View source: R/nn_layers.R View source: R/nn_functional.R
| ggml_layer_conv_1d | R Documentation |
Create a Conv1D Layer Object
Add 1D Convolution Layer
ggml_layer_conv_1d(
model,
filters,
kernel_size,
activation = NULL,
input_shape = NULL,
strides = 1L,
padding = "valid",
name = NULL,
trainable = TRUE
)
ggml_layer_conv_1d(
model,
filters,
kernel_size,
activation = NULL,
input_shape = NULL,
strides = 1L,
padding = "valid",
name = NULL,
trainable = TRUE
)
model |
A ggml_sequential_model object |
filters |
Number of output filters |
kernel_size |
Integer kernel size |
activation |
Activation function name: "relu", "sigmoid", "tanh", "softmax", or NULL |
input_shape |
Input shape c(L, C) - required for first layer only (length, channels) |
strides |
Integer stride (default 1) |
padding |
"valid" (no padding) or "same" (preserve length) |
name |
Optional character name for the layer. |
trainable |
Logical; whether the layer weights are updated during training. |
A ggml_layer object.
The model object with the conv_1d layer appended (invisibly).
model <- ggml_model_sequential() |>
ggml_layer_conv_1d(32, 3, activation = "relu",
input_shape = c(100, 1))
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