优化资源占用
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@ -8,6 +8,9 @@ from douzero.env.env import get_obs
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def _load_model(position, model_path, model_type, use_legacy, use_lite, use_onnx=False):
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def _load_model(position, model_path, model_type, use_legacy, use_lite, use_onnx=False):
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from douzero.dmc.models import model_dict_new, model_dict_new_lite, model_dict, model_dict_legacy, model_dict_lite
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from douzero.dmc.models import model_dict_new, model_dict_new_lite, model_dict, model_dict_legacy, model_dict_lite
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model_path = model_path + '.onnx'
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if use_onnx and os.path.exists(model_path):
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return None
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model = None
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model = None
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if model_type == "general":
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if model_type == "general":
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if use_lite:
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if use_lite:
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@ -29,21 +32,19 @@ def _load_model(position, model_path, model_type, use_legacy, use_lite, use_onnx
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model.load_state_dict(model_state_dict)
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model.load_state_dict(model_state_dict)
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# torch.save(model.state_dict(), model_path.replace(".ckpt", "_nobn.ckpt"))
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# torch.save(model.state_dict(), model_path.replace(".ckpt", "_nobn.ckpt"))
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model.eval()
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model.eval()
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model_path = model_path + '.onnx'
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if use_onnx and not os.path.exists(model_path):
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if use_onnx:
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onnx_params = model.get_onnx_params(torch.device('cpu'))
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if not os.path.exists(model_path):
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torch.onnx.export(
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onnx_params = model.get_onnx_params(torch.device('cpu'))
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model,
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torch.onnx.export(
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onnx_params['args'],
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model,
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model_path,
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onnx_params['args'],
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export_params=True,
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model_path,
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opset_version=10,
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export_params=True,
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do_constant_folding=True,
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opset_version=10,
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input_names=onnx_params['input_names'],
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do_constant_folding=True,
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output_names=onnx_params['output_names'],
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input_names=onnx_params['input_names'],
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dynamic_axes=onnx_params['dynamic_axes']
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output_names=onnx_params['output_names'],
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)
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dynamic_axes=onnx_params['dynamic_axes']
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)
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return None
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return None
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return model
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return model
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