Release history¶
0.2.0 (November 2, 2020)¶
Added
Added documentation for package description, installation, usage, API, examples, and project information. (#20)
Added LMU FFT cell variant and auto-switching LMU class. (#21)
LMUs can now be used with any Keras RNN cell (e.g. LSTMs or GRUs) through the
hidden_cell
parameter. This can take an RNN cell (liketf.keras.layers.SimpleRNNCell
ortf.keras.layers.LSTMCell
) or a feedforward layer (liketf.keras.layers.Dense
) orNone
(to create a memory-only LMU). The output of the LMU memory component will be fed to thehidden_cell
. (#22)Added
hidden_to_memory
,memory_to_memory
, andinput_to_hidden
parameters toLMUCell
, which can be used to enable/disable connections between components of the LMU. They default to disabled. (#22)LMUs can now be used with multi-dimensional memory components. This is controlled through a new
memory_d
parameter ofLMUCell
. (#22)Added
dropout
parameter toLMUCell
(which applies dropout to the input) andrecurrent_dropout
(which applies dropout to thememory_to_memory
connection, if it is enabled). Note that dropout can be added in the hidden component through thehidden_cell
object. (#22)
Changed
Renamed
lmu.lmu
module tolmu.layers
. (#22)Combined the
*_encoders_initializer``parameters of ``LMUCell
into a singlekernel_initializer
parameter. (#22)Combined the
*_kernel_initializer
parameters ofLMUCell
into a singlerecurrent_kernel_initializer
parameter. (#22)
Removed
Removed
Legendre
,InputScaled
,LMUCellODE
, andLMUCellGating
classes. (#22)Removed the
method
,realizer
, andfactory
arguments fromLMUCell
(they will take on the same default values as before, they just cannot be changed). (#22)Removed the
trainable_*
arguments fromLMUCell
. This functionality is largely redundant with the new functionality added for enabling/disabling internal LMU connections. These were primarily used previously for e.g. setting a connection to zero and then disabling learning, which can now be done more efficiently by disabling the connection entirely. (#22)Removed the
units
andhidden_activation
parameters ofLMUCell
(these are now specified directly in thehidden_cell
. (#22)Removed the dependency on
nengolib
. (#22)Dropped support for Python 3.5, which reached its end of life in September 2020. (#22)
0.1.0 (June 22, 2020)¶
Initial release of NengoLMU 0.1.0! Supports Python 3.5+.
The API is considered unstable; parts are likely to change in the future.
Thanks to all of the contributors for making this possible!