Using coremltools to convert a Keras model into mlmodel for iOS

convert_model.py

import coremltools
import numpy
from keras.datasets import mnist
from keras.models import Sequential
from keras.layers import Dense
from keras.layers import Dropout
from keras.utils import np_utils
from keras.models import load_model


def convert_model(model):
	print('converting...')
	coreml_model = coremltools.converters.keras.convert(model,input_names=['image'],image_input_names='image')
	coreml_model.author = 'YOUR NAME'
	coreml_model.license = 'MIT'
	coreml_model.short_description = 'Reads a handwritten digit. The model is based on keras mnist examples here. https://github.com/fchollet/keras/blob/master/examples/mnist_cnn.py but altered to strictly set up channels last as input_shape.'
	coreml_model.input_description['image'] = 'A 28x28 pixel Image'
	coreml_model.output_description['output1'] = 'A one-hot Multiarray were the index with the biggest float value (0-1) is the recognized digit. '
	coreml_model.save('keras_mnist_cnn.mlmodel')
	print('model converted')


import os.path
if os.path.isfile('my_mnist_keras_cnn_model.h5'): 
	model = load_model('my_mnist_keras_cnn_model.h5')
	convert_model(model)
else:
	print('no model found')

Excuse me. When use your example to convert my keras MNIST, I got this result:
Traceback (most recent call last):
File "/Users/jiayuli/work/STEM_project_2018/convert.py", line 26, in
convert_model(model)
File "/Users/jiayuli/work/STEM_project_2018/convert.py", line 13, in convert_model
coreml_model = coremltools.converters.keras.convert(model,input_names=['image'],image_input_names='image')
File "/usr/local/lib/python2.7/site-packages/coremltools/converters/keras/_keras_converter.py", line 722, in convert
custom_conversion_functions=custom_conversion_functions)
File "/usr/local/lib/python2.7/site-packages/coremltools/converters/keras/_keras_converter.py", line 527, in convertToSpec
custom_conversion_functions=custom_conversion_functions)
File "/usr/local/lib/python2.7/site-packages/coremltools/converters/keras/_keras2_converter.py", line 173, in _convert
graph.build()
File "/usr/local/lib/python2.7/site-packages/coremltools/converters/keras/_topology2.py", line 634, in build
for node in layer.inbound_nodes:
AttributeError: 'Conv2D' object has no attribute 'inbound_nodes'

Hi @jiayulinfs,
The problem is that currently coremltools supports Keras 1.2.2+ but it would be better if you pip the 1.2.2 itself; also, Tensorflow(if you're using it instead of Theano) should be 1.2.1 instead of 1.4.1. Then try removing the input_names parameter; worked for me, worth giving a shot.
Peace,
Akash