Model zoo (fix #3)

[beam2d]

This PR fixes #3 by adding functions.caffe.CaffeFunction, which loads a pretrained Caffe model and emulates its subnetwork. The usage is written in the reference documentation, though I also show it here. This is an example of loading BVLC reference CaffeNet and computes fc8 blob from data blob.

# Load the model
func = CaffeFunction('path/to/bvlc_reference_caffenet.caffemodel')

# Minibatch of size 10
x_data = numpy.ndarray((10, 3, 227, 227), dtype=numpy.float32)
...  # (Fill the minibatch here)

# Forward the pretrained net
x = Variable(x_data)
y, = func(inputs={'data': x}, outputs=['fc8'])

The inputs dict describes how to initialize the blobs by variables. The outputs list indicates which blobs to be output as variables. Also user can extracts parameterized layers from CaffeFunction.fs, which is a FunctionSet object containing Linear or Convolution2D objects.

[unnonouno]

Can we install protobuf in py3 environment?

[beam2d]

We can install it. CI passed it, too.

[unnonouno]

OK, no problem.

[unnonouno]

Which version of protobuf is required?

[unnonouno]

Do you have a unit test for this function?

[beam2d]

I'm thinking about the test, though I have no good plan, yet.

[beam2d]

I'll write an example of loading and using a Caffe reference model.

[beam2d]

I added an example. However, it outputs too low accuracy. I will try to resolve this issue.

[unnonouno]

How does this function behave when backward is called?

[beam2d]

This function just inserts a computational graph on top of the given variables in __call__, instead of inserting itself into the graph. Backward computation is done by each node in this graph, so CaffeFunction itself does not need to handle the backward.

[beam2d]

I updated the example code.

[beam2d]

I updated the code. It achieves the same accuracy as the original Caffe implementation. (Actually I've fixed testing mode and RGB order)

[unnonouno]

Please chmod +x download_model.py

[unnonouno]

s/descriptor/description/

[unnonouno]

What happens on py3?

[beam2d]

I changed the code to raise an exception in Python 3. I also wrote this behavior in the docstring.

[beam2d]

I added a warning routine on unknown layer types.

[unnonouno]

[itortoise]

I load my caffemodel and then Traceback ZeroDivisionError as:

File "", line 1, in
File "chainer/functions/caffe/caffe_function.py", line 119, in init
meth(self, layer)
File "chainer/functions/caffe/caffe_function.py", line 228, in _setup_convolution
nobias=not param.bias_term)
File "chainer/functions/convolution_2d.py", line 92, in init
0, wscale * math.sqrt(1. / (self.kh * self.kw * in_channels)),
ZeroDivisionError: float division by zero

[beam2d]

@itortoise Thank you for reporting an error. Would you open another issue for this?

[beam2d]

@itortoise #148 may fix your problem.