AttributeError: 'NoneType' object has no attribute 'size'

hello. when i use torch summary. it reports some issues about:

File “F:\Anaconda3\lib\site-packages\torchsummary\torchsummary.py”, line 23, in
[-1] + list(o.size())[1:] for o in output
AttributeError: ‘NoneType’ object has no attribute ‘size’

here is my model structure.
CommonsenseGRUModel(
(linear_in): Linear(in_features=1024, out_features=300, bias=True)
(norm1a): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
(norm1b): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
(norm1c): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
(norm1d): LayerNorm((1024,), eps=1e-05, elementwise_affine=True)
(norm3a): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm3b): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm3c): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(norm3d): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
(dropout): Dropout(p=0.5, inplace=False)
(dropout_rec): Dropout(p=False, inplace=False)
(cs_rnn_f): CommonsenseRNN(
(dropout): Dropout(p=False, inplace=False)
(dialogue_cell): CommonsenseRNNCell(
(g_cell): GRUCell(600, 150)
(p_cell): GRUCell(918, 150)
(r_cell): GRUCell(1218, 150)
(i_cell): GRUCell(918, 150)
(e_cell): GRUCell(750, 450)
(dropout): Dropout(p=False, inplace=False)
(dropout1): Dropout(p=False, inplace=False)
(dropout2): Dropout(p=False, inplace=False)
(dropout3): Dropout(p=False, inplace=False)
(dropout4): Dropout(p=False, inplace=False)
(dropout5): Dropout(p=False, inplace=False)
(attention): SimpleAttention(
(scalar): Linear(in_features=150, out_features=1, bias=False)
)
)
)
(cs_rnn_r): CommonsenseRNN(
(dropout): Dropout(p=False, inplace=False)
(dialogue_cell): CommonsenseRNNCell(
(g_cell): GRUCell(600, 150)
(p_cell): GRUCell(918, 150)
(r_cell): GRUCell(1218, 150)
(i_cell): GRUCell(918, 150)
(e_cell): GRUCell(750, 450)
(dropout): Dropout(p=False, inplace=False)
(dropout1): Dropout(p=False, inplace=False)
(dropout2): Dropout(p=False, inplace=False)
(dropout3): Dropout(p=False, inplace=False)
(dropout4): Dropout(p=False, inplace=False)
(dropout5): Dropout(p=False, inplace=False)
(attention): SimpleAttention(
(scalar): Linear(in_features=150, out_features=1, bias=False)
)
)
)
(sense_gru): GRU(768, 384, bidirectional=True)
(matchatt): MatchingAttention(
(transform): Linear(in_features=900, out_features=900, bias=True)
)
(linear): Linear(in_features=900, out_features=300, bias=True)
(smax_fc): Linear(in_features=300, out_features=7, bias=True)
)

here is about using summary.
input_size = [( 14,1, 1024), (14, 1, 1024), (14, 1, 1024), (14, 1, 1024), (14, 1, 768), (14, 1, 768), (14, 1, 768),(14, 1, 768), (14, 1, 768), (14, 1, 9), (1, 14)]
from torchsummary import summary
model_summary = summary(model,input_size = input_size)
print(model_summary)

Could you please give me some detailed suggestions about how to fix it?
Thanks, best wishes