问Tensorflow2 LSTM (cuDNN args)与tensorflow1 CuDNNLSTM实现差异

EN

  1. `activation` == `tanh`
  2. `recurrent_activation` == `sigmoid`
  3. `recurrent_dropout` == 0
  4. `unroll` is `False`
  5. `use_bias` is `True`
  6. Inputs are not masked or strictly right padded.

import tensorflow as tf
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import LSTM
from tensorflow.compat.v1.keras.layers import CuDNNLSTM

print(tf.__version__)

model1 = Sequential()
model1.add(LSTM(1, activation='tanh', recurrent_dropout=0, unroll=False, use_bias=True, return_sequences=0, input_shape=(1, 1)))
print(model1.summary())

model2 = Sequential()
model2.add(CuDNNLSTM(1, return_sequences=0, input_shape=(1, 1)))
print(model2.summary())

2.2.0
Model: "sequential"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
lstm (LSTM)               (None, 1)                 12        
=================================================================
Total params: 12
Trainable params: 12
Non-trainable params: 0
_________________________________________________________________
None
Model: "sequential_1"
_________________________________________________________________
Layer (type)                 Output Shape              Param #   
=================================================================
cu_dnnlstm (CuDNNLSTM)    (None, 1)                 16        
=================================================================
Total params: 16
Trainable params: 16
Non-trainable params: 0
_________________________________________________________________