mx.model.FeedForward.create
¶
Description¶
Create a MXNet Feedforward neural net model with the specified training.
Usage¶
mx.model.FeedForward.create(
symbol,
X,
y = NULL,
ctx = NULL,
begin.round = 1,
num.round = 10,
optimizer = "sgd",
initializer = mx.init.uniform(0.01),
eval.data = NULL,
eval.metric = NULL,
epoch.end.callback = NULL,
batch.end.callback = NULL,
array.batch.size = 128,
array.layout = "auto",
kvstore = "local",
verbose = TRUE,
arg.params = NULL,
aux.params = NULL,
input.names = NULL,
output.names = NULL,
fixed.param = NULL,
allow.extra.params = FALSE,
metric_cpu = TRUE,
...
)
Arguments¶
Argument |
Description |
---|---|
|
The symbolic configuration of the neural network. |
|
mx.io.DataIter or R array/matrix. The training data. |
|
R array, optional label of the data. This is only used when X is R array. |
|
mx.context or list of mx.context, optional. The devices used to perform training. |
|
integer (default=1). The initial iteration over the training data to train the model. |
|
integer (default=10). The number of iterations over training data to train the model. |
|
string, default=”sgd” The optimization method. |
|
initializer object. default=mx.init.uniform(0.01). The initialization scheme for parameters. |
|
mx.io.DataIter or list(data=R.array, label=R.array), optional. The validation set used for validation evaluation during the progress |
|
function, optional. The evaluation function on the results. |
|
function, optional. The callback when iteration ends. |
|
function, optional. The callback when one mini-batch iteration ends. |
|
integer (default=128). The batch size used for R array training. |
|
can be “auto”, “colmajor”, “rowmajor”, (detault=auto). The layout of array. “rowmajor” is only supported for two dimensional array. For matrix, “rowmajor” means dim(X) = c(nexample, nfeatures), “colmajor” means dim(X) = c(nfeatures, nexample) “auto” will auto detect the layout by match the feature size, and will report error when X is a square matrix to ask user to explicitly specify layout. |
|
string (default=”local”). The parameter synchronization scheme in multiple devices. |
|
logical (default=TRUE). Specifies whether to print information on the iterations during training. |
|
list, optional. Model parameter, list of name to NDArray of net’s weights. |
|
list, optional. Model parameter, list of name to NDArray of net’s auxiliary states. |
|
optional. The names of the input symbols. |
|
optional. The names of the output symbols. |
|
The parameters to be fixed during training. For these parameters, not gradients will be calculated and thus no space will be allocated for the gradient. |
|
Whether allow extra parameters that are not needed by symbol. If this is TRUE, no error will be thrown when arg_params or aux_params contain extra parameters that is not needed by the executor. |
Value¶
model
A trained mxnet model.