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Explore all Tensorflow open source software, libraries, packages, source code, cloud functions and APIs.

Popular New Releases in Tensorflow

tensorflow

TensorFlow 2.9.0-rc1

models

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transformers

v4.18.0: Checkpoint sharding, vision models

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Faceswap Windows and Linux Installers v2.0.0

tensorflow

TensorFlow 2.9.0-rc1

models

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transformers

v4.18.0: Checkpoint sharding, vision models

keras

Keras Release 2.9.0 RC2

faceswap

Faceswap Windows and Linux Installers v2.0.0

Popular Libraries in Tensorflow

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star image 164372 Apache-2.0

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star image 73392 NOASSERTION

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by huggingface python

star image 61400 Apache-2.0

🤗 Transformers: State-of-the-art Machine Learning for Pytorch, TensorFlow, and JAX.

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star image 55007 Apache-2.0

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star image 28940 Apache-2.0

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tensorflow

by tensorflow c++

star image 164372 Apache-2.0

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by tensorflow python

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by huggingface python

star image 61400 Apache-2.0

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keras

by keras-team python

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star image 41052 NOASSERTION

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by BVLC c++

star image 31723 NOASSERTION

Caffe: a fast open framework for deep learning.

Deep-Learning-Papers-Reading-Roadmap

by floodsung python

star image 30347

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bert

by google-research python

star image 28940 Apache-2.0

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Trending New libraries in Tensorflow

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by ultralytics python

star image 25236 GPL-3.0

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite

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by lyhue1991 python

star image 8872 Apache-2.0

Tensorflow2.0 🍎🍊 is delicious, just eat it! 😋😋

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by facebookresearch python

star image 7464 Apache-2.0

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by openai jupyter notebook

star image 7185 MIT

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by microsoft python

star image 6633 MIT

DeepSpeed is a deep learning optimization library that makes distributed training and inference easy, efficient, and effective.

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by EleutherAI python

star image 6100 MIT

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

PaddleGAN

by PaddlePaddle python

star image 5212 Apache-2.0

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.

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by jasonmayes javascript

star image 4798 Apache-2.0

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by MegEngine c++

star image 4177 NOASSERTION

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yolov5

by ultralytics python

star image 25236 GPL-3.0

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by lyhue1991 python

star image 8872 Apache-2.0

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detr

by facebookresearch python

star image 7464 Apache-2.0

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by openai jupyter notebook

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by microsoft python

star image 6633 MIT

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gpt-neo

by EleutherAI python

star image 6100 MIT

An implementation of model parallel GPT-2 and GPT-3-style models using the mesh-tensorflow library.

PaddleGAN

by PaddlePaddle python

star image 5212 Apache-2.0

PaddlePaddle GAN library, including lots of interesting applications like First-Order motion transfer, Wav2Lip, picture repair, image editing, photo2cartoon, image style transfer, GPEN, and so on.

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by jasonmayes javascript

star image 4798 Apache-2.0

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by MegEngine c++

star image 4177 NOASSERTION

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1

204 Libraries

13498

2

95 Libraries

86990

3

87 Libraries

3964

4

75 Libraries

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5

70 Libraries

70986

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69 Libraries

384312

7

69 Libraries

42215

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55 Libraries

10064

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50 Libraries

14754

10

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Trending Kits in Tensorflow

No Trending Kits are available at this moment for Tensorflow

Trending Discussions on Tensorflow

    What is XlaBuilder for?
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QUESTION

What is XlaBuilder for?

Asked 2022-Mar-20 at 18:41

What's the XLA class XlaBuilder for? The docs describe its interface but don't provide a motivation.

The presentation in the docs, and indeed the comment above XlaBuilder in the source code

1// A convenient interface for building up computations.
2

suggests it's no more than a utility. However, this doesn't appear to explain its behaviour in other places. For example, we can construct an XlaOp with an XlaBuilder via e.g.

1// A convenient interface for building up computations.
2XlaOp ConstantLiteral(XlaBuilder* builder, const LiteralSlice& literal);
3

Here, it's not clear to me what role builder plays (note functions for constructing XlaOps aren't documented on the published docs). Further, when I add two XlaOps (with + or Add) it appears the ops must be constructed with the same builder, else I see

1// A convenient interface for building up computations.
2XlaOp ConstantLiteral(XlaBuilder* builder, const LiteralSlice& literal);
3F tensorflow/core/platform/statusor.cc:33] Attempting to fetch value instead of handling error Invalid argument: No XlaOp with handle -1
4

Indeed, XlaOp retains a handle for an XlaBuilder. This suggests to me that the XlaBuilder has a more fundamental significance.

Beyond the title question, is there a use case for using multiple XlaBuilders, or would you typically use one global instance for everything?

ANSWER

Answered 2021-Dec-15 at 01:32

XlaBuilder is the C++ API for building up XLA computations -- conceptually this is like building up a function, full of various operations, that you could execute over and over again on different input data.

Some background, XLA serves as an abstraction layer for creating executable blobs that run on various target accelerators (CPU, GPU, TPU, IPU, ...), conceptually kind of an "accelerator virtual machine" with conceptual similarities to earlier systems like PeakStream or the line of work that led to ArBB.

The XlaBuilder is a way to enqueue operations into a "computation" (similar to a function) that you want to run against the various set of accelerators that XLA can target. The operations at this level are often referred to as "High Level Operations" (HLOs).

The returned XlaOp represents the result of the operation you've just enqueued. (Aside/nerdery: this is a classic technique used in "builder" APIs that represent the program in "Static Single Assignment" form under the hood, the operation itself and the result of the operation can be unified as one concept!)

XLA computations are very similar to functions, so you can think of what you're doing with an XlaBuilder like building up a function. (Aside: they're called "computations" because they do a little bit more than a straightforward function -- conceptually they are coroutines that can talk to an external "host" world and also talk to each other via networking facilities.)

So the fact XlaOps can't be used across XlaBuilders may make more sense with that context -- in the same way that when building up a function you can't grab intermediate results in the internals of other functions, you have to compose them with function calls / parameters. In XlaBuilder you can Call another built computation, which is a reason you might use multiple builders.

As you note, you can choose to inline everything into one "mega builder", but often programs are structured as functions that get composed together, and ultimately get called from a few different "entry points". XLA currently aggressively specializes for the entry points it sees API users using, but this is a design artifact similar to inlining decisions, XLA can conceptually reuse computations built up / invoked from multiple callers if it thought that was the right thing to do. Usually it's most natural to enqueue things into XLA however is convenient for your description from the "outside world", and allow XLA to inline and aggressively specialize the "entry point" computations you've built up as you execute them, in Just-in-Time compilation fashion.

Source https://stackoverflow.com/questions/70339753