NNLM | 简单实现NNLM | Machine Learning library

by FuYanzhe2 Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(5)Vulnerabilities Install Support

kandi X-RAY | NNLM Summary

NNLM is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Tensorflow applications. NNLM has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. However NNLM build file is not available. You can download it from GitHub.

Neural Network Language Model 论文《A Neural Probabilistic Language Model.2003》. requirement： - python3 - tensorflow 1.4.

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NNLM has a low active ecosystem.

It has 24 star(s) with 8 fork(s). There are 1 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 0 have been closed. On average issues are closed in 534 days. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of NNLM is current.

Quality

NNLM has 0 bugs and 0 code smells.

Security

NNLM has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

NNLM code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

NNLM is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

NNLM releases are not available. You will need to build from source code and install.

NNLM has no build file. You will be need to create the build yourself to build the component from source.

NNLM saves you 61 person hours of effort in developing the same functionality from scratch.

It has 160 lines of code, 9 functions and 3 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

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

Preprocess the input file
Builds the vocabulary
Get the next batch
Resets the batch pointer

Get all kandi verified functions for this library.

NNLM Key Features

No Key Features are available at this moment for NNLM.

NNLM Examples and Code Snippets

No Code Snippets are available at this moment for NNLM.

Community Discussions

Trending Discussions on NNLM

TensorFlow word embedding model + LDA Negative values in data passed to LatentDirichletAllocation.fit

Keras hub text layer, with a sequence of documents to LSTM

Why does this tf.keras model behave differently than expected on sliced inputs?

ValueError: Unknown layer: KerasLayer

Using Pandas/Numpy input data for tensorflow hub layer that accepts one dimensional input

QUESTION

TensorFlow word embedding model + LDA Negative values in data passed to LatentDirichletAllocation.fit

Asked 2022-Feb-24 at 09:31

I am trying to use a pre-trained model from TensorFlow hub instead of frequency vectorization techniques for word embedding before passing the resultant feature vector to the LDA model.

I followed the steps for the TensorFlow model, but I got this error upon passing the resultant feature vector to the LDA model:

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ANSWER

Answered 2022-Feb-24 at 09:31

As the fit function of LatentDirichletAllocation does not allow a negative array, I will recommend you to apply softplus on the embeddings.

Here is the code snippet:

Source https://stackoverflow.com/questions/71249109

QUESTION

Keras hub text layer, with a sequence of documents to LSTM

Asked 2021-Nov-03 at 10:59

I would like to use a sequence of documents to predict a target label:

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ANSWER

Answered 2021-Nov-03 at 10:59

You just need to make sure that you provide both your sentences and labels during training and that both your input and output shapes are correct. Here is a simple, working example where the input contains two sentences and a corresponding label:

Source https://stackoverflow.com/questions/69816154

QUESTION

Why does this tf.keras model behave differently than expected on sliced inputs?

Asked 2021-Feb-13 at 21:43

I'm coding a Keras model which, given (mini)-batches of tensors, applies the same layer to each of their elements. Just to give a little bit of context, I'm giving as input groups (of fixed size) of strings, which must be encoded one by one by an encoding layer. Thus, the input size comprising the (mini)-batch size is (None, n_sentences_per_sample, ), where n_sentences_per_sample is a fixed value known a prior.

To do so, I use this custom function when creating the model in the Functional API:

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ANSWER

Answered 2021-Feb-13 at 21:43

I finally came to the conclusion that the problem was into the line

Source https://stackoverflow.com/questions/66186921

QUESTION

ValueError: Unknown layer: KerasLayer

Asked 2020-May-23 at 16:15

I have the following code:

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ANSWER

Answered 2020-May-09 at 06:33

Mentioning the Answer in this (Answer) Section even though it is present in the Comments Section, for the benefit of the community.

Adding the import statement: import tensorflow_hub as hub and then using a custom layer with custom_objects={'KerasLayer': hub.KerasLayer} in the model_from_json() statement has resolved the error.

Complete working code is shown below:

Source https://stackoverflow.com/questions/61374496

QUESTION

Using Pandas/Numpy input data for tensorflow hub layer that accepts one dimensional input

Asked 2020-May-06 at 04:18

Good afternoon. I'm trying to re-use an NNLM layer from tensorflow hub to do transfer learning for an NLP task.

I'm trying to get this started using the IMDB dataset.

The issue I'm running into is that many tensorflow hub NNLM layers come with the following caveat: The module takes a batch of sentences in a 1-D tensor of strings as input. Most of the examples I see out there are using pre-loaded datasets, but the vast majority of the data I work with is either stored in pandas or Numpy, so I'm trying to get the input data to work from this format.

The layer I'm trying to use can be found here: https://tfhub.dev/google/Wiki-words-500/2

So far, I have tried the following without success.

Approach 1: Converting the pandas dataframe or numpy array into a tensorflow dataset object.

...

ANSWER

Answered 2020-May-06 at 04:18

Mentioning the Answer in this (Answer) section even though it is already present in the Comments Section, for the benefit of the Community.

Passing Raw Text Values instead of the Tokens (generated using Tokenizer) has resolved the issue.

Example code is shown below:

Source https://stackoverflow.com/questions/60857773

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

Vulnerabilities

No vulnerabilities reported

Install NNLM

You can download it from GitHub.
You can use NNLM 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.

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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