| |
| |
| ``mx.nd.FullyConnected`` |
| ================================================ |
| |
| Description |
| ---------------------- |
| |
| Applies a linear transformation: :math:`Y = XW^T + b`. |
| |
| If ``flatten`` is set to be true, then the shapes are: |
| |
| - **data**: `(batch_size, x1, x2, ..., xn)` |
| - **weight**: `(num_hidden, x1 * x2 * ... * xn)` |
| - **bias**: `(num_hidden,)` |
| - **out**: `(batch_size, num_hidden)` |
| |
| If ``flatten`` is set to be false, then the shapes are: |
| |
| - **data**: `(x1, x2, ..., xn, input_dim)` |
| - **weight**: `(num_hidden, input_dim)` |
| - **bias**: `(num_hidden,)` |
| - **out**: `(x1, x2, ..., xn, num_hidden)` |
| |
| The learnable parameters include both ``weight`` and ``bias``. |
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| If ``no_bias`` is set to be true, then the ``bias`` term is ignored. |
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| .. note:: |
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| The sparse support for FullyConnected is limited to forward evaluation with `row_sparse` |
| weight and bias, where the length of `weight.indices` and `bias.indices` must be equal |
| to `num_hidden`. This could be useful for model inference with `row_sparse` weights |
| trained with importance sampling or noise contrastive estimation. |
| |
| To compute linear transformation with 'csr' sparse data, sparse.dot is recommended instead |
| of sparse.FullyConnected. |
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| Arguments |
| ------------------ |
| |
| +----------------------------------------+------------------------------------------------------------+ |
| | Argument | Description | |
| +========================================+============================================================+ |
| | ``data`` | NDArray-or-Symbol. | |
| | | | |
| | | Input data. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``weight`` | NDArray-or-Symbol. | |
| | | | |
| | | Weight matrix. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``bias`` | NDArray-or-Symbol. | |
| | | | |
| | | Bias parameter. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``num.hidden`` | int, required. | |
| | | | |
| | | Number of hidden nodes of the output. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``no.bias`` | boolean, optional, default=0. | |
| | | | |
| | | Whether to disable bias parameter. | |
| +----------------------------------------+------------------------------------------------------------+ |
| | ``flatten`` | boolean, optional, default=1. | |
| | | | |
| | | Whether to collapse all but the first axis of the input | |
| | | data | |
| | | tensor. | |
| +----------------------------------------+------------------------------------------------------------+ |
| |
| Value |
| ---------- |
| |
| ``out`` The result mx.ndarray |
| |
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| Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/nn/fully_connected.cc#L291 |
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