Fix precision issue in the action_mapping function (#368)

* Update common.py

* fix precision issue

fix #367

parl/core/fluid/plutils/common.py

@@ -37,7 +37,7 @@ def fetch_framework_var(attr_name):
     core_var = scope.find_var(attr_name)
     if core_var == None:
         raise KeyError(
-            "Unable to find the variable:{}. Synchronize paramsters before initialization or attr_name does not exist."
+            "Unable to find the variable:{}. Synchronize parameters before initialization or attr_name does not exist."
             .format(attr_name))
     shape = core_var.get_tensor().shape()
     framework_var = fluid.layers.create_parameter(

parl/utils/rl_utils.py

@@ -15,7 +15,7 @@
 import numpy as np
 import scipy.signal
 
-__all__ = ['calc_discount_sum_rewards', 'calc_gae']
+__all__ = ['calc_discount_sum_rewards', 'calc_gae', 'action_mapping']
 
 
 def calc_discount_sum_rewards(rewards, gamma):
@@ -49,3 +49,24 @@ def calc_gae(rewards, values, next_value, gamma, lam):
     tds = rewards + gamma * np.append(values[1:], next_value) - values
     advantages = calc_discount_sum_rewards(tds, gamma * lam)
     return advantages
+
+
+def action_mapping(model_output_act, low_bound, high_bound):
+    """ mapping action space [-1, 1] of model output 
+        to new action space [low_bound, high_bound].
+
+    Args:
+        model_output_act: np.array, which value is in [-1, 1]
+        low_bound: float, low bound of env action space
+        high_bound: float, high bound of env action space
+
+    Returns:
+        action: np.array, which value is in [low_bound, high_bound]
+    """
+    assert np.all(((model_output_act<=1.0 + 1e-3), (model_output_act>=-1.0 - 1e-3))), \
+        'the action should be in range [-1.0, 1.0]'
+    assert high_bound > low_bound
+    action = low_bound + (model_output_act - (-1.0)) * (
+        (high_bound - low_bound) / 2.0)
+    action = np.clip(action, low_bound, high_bound)
+    return action

parl/utils/utils.py

@@ -18,9 +18,9 @@ import subprocess
 import numpy as np
 
 __all__ = [
-    'has_func', 'action_mapping', 'to_str', 'to_byte', 'is_PY2', 'is_PY3',
-    'MAX_INT32', '_HAS_FLUID', '_HAS_TORCH', '_IS_WINDOWS', '_IS_MAC',
-    'kill_process', 'get_fluid_version'
+    'has_func', 'to_str', 'to_byte', 'is_PY2', 'is_PY3', 'MAX_INT32',
+    '_HAS_FLUID', '_HAS_TORCH', '_IS_WINDOWS', '_IS_MAC', 'kill_process',
+    'get_fluid_version'
 ]
 
 
@@ -37,27 +37,6 @@ def has_func(obj, fun):
     return callable(check_fun)
 
 
-def action_mapping(model_output_act, low_bound, high_bound):
-    """ mapping action space [-1, 1] of model output 
-        to new action space [low_bound, high_bound].
-
-    Args:
-        model_output_act: np.array, which value is in [-1, 1]
-        low_bound: float, low bound of env action space
-        high_bound: float, high bound of env action space
-
-    Returns:
-        action: np.array, which value is in [low_bound, high_bound]
-    """
-    assert np.all(((model_output_act<=1.0), (model_output_act>=-1.0))), \
-        'the action should be in range [-1.0, 1.0]'
-    assert high_bound > low_bound
-    action = low_bound + (model_output_act - (-1.0)) * (
-        (high_bound - low_bound) / 2.0)
-    action = np.clip(action, low_bound, high_bound)
-    return action
-
-
 def to_str(byte):
     """ convert byte to string in pytohn2/3
     """