Running main_test. py alone resulted in an error

[shushushulian]

Configure the following code according to the same configuration as the test_stngle. sh file, but there will be an error message indicating inconsistent loading model sizes. ` from gln.common.cmd_args import cmd_args import argparse import os import random import numpy as np import torch from gln.test.model_inference import RetroGLN

os.environ["CUDA_VISIBLE_DEVICES"] = "0"

random.seed(cmd_args.seed) np.random.seed(cmd_args.seed) torch.manual_seed(cmd_args.seed)

cmd_opt = argparse.ArgumentParser(description='Argparser for test only') cmd_opt.add_argument('-model_for_test', default=None, help='model for test') local_args = argparse.Namespace( model_for_test="dropbox/schneider50k.ckpt", )

cmd_args.dropbox = "GLN-master/dropbox" cmd_args.data_name = 'schneider50k' model = RetroGLN(cmd_args.dropbox, local_args.model_for_test) **Error content** ~/Code/Retro/mutilstep/GLN-master/gln/test/model_inference.py in init(self, dropbox, model_dump) 37 model_file = os.path.join(model_dump, 'model.dump') 38 self.gln = GraphPath(self.args) ---> 39 self.gln.load_state_dict(torch.load(model_file)) 40 self.gln.cuda() 41 self.gln.eval()

~/.conda/envs/GLN/lib/python3.7/site-packages/torch/nn/modules/module.py in load_state_dict(self, state_dict, strict) 1666 if len(error_msgs) > 0: 1667 raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( -> 1668 self.class.name, "\n\t".join(error_msgs))) 1669 return _IncompatibleKeys(missing_keys, unexpected_keys) 1670

RuntimeError: Error(s) in loading state_dict for GraphPath: size mismatch for tpl_fwd_predicate.prod_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for tpl_fwd_predicate.tpl_enc.prod_gnn.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for tpl_fwd_predicate.tpl_enc.react_gnn.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for prod_center_predicate.prod_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for prod_center_predicate.prod_center_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for reaction_predicate.prod_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for reaction_predicate.react_enc.react_gnn.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). `

[hyj-real]

Configure the following code according to the same configuration as the test_stngle. sh file, but there will be an error message indicating inconsistent loading model sizes. ` from gln.common.cmd_args import cmd_args import argparse import os import random import numpy as np import torch from gln.test.model_inference import RetroGLN

os.environ["CUDA_VISIBLE_DEVICES"] = "0"

random.seed(cmd_args.seed) np.random.seed(cmd_args.seed) torch.manual_seed(cmd_args.seed)

cmd_opt = argparse.ArgumentParser(description='Argparser for test only') cmd_opt.add_argument('-model_for_test', default=None, help='model for test') local_args = argparse.Namespace( model_for_test="dropbox/schneider50k.ckpt", )

cmd_args.dropbox = "GLN-master/dropbox" cmd_args.data_name = 'schneider50k' model = RetroGLN(cmd_args.dropbox, local_args.model_for_test) **Error content** ~/Code/Retro/mutilstep/GLN-master/gln/test/model_inference.py in init(self, dropbox, model_dump) 37 model_file = os.path.join(model_dump, 'model.dump') 38 self.gln = GraphPath(self.args) ---> 39 self.gln.load_state_dict(torch.load(model_file)) 40 self.gln.cuda() 41 self.gln.eval()

~/.conda/envs/GLN/lib/python3.7/site-packages/torch/nn/modules/module.py in load_state_dict(self, state_dict, strict) 1666 if len(error_msgs) > 0: 1667 raise RuntimeError('Error(s) in loading state_dict for {}:\n\t{}'.format( -> 1668 self.class.name, "\n\t".join(error_msgs))) 1669 return _IncompatibleKeys(missing_keys, unexpected_keys) 1670

RuntimeError: Error(s) in loading state_dict for GraphPath: size mismatch for tpl_fwd_predicate.prod_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for tpl_fwd_predicate.tpl_enc.prod_gnn.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for tpl_fwd_predicate.tpl_enc.react_gnn.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for prod_center_predicate.prod_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for prod_center_predicate.prod_center_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for reaction_predicate.prod_enc.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). size mismatch for reaction_predicate.react_enc.react_gnn.w_n2l.weight: copying a param with shape torch.Size([128, 39]) from checkpoint, the shape in current model is torch.Size([128, 66]). `

I've also encountered the same problem. May I ask if you've solved it?