在Tesnprflow服务器中转置Conv2D

Question

我无法确定某种型号

没问题

import tensorflow as tf 
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Activation, Flatten, Conv2D,MaxPooling2D

model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=(192,64,3)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

saved_to_path = tf.keras.experimental.export(
        model, '/tensorflow-serving/test/my_simple_tf_keras_saved_model')

问题

import tensorflow as tf 
from tensorflow.keras.models import Sequential
from tensorflow.keras.layers import Activation, Flatten, Conv2D,MaxPooling2D

model = Sequential()
model.add(Conv2D(32, (3, 3), input_shape=(192,64,1)))
model.add(Activation('relu'))
model.add(MaxPooling2D(pool_size=(2, 2)))

saved_to_path = tf.keras.experimental.export(
        model, '/tensorflow-serving/test/my_simple_tf_keras_saved_model')

错误 当我运行非服务器模型时 { "error": "Fused conv implementation does not support grouped convolutions for now.\n\t [[{{node conv2d/BiasAdd}}]]" }

Conv2D不适用于一个频道。但是可以使用三个频道。

我需要一个单通道输入信号。怎样成为？ 需要 Conv2D(32, (3, 3), input_shape=(192,64,1))

是包还是特色？