Train file runs without errors

acme/acme/requirements.txt

@@ -1,29 +1,29 @@
-jax==0.3.6
-gym
-dm-haiku
-atari-py
-numpy==1.22.4
-rlax
-tensorflow-estimator==2.8.0
+absl-py
+jaxlib==0.3.5
+bsuite
 tensorflow_probability==0.15.0
-gym[atari]
 dm-env
-trfl
+jax==0.3.6
 optax
-flax
-typing-extensions
-bsuite
-dm-reverb==0.7.2
 rlds
-chex
-keras==2.8.0
-dm-sonnet
-tensorflow==2.8.0
-pillow
 dm-control==0.0.364896371
+atari-py
+gym
+pillow
+gym[atari]
+dm-haiku
+dm-sonnet
+dm-launchpad==0.5.2
 pygame==2.1.0
-jaxlib==0.3.5
+typing-extensions
 tensorflow-datasets==4.5.2
-dm-launchpad==0.5.2
-absl-py
+chex
+rlax
+tensorflow==2.8.0
+tensorflow-estimator==2.8.0
 dm-tree
+flax
+keras==2.8.0
+numpy==1.22.4
+trfl
+dm-reverb==0.7.2

arch_gym/envs/custom_gym.py

@@ -6,9 +6,9 @@ class ExampleEnv(Env):
     def __init__(self):
         super(ExampleEnv, self).__init__()
 
-        self.energy = 0.0;
-        self.area = 0.0;
-        self.latency = 0.0;
+        self.energy = 0.0
+        self.area = 0.0
+        self.latency = 0.0
 
         self.ideal = {'num_cores':4, 'freq':2.0, 'mem_type':'SRAM', 'mem_size':32}
 
@@ -42,9 +42,9 @@ def step(self, action):
         return observation, reward, done, {}
 
     def reset(self):
-        self.energy = 0.0;
-        self.area = 0.0;
-        self.latency = 0.0;
+        self.energy = 0.0
+        self.area = 0.0
+        self.latency = 0.0
         return np.array([self.energy, self.area, self.latency], dtype=np.float32)
 
     def render(self, mode='human'):

arch_gym/envs/customenv_wrapper.py

@@ -15,7 +15,7 @@
 """Wraps an OpenAI Gym environment to be used as a dm_env environment."""
 
 from typing import Any, Dict, List, Optional
-
+import acme
 from acme import specs
 from acme import types
 from acme import wrappers

sims/CustomEnv/random_walker_logs/num_steps_100_num_episodes_2/fitness.csv

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