InferenceHelper | Helper Class for Deep Learning Inference Frameworks | Machine Learning library

 by   iwatake2222 C++ Version: 20210816 License: Apache-2.0

kandi X-RAY | InferenceHelper Summary

kandi X-RAY | InferenceHelper Summary

InferenceHelper is a C++ library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch, Tensorflow applications. InferenceHelper has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

TensorFlow Lite + XNNPACK. TensorFlow Lite + EdgeTPU. TensorFlow Lite + GPU. TensorFlow Lite + NNAPI.
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              InferenceHelper has a low active ecosystem.
              It has 102 star(s) with 22 fork(s). There are 9 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 2 open issues and 19 have been closed. On average issues are closed in 78 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of InferenceHelper is 20210816

            kandi-Quality Quality

              InferenceHelper has 0 bugs and 0 code smells.

            kandi-Security Security

              InferenceHelper has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              InferenceHelper code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              InferenceHelper is licensed under the Apache-2.0 License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              InferenceHelper releases are available to install and integrate.
              Installation instructions, examples and code snippets are available.
              It has 36 lines of code, 0 functions and 1 files.
              It has low code complexity. Code complexity directly impacts maintainability of the code.

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            InferenceHelper Key Features

            No Key Features are available at this moment for InferenceHelper.

            InferenceHelper Examples and Code Snippets

            No Code Snippets are available at this moment for InferenceHelper.

            Community Discussions

            QUESTION

            Tensorflow RNN: how to infer a sequence without duplicates?
            Asked 2018-Feb-05 at 10:55

            I'm working on a seq2seq RNN generating an output sequence of labels given a seed label. During the inference step I'd like to generate sequences containing only unique labels (i.e. skip labels that have already been added to the output sequence). To do this I created a sampler object that tries to remember the labels that have been added to the output and reduce their logit value to -np.inf.

            Here is the sampler code:

            ...

            ANSWER

            Answered 2018-Feb-05 at 10:55

            So, after some investigation I found answers to all my questions related to this thread. The main question was: why self.ids_mask in InferenceSampler does not update? The reason is in the internals of dynamic_decode. According to this answer in Tensorflow's issue tracker:

            ... only tensors defined inside the loop will be evaluated every loop iteration. All tensors defined outside a loop will be evaluated exactly once.

            In my case, self.ids_mask is specified outside the loop. That means that I need to re-write dynamic_decode to get what I want. The code below is a bit modified version of the initial task, but it does almost the same.

            Let's start with a new dynamic_decode which should create and update the mask collecting sample_ids that have been already predicted. I removed the code which i didn't modify, follow the initial_mask and mask variables.

            New dynamic_decode:

            Source https://stackoverflow.com/questions/47795391

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

            Vulnerabilities

            No vulnerabilities reported

            Install InferenceHelper

            Add this repository into your project (Using git submodule is recommended)
            Download prebuilt libraries sh third_party/download_prebuilt_libraries.sh

            Support

            TensorFlow LiteTensorFlow Lite with delegate (XNNPACK, GPU, EdgeTPU, NNAPI)TensorRT (GPU, DLA)OpenCV(dnn)OpenCV(dnn) with GPUOpenVINO with OpenCV (xml+bin)ncnnncnn with VulkanMNN (with Vulkan)SNPE (Snapdragon Neural Processing Engine SDK (Qualcomm Neural Processing SDK for AI v1.51.0))Arm NNNNablaNNabla with CUDA
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            CLONE
          • HTTPS

            https://github.com/iwatake2222/InferenceHelper.git

          • CLI

            gh repo clone iwatake2222/InferenceHelper

          • sshUrl

            git@github.com:iwatake2222/InferenceHelper.git

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