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DeepSpace

A collection of search space for the DeepHyper package.

Requirements

Graphviz.

Quick Start

Generate a neural architecture space for fully connected networks with residual connections:

from deepspace.tabular import DenseSkipCoSpace

def create_search_space(input_shape=(54,), output_shape=(7,), **kwargs)
    return DenseSkipCoSpace()(input_shape, output_shape, num_layers=10, dropout=0.0)

Generate a neural architecture space for AutoEncoder guided by an estimator:

from deepspace.tabular import SupervisedRegAutoEncoderSpace

factory = SupervisedRegAutoEncoderSpace()(
     input_shape=(100,), output_shape=[(100), (10,)]
)

Metadata

Release files for deepspace 0.0.6

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for deepspace 0.0.6
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Table of built distributions (wheels) for deepspace 0.0.6
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deepspace-0.0.6-py2.py3-none-any.whl Python 2, Python 3 none any Details

Total release size: 14.5 kB

Release files / deepspace-0.0.6.tar.gz

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Release files / deepspace-0.0.6-py2.py3-none-any.whl

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