Use Slim to overview model in Tensorflow like model.summary() in Keras
阿新 • • 發佈:2019-02-27
convert num kernel code http style int tensor bytes
model.summary() in Tensorflow like Keras
Use Slim
Example:
import numpy as np from tensorflow.python.layers import base import tensorflow as tf import tensorflow.contrib.slim as slim x = np.zeros((1,4,4,3)) x_tf = tf.convert_to_tensor(x, np.float32) z_tf = tf.layers.conv2d(x_tf, filters=32, kernel_size=(3,3))def model_summary(): model_vars = tf.trainable_variables() slim.model_analyzer.analyze_vars(model_vars, print_info=True) model_summary()
Output:
--------- Variables: name (type shape) [size] --------- conv2d/kernel:0 (float32_ref 3x3x3x32) [864, bytes: 3456] conv2d/bias:0 (float32_ref 32) [32, bytes: 128] Total size of variables:896 Total bytes of variables: 3584
來源: https://stackoverflow.com/questions/46560313/is-there-an-easy-way-to-get-something-like-keras-model-summary-in-tensorflow
Use Slim to overview model in Tensorflow like model.summary() in Keras