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Copy delayed version of the input signal on the space dimensions.
For example, for ``time_frames=3`` and ``gap=2``::
[ X(1) Y(1) [ X(1) Y(1) 0 0 0 0
X(2) Y(2) X(2) Y(2) 0 0 0 0
X(3) Y(3) --> X(3) Y(3) X(1) Y(1) 0 0
X(4) Y(4) X(4) Y(4) X(2) Y(2) 0 0
X(5) Y(5) X(5) Y(5) X(3) Y(3) X(1) Y(1)
X(6) Y(6) ... ... ... ... ... ... ]
X(7) Y(7)
X(8) Y(8)
... ... ]
This node provides similar functionality as the ``TimeFramesNode``, only
that it performs a time embedding into the past rather than into the future.
See ``TimeDelaySlidingWindowNode`` for a sliding window delay node for
application in a non-batch manner.
Original code contributed by Sebastian Hoefer.
Dec 31, 2010
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_train_seq List of tuples:: |
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dtype dtype |
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input_dim Input dimensions |
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output_dim Output dimensions |
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supported_dtypes Supported dtypes |
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Input arguments: time_frames -- Number of delayed copies gap -- Time delay between the copies
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Process the data contained in `x`. If the object is still in the training phase, the function `stop_training` will be called. `x` is a matrix having different variables on different columns and observations on the rows. By default, subclasses should overwrite `_execute` to implement their execution phase. The docstring of the `_execute` method overwrites this docstring.
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This function returns a pseudo-inverse of the execute frame. y == execute(x) only if y belongs to the domain of execute and has been computed with a sufficently large x. If gap > 1 some of the last rows will be filled with zeros.
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