dusanstanojeviccs

import Component from '@glimmer/component';
import { action } from '@ember/object';

export default class extends Component {
  @action
  change() {
  	console.log("A1");
    this.args._wrapper.mike += "10"
  }
}

dusanstanojeviccs

import Controller from '@ember/controller';

export default class ApplicationController extends Controller {
  appName = 'Ember Twiddle';
}

dusanstanojeviccs

import Component from '@glimmer/component';

export default class extends Component {
}

dusanstanojeviccs

import Controller from '@ember/controller';

export default class ApplicationController extends Controller {
  appName = 'Ember Twiddle';
}

dusanstanojeviccs

import Component from '@glimmer/component';
import { tracked } from '@glimmer/tracking';
import { action,computed } from '@ember/object';

export default class extends Component {
  @tracked dusan = 10;
  
	@computed("dusan")
  get answer() {
    console.log("Answer");

dusanstanojeviccs

import Controller from '@ember/controller';

export default class ApplicationController extends Controller {
  appName = 'Ember Twiddle';
}

dusanstanojeviccs

import Component from '@glimmer/component';
import { inject as service } from "@ember/service";
import { action } from "@ember/object";
import { later } from "@ember/runloop";
import { tracked } from "@glimmer/tracking";

export default class extends Component {
  @service iner;
  @tracked model;
  

dusanstanojeviccs

import Component from '@ember/component';
import {action} from '@ember/object';

export default class extends Component {
  @action
  change() {
  	this.set("name", "Dux");
  }
}

dusanstanojeviccs

def conv2d_output(conv_layer, input_height = 128, input_width = 128):
    """Calculates the output dimensions of a convolutional layer in PyTorch.

    Keyword arguments:
    conv_layer -- the nn.Conv2d object
    input_height -- the height of the input image to be processed by Conv2d
    input_width -- the width of the input image to be processed by Conv2d
    """
    
    # We need to get all of the values from the conv layer    

dusanstanojeviccs

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