deepar | Tensorflow implementation of Amazon DeepAR | AWS library

by arrigonialberto86 Python Version: Current License: MIT

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | deepar Summary

deepar is a Python library typically used in Cloud, AWS, Tensorflow, Amazon S3 applications. deepar has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can download it from GitHub.

Tensorflow implementation of Amazon DeepAR.

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Quality

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Support

deepar has a low active ecosystem.

It has 196 star(s) with 66 fork(s). There are 11 watchers for this library.

It had no major release in the last 6 months.

There are 6 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of deepar is current.

Quality

deepar has 0 bugs and 0 code smells.

Security

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

deepar code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

deepar 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

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

Build file is available. You can build the component from source.

Installation instructions are not available. Examples and code snippets are available.

deepar saves you 127 person hours of effort in developing the same functionality from scratch.

It has 456 lines of code, 43 functions and 11 files.

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

Top functions reviewed by kandi - BETA

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

Instantiate and fit the model
Fit the Keras model
Generate timestamps from a ts_obj
Build the keras model
Generate test data
Return a time series
Calculate the predicted sample prediction
Predict theta from input_list
Return a list of time series with t_min

Get all kandi verified functions for this library.

deepar Key Features

No Key Features are available at this moment for deepar.

deepar Examples and Code Snippets

No Code Snippets are available at this moment for deepar.

Community Discussions

Trending Discussions on deepar

ModuleNotFoundError: No module named 'mxnet'

how to use ARIMA model in AWS sagemaker?

Pandas groupby get value of a column where another column is minimum

Sagemaker Endpoint BrokenPipeError at DeepAR Prediction

java.lang.UnsatisfiedLinkError: No implementation found (When Implement a SDK)

How to load a GluonTS DeepAR model

GluonTS DeepAR prediction non deterministic

Impossible import a module due to a dependency in Python

Tracking SageMaker Estimator with MLFlow

How in GluonTS transformation function is automatically called from DeepARE class , even though i have not used object to call it?

QUESTION

ModuleNotFoundError: No module named 'mxnet'

Asked 2021-Nov-06 at 19:16

I have been looking for the solution for this error for a whole morning. I created an separate environment for python 3.6 and I still got this error. I am using anacondas. So i am so frustrated.

ModuleNotFoundError: No module named 'mxnet'

...

ANSWER

Answered 2021-Nov-06 at 19:10

use pip install mxnet. don't use conda install mxnet. if there is an error about permission, then use pip install mxnet --user. It worked for me.

Source https://stackoverflow.com/questions/69866838

QUESTION

how to use ARIMA model in AWS sagemaker?

Asked 2021-Sep-22 at 14:45

I have created an ARIMA model for time-series forecasting and want to deploy it so as to use it at the API endpoint. But I am unable to find a way to deploy it on AWS SageMaker, how can I deploy it. I don't want to use DeepAR. Or is there any way to deploy the pickle file on SageMaker?

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ANSWER

Answered 2021-Sep-22 at 14:45

You can use Amazon Forecast, which has ARIMA built in

Or, if you prefer SageMaker, you need to build your own Docker container, publish it to ECR, and then use that

https://sagemaker-examples.readthedocs.io/en/latest/advanced_functionality/scikit_bring_your_own/scikit_bring_your_own.html#The-example

Source https://stackoverflow.com/questions/69254978

QUESTION

Pandas groupby get value of a column where another column is minimum

Asked 2021-Jun-28 at 18:21

I have a dataframe df like this:

region model metrics Tokyo ARIMA 0.1 Tokyo FeedForward 0.2 Tokyo DeepAR 0.3 Osaka ARIMA 0.5 Osaka FeedForward 0.2 Osaka DeepAR 0.1

I want to group this by region and return the minimum value of metrics in each group, as well as the model value where the metrics is minimum.

The expected result:

...

ANSWER

Answered 2021-Jun-28 at 18:12

How about sort by value of metrics and drop duplicates remaining the smallest one like this.

Source https://stackoverflow.com/questions/68168208

QUESTION

Sagemaker Endpoint BrokenPipeError at DeepAR Prediction

Asked 2021-Mar-19 at 14:47

I've created an SageMaker Endpoint from a trained DeepAR-Model using following code:

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ANSWER

Answered 2021-Mar-19 at 14:47

I believe that Tarun might on the right path. The BrokenPipeError that you got is thrown when the connection is abruptly closed. See the python docs for BrokenPipeError. The SageMaker endpoint probably drops the connection as soon as you go over the limit of 5MB. I suggest you try a smaller dataset. Also the data you send might get enlarged because of how sagemaker.tensorflow.model.TensorFlowPredictor encodes the data according to this comment on a similar issue.

If that doesn't work I've also seen a couple of people having problems with their networks in general. Specifically firewall/antivirus (for example this comment) or network timeout.

Hope this points you in the right direction.

Source https://stackoverflow.com/questions/66561959

QUESTION

java.lang.UnsatisfiedLinkError: No implementation found (When Implement a SDK)

Asked 2020-Nov-29 at 05:58

I am trying out to integrate a third-party SDK (DeepAR). But when I build it, that time it shows an error. I tried to fix it. If I create a simple new project it's working properly. But my existing apps I use camera and ndk. Please help me to find out the error.

Here is the Cmakelist file.

...

ANSWER

Answered 2020-Nov-29 at 05:58

After I week later I found the solution. It creates conflict with the library. I change CMakeLists file as a new then the conflict remove.

Now Working CMakeList file is:

Source https://stackoverflow.com/questions/64917805

QUESTION

How to load a GluonTS DeepAR model

Asked 2020-Sep-27 at 15:09

I am new to GluonTS and deep learning in general. I have a GluonTS DeepAR model which has files like -

...

ANSWER

Answered 2020-Sep-27 at 15:09

The way to load a GluonTS model is to use the Predictor class and deserialize it -

Source https://stackoverflow.com/questions/63696163

QUESTION

GluonTS DeepAR prediction non deterministic

Asked 2020-Jul-05 at 14:00

I'm working on DeepAR using GluonTS. After I trained a model using the proper method, I got a predictor that i named predictor. Then, I used this to perform a prediction like in this case:

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ANSWER

Answered 2020-Jul-05 at 14:00

DeepAR performs a probabilistic forecasting, so it estimates, during training, the statistical distribution of the time series. Consequently, when you predict a series, it samples a distribution, resulting in your non-determinism.

For reducing the variance in your prediction, you can specify the parameter num_samples in the method predict, for indicating the number of times it has to sample the distribution for calculating the mean to return you.

Source https://stackoverflow.com/questions/62593403

QUESTION

Impossible import a module due to a dependency in Python

Asked 2020-Jun-26 at 13:48

I'm trying to import gluonts in a Jupyter Notebook, so I installed the module through:

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ANSWER

Answered 2020-Jun-26 at 13:48

The problem you have is that you uninstalled pandas after its importation, so the notebook kept the old version, even if you imported the newly installed module. To solve the problem you have to restart your notebook, after deletion of the old pandas and the installation of the new version. Another way to permanently solve this issue is, just after the notebook startup, to uninstall and to update pandas before every importation. I figured this out after reading comments and trying what they said.

Source https://stackoverflow.com/questions/62556786

QUESTION

Tracking SageMaker Estimator with MLFlow

Asked 2020-Apr-24 at 09:24

I'm working on a version tracking system for a ML project and want to use MLflow to do so. My project uses AWS Sagemaker's DeepAR for forecast.

What I want to do is very simple. I'm trying do log the Sagemaker DeepAR model (Sagemaker Estimator) with MLFlow. As it doesn't have a "log_model" funcion in it's "mlflow.sagemaker" module, I tried to use the "mlflow.pyfunc" module to do the log. Unfortunatelly it didn't worked. How can I log the Sagemaker model and get the cloudpickle and yaml files generated by MLFlow?

My code for now:

mlflow.pyfunc.log_model(model)

Where model is a sagemaker.estimator.Estimator object and the error I get from the code is

mlflow.exceptions.MlflowException: Either `loader_module` or `python_model` must be specified. A `loader_module` should be a python module. A `python_model` should be a subclass of PythonModel

I know AWS Sagemaker logs my models, but it is really important to my project to do the log with MLFlow too.

...

ANSWER

Answered 2020-Apr-24 at 09:24

You cannot use pyfunc to store Any type object.

You should either specify one of loader_module as shown in the example below or you must write the wrapper that implements PythonModel interface and provides logic to deserialize your model from previously-stored artifacts as described here https://www.mlflow.org/docs/latest/models.html#example-saving-an-xgboost-model-in-mlflow-format

example with loader:

Source https://stackoverflow.com/questions/61377643

QUESTION

How in GluonTS transformation function is automatically called from DeepARE class , even though i have not used object to call it?

Asked 2020-Apr-02 at 11:01

I am working with DeepARE library in gluonTS. I am right now debugging how the DeepARE class work. It contains create_transformation function and predictor function, when the DeepARE constructor is passed to object, all functions inside DeepARE are automatically implemented. How is this possible, what i have read about python class is that you have to call a function through object to use it. How is this done here.

The code is here:

...

ANSWER

Answered 2020-Apr-02 at 11:01

DeepAREstimator derives from GluonEstimator, which implements the train-method.

When you look at the code you can see that GluonEstimator calls create_transformation, etc. which are implemented by child-classes (in your case DeepAREstimator).

Source https://stackoverflow.com/questions/60903995

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

Vulnerabilities

No vulnerabilities reported

Install deepar

You can download it from GitHub.
You can use deepar 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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