小编Mat*_*ski的帖子

我正在编写一个代码,用于在tensorflow中从光盘读取图像和标签,然后尝试调用tf.estimator.inputs.numpy_input_fn.如何传递整个数据集而不是单个图像.我的代码看起来像:

filenames = tf.constant(filenames)
labels = tf.constant(labels)

dataset = tf.data.Dataset.from_tensor_slices((filenames, labels))
dataset = dataset.map(_parse_function)
dataset_batched = dataset.batch(10)
iterator = dataset_batched.make_one_shot_iterator()
features, labels = iterator.get_next()

with tf.Session() as sess:

  print(dataset_batched)
  print(np.shape(sess.run(features)))
  print(np.shape(sess.run(labels)))

  mnist_classifier = tf.estimator.Estimator(model_fn=cnn_model_mk, model_dir=dir)
  train_input_fn = tf.estimator.inputs.numpy_input_fn(x={"x": np.array(sess.run(features))},
                                                  y=np.array(sess.run(labels)),
                                                  batch_size=1,
                                                  num_epochs=None,
                                                  shuffle=False)
  mnist_classifier.train(input_fn=train_input_fn, steps=1)

我的问题是如何在这里传递数据集 x={"x": np.array(sess.run(features))}