machine-learning-algorithms

Describe the issue:
During computing Channel Dependencies reshape_break_channel_dependency does following code to ensure that the number of input channels equals the number of output channels:

in_shape = op_node.auxiliary['in_shape']
out_shape = op_node.auxiliary['out_shape']
in_channel = in_shape[1]
out_channel = out_shape[1]
return in_channel != out_channel

This is correct

Hello everyone,

First of all, I want to take a moment to thank all contributors and people who supported this project in any way ;) you are awesome!

If you like the project and have any interest in contributing/maintaining it, you can contact me here or send me a msg privately:

• Email: nidhalbacc@gmail.com

PS: You need to be familiar with python and machine learning

Describe the bug
If min_samples_split is a small float, then it may be equivalent to splitting on < 2 samples. This causes cuml to blow up:

RuntimeError: exception occured! file=../src/decisiontree/decisiontree.cu line=41: Invalid value for min_samples_split: 1. Should be >= 2.
Obtained 64 stack frames
#0 in /home/mboling/miniconda3/lib/python3.8/site-packages/cuml/common/../../..

Description

Currently our unit tests are disorganized and each test creates example StellarGraph graphs in different or similar ways with no sharing of this code.

This issue is to improve the unit tests by making functions to create example graphs available to all unit tests by, for example, making them pytest fixtures at the top level of the tests (see https://docs.pytest.org/en/latest/

Describe the bug
How can I load the LearningShapelets model which is already fitted?
When I run the code below, I get this error: NotFittedError: This LearningShapelets instance is not fitted yet. Call 'fit' with appropriate arguments before using this estimator.

To Reproduce
A code sample to reproduce the problem:

from joblib import dump, load
from keras.models import load_