I use Ubuntu 16.04
Theano 0.8
Lasagne 0.2dev2
nolearn 0.61dev0
in the file .theanorc
[global]
floatX=float32
device=cpu
optimizer=None
I set to run on the CPU just to simplify and because I have GPU with only
1Gb that is not enought for this model.
The 4Gb of RAM on the main board appear fully used during the training.
My Python come simply imported the VGG convolutional neural net availabe in
internet written in Lasagne that I rewrote in nolearn.
At the time when the fit function is working
cnn.fit(train224,target)
I receive the following error message after the description of the net
provided by nolearn.
# Neural Network with 119586826 learnable parameters
## Layer information
name size total cap.Y cap.X cov.Y cov.X
---------- ----------- ------- ------- ------- ------- -------
input 3x224x224 150528 100.00 100.00 100.00 100.00
conv1_1 64x224x224 3211264 100.00 100.00 1.34 1.34
conv1_2 64x224x224 3211264 60.00 60.00 2.23 2.23
pool1 64x112x112 802816 60.00 60.00 2.23 2.23
conv2_1 128x112x112 1605632 66.67 66.67 4.02 4.02
conv2_2 128x112x112 1605632 46.15 46.15 5.80 5.80
pool2 128x56x56 401408 46.15 46.15 5.80 5.80
conv3_1 256x56x56 802816 57.14 57.14 9.38 9.38
conv3_2 256x56x56 802816 41.38 41.38 12.95 12.95
conv3_3 256x56x56 802816 32.43 32.43 16.52 16.52
pool3 256x28x28 200704 32.43 32.43 16.52 16.52
conv4_1 512x28x28 401408 45.28 45.28 23.66 23.66
conv4_2 512x28x28 401408 34.78 34.78 30.80 30.80
conv4_3 512x28x28 401408 28.24 28.24 37.95 37.95
pool4 512x14x14 100352 28.24 28.24 37.95 37.95
conv5_1 512x14x14 100352 41.03 41.03 52.23 52.23
conv5_2 512x14x14 100352 32.21 32.21 66.52 66.52
conv5_3 512x14x14 100352 26.52 26.52 80.80 80.80
pool5 512x7x7 25088 26.52 26.52 80.80 80.80
fc6 4096 4096 100.00 100.00 100.00 100.00
fc6dropout 4096 4096 100.00 100.00 100.00 100.00
fc7 4096 4096 100.00 100.00 100.00 100.00
fc7dropout 4096 4096 100.00 100.00 100.00 100.00
fc8 10 10 100.00 100.00 100.00 100.00
Explanation
X, Y: image dimensions
cap.: learning capacity
cov.: coverage of image
magenta: capacity too low (<1/6)
cyan: image coverage too high (>100%)
red: capacity too low and coverage too high
Traceback (most recent call last):
File "/home/alberto/pycharm-community-2016.2.3/helpers/pydev/pydevd.py",
line 1580, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "/home/alberto/pycharm-community-2016.2.3/helpers/pydev/pydevd.py",
line 964, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "/home/alberto/Scrivania/deep_learn/mnist_example/kagle
dataset_2_VGG.py", line 248, in <module>
cnn.fit(train224,target) # train the CNN model for n epochs
File
"/home/alberto/.local/lib/python2.7/site-packages/nolearn/lasagne/base.py",
line 674, in fit
self.train_loop(X, y, epochs=epochs)
File
"/home/alberto/.local/lib/python2.7/site-packages/nolearn/lasagne/base.py",
line 737, in train_loop
self.apply_batch_func(self.train_iter_, Xb, yb))
File
"/home/alberto/.local/lib/python2.7/site-packages/nolearn/lasagne/base.py",
line 828, in apply_batch_func
return func(Xb) if yb is None else func(Xb, yb)
File
"/home/alberto/.local/lib/python2.7/site-packages/theano/compile/function_module.py"
, line 871, in __call__
storage_map=getattr(self.fn, 'storage_map', None))
File "/home/alberto/.local/lib/python2.7/site-packages/theano/gof/link.py"
, line 314, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File
"/home/alberto/.local/lib/python2.7/site-packages/theano/compile/function_module.py"
, line 859, in __call__
outputs = self.fn()
MemoryError:
Apply node that caused the error: Elemwise{add,no_inplace}(AbstractConv2d{
border_mode=(1, 1), subsample=(1, 1), filter_flip=False, imshp=(None, 3, 224
, 224), kshp=(64, 3, 3, 3)}.0, DimShuffle{x,0,x,x}.0)
Toposort index: 65
Inputs types: [TensorType(float32, 4D), TensorType(float32, (True, False,
True, True))]
Inputs shapes: [(128, 64, 224, 224), (1, 64, 1, 1)]
Inputs strides: [(12845056, 200704, 896, 4), (256, 4, 4, 4)]
Inputs values: ['not shown', 'not shown']
Outputs clients: [[Elemwise{abs_,no_inplace}(Elemwise{add,no_inplace}.0),
Elemwise{add,no_inplace}(Elemwise{add,no_inplace}.0, Elemwise{abs_,
no_inplace}.0)]]
Backtrace when the node is created(use Theano flag traceback.limit=N to
make it longer):
File "/home/alberto/pycharm-community-2016.2.3/helpers/pydev/pydevd.py",
line 1580, in <module>
globals = debugger.run(setup['file'], None, None, is_module)
File "/home/alberto/pycharm-community-2016.2.3/helpers/pydev/pydevd.py",
line 964, in run
pydev_imports.execfile(file, globals, locals) # execute the script
File "/home/alberto/Scrivania/deep_learn/mnist_example/kagle
dataset_2_VGG.py", line 241, in <module>
cnn.initialize()
File
"/home/alberto/.local/lib/python2.7/site-packages/nolearn/lasagne/base.py",
line 479, in initialize
self.y_tensor_type,
File
"/home/alberto/.local/lib/python2.7/site-packages/nolearn/lasagne/base.py",
line 602, in _create_iter_funcs
layers, target=y_batch, **objective_kw)
File
"/home/alberto/.local/lib/python2.7/site-packages/nolearn/lasagne/base.py",
line 189, in objective
output_layer, deterministic=deterministic, **get_output_kw)
File
"/home/alberto/.local/lib/python2.7/site-packages/lasagne/layers/helper.py",
line 191, in get_output
all_outputs[layer] = layer.get_output_for(layer_inputs, **kwargs)
File
"/home/alberto/.local/lib/python2.7/site-packages/lasagne/layers/conv.py",
line 337, in get_output_for
activation = conved + self.b.dimshuffle(('x', 0) + ('x',) * self.n)
HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and
storage map footprint of this apply node.
Backend TkAgg is interactive backend. Turning interactive mode on.
We've got an error while stopping in post-mortem: <type 'exceptions.
KeyboardInterrupt'>
Process finished with exit code 1
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