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donaldsebleung/
california-housing-linear-simple

Name: california-housing-linear-simple
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Predicting California house prices with MindSpore

A simple linear regression model to predict house prices in California

A simple linear regression model to predict house prices in California.

This model was trained on the California Housing Dataset using MindSpore 2.8.0 and exported in MindIR format as california-housing-linear-simple.mindir.

The dependencies are specified in the included requirements.txt.

pip install -r requirements.txt

Load the model weights and initialize the mindspore.nn.GraphCell.

python

import mindspore
import mindspore.nn as nn

graph = mindspore.load('california-housing-linear-simple.mindir')
model = nn.GraphCell(graph)

A mindspore.Tensor of shape (n, 8) where n is the number of input samples.

Each input feature has dtype=mindspore.dtype.float16.

A mindspore.Tensor of shape (n, 1) where n is the number of output predictions.

Each output prediction has dtype=mindspore.dtype.float16.

See the included notebook 01-load-infer.ipynb for details.