Support both 32-bit and 64-bit types in UnityEnvironment (#1471)

We check for the single brain case in UnityEnvironment by checking
for applicable non-dict types in the step arguments. However for ints
and floats we just use `np.int_` and `np.float_` for the check, which
are the defaults for your system.

This means if you are using an application (like baselines in #1448)
which uses the wrong int/float size an error will be thrown.  This
change explicitly allows both 32 and 64-bit numbers.

Author: Jonathan Harper

ml-agents/mlagents/envs/environment.py

@@ -20,6 +20,10 @@
 
 
 class UnityEnvironment(object):
+    SCALAR_ACTION_TYPES = (int, np.int32, np.int64, float, np.float32, np.float64)
+    SINGLE_BRAIN_ACTION_TYPES = SCALAR_ACTION_TYPES + (list, np.ndarray)
+    SINGLE_BRAIN_TEXT_TYPES = (str, list, np.ndarray)
+
     def __init__(self, file_name=None, worker_id=0,
                  base_port=5005, seed=0,
                  docker_training=False, no_graphics=False):
@@ -270,7 +274,7 @@ def step(self, vector_action=None, memory=None, text_action=None, value=None) ->
 
         # Check that environment is loaded, and episode is currently running.
         if self._loaded and not self._global_done and self._global_done is not None:
-            if isinstance(vector_action, (int, np.int_, float, np.float_, list, np.ndarray)):
+            if isinstance(vector_action, self.SINGLE_BRAIN_ACTION_TYPES):
                 if self._num_external_brains == 1:
                     vector_action = {self._external_brain_names[0]: vector_action}
                 elif self._num_external_brains > 1:
@@ -282,7 +286,7 @@ def step(self, vector_action=None, memory=None, text_action=None, value=None) ->
                         "There are no external brains in the environment, "
                         "step cannot take a vector_action input")
 
-            if isinstance(memory, (int, np.int_, float, np.float_, list, np.ndarray)):
+            if isinstance(memory, self.SINGLE_BRAIN_ACTION_TYPES):
                 if self._num_external_brains == 1:
                     memory = {self._external_brain_names[0]: memory}
                 elif self._num_external_brains > 1:
@@ -294,7 +298,7 @@ def step(self, vector_action=None, memory=None, text_action=None, value=None) ->
                         "There are no external brains in the environment, "
                         "step cannot take a memory input")
 
-            if isinstance(text_action, (str, list, np.ndarray)):
+            if isinstance(text_action, self.SINGLE_BRAIN_TEXT_TYPES):
                 if self._num_external_brains == 1:
                     text_action = {self._external_brain_names[0]: text_action}
                 elif self._num_external_brains > 1:
@@ -306,7 +310,7 @@ def step(self, vector_action=None, memory=None, text_action=None, value=None) ->
                         "There are no external brains in the environment, "
                         "step cannot take a value input")
 
-            if isinstance(value, (int, np.int_, float, np.float_, list, np.ndarray)):
+            if isinstance(value, self.SINGLE_BRAIN_ACTION_TYPES):
                 if self._num_external_brains == 1:
                     value = {self._external_brain_names[0]: value}
                 elif self._num_external_brains > 1:
@@ -419,14 +423,14 @@ def _close(self):
         if self.proc1 is not None:
             self.proc1.kill()
 
-    @staticmethod
-    def _flatten(arr):
+    @classmethod
+    def _flatten(cls, arr):
         """
         Converts arrays to list.
         :param arr: numpy vector.
         :return: flattened list.
         """
-        if isinstance(arr, (int, np.int_, float, np.float_)):
+        if isinstance(arr, cls.SCALAR_ACTION_TYPES):
             arr = [float(arr)]
         if isinstance(arr, np.ndarray):
             arr = arr.tolist()