlobalPowerLimitOptimizer(
             monitor=monitor,
@@ -545,8 +547,6 @@ def main_worker(gpu, ngpus_per_node, args):
         monitor = None
         plo = None
 
-
-
     for epoch in range(args.start_epoch, args.epochs):
         if args.local_rank == 0 or args.gpu is not None:
             plo.on_epoch_begin()
diff --git a/pyproject.toml b/pyproject.toml
index 7e792114..e9eaf44e 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -16,6 +16,7 @@ ignore = [
   "B019",     # Usage of functools.lru_cache
   "PLR0913",  # Too many function arguments
   "B905",     # zip strict argument
+  "PLR0915",  # Too many statements
 ]
 line-length = 120
 
diff --git a/zeus/optimizer/power_limit.py b/zeus/optimizer/power_limit.py
index 50bfc987..2c15fb57 100644
--- a/zeus/optimizer/power_limit.py
+++ b/zeus/optimizer/power_limit.py
@@ -81,6 +81,7 @@ class Done:
 @dataclass
 class Measurement:
     """POD for GPU energy and time measurements for one power limit."""
+
     power_limit: int  # In Watts.
     energy: float
     time: float
@@ -187,9 +188,15 @@ def __init__(
         else:
             measurements = json.load(self.profile_path.open())["measurements"]
             self.measurements = [Measurement(**m) for m in measurements]
-            self.logger.info("Loaded previous profiling results from '%s'.", str(self.profile_path))
+            self.logger.info(
+                "Loaded previous profiling results from '%s'.", str(self.profile_path)
+            )
             optimal_power_limit = self._compute_optimal_power_limit()
-            self.logger.info("Optimal power limit is %d W.", optimal_power_limit // 1000)
+            self.logger.info(
+                "Optimal power limit is %d W for eta_knob %f.",
+                optimal_power_limit // 1000,
+                self.eta_knob,
+            )
             self.state = Done(optimal_power_limit=optimal_power_limit)
             self._set_power_limit(self.state.optimal_power_limit)
 
@@ -257,11 +264,13 @@ def on_step_begin(self) -> None:
                     "Finished profiling for power limit %d W.",
                     self.state.current_power_limit // 1000,
                 )
-                self.measurements.append(Measurement(
-                    power_limit=self.state.current_power_limit // 1000,
-                    energy=measurement.total_energy,
-                    time=measurement.time,
-                ))
+                self.measurements.append(
+                    Measurement(
+                        power_limit=self.state.current_power_limit // 1000,
+                        energy=measurement.total_energy,
+                        time=measurement.time,
+                    )
+                )
                 # If we're done profiling all power limits, compute the optimal
                 # power limit and transition to the Done state. Otherwise, move
                 # on to the Warmup phase for the next power limit.
@@ -317,7 +326,8 @@ def _compute_optimal_power_limit(self) -> int:
         """
         max_power = max(self.power_limits) // 1000 * len(self.monitor.gpu_indices)
         cost_map = {
-            measurement.power_limit * 1000: zeus_cost(
+            measurement.power_limit
+            * 1000: zeus_cost(
                 energy=measurement.energy,
                 time=measurement.time,
                 eta_knob=self.eta_knob,