spinup | spinup is a virtual machine manager
kandi X-RAY | spinup Summary
kandi X-RAY | spinup Summary
spinup is a virtual machine manager based on libvirt.
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Top functions reviewed by kandi - BETA
- Create a VM
- Returns a list of ip addresses for a machine
- Create a disk image
- Run a shell command
- Return default username for a machine
- Create a cloud config drive
- Create a new virtual machine
- Generate a random MAC address
- Split a list
- Create a new machine
- SSH VM
- Get the current cluster and machine
- Process a network descriptor
- Returns the network associated with the given IP
- Fetch the image
- Show status of a VM
- Shut down the virtual machine
- Start a virtual machine in the current directory
- Process command line arguments
- Destroy a virtual machine
spinup Key Features
spinup Examples and Code Snippets
Community Discussions
Trending Discussions on spinup
QUESTION
I have a worksheet form spinner that needs to increment a cell value from 1 to 100. The SpinUp and SpinDown event procedures are housed in the Sheet1 VBA object, but I can only select one in the Assign Macro menu. This means the spinner can only increment up or down, irrespective of where I click.
How do I combine the two so the spinner works correctly?
Please don't suggest using an ActiveX spinner. I have done this successfully, but it has compatibility issues with Mac Excel versions so want to avoid it.
My spinner is called Spinner1 and the code in Sheet1 is:
ANSWER
Answered 2022-Apr-04 at 14:50Private lngPrevVal As Long
Sub Spinner1_Change()
Dim s As Spinner
Set s = Sheets("sheet1").Shapes("Spinner 1").OLEFormat.Object
If s.Value > lngPrevVal Then
Sheets("sheet1").Range("a1").Value = "Up"
Else
Sheets("sheet1").Range("a1").Value = "Down"
End If
lngPrevVal = s.Value
End Sub
QUESTION
I am following the OpenAI's spinningUp tutorial and I stucked in the installation part of the project. I am using Anaconda as said and when I do:
...ANSWER
Answered 2020-May-19 at 14:50torch==1.3 on pypi only has files for linux and macOS, see here.
You will need to install it seperately using the index from the torch website:
QUESTION
I have been going through the implementation of neural network in openAI code for any Vanilla Policy Gradient (As a matter of fact, this part is used nearly everywhere). The code looks something like this :
...ANSWER
Answered 2020-Apr-13 at 08:59Note that this is a discrete action space - there are action_space.n different possible actions at every step, and the agent chooses one.
To do this the MLP is returning the logits (which are a function of the probabilities) of the different actions. This is specified in the code by + [act_dim] which is appending count of the action_space as the final MLP layer. Note that the last layer of an MLP is the output layer. The input layer is not specified in tensorflow, it is inferred from the inputs.
tf.random.categorical takes the logits and samples a policy action pi from them, which is returned as a number.
mlp_categorical_policy also returns logp, the log probability of the action a (used to assign credit), and logp_pi, the log probability of the policy action pi.
It seems your question is more about the return from the mlp.
The mlp creates a series of fully connected layers in a loop. In each iteration of the loop, the mlp is creating a new layer using the previous layer x as an input and assigning it's output to overwrite x, with this line x = tf.layers.dense(inputs=x, units=h, activation=activation).
So the output is not the same as the input, on each iteration x is overwritten with the value of the new layer. This is the same kind of coding trick as x = x + 1, which increments x by 1. This effectively chains the layers together.
The output of tf.layers.dense is a tensor of size [:,h] where : is the batch dimension (and can usually be ignored). The creation of the last layer happens outisde the loop, it can be seen that the number of nodes in this layer is act_dim (so shape is [:,3]). You can check the shape by doing this:
QUESTION
I am trying to set up a CA and I need a root certificate for this CA. This root certificate has to be signed by a public CA and the signing algorithm has to be ECDSA with prime256v1 curve.
I am following this issue on LetsEncryp forum. However, I am using a separate utility for generating the keys and CSR. This utility helps me generate ECDSA keys and CSR successfully. Following is the CSR that's generated:
...ANSWER
Answered 2020-Jan-03 at 17:01LetsEncrypt does not issue anything except Domain Validated certificates. No code signing certificates, no root CA certificates, nothing else.
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Install spinup
You can use spinup like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.
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