wassname/pyrobolearn
1
0
Fork 0
mirror of https://github.com/wassname/pyrobolearn.git synced 2026-09-10 12:21:16 +08:00
Code Issues Packages Projects Releases Wiki Activity

correct few errors in policies

Browse Source
This commit is contained in:
Brian Delhaisse
2019-04-17 18:05:59 +02:00
parent 622b834857
commit 40d95ecde8
2 changed files with 12 additions and 4 deletions
Download Patch File Download Diff File Expand all files Collapse all files
pyrobolearn/policies/basic_policy.py
+3
View File
@@ -42,6 +42,9 @@ class RandomPolicy(Policy):
np.random.seed(seed)
self._seed = seed
def reset(self):
pass
def predict(self, state=None, to_numpy=True):
spaces = self.actions.space
return [space.sample() for space in spaces]
pyrobolearn/policies/policy.py
+9 -4
View File
@@ -504,6 +504,10 @@ class Policy(object):
action_data[idx] = self.__convert_to_numpy(discrete_data, to_numpy=to_numpy)
else:
action_data[idx] = self.__convert_to_numpy(data, to_numpy=to_numpy)
elif isinstance(data, (float, int)):
action.data = int(data)
action_data[idx] = int(data)
# elif isinstance(data, (float, int)):
# discrete_data = np.argmax(data)
# action.data = discrete_data
@@ -511,7 +515,7 @@ class Policy(object):
# action_data[idx] = discrete_data
else:
raise TypeError(
"Expecting the `data` action to be a numpy array or torch.Tensor, instead got: "
"Expecting the `data` action to be an int, numpy array, torch.Tensor, instead got: "
"{}".format(type(data)))
else: # continuous action
if isinstance(data, np.ndarray):
@@ -519,8 +523,8 @@ class Policy(object):
elif isinstance(data, torch.Tensor):
action.torch_data = data
action_data[idx] = self.__convert_to_numpy(data, to_numpy=to_numpy)
# elif isinstance(data, (float, int)):
# pass
elif isinstance(data, (float, int)):
action.data = data
else:
raise TypeError(
"Expecting `data` to be a numpy array or torch.Tensor, instead got: "
@@ -682,7 +686,8 @@ class Policy(object):
Returns:
Action: action
"""
return self.act(*args, **kwargs)
return self.act(state=state, deterministic=deterministic, to_numpy=to_numpy, return_logits=return_logits,
apply_action=apply_action)
def __repr__(self):
"""Return representation of python object."""