poeticHadoop的博客

教程本节包含演示如何在 TensorFlow 中执行特定任务的教程。如果您是 TensorFlow 的新手，那么在阅读这些教程之前，我们建议阅读“入门”一节中的文档。[1]以下教程解释了 TensorFlow 系统上CPU和GPU的交互：(1)使用GPU[2]以下教程介绍了图像识别的不同方面：(1)图像识别，它引入了图像识别领域和一个用于识别图像的模型（Incept

tensorflow/python/ops/math_ops.py.就是求平方的函数库

定义的文件路径：tensorflow/python/ops/array_ops.py.举个例子：tf.zeros([3, 4], tf.int32)  # [[0, 0, 0, 0], [0, 0, 0, 0], [0, 0, 0, 0]]可以看出，创建一个数组并初始化它们都为0Args:shape: A list of integers, a tuple of integ

tensorflow/tensorflow/python/ops的 random_ops.py 文件有定义# pylint: disable=protected-accessdef random_normal(shape, mean=0.0, stddev=1.0, dtype=dty

jhczz@vaio:~$ suPassword: root@vaio:/home/jhczz# apt-get install python3-tkReading package lists... DoneBuilding dependency tree       Reading state information... DoneThe following packag

import numpy as npx_data = np.random.rand(100).astype(np.float32)print(x_data)运行效果如下：

import tensorflow as tfimport numpy as npx_data = np.random.rand(100).astype(np.float32)y_data = x_data*0.1 + 0.3#print(x_data)#print(y_data)Weights = tf.Variable(tf.random_uniform([1], -1.0, 1.

import numpy as npx_data = np.random.rand(100).astype(np.float32)y_data = x_data*0.1 + 0.3print(x_data)print(y_data)

C:\Users\Administrator>pip install tensorflowCollecting tensorflow  Downloading tensorflow-1.4.0-cp36-cp36m-win_amd64.whl (28.3MB)    100% |████████████████████████████████| 28.3MB 72kB/sColle

root@xxx:/home/czz# pip3 install --upgrade pipCollecting pip  Using cached pip-9.0.1-py2.py3-none-any.whlInstalling collected packages: pip  Found existing installation: pip 8.1.1    Not uni

[08:40:08]root@xxx:/home/czz# pip3 install tensorflow[08:40:15]Collecting tensorflow[08:40:16]  Downloading tensorflow-1.4.1-cp35-cp35m-manylinux1_x86_64.whl (40.7MB)[08:42:15]    100% |||||||||

import tensorflow as tfimport numpy as npx_data = np.random.rand(100).astype(np.float32)y_data = x_data*0.1 + 0.3#print(x_data)#print(y_data)Weights = tf.Variable(tf.random_uniform([1], -1.0,

WARNING:tensorflow:From /usr/local/lib/python3.5/dist-packages/tensorflow/python/util/tf_should_use.py:107: initialize_all_variables (from tensorflow.python.ops.variables) is deprecated and will be re