Unity 机器学习代理工具包 (ML-Agents) 是一个开源项目,它使游戏和模拟能够作为训练智能代理的环境。
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import io
import os
from unittest import mock
import numpy as np
import pytest
import tempfile
from mlagents_envs.communicator_objects.demonstration_meta_pb2 import (
DemonstrationMetaProto,
)
from mlagents.trainers.brain import BrainParameters
from mlagents.trainers.demo_loader import (
load_demonstration,
demo_to_buffer,
get_demo_files,
write_delimited,
)
BRAIN_PARAMS = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=8,
camera_resolutions=[],
vector_action_space_size=[2],
vector_action_descriptions=[],
vector_action_space_type=1,
)
def test_load_demo():
path_prefix = os.path.dirname(os.path.abspath(__file__))
behavior_spec, pair_infos, total_expected = load_demonstration(
path_prefix + "/test.demo"
)
assert np.sum(behavior_spec.observation_shapes[0]) == 8
assert len(pair_infos) == total_expected
_, demo_buffer = demo_to_buffer(path_prefix + "/test.demo", 1, BRAIN_PARAMS)
assert len(demo_buffer["actions"]) == total_expected - 1
def test_load_demo_dir():
path_prefix = os.path.dirname(os.path.abspath(__file__))
behavior_spec, pair_infos, total_expected = load_demonstration(
path_prefix + "/test_demo_dir"
)
assert np.sum(behavior_spec.observation_shapes[0]) == 8
assert len(pair_infos) == total_expected
_, demo_buffer = demo_to_buffer(path_prefix + "/test_demo_dir", 1, BRAIN_PARAMS)
assert len(demo_buffer["actions"]) == total_expected - 1
def test_demo_mismatch():
path_prefix = os.path.dirname(os.path.abspath(__file__))
# observation mismatch
with pytest.raises(RuntimeError):
brain_params_obs = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=9,
camera_resolutions=[],
vector_action_space_size=[2],
vector_action_descriptions=[],
vector_action_space_type=1,
)
_, demo_buffer = demo_to_buffer(path_prefix + "/test.demo", 1, brain_params_obs)
# action mismatch
with pytest.raises(RuntimeError):
brain_params_act = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=8,
camera_resolutions=[],
vector_action_space_size=[3],
vector_action_descriptions=[],
vector_action_space_type=1,
)
_, demo_buffer = demo_to_buffer(path_prefix + "/test.demo", 1, brain_params_act)
# action type mismatch
with pytest.raises(RuntimeError):
brain_params_type = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=8,
camera_resolutions=[],
vector_action_space_size=[2],
vector_action_descriptions=[],
vector_action_space_type=0,
)
_, demo_buffer = demo_to_buffer(
path_prefix + "/test.demo", 1, brain_params_type
)
# vis obs mismatch
with pytest.raises(RuntimeError):
brain_params_vis = BrainParameters(
brain_name="test_brain",
vector_observation_space_size=8,
camera_resolutions=[[30, 40]],
vector_action_space_size=[2],
vector_action_descriptions=[],
vector_action_space_type=1,
)
_, demo_buffer = demo_to_buffer(path_prefix + "/test.demo", 1, brain_params_vis)
def test_edge_cases():
path_prefix = os.path.dirname(os.path.abspath(__file__))
# nonexistent file and directory
with pytest.raises(FileNotFoundError):
get_demo_files(os.path.join(path_prefix, "nonexistent_file.demo"))
with pytest.raises(FileNotFoundError):
get_demo_files(os.path.join(path_prefix, "nonexistent_directory"))
with tempfile.TemporaryDirectory() as tmpdirname:
# empty directory
with pytest.raises(ValueError):
get_demo_files(tmpdirname)
# invalid file
invalid_fname = os.path.join(tmpdirname, "mydemo.notademo")
with open(invalid_fname, "w") as f:
f.write("I'm not a demo")
with pytest.raises(ValueError):
get_demo_files(invalid_fname)
# invalid directory
with pytest.raises(ValueError):
get_demo_files(tmpdirname)
# valid file
valid_fname = os.path.join(tmpdirname, "mydemo.demo")
with open(valid_fname, "w") as f:
f.write("I'm a demo file")
assert get_demo_files(valid_fname) == [valid_fname]
# valid directory
assert get_demo_files(tmpdirname) == [valid_fname]
@mock.patch("mlagents.trainers.demo_loader.get_demo_files", return_value=["foo.demo"])
def test_unsupported_version_raises_error(mock_get_demo_files):
# Create a metadata proto with an unsupported version
bad_metadata = DemonstrationMetaProto()
bad_metadata.api_version = 1337
# Write the metadata to a temporary buffer, which will get returned by open()
buffer = io.BytesIO()
write_delimited(buffer, bad_metadata)
m = mock.mock_open(read_data=buffer.getvalue())
# Make sure that we get a RuntimeError when trying to load this.
with mock.patch("builtins.open", m):
with pytest.raises(RuntimeError):
load_demonstration("foo")