我有一个以Softmax层结尾的keras模型。根据定义,Softmax的输出形状与输入相同,但在我的情况下,它具有额外的尺寸:[1,None,20]而不是[None,20]
有人可以向我解释为什么吗?目前,我固定了挤压,但还是很奇怪
谢谢!
def create_keras_model_embedding():
l = tf.keras.layers
a = l.Input(shape=(784,))
embedded_lookup_feature = tf.feature_column.numeric_column('x', shape=(784))
dense_features = l.DenseFeatures(embedded_lookup_feature)({'x': a})#{'x': a}
dense = l.Dense(784)(dense_features)
dense_2 = l.Dense(10, kernel_initializer='zeros')(dense),
output = l.Softmax(axis=1)(dense_2)
output = tf.squeeze(output)
return tf.keras.Model(inputs=a, outputs=output)
仅使用Activation
,这是更标准且常见的做法。
from tensorflow.keras.layers import *
from tensorflow.keras.models import Model, Sequential
import tensorflow as tf
def create_keras_model_embedding():
l = tf.keras.layers
a = l.Input(shape=(784,))
embedded_lookup_feature = tf.feature_column.numeric_column('x', shape=(784))
dense_features = l.DenseFeatures(embedded_lookup_feature)({'x': a})#{'x': a}
dense = l.Dense(784)(dense_features)
dense_2 = l.Dense(10, kernel_initializer='zeros')(dense)
output = l.Activation('softmax')(dense_2)
return tf.keras.Model(inputs=a, outputs=output)
model = create_keras_model_embedding()
model.summary()
Model: "model_1"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
input_3 (InputLayer) [(None, 784)] 0
_________________________________________________________________
dense_features_2 (DenseFeatu (None, 784) 0
_________________________________________________________________
dense_4 (Dense) (None, 784) 615440
_________________________________________________________________
dense_5 (Dense) (None, 10) 7850
_________________________________________________________________
activation_1 (Activation) (None, 10) 0
=================================================================
Total params: 623,290
Trainable params: 623,290
Non-trainable params: 0
_________________________