Large error when using the genrate sentence method at the end

[mherath]

Hi there,

Thank you for taking your time to code and present it all in your tutorial. I've enjoyed trying them out so far. However I ran into this rather massive error when I tried to run the generate_sentence method in the portion of the tutorial where you generate words.
The error is as follows (bear with me here, it is rather long):

Traceback (most recent call last):
File "RNN.py", line 325, in
sent = generate_sentence(model)
File "RNN.py", line 306, in generate_sentence
next_word_probs = model.forward_propagation(new_sentence)
File "/home/mahesh/miniconda2/lib/python2.7/site-packages/theano/compile/function_module.py", line 917, in call
storage_map=getattr(self.fn, 'storage_map', None))
File "/home/mahesh/miniconda2/lib/python2.7/site-packages/theano/gof/link.py", line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File "/home/mahesh/miniconda2/lib/python2.7/site-packages/theano/compile/function_module.py", line 903, in call
self.fn() if output_subset is None else
File "/home/mahesh/miniconda2/lib/python2.7/site-packages/theano/scan_module/scan_op.py", line 963, in rval
r = p(n, [x[0] for x in i], o)
File "/home/mahesh/miniconda2/lib/python2.7/site-packages/theano/scan_module/scan_op.py", line 952, in p
self, node)
File "theano/scan_module/scan_perform.pyx", line 405, in theano.scan_module.scan_perform.perform (/home/mahesh/.theano/compiledir_Linux-3.17-fc21.x86_64-x86_64-with-fedora-21-Twenty_One-x86_64-2.7.13-64/scan_perform/mod.cpp:4606)
File "/home/mahesh/miniconda2/lib/python2.7/site-packages/theano/gof/link.py", line 325, in raise_with_op
reraise(exc_type, exc_value, exc_trace)
File "theano/scan_module/scan_perform.pyx", line 397, in theano.scan_module.scan_perform.perform (/home/mahesh/.theano/compiledir_Linux-3.17-fc21.x86_64-x86_64-with-fedora-21-Twenty_One-x86_64-2.7.13-64/scan_perform/mod.cpp:4490)
ValueError: Shape mismatch: A.shape[1] != x.shape[0]
Apply node that caused the error: CGemv{no_inplace}(Subtensor{::, int32}.0, TensorConstant{1.0}, W_copy, <TensorType(float64, vector)>, TensorConstant{1.0})
Toposort index: 2
Inputs types: [TensorType(float64, vector), TensorType(float64, scalar), TensorType(float64, matrix), TensorType(float64, vector), TensorType(float64, scalar)]
Inputs shapes: [(50,), (), (50, 50), (100,), ()]
Inputs strides: [(64000,), (), (400, 8), (8,), ()]
Inputs values: ['not shown', array(1.0), 'not shown', 'not shown', array(1.0)]
Outputs clients: [[Elemwise{tanh,no_inplace}(CGemv{no_inplace}.0)]]

HINT: Re-running with most Theano optimization disabled could give you a back-trace of when this node was created. This can be done with by setting the Theano flag 'optimizer=fast_compile'. If that does not work, Theano optimizations can be disabled with 'optimizer=None'.
HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and storage map footprint of this apply node.
Apply node that caused the error: forall_inplace,cpu,scan_fn}(Shape_i{0}.0, Subtensor{int64:int64:int8}.0, IncSubtensor{InplaceSet;:int64:}.0, Shape_i{0}.0, V, U, W)
Toposort index: 7
Inputs types: [TensorType(int64, scalar), TensorType(int32, vector), TensorType(float64, matrix), TensorType(int64, scalar), TensorType(float64, matrix), TensorType(float64, matrix), TensorType(float64, matrix)]
Inputs shapes: [(), (1,), (1, 100), (), (8000, 50), (50, 8000), (50, 50)]
Inputs strides: [(), (4,), (800, 8), (), (400, 8), (64000, 8), (400, 8)]
Inputs values: [array(1), array([0], dtype=int32), 'not shown', array(1), 'not shown', 'not shown', 'not shown']
Outputs clients: [[], ['output']]

HINT: Re-running with most Theano optimization disabled could give you a back-trace of when this node was created. This can be done with by setting the Theano flag 'optimizer=fast_compile'. If that does not work, Theano optimizations can be disabled with 'optimizer=None'.
HINT: Use the Theano flag 'exception_verbosity=high' for a debugprint and storage map footprint of this apply node.

I can't quite figure out what the issue is over here.
I would be grateful for any help you can give me in resolving this issue. I would love to get this code working in its entireity :)

thanks,

Mahesh