mirror of
https://github.com/vale981/ray
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172 lines
6 KiB
Python
172 lines
6 KiB
Python
from gym.spaces import Box, Discrete, MultiDiscrete
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import numpy as np
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import tree # pip install dm_tree
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import unittest
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import ray
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from ray.rllib.utils.framework import try_import_tf, try_import_torch
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from ray.rllib.utils.numpy import flatten_inputs_to_1d_tensor as flatten_np
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from ray.rllib.utils.test_utils import check
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from ray.rllib.utils.tf_utils import flatten_inputs_to_1d_tensor as flatten_tf
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from ray.rllib.utils.torch_utils import flatten_inputs_to_1d_tensor as \
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flatten_torch
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tf1, tf, tfv = try_import_tf()
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torch, _ = try_import_torch()
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class TestUtils(unittest.TestCase):
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# Nested struct of data with B=3.
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struct = {
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"a": np.array([1, 3, 2]),
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"b": (
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np.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0], [7.0, 8.0, 9.0]]),
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np.array([[[8.0], [7.0], [6.0]], [[5.0], [4.0], [3.0]],
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[[2.0], [1.0], [0.0]]]),
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),
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"c": {
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"ca": np.array([[1, 2], [3, 5], [0, 1]]),
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"cb": np.array([1.0, 2.0, 3.0])
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}
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}
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# Nested struct of data with B=2 and T=1.
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struct_w_time_axis = {
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"a": np.array([[1], [3]]),
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"b": (
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np.array([[[1.0, 2.0, 3.0]], [[4.0, 5.0, 6.0]]]),
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np.array([[[[8.0], [7.0], [6.0]]], [[[5.0], [4.0], [3.0]]]]),
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),
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"c": {
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"ca": np.array([[[1, 2]], [[3, 5]]]),
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"cb": np.array([[1.0], [2.0]])
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}
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}
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# Corresponding space struct.
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spaces = dict({
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"a": Discrete(4),
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"b": (Box(-1.0, 10.0, (3, )), Box(-1.0, 1.0, (3, 1))),
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"c": dict({
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"ca": MultiDiscrete([4, 6]),
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"cb": Box(-1.0, 1.0, ()),
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})
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})
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@classmethod
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def setUpClass(cls) -> None:
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ray.init()
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@classmethod
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def tearDownClass(cls) -> None:
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ray.shutdown()
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def test_flatten_inputs_to_1d_tensor(self):
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# B=3; no time axis.
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check(
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flatten_np(self.struct, spaces_struct=self.spaces),
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np.array([
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[
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0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, 8.0, 7.0, 6.0, 0.0, 1.0,
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0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0
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],
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[
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0.0, 0.0, 0.0, 1.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0
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],
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[
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0.0, 0.0, 1.0, 0.0, 7.0, 8.0, 9.0, 2.0, 1.0, 0.0, 1.0, 0.0,
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0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 3.0
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],
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]))
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struct_tf = tree.map_structure(lambda s: tf.convert_to_tensor(s),
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self.struct)
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check(
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flatten_tf(struct_tf, spaces_struct=self.spaces),
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np.array([
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[
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0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, 8.0, 7.0, 6.0, 0.0, 1.0,
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0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0
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],
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[
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0.0, 0.0, 0.0, 1.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0
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],
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[
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0.0, 0.0, 1.0, 0.0, 7.0, 8.0, 9.0, 2.0, 1.0, 0.0, 1.0, 0.0,
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0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 3.0
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],
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]))
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struct_torch = tree.map_structure(lambda s: torch.from_numpy(s),
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self.struct)
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check(
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flatten_torch(struct_torch, spaces_struct=self.spaces),
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np.array([
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[
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0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, 8.0, 7.0, 6.0, 0.0, 1.0,
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0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0
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],
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[
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0.0, 0.0, 0.0, 1.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0
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],
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[
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0.0, 0.0, 1.0, 0.0, 7.0, 8.0, 9.0, 2.0, 1.0, 0.0, 1.0, 0.0,
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0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 3.0
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],
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]))
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def test_flatten_inputs_to_1d_tensor_w_time_axis(self):
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# B=2; T=1
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check(
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flatten_np(
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self.struct_w_time_axis,
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spaces_struct=self.spaces,
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time_axis=True),
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np.array([
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[[
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0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, 8.0, 7.0, 6.0, 0.0, 1.0,
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0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0
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]],
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[[
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0.0, 0.0, 0.0, 1.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0
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]],
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]))
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struct_tf = tree.map_structure(lambda s: tf.convert_to_tensor(s),
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self.struct_w_time_axis)
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check(
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flatten_tf(struct_tf, spaces_struct=self.spaces, time_axis=True),
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np.array([
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[[
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0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, 8.0, 7.0, 6.0, 0.0, 1.0,
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0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0
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]],
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[[
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0.0, 0.0, 0.0, 1.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0
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]],
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]))
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struct_torch = tree.map_structure(lambda s: torch.from_numpy(s),
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self.struct_w_time_axis)
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check(
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flatten_torch(
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struct_torch, spaces_struct=self.spaces, time_axis=True),
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np.array([
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[[
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0.0, 1.0, 0.0, 0.0, 1.0, 2.0, 3.0, 8.0, 7.0, 6.0, 0.0, 1.0,
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0.0, 0.0, 0.0, 0.0, 1.0, 0.0, 0.0, 0.0, 1.0
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]],
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[[
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0.0, 0.0, 0.0, 1.0, 4.0, 5.0, 6.0, 5.0, 4.0, 3.0, 0.0, 0.0,
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0.0, 1.0, 0.0, 0.0, 0.0, 0.0, 0.0, 1.0, 2.0
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]],
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]))
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if __name__ == "__main__":
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import pytest
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import sys
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sys.exit(pytest.main(["-v", __file__]))
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