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- The following are 30 code examples for showing how to use keras.layers.Permute.These examples are extracted from open source projects. You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example.
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Permute 3.1.3
Video, audio and image files come in many different kinds and shapes, but sometimes you need a specific format since your iPad or DVD player won’t play that video. That is what Permute is for – easily convert your media files to various different formats.
Key Features
- Easy to Use – built from the ground up, Permute is a perfect example of what a Mac app should be. With a gorgeous interface and drag & drop simplicity no need for complicated options.
- Insanely Fast – Permute was engineered to be incredibly fast. Let us take care of the hard stuff. Just select the video format you want and it’ll be done faster than you can say “hardware acceleration” – MP4 and HEVC presets now take advantage of your machine’s hardware acceleration capabitlities, speeding up HEVC conversions more than 3 times over previous versions of Permute!
- PDF Support – Permute 3 now includes support for stitching multiple images into a single PDF.
- Everything Included – It doesn’t matter if you’re converting home movies or processing images. Permute can do it all. We support nearly every format and have plenty of device presets to choose from.
- Looks Amazing – Whether you use dark mode or not, Permute will look amazing. Taking advantage of the modern technologies, Permute will even change its icon in dark mode.
- Keep the Schedule – Video re-encoding is quite demanding on computer resources. This is why you can now schedule Permute to convert videos e.g. at night when you’re not using your computer.
- And so much more! – There are so many other great features in Permute – adjust volume of an audio file or an audio track in a video. Batch-resize, rotate and flip images and videos. And more!
This is a somewhat silly question but I can't seem to figure out how permute works in matlab. Take the documentation example: A = 1 2; 3 4; permute(A,2 1) ans = 1. = 6 Calculate the denominator (n - r)!: (n - r)! = 1 Calculate our permutation value n P r for n = 3 and r = 3: 3 P. An inversion of a permutation σ is a pair (i,j) of positions where the entries of a permutation are in the opposite order: i σj. So a descent is just an inversion at two adjacent positions. For example, the permutation σ = 23154 has three inversions: (1,3), (2,3), (4,5), for the pairs of entries (2,1), (3,1), (5,4). Sometimes an inversion is defined as the pair of values.
What’s New:
Permute 3.0?
New Features
New Features
Permute 2 1 3 0
- Completely Rewritten – Permute 3 was started from scratch – completely new project, everything written from the ground up again.
- UI Redesign – the UI has been redesigned from the ground up. It’s faster, more fluent and visually pleasing.
- Dark Mode – Permute now works 100% with the dark mode, even adjusting its Dock icon based on your macOS theme.
- Image Stitching – Stitch images together into a PDF.
- HEVC (H.265) Hardware Acceleration – HEVC (H.265) video encoding now supports hardware acceleration, resulting in conversions more than twice as fast.
- Scheduled Conversions – Schedule delayed conversion start.
- Groups – Put files into groups and set different settings for different groups.
- Customizations – Customize settings on a per-group basis without modifying the preset.
- Multiple Subtitles – Add or copy multiple subtitle tracks from the source file.
- … and many, many other minor fixes and improvements.
Screenshots
1 先看看官方中英文doc:
Permute 2 1 3/4
1.1 permute(dims)
将tensor的维度换位。
参数: - __dims__ (int .*) - 换位顺序
例:
1.2 permute(*dims) → Tensor
Permute the dimensions of this tensor.
Parameters: *dims (int..) – The desired ordering of dimensions
Example:
2 pytorch permute的使用
permute函数功能还是比较简单的,下面主要介绍几个细节点:
2.1 transpose与permute的异同
Tensor.permute(a,b,c,d, ..):permute函数可以对任意高维矩阵进行转置,但没有 torch.permute() 这个调用方式, 只能 Tensor.permute():
Chronicle bills & income 8 7 2. torch.transpose(Tensor, a,b):transpose只能操作2D矩阵的转置,有两种调用方式;
Permute(0 2 3 1)
另:连续使用transpose也可实现permute的效果:
从以上操作中可知,permute相当于可以同时操作于tensor的若干维度,transpose只能同时作用于tensor的两个维度;
2.2 permute函数与contiguous、view函数之关联
contiguous:view只能作用在contiguous的variable上,如果在view之前调用了transpose、permute等,就需要调用contiguous()来返回一个contiguous copy;
一种可能的解释是:有些tensor并不是占用一整块内存,而是由不同的数据块组成,而tensor的view()操作依赖于内存是整块的,这时只需要执行contiguous()这个函数,把tensor变成在内存中连续分布的形式;
判断ternsor是否为contiguous,可以调用torch.Tensor.is_contiguous()函数: Chief architect premier x10 20 1 1 1 download free.
另:在pytorch的最新版本0.4版本中,增加了torch.reshape(),与 numpy.reshape() 的功能类似,大致相当于 tensor.contiguous().view(),这样就省去了对tensor做view()变换前,调用contiguous()的麻烦;
3 permute与view函数功能demo
利用函数 permute(2,0,1) 可以把 Tensor([[[1,2,3],[4,5,6]]]) 转换成:
Permute 2 1 3 Sezon
如果使用view(1,3,2) 可以得到:
5 参考
Permute 2 1 3 =
发布于 2019-08-09