abstract
- abstraction class¶
The file yann.layers.abstract.py
contains the definition for the abstract layer:
Todo
- LSTM / GRN layers
- An Embed layer that is going to create a new embedding space for two layer’s activations to project on to the same space and minimize its distances.
-
class
yann.layers.abstract.
layer
(id, type, verbose=2)[source]¶ Prototype for what a layer should look like. Every layer should inherit from this. This is a template class do not use this directly, you need to use a specific type of layer which again will be called by
yann.network.network.add_layer
Parameters: - id – String
- origin – String id
- type – string-
'classifier'
,'dot-product'
,'objective'
,'conv_pool'
,'input'
.. .
Notes
- Use
self.type
,self.origin
, self.destination``,self.output
,self.inference
self.output_shape
for outside calls and purposes.
-
get_params
(borrow=True, verbose=2)[source]¶ This method returns the parameters of the layer in a numpy ndarray format.
Parameters: - borrow – Theano borrow, default is True.
- verbose – As always
Notes
This is a slow method, because we are taking the values out of GPU. Ordinarily, I should have used get_value( borrow = True ), but I can’t do this because some parameters are theano.tensor.var.TensorVariable which needs to be run through eval.