Creats a new instance of darch class

This function prints out the weight in a heat map, 3D surface, or histogram

1 | ```
print_weight(darch, num_of_layer, show_derivative = F, type = "heatmap")
``` |

`darch` |
DArch instance |

`num_of_layer` |
the number of the layer to print |

`show_derivative` |
T to show the weight value. F to show the percentage weight change in the finetuning stage. This helps spot the network saturation problem. |

`type` |
type of the graph. It supports "heatmap", "surface", and "histogram" |

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 | ```
# Example of Regression
input <- matrix(runif(1000), 500, 2)
input_valid <- matrix(runif(100), 50, 2)
target <- rowSums(input + input^2)
target_valid <- rowSums(input_valid + input_valid^2)
# create a new deep neural network for classificaiton
dnn_regression <- new_dnn(
c(2, 50, 50, 20, 1), # The layer structure of the deep neural network.
# The first element is the number of input variables.
# The last element is the number of output variables.
hidden_layer_default = rectified_linear_unit_function,
# for hidden layers, use rectified_linear_unit_function
output_layer_default = linearUnitDerivative
# for regression, use linearUnitDerivative function
)
# print the layer weights
# this function can print heatmap, histogram, or a surface
print_weight(dnn_regression, 1, type = "heatmap")
print_weight(dnn_regression, 2, type = "surface")
print_weight(dnn_regression, 3, type = "histogram")
``` |

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