Description
python代码：
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
inputs = tf.random.normal([32, 10, 8])
lstm = tf.keras.layers.LSTM(4)
output = lstm(inputs)
print(output.shape)
#(32, 4)
lstm = tf.keras.layers.LSTM(4, return_sequences=True, return_state=True)
whole_seq_output, final_memory_state, final_carry_state = lstm(inputs)
print(whole_seq_output.shape)
#(32, 10, 4)
print(final_memory_state.shape)
#(32, 4)
print(final_carry_state.shape)
#(32, 4)
C#代码：
var inputs = tf.random.normal(new Shape(32, 10, 8));
var lstm = new Tensorflow.Keras.Layers.LSTM(new LSTMArgs()
{
Units = 4,
//InputShape = new Shape(10,8)
});
var y = lstm.Apply(inputs);//在这个位置报错，提示索引超出范围
print(y.shape);
Reproduction Steps
No response
Known Workarounds
无解决办法
No response
Configuration and Other Information
No response
Description
python代码：
import numpy as np
import tensorflow as tf
from tensorflow import keras
from tensorflow.keras import layers
inputs = tf.random.normal([32, 10, 8])
lstm = tf.keras.layers.LSTM(4)
output = lstm(inputs)
print(output.shape)
#(32, 4)
lstm = tf.keras.layers.LSTM(4, return_sequences=True, return_state=True)
whole_seq_output, final_memory_state, final_carry_state = lstm(inputs)
print(whole_seq_output.shape)
#(32, 10, 4)
print(final_memory_state.shape)
#(32, 4)
print(final_carry_state.shape)
#(32, 4)
C#代码：
var inputs = tf.random.normal(new Shape(32, 10, 8));
var lstm = new Tensorflow.Keras.Layers.LSTM(new LSTMArgs()
{
Units = 4,
//InputShape = new Shape(10,8)
});
var y = lstm.Apply(inputs);//在这个位置报错，提示索引超出范围
print(y.shape);
Reproduction Steps
No response
Known Workarounds
无解决办法
No response
Configuration and Other Information
No response