TensorFlow2.0:如何为numpy矩阵输入创建feature_columns

import tensorflow as tf
from tensorflow import feature_column

# 假设numpy矩阵输入为x
feature_columns = []
for i in range(x.shape[1]):
    feature_columns.append(feature_column.numeric_column(str(i)))

def input_fn():
    # 假设numpy矩阵输入为x，对应的标签为y
    dataset = tf.data.Dataset.from_tensor_slices((x, y))
    dataset = dataset.shuffle(buffer_size=len(x))
    dataset = dataset.batch(batch_size)
    return dataset

model = tf.keras.Sequential([
    tf.keras.layers.DenseFeatures(feature_columns),
    tf.keras.layers.Dense(units=10, activation='relu'),
    tf.keras.layers.Dense(units=1, activation='sigmoid')
])

model.compile(optimizer='adam',
              loss='binary_crossentropy',
              metrics=['accuracy'])

model.fit(input_fn(), epochs=num_epochs)