Initial commit

Divers/renforcement3/predict.py

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+import gym
+import tensorflow as tf
+import numpy as np
+
+env=gym.make("CartPole-v0")
+env._max_episode_steps=500
+
+model=tf.keras.models.load_model("my_model")
+
+while True:
+  observations=env.reset()
+  score=0
+  while True:
+    env.render()
+    valeurs_q=model(np.expand_dims(observations, axis=0))
+    action=int(tf.argmax(valeurs_q[0], axis=-1))
+    observations, reward, done, info=env.step(action)
+    if done:
+      print("SCORE", score)
+      break
+    score+=1