Plus

master.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/es.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -393,7 +393,7 @@ def delete_env(self, env_name):
         logger.debug('Optimizer {} delete env {}...'.format(self.optim_id, env_name))
 
         niches = self.fiber_shared["niches"]
-        niches[optim_id].delete_env(env_name)
+        niches[self.optim_id].delete_env(env_name)
 
     def start_chunk_fiber(self, runner, batches_per_chunk, batch_size, *args):
         logger.debug('Optimizer {} spawning {} batches of size {}'.format(

poet_distributed/logger.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/niches/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/niches/box2d/__init__.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/niches/box2d/bipedal_walker_custom.py

@@ -1,6 +1,6 @@
 # The following code is modified from openai/gym (https://github.com/openai/gym) under the MIT License.
 
-# Modifications Copyright (c) 2019 Uber Technologies, Inc.
+# Modifications Copyright (c) 2020 Uber Technologies, Inc.
 
 
 import sys
@@ -169,18 +169,19 @@ def set_env_config(self, env_config):
     def _set_terrain_number(self):
         self.hardcore = False
         self.GRASS = 0
-        self.STUMP, self.STAIRS, self.PIT = -1, -1, -1
+#        self.STUMP, self.STAIRS, self.PIT = -1, -1, -1
+        self.PIT = -1,
         self._STATES_ = 1
 
-        if self.config.stump_width and self.config.stump_height and self.config.stump_float:
-            # STUMP exist
-            self.STUMP = self._STATES_
-            self._STATES_ += 1
+        # if self.config.stump_width and self.config.stump_height and self.config.stump_float:
+        #     # STUMP exist
+        #     self.STUMP = self._STATES_
+        #     self._STATES_ += 1
 
-        if self.config.stair_height and self.config.stair_width and self.config.stair_steps:
-            # STAIRS exist
-            self.STAIRS = self._STATES_
-            self._STATES_ += 1
+        # if self.config.stair_height and self.config.stair_width and self.config.stair_steps:
+        #     # STAIRS exist
+        #     self.STAIRS = self._STATES_
+        #     self._STATES_ += 1
 
         if self.config.pit_gap:
             # PIT exist
@@ -280,61 +281,61 @@ def _generate_terrain(self, hardcore):
                     self.terrain_x[-1] = self.terrain_x[-1] - pit_diff * TERRAIN_STEP
                     pit_diff = 0
 
-            elif state == self.STUMP and oneshot:
-                # input parameter stump_width, stump_height, stump_float
-                #stump_width = self.np_random.uniform(*self.config.stump_width)
-                stump_width = self.np_random.randint(*self.config.stump_width)
-                stump_height = self.np_random.uniform(
-                    *self.config.stump_height)
-                stump_float = self.np_random.randint(*self.config.stump_float)
-                #counter = np.ceil(stump_width)
-                counter = stump_width
-                countery = stump_height
-                poly = [
-                    (x,                      y + stump_float * TERRAIN_STEP),
-                    (x + stump_width * TERRAIN_STEP, y + stump_float * TERRAIN_STEP),
-                    (x + stump_width * TERRAIN_STEP, y + countery *
-                     TERRAIN_STEP + stump_float * TERRAIN_STEP),
-                    (x,                      y + countery *
-                     TERRAIN_STEP + stump_float * TERRAIN_STEP),
-                ]
-                self.fd_polygon.shape.vertices = poly
-                t = self.world.CreateStaticBody(
-                    fixtures=self.fd_polygon)
-                t.color1, t.color2 = (1, 1, 1), (0.6, 0.6, 0.6)
-                self.terrain.append(t)
-
-            elif state == self.STAIRS and oneshot:
-                # input parameters: stair_height, stair_width, stair_steps
-                stair_height = self.np_random.uniform(
-                    *self.config.stair_height)
-                stair_slope = 1 if self.np_random.rand() > 0.5 else -1
-                stair_width = self.np_random.randint(*self.config.stair_width)
-                stair_steps = self.np_random.randint(*self.config.stair_steps)
-                original_y = y
-                for s in range(stair_steps):
-                    poly = [
-                        (x + (s * stair_width) * TERRAIN_STEP, y +
-                         (s * stair_height * stair_slope) * TERRAIN_STEP),
-                        (x + ((1 + s) * stair_width) * TERRAIN_STEP, y +
-                         (s * stair_height * stair_slope) * TERRAIN_STEP),
-                        (x + ((1 + s) * stair_width) * TERRAIN_STEP, y +
-                         (-stair_height + s * stair_height * stair_slope) * TERRAIN_STEP),
-                        (x + (s * stair_width) * TERRAIN_STEP, y + (-stair_height +
-                                                                    s * stair_height * stair_slope) * TERRAIN_STEP),
-                    ]
-                    self.fd_polygon.shape.vertices = poly
-                    t = self.world.CreateStaticBody(
-                        fixtures=self.fd_polygon)
-                    t.color1, t.color2 = (1, 1, 1), (0.6, 0.6, 0.6)
-                    self.terrain.append(t)
-                counter = stair_steps * stair_width + 1
-
-            elif state == self.STAIRS and not oneshot:
-                s = stair_steps * stair_width - counter
-                n = s // stair_width
-                y = original_y + (n * stair_height * stair_slope) * TERRAIN_STEP - \
-                    (stair_height if stair_slope == -1 else 0) * TERRAIN_STEP
+            # elif state == self.STUMP and oneshot:
+            #     # input parameter stump_width, stump_height, stump_float
+            #     #stump_width = self.np_random.uniform(*self.config.stump_width)
+            #     stump_width = self.np_random.randint(*self.config.stump_width)
+            #     stump_height = self.np_random.uniform(
+            #         *self.config.stump_height)
+            #     stump_float = self.np_random.randint(*self.config.stump_float)
+            #     #counter = np.ceil(stump_width)
+            #     counter = stump_width
+            #     countery = stump_height
+            #     poly = [
+            #         (x,                      y + stump_float * TERRAIN_STEP),
+            #         (x + stump_width * TERRAIN_STEP, y + stump_float * TERRAIN_STEP),
+            #         (x + stump_width * TERRAIN_STEP, y + countery *
+            #          TERRAIN_STEP + stump_float * TERRAIN_STEP),
+            #         (x,                      y + countery *
+            #          TERRAIN_STEP + stump_float * TERRAIN_STEP),
+            #     ]
+            #     self.fd_polygon.shape.vertices = poly
+            #     t = self.world.CreateStaticBody(
+            #         fixtures=self.fd_polygon)
+            #     t.color1, t.color2 = (1, 1, 1), (0.6, 0.6, 0.6)
+            #     self.terrain.append(t)
+
+            # elif state == self.STAIRS and oneshot:
+            #     # input parameters: stair_height, stair_width, stair_steps
+            #     stair_height = self.np_random.uniform(
+            #         *self.config.stair_height)
+            #     stair_slope = 1 if self.np_random.rand() > 0.5 else -1
+            #     stair_width = self.np_random.randint(*self.config.stair_width)
+            #     stair_steps = self.np_random.randint(*self.config.stair_steps)
+            #     original_y = y
+            #     for s in range(stair_steps):
+            #         poly = [
+            #             (x + (s * stair_width) * TERRAIN_STEP, y +
+            #              (s * stair_height * stair_slope) * TERRAIN_STEP),
+            #             (x + ((1 + s) * stair_width) * TERRAIN_STEP, y +
+            #              (s * stair_height * stair_slope) * TERRAIN_STEP),
+            #             (x + ((1 + s) * stair_width) * TERRAIN_STEP, y +
+            #              (-stair_height + s * stair_height * stair_slope) * TERRAIN_STEP),
+            #             (x + (s * stair_width) * TERRAIN_STEP, y + (-stair_height +
+            #                                                         s * stair_height * stair_slope) * TERRAIN_STEP),
+            #         ]
+            #         self.fd_polygon.shape.vertices = poly
+            #         t = self.world.CreateStaticBody(
+            #             fixtures=self.fd_polygon)
+            #         t.color1, t.color2 = (1, 1, 1), (0.6, 0.6, 0.6)
+            #         self.terrain.append(t)
+            #     counter = stair_steps * stair_width + 1
+
+            # elif state == self.STAIRS and not oneshot:
+            #     s = stair_steps * stair_width - counter
+            #     n = s // stair_width
+            #     y = original_y + (n * stair_height * stair_slope) * TERRAIN_STEP - \
+            #         (stair_height if stair_slope == -1 else 0) * TERRAIN_STEP
 
             oneshot = False
             self.terrain_y.append(y)

poet_distributed/niches/box2d/box2d.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -22,12 +22,13 @@
         name='default_env',
         ground_roughness=0,
         pit_gap=[],
-        stump_width=[],
-        stump_height=[],
-        stump_float=[],
-        stair_height=[],
-        stair_width=[],
-        stair_steps=[])
+        stump_width = [],
+        stump_height = [],
+        stump_float = [],
+        stair_height = [],
+        stair_width = [],
+        stair_steps = []
+        )
 
 class Box2DNiche(Niche):
     def __init__(self, env_configs, seed, init='random', stochastic=False):

poet_distributed/niches/box2d/env.py

@@ -1,6 +1,6 @@
 # The following code is modified from hardmaru/estool (https://github.com/hardmaru/estool/) under the MIT License.
 
-# Modifications Copyright (c) 2019 Uber Technologies, Inc.
+# Modifications Copyright (c) 2020 Uber Technologies, Inc.
 
 
 from collections import namedtuple
@@ -39,7 +39,7 @@ def make_env(env_name, seed, render_mode=False, env_config=None):
                         input_size=24,
                         output_size=4,
                         time_factor=0,
-                        layers=[40, 40],
+                        layers=[30, 30],
                         activation='tanh',
                         noise_bias=0.0,
                         output_noise=[False, False, False],

poet_distributed/niches/box2d/model.py

@@ -1,6 +1,6 @@
 # The following code is modified from hardmaru/estool (https://github.com/hardmaru/estool/) under the MIT License.
 
-# Modifications Copyright (c) 2019 Uber Technologies, Inc.
+# Modifications Copyright (c) 2020 Uber Technologies, Inc.
 
 
 import numpy as np

poet_distributed/niches/core.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/noise.py

@@ -2,7 +2,7 @@
 # (https://github.com/openai/evolution-strategies-starter)
 # under the MIT License.
 
-# Modifications Copyright (c) 2019 Uber Technologies, Inc.
+# Modifications Copyright (c) 2020 Uber Technologies, Inc.
 
 
 import numpy as np

poet_distributed/noise_module.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.

poet_distributed/novelty.py

@@ -1,4 +1,4 @@
-# Copyright (c) 2019 Uber Technologies, Inc.
+# Copyright (c) 2020 Uber Technologies, Inc.
 #
 # Licensed under the Apache License, Version 2.0 (the "License");
 # you may not use this file except in compliance with the License.
@@ -16,14 +16,15 @@
 import numpy as np
 
 def env2array(env):
-    arr = [0., 0., 0., 0., 0.]
+    # arr = [0., 0., 0., 0., 0.]
+    arr = [0., 0.,0.]
     arr[0] = env.ground_roughness
     if len(env.pit_gap) > 0:
         arr[1] = env.pit_gap[0]
         arr[2] = env.pit_gap[1]
-    if len(env.stump_height) > 0:
-        arr[3] = env.stump_height[0]
-        arr[4] = env.stump_height[1]
+    # if len(env.stump_height) > 0:
+    #     arr[3] = env.stump_height[0]
+    #     arr[4] = env.stump_height[1]
 
     return arr
 
@@ -36,7 +37,8 @@ def euclidean_distance(nx, ny, normalize=False):
     y = y.astype(float)
 
     if normalize:
-        norm = np.array([8., 8., 8., 3., 3.])
+        # norm = np.array([8., 8., 8., 3., 3.])
+        norm = np.array([8., 8., 8])
         x /= norm
         y /= norm
 

poet_distributed/optimizers.py

@@ -2,7 +2,7 @@
 # (https://github.com/openai/evolution-strategies-starter)
 # under the MIT License.
 
-# Modifications Copyright (c) 2019 Uber Technologies, Inc.
+# Modifications Copyright (c) 2020 Uber Technologies, Inc.
 
 
 import numpy as np