tensorflow flags

This article mainly introduces the method that TensorFlow uses the flags to define the command line parameters, and now share to everyone, also to make a reference. Come and see it together. TF defines tf.app.flags, which is used to support accepting command-line pass parameters, equivalent to accepting argv. Import TensorFlow as tf# the first is the paramet

TF defines tf.app.flags, which is used to support accepting command-line pass parameters, which is equivalent to accepting argv. Import TensorFlow as TF #第一个是参数名称, the second parameter is the default value, and the third is the parameter description tf.app.flags.DEFINE_string (' str_name ', ' def_v_1 ', " Descrip1 ") Tf.app.flags.DEFINE_integer (' Int_name ', ten," Descript2 ") Tf.app.flags.DEFINE_boolean (' Bool_ Name ', False, ' DESCRIPT3 ')

Import TensorFlow as TF #第一个是参数名称, the second parameter is the default value, and the third is the parameter description tf.app.flags.DEFINE_string (' str_name ', ' def_v_1 ', " Descrip1 ") Tf.app.flags.DEFINE_integer (' Int_name ', ten," Descript2 ") Tf.app.flags.DEFINE_boolean (' Bool_ Name ', False, ' DESCRIPT3 ') FLAGS = Tf.app.flags.FLAGS #必须带参数, otherwise: ' Typeerror:main () takes no arguments (1

The usage of the enumeration type flag [Flags] feature and the method for adding enumeration types, flags Enumeration Suppose there is a code segment like this. You need to determine which weapons the role is equipped with, and then perform other operations based on this attribute of the role. In this case, we can use enumeration to mark the weapons that a role can equip. Public enum Equipment {Knife, gun,

shown below. Import TensorFlow as TF # Flags for defining the Tf.train.ClusterSpec tf.app.flags.DEFINE_string ("Ps_hosts", "", "Comma-separated List of Hostname:port pairs") tf.app.flags.DEFINE_string ("Worker_hosts", "", "Comma-separated List of Hostname:port pairs") # Flags for defining the Tf.train.Server Tf.app.flags.DE Fine_string

SOURCE Url:https://stackoverflow.com/questions/43437590/why-is-flags-necessary Usually FLAGS are used to pass command line arguments into your program. e.g. Import TensorFlow as tf fs = Tf.app.flags fs. Define_integer (' N_epochs ', +, ' number of epochs to train [] ') FLAGS = fs.

them for the parallel computing gradient. Then, the calculation results are merged. This method requires the In-graph replication method (for example, In the CIFAR-10 multi-GPU trainer we use this method to calculate the average of the gradient) copy Between the graph (Between-graph replication) (for example,tf.train.SyncReplicasOptimizer. Examples of distributed training programs The following code is a general code framework of a distributed training program, which implements two methods: Cop

problem. Softmax regression solves two or more categories. Logistic regression models are widely used in classification. Tensorflow-1.1.0/tensorflow/examples/tutorials/mnist/mnist_softmax.py. Load data. Import the input_data.py file and tensorflow. contrib. learn. read_data_sets to load data. FLAGS. data_dir MNIST pat

_writer.add_run_metadata (Run_metadata, ' step%d '% i) train_writer.add_summary (summary, i) print (' Adding run metadata For ', i) Else: # Record A summary summary, _ = Sess.run ([merged, Train_step], feed_dict=feed_dict (True)) Train_writer.add_summary (Summary, i) def main (_): If Tf.gfile.Exists (flags.summaries_dir): tf.gfile.DeleteRe Cursively (Flags.summaries_dir) tf.gfile.MakeDirs (Flags.summaries_dir) train () if __name__ = = ' __main__ ': tf.app.ru N () which

Development environment: Mac OS 10.12.5Python 2.7.10GCC 4.2.1Mac default is no pip, install PIP.sudo easy_install pip1. Installing virtualenvsudo pip install virtualenv--upgradeCreate a working directory:sudo virtualenv--system-site-packages ~/tensorflowMake the directory, activate the sandboxCD ~/tensorflowSOURCE Bin/activateInstall TensorFlow in 2.virtualenvAfter entering the sandbox, execute the following command to install

1. Download and install Anaconda1.1 downloadDownload the Linux version from Anaconda official website (https://www.continuum.io/downloads)https://repo.continuum.io/archive/(Recommended python3.5)1.2 InstallationCD ~/downloadssudo bash anaconda2-5.0.1-linux-x86_64.sh (download the corresponding version of Python2.7 here)Ask if you want to add the Anaconda bin to the user's environment variable and select yes!Installation is complete.2. Install tensorflow2.1 set up

A non-empty zero-indexed array a consisting of n integers is given.A?Peak? Is an array element which is larger than its neighbors. More precisely, it is an index p Such that 0 For example, the following array: ? A[0] = 1 A[1] = 5 A[2] = 3 A[3] = 4 A[4] = 3 A[5] = 4 A[6] = 1 A[7] = 2 A[8] = 3 A[9] = 4 A[10] = 6 A[11] = 2 Has exactly four peaks: elements 1, 3, 5 and 10. You are going on a trip to a range of mountains whose relative heights are represented by array A, as shown in a figure below.

Label:What is a trace flag? For DBAs, mastering trace flag is one of the prerequisites for becoming a SQL Server whiz, and in most cases, trace flag is just a pifo of a sword walk, not necessary, but in many cases, using these tags will give you better control over SQL The behavior of the server. Here is the official tag for trace flag: A trace flag is a token that enables or disables certain behavior of SQL Server. It is not difficult to see from the above definition that Trace flag is a way

Through a few routines, we gradually established a perceptual knowledge of tensorflow. This article will further from the internal principle of deep understanding, and then for reading source to lay a good foundation.1. Graph (graph)The TensorFlow calculation is abstracted as a forward graph that includes several nodes. As shown in the example:The corresponding TensorFl