{
  "real_training_value": 1.5,
  "fixed_noise": [
    -1.0,
    1.0
  ],
  "initial": {
    "D": {
      "w": 0.4,
      "b": -0.1
    },
    "G": {
      "a": 0.5,
      "c": 0.0
    }
  },
  "D_step": {
    "G_fixed": {
      "a": 0.5,
      "c": 0.0
    },
    "gradients": {
      "w": -0.5414555771245682,
      "b": 0.09772766653549525
    },
    "finite_difference_errors": {
      "w": 1.385820347366007e-10,
      "b": 9.036227321956858e-11
    },
    "D_after": {
      "w": 0.45414555771245685,
      "b": -0.10977276665354953
    },
    "loss_before": 1.1234529364511556,
    "loss_after": 1.0938781019122463
  },
  "G_step": {
    "D_fixed": {
      "w": 0.45414555771245685,
      "b": -0.10977276665354953
    },
    "gradients": {
      "a": 0.025594619599051488,
      "c": -0.2393648279235713
    },
    "finite_difference_errors": {
      "a": 8.654826855192255e-12,
      "c": 2.0472207262756115e-11
    },
    "G_after": {
      "a": 0.49744053804009486,
      "c": 0.023936482792357133
    },
    "loss_before": 0.7559513093729658,
    "loss_after": 0.7501709216536937
  },
  "generated_values_before": [
    -0.5,
    0.5
  ],
  "generated_values_after": [
    -0.47350405524773775,
    0.521377020832452
  ],
  "G_objective": "non-saturating -mean(log D(G(z)))",
  "D_objective": "-log D(real) - mean(log(1-D(fake)))",
  "image_generated": false,
  "TensorFlow_or_PyTorch_run": false
}