jlebensold

function logger() {                                        
  return function (target, key, descriptor) {              
    const initialValue = descriptor.value;                 
    descriptor.value = function() {                        
      console.log(`>"${key}" with`, arguments);            
      return  initialValue.apply(null, arguments);         
    };                                                     
    return descriptor;                                     
  }                                                        
}                                                          

jlebensold

let pastryList: list(pastry) = [                                                 
  { label: "🥐  Croissants",  flour: 0.7, butter: 0.5, sugar: 0.2, eggs: 0.0 },   
  { label: "🍪  Cookies", flour: 0.5, butter: 0.4, sugar: 0.5, eggs: 0.2 },       
  { label: "🥞  Pancakes", flour: 0.7, butter: 0.5, sugar: 0.3, eggs: 0.3 },      
  { label: "🍩  Dougnuts", flour: 0.5, butter: 0.2, sugar: 0.8, eggs: 0.1 }       
];                                                                               
                                                                                 
let theList = List.map((item) => <Text>{item.label}</Text>, pastryList);         

jlebensold

from pathlib import Path
import torch
import torch.nn as nn
import torch.nn.functional as F


class TanhNet(nn.Module):
    def __init__(self, in_features, h_units):
        super(TanhNet, self).__init__()
        self.fc1 = nn.Linear(in_features, h_units)