minibatch | Python stream processing for humans | Data Manipulation library

by omegaml Python Version: 0.5.1 License: Non-SPDX

X-Ray Key Features Code Snippets(3)Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | minibatch Summary

minibatch is a Python library typically used in Utilities, Data Manipulation applications. minibatch has no bugs, it has no vulnerabilities, it has build file available and it has low support. However minibatch has a Non-SPDX License. You can install using 'pip install minibatch' or download it from GitHub, PyPI.

Python stream processing for humans

Support

Quality

Security

License

Reuse

Support

minibatch has a low active ecosystem.

It has 175 star(s) with 11 fork(s). There are 5 watchers for this library.

There were 1 major release(s) in the last 12 months.

There are 0 open issues and 1 have been closed. There are 1 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of minibatch is 0.5.1

Quality

minibatch has 0 bugs and 14 code smells.

Security

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

minibatch code analysis shows 0 unresolved vulnerabilities.

There are 2 security hotspots that need review.

License

minibatch has a Non-SPDX License.

Non-SPDX licenses can be open source with a non SPDX compliant license, or non open source licenses, and you need to review them closely before use.

Reuse

minibatch releases are available to install and integrate.

Deployable package is available in PyPI.

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

minibatch saves you 597 person hours of effort in developing the same functionality from scratch.

It has 1391 lines of code, 171 functions and 32 files.

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

Top functions reviewed by kandi - BETA

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

Run the window
Run the emitfn and return the result
Process a QuerySet
Delete objects from the database
Get or create a stream
Reset the mongoengine
Connect to mongoengine
Return mongodb url
Clean up the database
Start the consumer
Return a generator of documents that match the criteria
Consumer function
Decorator to create an emitter
Create an emitter
Attach the source to the stream
Produce data
Attach this stream to source
Serialize a function
Generator to stream changes
Append event to the stream
Clean the database
Setup the router
Push messages into a stream
Set the batch size
Return celery state
Connect to stream
Puts multiple messages
Create a stream

Get all kandi verified functions for this library.

minibatch Key Features

No Key Features are available at this moment for minibatch.

minibatch Examples and Code Snippets

Generate an RNN layer .

python

Lines of Code : 321

License : Non-SPDX (Apache License 2.0)

Copy

def raw_rnn(cell,
            loop_fn,
            parallel_iterations=None,
            swap_memory=False,
            scope=None):
  """Creates an `RNN` specified by RNNCell `cell` and loop function `loop_fn`.

  **NOTE: This method is still in tes

Construct an RNN layer .

python

Lines of Code : 173

License : Non-SPDX (Apache License 2.0)

Copy

def static_rnn(cell,
               inputs,
               initial_state=None,
               dtype=None,
               sequence_length=None,
               scope=None):
  """Creates a recurrent neural network specified by RNNCell `cell`.

  The sim

Implementation of RNN .

python

Lines of Code : 149

License : Non-SPDX (Apache License 2.0)

Copy

def _rnn_step(time,
              sequence_length,
              min_sequence_length,
              max_sequence_length,
              zero_output,
              state,
              call_cell,
              state_size,
              skip_conditional

Community Discussions

Trending Discussions on minibatch

Deep Q Learning - Cartpole Environment

PyMC3 Minibatch ADVI

Manual Calculation of tanh in Tensorflow Keras Model is resulting in Nan

tqdm notebook - 2 inner bars

Error updating ner model in spacy 3, any advice?

ValueError in Custom Keras Layer

Deep learning with Tensorflow: personalized training loop that learn with one element at a time

How can i work with Example for nlp.update problem with spacy3.0

spacy 3 NER Scorer() throws TypeError: score() takes 2 positional arguments but 3 were given

CS 231n: Gradient of Softmax Implementation Error

QUESTION

Deep Q Learning - Cartpole Environment

Asked 2021-May-31 at 22:21

I have a concern in understanding the Cartpole code as an example for Deep Q Learning. The DQL Agent part of the code as follow:

...

ANSWER

Answered 2021-May-31 at 22:21

self.model.predict(state) will return a tensor of shape of (1, 2) containing the estimated Q values for each action (in cartpole the action space is {0,1}). As you know the Q value is a measure of the expected reward.

By setting self.model.predict(state)[0][action] = target (where target is the expected sum of rewards) it is creating a target Q value on which to train the model. By then calling model.fit(state, train_target) it is using the target Q value to train said model to approximate better Q values for each state.

I don't understand why you are saying that the loss becomes 0: the target is set to the discounted sum of rewards plus the current reward

Source https://stackoverflow.com/questions/67773479

QUESTION

PyMC3 Minibatch ADVI

Asked 2021-May-31 at 17:36

I’m trying to use PyMC3 Minibatch ADVI for Bayesian Regression. The pm.fit function throws the following error and I’m not sure how to fix it.

It says that the ‘str’ object has no attribute ‘type’. What is any ‘str’ object from the error message here? I’ve mapped float tensors for more_replacements to the best of what I know.

...

ANSWER

Answered 2021-May-31 at 17:34

The blog post you are working from shows

Source https://stackoverflow.com/questions/67738634

QUESTION

Manual Calculation of tanh in Tensorflow Keras Model is resulting in Nan

Asked 2021-May-31 at 09:48

Please find the below TF Keras Model in which I am using tanh activation function in the Hidden Layers.

While the value of Logits are proper, the values that are calculated by implementing the tanh function manually is resulting in Nan.

It may be because of the Runtime Warnings shown below:

/home/abc/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:76: RuntimeWarning: overflow encountered in exp

/home/abc/anaconda3/lib/python3.7/site-packages/ipykernel_launcher.py:76: RuntimeWarning: invalid value encountered in true_divide

Complete reproducible code is mentioned below:

...

ANSWER

Answered 2021-May-31 at 09:48

Normalizing resolves the issue of overflowing:

Source https://stackoverflow.com/questions/67767519

QUESTION

tqdm notebook - 2 inner bars

Asked 2021-May-27 at 14:34

I'm trying to print training progress bar using tqdm.
I'd like to track the progress of the epochs, and for each epoch i have 2 progress bars: the train_loader minibatches, and validation_loader minibatches.
The code is something like that:

...

ANSWER

Answered 2021-May-27 at 14:34

You can reuse your progress bars and do the updates manually like this:

Source https://stackoverflow.com/questions/67723652

QUESTION

Error updating ner model in spacy 3, any advice?

Asked 2021-May-16 at 03:08

I am currently updating the NER model from fr_core_news_lg pipeline. The code used to work about 1 or 2 months ago, when I last used it. But now, something happened and I can't run it anymore. I haven't change anything from the code, just wanted to run it again. But I received the following error:

...

ANSWER

Answered 2021-May-16 at 03:08

I think this code should work for you:

Source https://stackoverflow.com/questions/67540692

QUESTION

ValueError in Custom Keras Layer

Asked 2021-May-12 at 13:13

I implemented a custom layer for Minibatch Standard Deviation:

...

ANSWER

Answered 2021-May-12 at 13:13

There are two ways to get tensor shapes for some tensor (say x): x.shape and tf.shape(x). These two are fundamentally different: The former simply returns a python list of the shape, and the latter adds an op in the dynamic computation graph, including placeholders for None dimensions.

In short, instead of

Source https://stackoverflow.com/questions/67503053

QUESTION

Deep learning with Tensorflow: personalized training loop that learn with one element at a time

Asked 2021-May-06 at 16:23

I need to use batch with element of different size, so i try to create a personalized training loop, the main idea is to start from the one supplied from keras:

...

ANSWER

Answered 2021-May-05 at 17:04

grads variable only contains the gradients of variables. to apply them you need to move the optimizer inside the last For loop. but why not writing a normal training loop and then set the batch_size to one?

====== Update

you can calculate the loss for each sample in the last For loop and then do a reduce_mean to calculate the mean of loss and then calculate the grads. code updated.

Source https://stackoverflow.com/questions/67405427

QUESTION

How can i work with Example for nlp.update problem with spacy3.0

Asked 2021-May-06 at 04:05

i am trying to train my data with spacy v3.0 and appareantly the nlp.update do not accept any tuples. Here is the piece of code:

...

ANSWER

Answered 2021-May-06 at 04:05

You didn't provide your TRAIN_DATA, so I cannot reproduce it. However, you should try something like this:

Source https://stackoverflow.com/questions/66675261

QUESTION

spacy 3 NER Scorer() throws TypeError: score() takes 2 positional arguments but 3 were given

Asked 2021-Apr-23 at 14:40

Running into the following error when trying to get scores on my test set using Scorer

TypeError: score() takes 2 positional arguments but 3 were given

...

ANSWER

Answered 2021-Apr-23 at 14:40

Since spaCy v3, scorer.score just takes a list of examples. Each Exampleobject holds two Doc objects:

one reference doc with the gold-standard annotations, created for example from the given annot dictionary
one predicted doc with the predictions. The scorer will then compare the two.

So you want something like this:

Source https://stackoverflow.com/questions/67229277

QUESTION

CS 231n: Gradient of Softmax Implementation Error

Asked 2021-Apr-02 at 06:24

I was trying to solve the CS 231n assignment 1 and had problems implementing gradient for softmax. Note, I'm not enrolled in the course and just doing it for learning purposes. I calculated the gradient by hand initially and it seems fine to me and I implemented the gradient as below, but when the code is run against numerical gradient the results are not matching, I want to understand where I'm going wrong in this implementation if someone could please help me clarify this clearly.

Thank you.

Code:

...

ANSWER

Answered 2021-Apr-02 at 06:24

I figured out the answer myself.

The line:

Source https://stackoverflow.com/questions/66910415

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

Vulnerabilities

No vulnerabilities reported

Install minibatch

You can install using 'pip install minibatch' or download it from GitHub, PyPI.
You can use minibatch 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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