Keras Model.fit详细格式 [英] Keras Model.fit Verbose Formatting

问题描述

我正在Jupyter笔记本中运行Keras model.fit()，如果将verbose设置为1，则输出将非常混乱.

I'm running Keras model.fit() in Jupyter notebook, and the output is very messy if verbose is set to 1:

    Train on 6400 samples, validate on 800 samples
    Epoch 1/200
    2080/6400 [========>.....................] - ETA: 39s - loss: 0.4383 - acc: 0.79 
    - ETA: 34s - loss: 0.3585 - acc: 0.84 - ETA: 33s - loss: 0.3712 - acc: 0.84 
    - ETA: 34s - loss: 0.3716 - acc: 0.84 - ETA: 33s - loss: 0.3675 - acc: 0.84 
    - ETA: 33s - loss: 0.3650 - acc: 0.84 - ETA: 34s - loss: 0.3759 - acc: 0.83 
    - ETA: 34s - loss: 0.3933 - acc: 0.82 - ETA: 34s - loss: 0.3985 - acc: 0.82 
    - ETA: 34s - loss: 0.4057 - acc: 0.82 - ETA: 33s - loss: 0.4071 - acc: 0.81 
    ....

如您所见，ETA，损失，acc输出始终附加在日志中，而不是像进度条的工作原理一样替换第一行中的原始ETA/loss/acc值.

As you can see, the ETA, loss, acc outputs kept appending to the log, instead of replacing the original ETA/loss/acc values within the first line, just like how the progress bar works.

我该如何解决它，以使进度条，ETA，损失和损益只有1行； acc显示每个纪元?现在，随着训练的继续，我的细胞输出中有大量此类细胞.

How do I fix it it so that only 1 line of progress bar, ETA, loss & acc are shown per epoch? Right now, my cell output has tons of these lines as the training continues.

我正在Windows 10上运行Python 3.6.1，具有以下模块版本:

I'm running Python 3.6.1 on Windows 10, with the following module versions:

jupyter                            1.0.0
jupyter-client                     5.0.1
jupyter-console                    5.1.0
jupyter-core                       4.3.0
jupyterthemes                      0.19.0
Keras                              2.2.0
Keras-Applications                 1.0.2
Keras-Preprocessing                1.0.1
tensorflow-gpu                     1.7.0

谢谢.

推荐答案

您可以尝试Keras自适应的TQDM进度条库版本.

You can try the Keras-adapted version of the TQDM progress bar library.

• 原始 TQDM库: https://github.com/tqdm/tqdm
• TQDM的 Keras版本: https://github.com/bstriner /keras-tqdm

• The original TQDM library: https://github.com/tqdm/tqdm
• The Keras version of TQDM: https://github.com/bstriner/keras-tqdm

使用说明可以归结为:

1. 安装例如每个pip install keras-tqdm(稳定)或pip install git+https://github.com/bstriner/keras-tqdm.git(对于最新的dev版本)

1. install e.g. per pip install keras-tqdm (stable) or pip install git+https://github.com/bstriner/keras-tqdm.git (for latest dev-version)

使用from keras_tqdm import TQDMNotebookCallback

使用verbose=0或verbose=2设置运行Keras的fit或fit_generator，但具有对导入的TQDMNotebookCallback的回调，例如model.fit(X_train, Y_train, verbose=0, callbacks=[TQDMNotebookCallback()])

run Keras' fit or fit_generator with verbose=0 or verbose=2 settings, but with a callback to the imported TQDMNotebookCallback, e.g. model.fit(X_train, Y_train, verbose=0, callbacks=[TQDMNotebookCallback()])

结果:

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