change env to vecenv for higher code coverage rate
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.github/workflows/pytest.yml
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2
.github/workflows/pytest.yml
vendored
@ -37,4 +37,4 @@ jobs:
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- name: Test with pytest
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- name: Test with pytest
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run: |
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run: |
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pip install pytest pytest-cov
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pip install pytest pytest-cov
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pytest --cov tianshou -s
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pytest --cov tianshou
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@ -8,9 +8,9 @@ from torch import nn
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from torch.utils.tensorboard import SummaryWriter
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from torch.utils.tensorboard import SummaryWriter
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from tianshou.policy import DDPGPolicy
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from tianshou.policy import DDPGPolicy
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from tianshou.env import SubprocVectorEnv
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from tianshou.utils import tqdm_config, MovAvg
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from tianshou.utils import tqdm_config, MovAvg
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from tianshou.data import Collector, ReplayBuffer
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from tianshou.data import Collector, ReplayBuffer
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from tianshou.env import VectorEnv, SubprocVectorEnv
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class Actor(nn.Module):
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class Actor(nn.Module):
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@ -92,7 +92,7 @@ def test_ddpg(args=get_args()):
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args.action_shape = env.action_space.shape or env.action_space.n
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args.action_shape = env.action_space.shape or env.action_space.n
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args.max_action = env.action_space.high[0]
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args.max_action = env.action_space.high[0]
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# train_envs = gym.make(args.task)
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# train_envs = gym.make(args.task)
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train_envs = SubprocVectorEnv(
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train_envs = VectorEnv(
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[lambda: gym.make(args.task) for _ in range(args.training_num)],
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[lambda: gym.make(args.task) for _ in range(args.training_num)],
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reset_after_done=True)
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reset_after_done=True)
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# test_envs = gym.make(args.task)
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# test_envs = gym.make(args.task)
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