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python - 警告 :tensorflow :`write_grads` will be ignored in TensorFlow 2. 0 为 `TensorBoard` 回调

转载 作者:行者123 更新时间:2023-12-03 19:06:44 25 4
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我正在使用以下代码行使用 tensorboard 可视化 ANN 模型的梯度

  tensorboard_callback = tf.compat.v1.keras.callbacks.TensorBoard(log_dir='./Graph', histogram_freq=1, write_graph = True, write_grads =True, write_images = False)

tensorboard_callback .set_model(model)


%tensorboard --logdir ./Graph
我收到一条警告消息,上面写着“警告:tensorflow: write_grads 将在 TensorFlow 2.0 中忽略 TensorBoard 回调。”
我得到了张量板输出,但没有渐变。
enter image description here
可能的原因是什么?
(注:我使用的是 2.3.0 tensorflow 版本)
谢谢你。

最佳答案

Write_Grads未在 TF2.x 中实现.这是仍然开放的备受期待的功能请求之一。请查看此 GitHub issue作为功​​能请求。所以,我们只需要导入TF1.x模块和使用write_grads如以下代码所示。

# Load the TensorBoard notebook extension
%load_ext tensorboard

import tensorflow as tf
import datetime

# Clear any logs from previous runs
!rm -rf ./logs/

# Disable V2 behavior
tf.compat.v1.disable_v2_behavior()

mnist = tf.keras.datasets.mnist

(x_train, y_train),(x_test, y_test) = mnist.load_data()

x_train, x_test = x_train / 255.0, x_test / 255.0


def create_model():

return tf.keras.models.Sequential([

tf.keras.layers.Flatten(input_shape=(28, 28)),

tf.keras.layers.Dense(512, activation='relu'),

tf.keras.layers.Dropout(0.2),

tf.keras.layers.Dense(10, activation='softmax')

])



model = create_model()

model.compile(optimizer='adam',

loss='sparse_categorical_crossentropy',

metrics=['accuracy'])


log_dir = "logs/fit/" + datetime.datetime.now().strftime("%Y%m%d-%H%M%S")

tensorboard_callback = tf.compat.v1.keras.callbacks.TensorBoard(log_dir=log_dir, histogram_freq=1, write_grads =True)

model.fit(x=x_train, y=y_train, epochs=1, validation_data=(x_test, y_test), callbacks=[tensorboard_callback])

%tensorboard --logdir logs/fit
输出:
Downloading data from https://storage.googleapis.com/tensorflow/tf-keras-datasets/mnist.npz
11493376/11490434 [==============================] - 0s 0us/step

Train on 60000 samples, validate on 10000 samples
WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training_v1.py:2048: Model.state_updates (from tensorflow.python.keras.engine.training) is deprecated and will be removed in a future version.
Instructions for updating:
This property should not be used in TensorFlow 2.0, as updates are applied automatically.
32/60000 [..............................] - ETA: 0s - loss: 2.3311 - acc: 0.0312WARNING:tensorflow:Callbacks method `on_train_batch_end` is slow compared to the batch time (batch time: 0.0055s vs `on_train_batch_end` time: 0.0235s). Check your callbacks.
60000/60000 [==============================] - 17s 288us/sample - loss: 0.2187 - acc: 0.9349 - val_loss: 0.1012 - val_acc: 0.9690
<tensorflow.python.keras.callbacks.History at 0x7f7ebd1d3d30>
enter image description here

关于python - 警告 :tensorflow :`write_grads` will be ignored in TensorFlow 2. 0 为 `TensorBoard` 回调,我们在Stack Overflow上找到一个类似的问题: https://stackoverflow.com/questions/63388030/

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