Apply 1D conv with un-shared weights.
Apply 1D conv with un-shared weights.
k_local_conv1d(inputs, kernel, kernel_size, strides, data_format = NULL)Arguments
| inputs | 3D tensor with shape: (batch_size, steps, input_dim) |
| kernel | the unshared weight for convolution, with shape (output_length, feature_dim, filters) |
| kernel_size | a list of a single integer, specifying the length of the 1D convolution window |
| strides | a list of a single integer, specifying the stride length of the convolution |
| data_format | the data format, channels_first or channels_last |
Value
the tensor after 1d conv with un-shared weights, with shape (batch_size, output_length, filters)
Keras Backend
This function is part of a set of Keras backend functions that enable lower level access to the core operations of the backend tensor engine (e.g. TensorFlow, CNTK, Theano, etc.).
You can see a list of all available backend functions here: https://keras.rstudio.com/articles/backend.html#backend-functions.