adelorenzo/stable
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Merge branch 'freqtrade:develop' into develop

Browse Source
This commit is contained in:
Richard Jozsa
2023-03-28 01:23:24 +02:00
committed by GitHub
parent 66c326b789 8ae44c204e
commit 7cbc0ce80a
96 changed files with 1883 additions and 731 deletions
Download Patch File Download Diff File Expand all files Collapse all files

2
freqtrade/freqai/RL/Base3ActionRLEnv.py
View File

@@ -47,7 +47,7 @@ class Base3ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action)
self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action])
self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None
if self.is_tradesignal(action):

2
freqtrade/freqai/RL/Base4ActionRLEnv.py
View File

@@ -48,7 +48,7 @@ class Base4ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action)
self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action])
self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None
if self.is_tradesignal(action):

2
freqtrade/freqai/RL/Base5ActionRLEnv.py
View File

@@ -49,7 +49,7 @@ class Base5ActionRLEnv(BaseEnvironment):
self._update_unrealized_total_profit()
step_reward = self.calculate_reward(action)
self.total_reward += step_reward
self.tensorboard_log(self.actions._member_names_[action])
self.tensorboard_log(self.actions._member_names_[action], category="actions")
trade_type = None
if self.is_tradesignal(action):

22
freqtrade/freqai/RL/BaseEnvironment.py
View File

@@ -137,7 +137,8 @@ class BaseEnvironment(gym.Env):
self.np_random, seed = seeding.np_random(seed)
return [seed]
def tensorboard_log(self, metric: str, value: Union[int, float] = 1, inc: bool = True):
def tensorboard_log(self, metric: str, value: Optional[Union[int, float]] = None,
inc: Optional[bool] = None, category: str = "custom"):
"""
Function builds the tensorboard_metrics dictionary
to be parsed by the TensorboardCallback. This
@@ -149,17 +150,24 @@ class BaseEnvironment(gym.Env):
def calculate_reward(self, action: int) -> float:
if not self._is_valid(action):
self.tensorboard_log("is_valid")
self.tensorboard_log("invalid")
return -2
:param metric: metric to be tracked and incremented
:param value: value to increment `metric` by
:param inc: sets whether the `value` is incremented or not
:param value: `metric` value
:param inc: (deprecated) sets whether the `value` is incremented or not
:param category: `metric` category
"""
if not inc or metric not in self.tensorboard_metrics:
self.tensorboard_metrics[metric] = value
increment = True if value is None else False
value = 1 if increment else value
if category not in self.tensorboard_metrics:
self.tensorboard_metrics[category] = {}
if not increment or metric not in self.tensorboard_metrics[category]:
self.tensorboard_metrics[category][metric] = value
else:
self.tensorboard_metrics[metric] += value
self.tensorboard_metrics[category][metric] += value
def reset_tensorboard_log(self):
self.tensorboard_metrics = {}

16
freqtrade/freqai/RL/TensorboardCallback.py
View File

@@ -13,7 +13,7 @@ class TensorboardCallback(BaseCallback):
episodic summary reports.
"""
def __init__(self, verbose=1, actions: Type[Enum] = BaseActions):
super(TensorboardCallback, self).__init__(verbose)
super().__init__(verbose)
self.model: Any = None
self.logger = None # type: Any
self.training_env: BaseEnvironment = None # type: ignore
@@ -46,14 +46,12 @@ class TensorboardCallback(BaseCallback):
local_info = self.locals["infos"][0]
tensorboard_metrics = self.training_env.get_attr("tensorboard_metrics")[0]
for info in local_info:
if info not in ["episode", "terminal_observation"]:
self.logger.record(f"_info/{info}", local_info[info])
for metric in local_info:
if metric not in ["episode", "terminal_observation"]:
self.logger.record(f"info/{metric}", local_info[metric])
for info in tensorboard_metrics:
if info in [action.name for action in self.actions]:
self.logger.record(f"_actions/{info}", tensorboard_metrics[info])
else:
self.logger.record(f"_custom/{info}", tensorboard_metrics[info])
for category in tensorboard_metrics:
for metric in tensorboard_metrics[category]:
self.logger.record(f"{category}/{metric}", tensorboard_metrics[category][metric])
return True