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https://github.com/Farama-Foundation/Gymnasium.git
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redo black
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@@ -73,9 +73,7 @@ class AlgorithmicEnv(Env):
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# 1. Move read head left or right (or up/down)
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# 2. Write or not
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# 3. Which character to write. (Ignored if should_write=0)
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self.action_space = Tuple(
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[Discrete(len(self.MOVEMENTS)), Discrete(2), Discrete(self.base)]
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)
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self.action_space = Tuple([Discrete(len(self.MOVEMENTS)), Discrete(2), Discrete(self.base)])
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# Can see just what is on the input tape (one of n characters, or
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# nothing)
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self.observation_space = Discrete(self.base + 1)
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@@ -147,10 +145,7 @@ class AlgorithmicEnv(Env):
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move = self.MOVEMENTS[inp_act]
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outfile.write("Action : Tuple(move over input: %s,\n" % move)
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out_act = out_act == 1
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outfile.write(
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" write to the output tape: %s,\n"
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% out_act
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)
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outfile.write(" write to the output tape: %s,\n" % out_act)
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outfile.write(" prediction: %s)\n" % pred_str)
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else:
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outfile.write("\n" * 5)
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@@ -276,9 +271,7 @@ class TapeAlgorithmicEnv(AlgorithmicEnv):
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x_str = "Observation Tape : "
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for i in range(-2, self.input_width + 2):
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if i == x:
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x_str += colorize(
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self._get_str_obs(np.array([i])), "green", highlight=True
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)
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x_str += colorize(self._get_str_obs(np.array([i])), "green", highlight=True)
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else:
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x_str += self._get_str_obs(np.array([i]))
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x_str += "\n"
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@@ -311,10 +304,7 @@ class GridAlgorithmicEnv(AlgorithmicEnv):
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self.read_head_position = x, y
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def generate_input_data(self, size):
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return [
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[self.np_random.randint(self.base) for _ in range(self.rows)]
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for __ in range(size)
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]
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return [[self.np_random.randint(self.base) for _ in range(self.rows)] for __ in range(size)]
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def _get_obs(self, pos=None):
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if pos is None:
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@@ -336,9 +326,7 @@ class GridAlgorithmicEnv(AlgorithmicEnv):
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x_str += " " * len(label)
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for i in range(-2, self.input_width + 2):
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if i == x[0] and j == x[1]:
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x_str += colorize(
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self._get_str_obs((i, j)), "green", highlight=True
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)
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x_str += colorize(self._get_str_obs((i, j)), "green", highlight=True)
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else:
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x_str += self._get_str_obs((i, j))
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x_str += "\n"
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