python - 张量板 : How to view model summary?

Question

问题陈述

• 运行具有多种配置的模型并比较图表。根据绘图分析，选择配置。

在上面的语句中，我能够使用模型的名称来绘制模型的多次运行。现在我还需要 Tensorboard 来显示每次运行的模型配置/摘要。

问题是是否可以在 Tensorboard 中查看模型每次运行对应的模型摘要？

Answer 1

您可以使用 text摘要与模型摘要，如下所示:

import tensorflow as tf

# Get model summary as a string
def get_summary_str(model):
    lines = []
    model.summary(print_fn=lines.append)
    # Add initial spaces to avoid markdown formatting in TensorBoard
    return '    ' + '\n    '.join(lines)

# Write a string to TensorBoard (1.x)
def write_string_summary_v1(writer, s):
    with tf.Graph().as_default(), tf.Session() as sess:
        summary = tf.summary.text('Model configuration', tf.constant(s))
        writer.add_summary(sess.run(summary))

# Write a string to TensorBoard (2.x)
def write_string_summary_v2(writer, s):
    with writer.as_default():
        tf.summary.text('Model configuration', s, step=0)

# Model 1
inp1 = tf.keras.Input(shape=(10,))
out1 = tf.keras.layers.Dense(100)(inp1)
model1 = tf.keras.Model(inputs=inp1, outputs=out1)
# Model 2
inp2 = tf.keras.Input(shape=(10,))
out2 = tf.keras.layers.Dense(200)(inp2)
out2 = tf.keras.layers.Dense(100)(out2)
model2 = tf.keras.Model(inputs=inp2, outputs=out2)
# Write model summaries to TensorBoard (1.x)
with tf.summary.FileWriter('log/model1') as writer1:
    write_string_summary_v1(writer1, get_summary_str(model1))
with tf.summary.FileWriter('log/model2') as writer2:
    write_string_summary_v1(writer2, get_summary_str(model2))
# Write model summaries to TensorBoard (2.x)
writer1 = tf.summary.create_file_writer('log/model1')
write_string_summary_v2(writer1, get_summary_str(model1))
writer2 = tf.summary.create_file_writer('log/model2')
write_string_summary_v2(writer2, get_summary_str(model2))

出于某种原因，在 2.0 中编写摘要工作正常，但是当我尝试显示它时 2.0 TensorBoard 失败，我认为这是一个错误。然而，TensorBoard 1.15 表现得很好(从任一版本编写)。结果看起来像这样: