coremltools: Wrong numpy range in setup.py

🐞Describe the bug

The setup.py for coremltools specifies the numpy dependency range as 'numpy >= 1.14.5'. However using any version before then 1.16.0 causes a segmentation fault. Any version >= to 1.16.0 works.

It would be nice to support versions before 1.16.0. That version is less than a year old. However at the very least the specified dependency ranges should be accurate.

Trace

No trace displayed. Only output is Segmentation fault: 11

To Reproduce

In a fresh/new Conda environment, run: pip install Pillow coremltools==3.0b6 numpy==1.15.4

Download the MNIST Model.

Execute the following code:

import coremltools
from PIL import Image
import numpy as np

data = np.empty((28,28), dtype=np.uint8)
input_image = Image.fromarray(data)

model = coremltools.models.MLModel('./Downloads/MNISTClassifier.mlmodel')
print(model.predict({'image': input_image}))

This give a segmentation fault.

If you then run pip install numpy==1.16.0, then the above code works.

System environment (please complete the following information):

• coremltools version (e.g., 3.0b5): 3.0b6
• OS (e.g., MacOS, Linux): MacOS
• macOS version (if applicable): 10.14.6
• XCode version (if applicable): Not using
• How you install python (anaconda, virtualenv, system): anaconda
• python version (e.g. 3.7): 3.6