diff --git a/examples/atari/atari_callbacks.py b/examples/atari/atari_callbacks.py
deleted file mode 100644
index d0b4315..0000000
--- a/examples/atari/atari_callbacks.py
+++ /dev/null
@@ -1,33 +0,0 @@
-from tianshou.highlevel.trainer import (
-    TrainerEpochCallbackTest,
-    TrainerEpochCallbackTrain,
-    TrainingContext,
-)
-from tianshou.policy import DQNPolicy
-
-
-class TestEpochCallbackDQNSetEps(TrainerEpochCallbackTest):
-    def __init__(self, eps_test: float):
-        self.eps_test = eps_test
-
-    def callback(self, epoch: int, env_step: int, context: TrainingContext) -> None:
-        policy: DQNPolicy = context.policy
-        policy.set_eps(self.eps_test)
-
-
-class TrainEpochCallbackNatureDQNEpsLinearDecay(TrainerEpochCallbackTrain):
-    def __init__(self, eps_train: float, eps_train_final: float):
-        self.eps_train = eps_train
-        self.eps_train_final = eps_train_final
-
-    def callback(self, epoch: int, env_step: int, context: TrainingContext) -> None:
-        policy: DQNPolicy = context.policy
-        logger = context.logger
-        # nature DQN setting, linear decay in the first 1M steps
-        if env_step <= 1e6:
-            eps = self.eps_train - env_step / 1e6 * (self.eps_train - self.eps_train_final)
-        else:
-            eps = self.eps_train_final
-        policy.set_eps(eps)
-        if env_step % 1000 == 0:
-            logger.write("train/env_step", env_step, {"train/eps": eps})
diff --git a/examples/atari/atari_dqn_hl.py b/examples/atari/atari_dqn_hl.py
index 0c435ee..1253529 100644
--- a/examples/atari/atari_dqn_hl.py
+++ b/examples/atari/atari_dqn_hl.py
@@ -2,10 +2,6 @@
 
 import os
 
-from examples.atari.atari_callbacks import (
-    TestEpochCallbackDQNSetEps,
-    TrainEpochCallbackNatureDQNEpsLinearDecay,
-)
 from examples.atari.atari_network import (
     IntermediateModuleFactoryAtariDQN,
     IntermediateModuleFactoryAtariDQNFeatures,
@@ -20,6 +16,10 @@ from tianshou.highlevel.params.policy_params import DQNParams
 from tianshou.highlevel.params.policy_wrapper import (
     PolicyWrapperFactoryIntrinsicCuriosity,
 )
+from tianshou.highlevel.trainer import (
+    TrainerEpochCallbackTestDQNSetEps,
+    TrainerEpochCallbackTrainDQNEpsLinearDecay,
+)
 from tianshou.utils import logging
 from tianshou.utils.logging import datetime_tag
 
@@ -80,9 +80,9 @@ def main(
         )
         .with_model_factory(IntermediateModuleFactoryAtariDQN())
         .with_trainer_epoch_callback_train(
-            TrainEpochCallbackNatureDQNEpsLinearDecay(eps_train, eps_train_final),
+            TrainerEpochCallbackTrainDQNEpsLinearDecay(eps_train, eps_train_final),
         )
-        .with_trainer_epoch_callback_test(TestEpochCallbackDQNSetEps(eps_test))
+        .with_trainer_epoch_callback_test(TrainerEpochCallbackTestDQNSetEps(eps_test))
         .with_trainer_stop_callback(AtariStopCallback(task))
     )
     if icm_lr_scale > 0:
diff --git a/examples/atari/atari_iqn_hl.py b/examples/atari/atari_iqn_hl.py
index 8f94ece..fd160df 100644
--- a/examples/atari/atari_iqn_hl.py
+++ b/examples/atari/atari_iqn_hl.py
@@ -3,10 +3,6 @@
 import os
 from collections.abc import Sequence
 
-from examples.atari.atari_callbacks import (
-    TestEpochCallbackDQNSetEps,
-    TrainEpochCallbackNatureDQNEpsLinearDecay,
-)
 from examples.atari.atari_network import (
     IntermediateModuleFactoryAtariDQN,
 )
@@ -17,6 +13,10 @@ from tianshou.highlevel.experiment import (
     IQNExperimentBuilder,
 )
 from tianshou.highlevel.params.policy_params import IQNParams
+from tianshou.highlevel.trainer import (
+    TrainerEpochCallbackTestDQNSetEps,
+    TrainerEpochCallbackTrainDQNEpsLinearDecay,
+)
 from tianshou.utils import logging
 from tianshou.utils.logging import datetime_tag
 
@@ -84,9 +84,9 @@ def main(
         )
         .with_preprocess_network_factory(IntermediateModuleFactoryAtariDQN(features_only=True))
         .with_trainer_epoch_callback_train(
-            TrainEpochCallbackNatureDQNEpsLinearDecay(eps_train, eps_train_final),
+            TrainerEpochCallbackTrainDQNEpsLinearDecay(eps_train, eps_train_final),
         )
-        .with_trainer_epoch_callback_test(TestEpochCallbackDQNSetEps(eps_test))
+        .with_trainer_epoch_callback_test(TrainerEpochCallbackTestDQNSetEps(eps_test))
         .with_trainer_stop_callback(AtariStopCallback(task))
         .build()
     )
diff --git a/tianshou/highlevel/trainer.py b/tianshou/highlevel/trainer.py
index 7f70563..da22a32 100644
--- a/tianshou/highlevel/trainer.py
+++ b/tianshou/highlevel/trainer.py
@@ -1,11 +1,11 @@
 from abc import ABC, abstractmethod
 from collections.abc import Callable
 from dataclasses import dataclass
-from typing import TypeVar
+from typing import TypeVar, cast
 
 from tianshou.highlevel.env import Environments
 from tianshou.highlevel.logger import TLogger
-from tianshou.policy import BasePolicy
+from tianshou.policy import BasePolicy, DQNPolicy
 from tianshou.utils.string import ToStringMixin
 
 TPolicy = TypeVar("TPolicy", bound=BasePolicy)
@@ -72,3 +72,52 @@ class TrainerCallbacks:
     epoch_callback_train: TrainerEpochCallbackTrain | None = None
     epoch_callback_test: TrainerEpochCallbackTest | None = None
     stop_callback: TrainerStopCallback | None = None
+
+
+class TrainerEpochCallbackTrainDQNSetEps(TrainerEpochCallbackTrain):
+    """Sets the epsilon value for DQN-based policies at the beginning of the training
+    stage in each epoch.
+    """
+
+    def __init__(self, eps_test: float):
+        self.eps_test = eps_test
+
+    def callback(self, epoch: int, env_step: int, context: TrainingContext) -> None:
+        policy = cast(DQNPolicy, context.policy)
+        policy.set_eps(self.eps_test)
+
+
+class TrainerEpochCallbackTrainDQNEpsLinearDecay(TrainerEpochCallbackTrain):
+    """Sets the epsilon value for DQN-based policies at the beginning of the training
+    stage in each epoch, using a linear decay in the first `decay_steps` steps.
+    """
+
+    def __init__(self, eps_train: float, eps_train_final: float, decay_steps: int = 1000000):
+        self.eps_train = eps_train
+        self.eps_train_final = eps_train_final
+        self.decay_steps = decay_steps
+
+    def callback(self, epoch: int, env_step: int, context: TrainingContext) -> None:
+        policy = cast(DQNPolicy, context.policy)
+        logger = context.logger
+        if env_step <= self.decay_steps:
+            eps = self.eps_train - env_step / self.decay_steps * (
+                self.eps_train - self.eps_train_final
+            )
+        else:
+            eps = self.eps_train_final
+        policy.set_eps(eps)
+        logger.write("train/env_step", env_step, {"train/eps": eps})
+
+
+class TrainerEpochCallbackTestDQNSetEps(TrainerEpochCallbackTest):
+    """Sets the epsilon value for DQN-based policies at the beginning of the test
+    stage in each epoch.
+    """
+
+    def __init__(self, eps_test: float):
+        self.eps_test = eps_test
+
+    def callback(self, epoch: int, env_step: int | None, context: TrainingContext) -> None:
+        policy = cast(DQNPolicy, context.policy)
+        policy.set_eps(self.eps_test)
diff --git a/tianshou/utils/logger/base.py b/tianshou/utils/logger/base.py
index 74e0fa4..e6bc09a 100644
--- a/tianshou/utils/logger/base.py
+++ b/tianshou/utils/logger/base.py
@@ -7,7 +7,7 @@ from typing import Any
 
 import numpy as np
 
-VALID_LOG_VALS_TYPE = int | Number | np.number | np.ndarray
+VALID_LOG_VALS_TYPE = int | Number | np.number | np.ndarray | float
 VALID_LOG_VALS = typing.get_args(
     VALID_LOG_VALS_TYPE,
 )  # I know it's stupid, but we can't use Union type in isinstance