torch_conv_tbc: Conv_tbc
In torch: Tensors and Neural Networks with 'GPU' Acceleration
View source: R/gen-namespace.R
torch_conv_tbc R Documentation
Conv_tbc
Description
Conv_tbc
Usage
torch_conv_tbc(self, weight, bias, pad = 0L)
Arguments
self
NA input tensor of shape (\mbox{sequence length} \times batch \times \mbox{in\_channels})
weight
NA filter of shape (\mbox{kernel width} \times \mbox{in\_channels} \times \mbox{out\_channels})
bias
NA bias of shape (\mbox{out\_channels})
pad
NA number of timesteps to pad. Default: 0
TEST
Applies a 1-dimensional sequence convolution over an input sequence.
Input and output dimensions are (Time, Batch, Channels) - hence TBC.
torch documentation built on May 29, 2024, 9:54 a.m.
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View source: R/gen-namespace.R
| torch_conv_tbc | R Documentation |
Conv_tbc
Description
Conv_tbc
Usage
torch_conv_tbc(self, weight, bias, pad = 0L)
Arguments
self |
NA input tensor of shape |
weight |
NA filter of shape ( |
bias |
NA bias of shape ( |
pad |
NA number of timesteps to pad. Default: 0 |
TEST
Applies a 1-dimensional sequence convolution over an input sequence. Input and output dimensions are (Time, Batch, Channels) - hence TBC.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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