outputs/claim1_depth.json

{
 "sweep": [
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
   "layers": 5,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
   "layers": 6,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
   "layers": 7,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
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   "dtype": "float32"
  },
  {
   "points": 9,
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   "grad_mismatches": 0,
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   "activation": "relu",
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   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
   "layers": 10,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
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   "dtype": "float32"
  },
  {
   "points": 9,
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   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "relu",
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   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
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  },
  {
   "points": 9,
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   "activation": "sigmoid",
   "layers": 6,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
   "layers": 7,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
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   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
   "layers": 9,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
   "layers": 10,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
   "layers": 11,
   "dtype": "float32"
  },
  {
   "points": 9,
   "value_mismatches": 0,
   "grad_mismatches": 0,
   "value_max_abs_err": 0.0,
   "grad_max_abs_err": 0.0,
   "activation": "sigmoid",
   "layers": 12,
   "dtype": "float32"
  }
 ],
 "lower_bound": {
  "one_layer_gradients": [
   -1.1183192729949951,
   -1.1183192729949951,
   -1.1183192729949951
  ],
  "constant": true,
  "note": "L=1 gives an x-independent AD gradient: values+independent gradients are impossible, so some depth is genuinely needed"
 }
}