📅  最后修改于: 2023-12-03 15:35:16.820000             🧑  作者: Mango
TensorFlow是由Google开发的一款机器学习框架。它提供了Python, C++, Java等语言的API,以及支持分布式计算的工具和库。TensorFlow Shell-Bash是一个基于Bash Shell的小工具,可以让开发者在终端中直接调用TensorFlow的Python API,方便快捷。
在Linux/Unix系统中,使用以下命令进行安装:
$ pip install tensorflow-shell
在命令行终端中输入tensorflow-shell
并按回车键启动,即可进入TensorFlow Shell-Bash环境。在该环境中,可以直接使用Python API进行模型的训练、性能测试等操作。例如:
$ tensorflow-shell
TensorFlow Shell-Bash v1.15.0
tensorflow-shell$ python
Python 3.6.9 (default, Oct 8 2020, 12:12:24)
[GCC 8.4.0] on linux
Type "help", "copyright", "credits" or "license" for more information.
>>> import tensorflow as tf
>>> x = tf.constant([1, 2, 3, 4])
>>> y = tf.square(x)
>>> with tf.Session() as sess:
... print(sess.run(y))
...
[ 1 4 9 16]
除了直接使用Python API,还可以使用一些命令来快速创建、加载、保存模型。例如:
$ tensorflow-shell
tensorflow-shell$ help
create <model_name> <tensorboard_dir> - 创建一个空白的模型并启动TensorBoard
load <model_path> - 加载一个已保存的模型
save <model_path> - 保存当前模型
summary - 查看当前模型的结构和参数
train <batch_size> <epochs> - 训练模型
test - 对模型进行性能测试
predict <input_tensor> - 对模型进行推理
quit - 退出TensorFlow Shell-Bash
tensorflow-shell$ create my_model logs
Creating model...
Model created successfully.
tensorflow-shell$ summary
Model: "sequential"
_________________________________________________________________
Layer (type) Output Shape Param #
=================================================================
dense (Dense) (None, 1) 2
=================================================================
Total params: 2
Trainable params: 2
Non-trainable params: 0
_________________________________________________________________
tensorflow-shell$ train 10 100
Epoch 1/100
10/10 [==============================] - 0s 14ms/sample - loss: 2.1029
Epoch 2/100
10/10 [==============================] - 0s 373us/sample - loss: 1.7651
...
Epoch 99/100
10/10 [==============================] - 0s 153us/sample - loss: 0.0359
Epoch 100/100
10/10 [==============================] - 0s 166us/sample - loss: 0.0355
tensorflow-shell$ save ./my_model
Model saved successfully.
tensorflow-shell$ quit
train
命令时,需要保证在进入TensorFlow Shell-Bash环境前已安装好所需的训练数据和标签数据。predict
命令时,需要保证在进入TensorFlow Shell-Bash环境前已安装好所需的待预测数据。create
命令时,需要提供新模型的名称和TensorBoard日志输出目录。load
命令时,需要提供已保存模型的路径。save
命令时,需要提供保存模型的路径。