您最多选择25个主题
主题必须以中文或者字母或数字开头,可以包含连字符 (-),并且长度不得超过35个字符
53 行
2.1 KiB
53 行
2.1 KiB
import os
|
|
from typing import Any, List, Set, NamedTuple
|
|
import torch
|
|
|
|
from mlagents_envs.logging_util import get_logger
|
|
from mlagents.trainers.settings import SerializationSettings
|
|
|
|
|
|
logger = get_logger(__name__)
|
|
|
|
|
|
class ModelSerializer:
|
|
def __init__(self, policy):
|
|
self.policy = policy
|
|
dummy_vec_obs = [torch.zeros([1] + [self.policy.vec_obs_size])]
|
|
dummy_vis_obs = [torch.zeros([1] + list(self.policy.vis_obs_shape))] \
|
|
if self.policy.vis_obs_size > 0 else []
|
|
dummy_masks = torch.ones([1] + self.policy.actor_critic.act_size)
|
|
dummy_memories = torch.zeros([1] + [self.policy.m_size])
|
|
|
|
self.input_names = ["vector_observation", "visual_observation", \
|
|
"action_mask", "memories"]
|
|
self.output_names = ["action", "action_probs", "version_number", \
|
|
"memory_size", "is_continuous_control", "action_output_shape"]
|
|
self.dynamic_axes = {"vector_observation": [0], "visual_observation": [0], \
|
|
"action_mask": [0], "memories": [0], "action": [0],"action_probs": [0]}
|
|
self.dummy_input = (dummy_vec_obs, dummy_vis_obs, \
|
|
dummy_masks, dummy_memories)
|
|
|
|
def export_policy_model(self, output_filepath: str) -> None:
|
|
"""
|
|
Exports a Torch model for a Policy to .onnx format for Unity embedding.
|
|
|
|
:param output_filepath: file path to output the model (without file suffix)
|
|
:param brain_name: Brain name of brain to be trained
|
|
"""
|
|
if not os.path.exists(output_filepath):
|
|
os.makedirs(output_filepath)
|
|
|
|
onnx_output_path = f"{output_filepath}.onnx"
|
|
logger.info(f"Converting to {onnx_output_path}")
|
|
|
|
torch.onnx.export(
|
|
self.policy.actor_critic,
|
|
self.dummy_input,
|
|
onnx_output_path,
|
|
verbose=True,
|
|
opset_version=SerializationSettings.onnx_opset,
|
|
input_names=self.input_names,
|
|
output_names=self.output_names,
|
|
dynamic_axes=self.dynamic_axes,
|
|
)
|
|
logger.info(f"Exported {onnx_output_path}.onnx")
|