python-sequence | package contains tools to create , edit and run action

by vxgmichel Python Version: v0.1.1 License: GPL-3.0

X-Ray Key Features Code Snippets Community Discussions(4)Vulnerabilities Install Support

kandi X-RAY | python-sequence Summary

python-sequence is a Python library. python-sequence has no bugs, it has no vulnerabilities, it has build file available, it has a Strong Copyleft License and it has low support. You can download it from GitHub.

This package contains tools to create, edit and run action-based sequences.

Support

Quality

Security

License

Reuse

Support

python-sequence has a low active ecosystem.

It has 7 star(s) with 2 fork(s). There are 1 watchers for this library.

It had no major release in the last 12 months.

python-sequence has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of python-sequence is v0.1.1

Quality

python-sequence has 0 bugs and 0 code smells.

Security

python-sequence has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

python-sequence code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

python-sequence is licensed under the GPL-3.0 License. This license is Strong Copyleft.

Strong Copyleft licenses enforce sharing, and you can use them when creating open source projects.

Reuse

python-sequence releases are available to install and integrate.

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

kandi has reviewed python-sequence and discovered the below as its top functions. This is intended to give you an instant insight into python-sequence implemented functionality, and help decide if they suit your requirements.

Execute the pre run
Format a record
Returns whether the thread is set
Build all ui files
Checks param_type
Test the connection to the database
Test for the test method
Handle mouse release events
Set line
Connect this io block with another UI
Updates the rectangle
Mouse move event handler
Drop event handler
Updates the selected block
Mouse press event handler
Parse command line arguments
Run the execution loop
Load all threads
The main loop
Start the database
Import an import
Update current tab widget
Close event handler
Run the sequence
Event handler
Save changes to file

Get all kandi verified functions for this library.

python-sequence Key Features

No Key Features are available at this moment for python-sequence.

python-sequence Examples and Code Snippets

No Code Snippets are available at this moment for python-sequence.

Community Discussions

Trending Discussions on python-sequence

ValueError: Can't convert non-rectangular Python sequence to Tensor when using tf.data.Dataset.from_tensor_slices

Cannot convert a list of "strings" to a tf.Dataset.from_tensor_slicer() - ValueError: Can't convert non-rectangular Python sequence to Tensor

Generate subsequences with windows size and stride for mutlidimensional data

Fitting Keras Sequential Model gives ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray)

QUESTION

ValueError: Can't convert non-rectangular Python sequence to Tensor when using tf.data.Dataset.from_tensor_slices

Asked 2020-Sep-15 at 22:59

This issue has been posted a handful of times in SO, but I still can't figure out what is the problem with my code, especially because it comes from a tutorial in medium and the author makes the code available on google colab

I have seen other users having problem with wrong variable types #56304986 (which is not my case, as my model input is the output of tokenizer) and even seen the function I am trying to use (tf.data.Dataset.from_tensor_slices) being suggested as a solution #56304986.

The line yielding error is:

...

ANSWER

Answered 2020-Sep-15 at 22:59

Turns out that I had caused the trouble by having commented the line

Source https://stackoverflow.com/questions/63907100

QUESTION

Cannot convert a list of "strings" to a tf.Dataset.from_tensor_slicer() - ValueError: Can't convert non-rectangular Python sequence to Tensor

Asked 2020-Jul-21 at 14:00

I have the following data:

...

ANSWER

Answered 2020-Jul-21 at 12:53

You will need to turn these strings into vectors, and pad them to equal length. I'll show you an example with just partial_x_train_actors_array:

Source https://stackoverflow.com/questions/63014556

QUESTION

Generate subsequences with windows size and stride for mutlidimensional data

Asked 2020-Jul-08 at 09:30

I have a list of n-dimensional sequences of varying length, but fixed n.
e.g. n=3
1. [ [1, 2, 3], [4, 5, 6], [4, 4, 4] ]
2. [ [4, 6, 7], [6, 4, 3] ]
3. [ [7, 9, 1], [6, 2, 0], [0, 7, 3], [3, 3, 8] ]

I want to create lists of all subsequences of window size w from these. E.g. for w = 2,
List 1: [ [1, 2, 3], [4, 5, 6] ]
List 2: [ [4, 5, 6] , [ 4, 4, 4] ]
List 3: [ [4, 6, 7], [6, 4, 3] ]
List 4: [ [7, 9, 1], [6, 2, 0] ] and so on...

I want a fast implementation of this in Python. I tried to implement the solution here: Split Python sequence (time series/array) into subsequences with overlap, but I am not sure how the strides are calculated for n-dimensional data points and I am getting weird results.

What is the best way to get such subsequences for variable window sizes?

...

ANSWER

Answered 2020-Jul-08 at 09:30

This is not necessarily a fast implementation, but this is a provisional implementation of what I think you want, taking your example question:

Source https://stackoverflow.com/questions/62781541

QUESTION

Fitting Keras Sequential Model gives ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray)

Asked 2020-Jul-05 at 18:52

I have the following array of lists (actors per movie):

...

ANSWER

Answered 2020-Jul-05 at 18:52

You are receiving this error as you are trying to convert the numpy.ndarry to Tensor. In short, your arrays are of different length and that is not accepted while converting it to Tensor.

What you have to do is make your x's of the same length and the y's of the same length.

There are several ways to achieve this. Based on the code you provided you can use something like below: The below code is pseudo-code and it just to demonstrate that you need arrays of equal length.

Source https://stackoverflow.com/questions/62729593

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install python-sequence

You can download it from GitHub.
You can use python-sequence 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.