NGS-Tutorial | NGS Tutorial | Genomics library

 by   Imamachi-n HTML Version: v1.1 License: MIT

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kandi X-RAY | NGS-Tutorial Summary

kandi X-RAY | NGS-Tutorial Summary

NGS-Tutorial is a HTML library typically used in Artificial Intelligence, Genomics applications. NGS-Tutorial has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

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              NGS-Tutorial has a low active ecosystem.
              It has 10 star(s) with 4 fork(s). There are 3 watchers for this library.
              OutlinedDot
              It had no major release in the last 12 months.
              There are 1 open issues and 0 have been closed. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of NGS-Tutorial is v1.1

            kandi-Quality Quality

              NGS-Tutorial has no bugs reported.

            kandi-Security Security

              NGS-Tutorial has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

            kandi-License License

              NGS-Tutorial is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

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              NGS-Tutorial releases are available to install and integrate.

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            NGS-Tutorial Key Features

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            NGS-Tutorial Examples and Code Snippets

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            Community Discussions

            Trending Discussions on NGS-Tutorial

            Gforth - How to get codepoints of a string?
            How to get intermediate layers' output of pre-trained BERT model in HuggingFace Transformers library?

            QUESTION

            Gforth - How to get codepoints of a string?
            Asked 2020-Nov-06 at 08:29

            I know that gforth stores characters as their codepoints in the stack, but the material I'm learning from doesn't show any word that helps to convert each character to codepoint.

            I also want to sum the codepoints of the string. What should I use to do that?

            ...

            ANSWER

            Answered 2020-Nov-06 at 08:29

            Characters and code points are not distinguishable in Forth. I.e., there is no way to get a character that is not a code point.

            In Forth you can distinguish primitive characters (ASCII) and extended characters (Unicode).

            See also Extended-Character word set:

            Extended characters are stored in memory encoded as one or more primitive characters (pchars).

            To read a primitive character (ASCII or pchar, usually an octet), we use c@ ( c-addr -- char )

            Source https://stackoverflow.com/questions/64691168

            QUESTION

            How to get intermediate layers' output of pre-trained BERT model in HuggingFace Transformers library?
            Asked 2020-Apr-29 at 00:19

            (I'm following this pytorch tutorial about BERT word embeddings, and in the tutorial the author is access the intermediate layers of the BERT model.)

            What I want is to access the last, lets say, 4 last layers of a single input token of the BERT model in TensorFlow2 using HuggingFace's Transformers library. Because each layer outputs a vector of length 768, so the last 4 layers will have a shape of 4*768=3072 (for each token).

            How can I implement this in TF/keras/TF2, to get the intermediate layers of pretrained model for an input token? (later I will try to get the tokens for each token in a sentence, but for now one token is enough).

            I'm using the HuggingFace's BERT model:

            ...

            ANSWER

            Answered 2020-Apr-29 at 00:12

            The third element of the BERT model's output is a tuple which consists of output of embedding layer as well as the intermediate layers hidden states. From documentation:

            hidden_states (tuple(tf.Tensor), optional, returned when config.output_hidden_states=True): tuple of tf.Tensor (one for the output of the embeddings + one for the output of each layer) of shape (batch_size, sequence_length, hidden_size).

            Hidden-states of the model at the output of each layer plus the initial embedding outputs.

            For the bert-base-uncased model, the config.output_hidden_states is by default True. Therefore, to access hidden states of the 12 intermediate layers, you can do the following:

            Source https://stackoverflow.com/questions/61465103

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

            Vulnerabilities

            No vulnerabilities reported

            Install NGS-Tutorial

            You can download it from GitHub.

            Support

            For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .
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