我安装了 TensorFlow (2.3) 的最新版本，在 Python 下运行良好，但在 Golang 下却出现异常：
...但不包含包 github.com/tensorflow/tensorflow/tensorflow/go/core/protobuf/for_core_protos_go_proto
通过将版本更改为 1.15.0，我让 TensorFlow 与 Golang 一起使用
现在，我面临以下问题：
使用 TensorFlow 2.3 的 Python 代码
import tensorflow as tf
df = pd.read_csv(data_path, sep=';')
X = df[df.columns[:8]]
y = df[df.columns[8:-1]]
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size = 0.3)
model = tf.keras.Sequential()
model.add(tf.keras.layers.Dense(8, activation='relu', name="inputNode"))
model.add(tf.keras.layers.Dense(150, activation='relu'))
model.add(tf.keras.layers.Dense(3, name="inferNode"))
model.compile(loss='mean_squared_error', optimizer='adam', metrics=['accuracy'])
model.fit(X_train, y_train, epochs=500)
tf.keras.models.save_model(model=model, filepath='./', save_format='tf')
使用 TensorFlow 1.15.0 的 Golang 代码
model, err := tf.LoadSavedModel("./", []string{"serve"}, nil)
if err != nil {
fmt.Printf("Error loading saved model: %s\n", err.Error())
return
}
defer model.Session.Close()
data := [][]float32{make([]float32, 8)}
data[0][0] = 1.0
data[0][1] = 1.0
data[0][2] = 1.0
data[0][3] = 1.0
data[0][4] = 1.0
data[0][5] = 1.0
data[0][6] = 1.0
data[0][7] = 1.0
tensor, _ := tf.NewTensor(data)
result, err := model.Session.Run(
map[tf.Output]*tf.Tensor{
model.Graph.Operation("inputNode_input").Output(0): tensor, // Replace this with your input layer name
},
[]tf.Output{
model.Graph.Operation("inferNode").Output(0), // Replace this with your output layer name
},
nil,
)
if err != nil {
fmt.Printf("Error running the session with input, err: %s\n", err.Error())
return
}
fmt.Printf("Result value: %v \n", result[0].Value())
golang 抛出这个异常：
-- FAIL: TestMlPredict (6.93s)
panic: nil-Operation. If the Output was created with a Scope object, see Scope.Err() for details. [recovered]
panic: nil-Operation. If the Output was created with a Scope object, see Scope.Err() for details.