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89 lines
3.0 KiB
Python
89 lines
3.0 KiB
Python
"""Test suite for JaxToNumpyV0."""
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import jax.numpy as jnp
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import numpy as np
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import pytest
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from gymnasium.experimental.wrappers import JaxToNumpyV0
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from gymnasium.experimental.wrappers.jax_to_numpy import jax_to_numpy, numpy_to_jax
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from gymnasium.utils.env_checker import data_equivalence
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from tests.testing_env import GenericTestEnv
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@pytest.mark.parametrize(
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"value, expected_value",
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[
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(1.0, np.array(1.0)),
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(2, np.array(2)),
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((3.0, 4), (np.array(3.0), np.array(4))),
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([3.0, 4], [np.array(3.0), np.array(4)]),
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(
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{
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"a": 6.0,
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"b": 7,
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},
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{"a": np.array(6.0), "b": np.array(7)},
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),
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(np.array(1.0), np.array(1.0)),
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(np.array([1, 2]), np.array([1, 2])),
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(np.array([[1.0], [2.0]]), np.array([[1.0], [2.0]])),
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(
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{"a": (1, np.array(2.0), np.array([3, 4])), "b": {"c": 5}},
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{
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"a": (np.array(1), np.array(2.0), np.array([3, 4])),
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"b": {"c": np.array(5)},
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},
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),
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],
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)
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def test_roundtripping(value, expected_value):
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"""We test numpy -> jax -> numpy as this is direction in the NumpyToJax wrapper."""
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assert data_equivalence(jax_to_numpy(numpy_to_jax(value)), expected_value)
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def jax_reset_func(self, seed=None, options=None):
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"""A jax-based reset function."""
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return jnp.array([1.0, 2.0, 3.0]), {"data": jnp.array([1, 2, 3])}
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def jax_step_func(self, action):
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"""A jax-based step function."""
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assert isinstance(action, jnp.DeviceArray), type(action)
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return (
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jnp.array([1, 2, 3]),
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jnp.array(5.0),
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jnp.array(True),
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jnp.array(False),
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{"data": jnp.array([1.0, 2.0])},
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)
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def test_jax_to_numpy_wrapper():
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"""Tests the ``JaxToNumpyV0`` wrapper."""
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jax_env = GenericTestEnv(reset_func=jax_reset_func, step_func=jax_step_func)
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# Check that the reset and step for jax environment are as expected
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obs, info = jax_env.reset()
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assert isinstance(obs, jnp.DeviceArray)
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assert isinstance(info, dict) and isinstance(info["data"], jnp.DeviceArray)
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obs, reward, terminated, truncated, info = jax_env.step(jnp.array([1, 2]))
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assert isinstance(obs, jnp.DeviceArray)
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assert isinstance(reward, jnp.DeviceArray)
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assert isinstance(terminated, jnp.DeviceArray) and isinstance(
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truncated, jnp.DeviceArray
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)
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assert isinstance(info, dict) and isinstance(info["data"], jnp.DeviceArray)
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# Check that the wrapped version is correct.
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numpy_env = JaxToNumpyV0(jax_env)
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obs, info = numpy_env.reset()
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assert isinstance(obs, np.ndarray)
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assert isinstance(info, dict) and isinstance(info["data"], np.ndarray)
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obs, reward, terminated, truncated, info = numpy_env.step(np.array([1, 2]))
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assert isinstance(obs, np.ndarray)
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assert isinstance(reward, float)
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assert isinstance(terminated, bool) and isinstance(truncated, bool)
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assert isinstance(info, dict) and isinstance(info["data"], np.ndarray)
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