如何在一次运行中从 Inception-v3 检索 fc 和 softmax 层的输出？答案

【问题标题】：How can I retrieve the output from both fc and softmax layers from Inception-v3 in a single run?如何在一次运行中从 Inception-v3 检索 fc 和 softmax 层的输出？
【发布时间】：2016-05-14 02:47:22
【问题描述】：

我想提取'pool_3:0' 和'softmax:0' 层的输出。我可以运行模型两次，每次运行都提取单层的输出，但这有点浪费。是否可以只运行一次模型？

我正在使用classify_image.py 提供的示例。这是相关的sn-p：

def run_inference_on_image(image_data):
  create_graph()
  with tf.Session() as sess:
    # Some useful tensors:
    # 'softmax:0': A tensor containing the normalized prediction across
    #   1000 labels.
    # 'pool_3:0': A tensor containing the next-to-last layer containing 2048
    #   float description of the image.
    # 'DecodeJpeg/contents:0': A tensor containing a string providing JPEG
    #   encoding of the image.
    # Runs the softmax tensor by feeding the image_data as input to the graph.
    softmax_tensor = sess.graph.get_tensor_by_name('softmax:0')
    predictions = sess.run(softmax_tensor,
                           {'DecodeJpeg:0': image_data})
    predictions = np.squeeze(predictions)

    # Creates node ID --> English string lookup.
    node_lookup = NodeLookup()

    top_k = predictions.argsort()[-FLAGS.num_top_predictions:][::-1]
    for node_id in top_k:
      human_string = node_lookup.id_to_string(node_id)
      score = predictions[node_id]
      print('%s (score = %.5f)' % (human_string, score))

    return predictions

【问题讨论】：

标签： tensorflow softmax

【解决方案1】：

您可以将张量列表传递给Session.run()，TensorFlow 将共享为计算它们所做的工作：

softmax_tensor = sess.graph.get_tensor_by_name('softmax:0')
pool_3 = sess.graph.get_tensor_by_name('pool_3:0')
predictions, pool3_val = sess.run([softmax_tensor, pool_3],
                                  {'DecodeJpeg:0': image_data})

【讨论】：