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96 行
2.9 KiB
96 行
2.9 KiB
import pytest
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from mlagents.trainers.sampler_class import SamplerManager
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from mlagents.trainers.sampler_class import (
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UniformSampler,
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MultiRangeUniformSampler,
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GaussianSampler,
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)
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from mlagents.trainers.exception import TrainerError
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def sampler_config_1():
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return {
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"mass": {"sampler-type": "uniform", "min_value": 5, "max_value": 10},
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"gravity": {
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"sampler-type": "multirange_uniform",
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"intervals": [[8, 11], [15, 20]],
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},
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}
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def check_value_in_intervals(val, intervals):
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check_in_bounds = [a <= val <= b for a, b in intervals]
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return any(check_in_bounds)
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def test_sampler_config_1():
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config = sampler_config_1()
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sampler = SamplerManager(config)
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assert sampler.is_empty() is False
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assert isinstance(sampler.samplers["mass"], UniformSampler)
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assert isinstance(sampler.samplers["gravity"], MultiRangeUniformSampler)
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cur_sample = sampler.sample_all()
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# Check uniform sampler for mass
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assert sampler.samplers["mass"].min_value == config["mass"]["min_value"]
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assert sampler.samplers["mass"].max_value == config["mass"]["max_value"]
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assert config["mass"]["min_value"] <= cur_sample["mass"]
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assert config["mass"]["max_value"] >= cur_sample["mass"]
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# Check multirange_uniform sampler for gravity
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assert sampler.samplers["gravity"].intervals == config["gravity"]["intervals"]
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assert check_value_in_intervals(
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cur_sample["gravity"], sampler.samplers["gravity"].intervals
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)
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def sampler_config_2():
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return {"angle": {"sampler-type": "gaussian", "mean": 0, "st_dev": 1}}
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def test_sampler_config_2():
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config = sampler_config_2()
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sampler = SamplerManager(config)
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assert sampler.is_empty() is False
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assert isinstance(sampler.samplers["angle"], GaussianSampler)
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# Check angle gaussian sampler
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assert sampler.samplers["angle"].mean == config["angle"]["mean"]
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assert sampler.samplers["angle"].st_dev == config["angle"]["st_dev"]
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def test_empty_samplers():
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empty_sampler = SamplerManager({})
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assert empty_sampler.is_empty()
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empty_cur_sample = empty_sampler.sample_all()
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assert empty_cur_sample == {}
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none_sampler = SamplerManager(None)
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assert none_sampler.is_empty()
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none_cur_sample = none_sampler.sample_all()
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assert none_cur_sample == {}
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def incorrect_uniform_sampler():
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# Do not specify required arguments to uniform sampler
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return {"mass": {"sampler-type": "uniform", "min-value": 10}}
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def incorrect_sampler_config():
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# Do not specify 'sampler-type' key
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return {"mass": {"min-value": 2, "max-value": 30}}
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def test_incorrect_uniform_sampler():
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config = incorrect_uniform_sampler()
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with pytest.raises(TrainerError):
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SamplerManager(config)
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def test_incorrect_sampler():
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config = incorrect_sampler_config()
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with pytest.raises(TrainerError):
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SamplerManager(config)
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