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Error codes
Matthieu HERNANDEZ edited this page Nov 28, 2020
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This is the error codes list returned by int StraightforwardNeuralNetwork::isValid()
metohd.
Code | Error Name | Description |
---|---|---|
Neural Network error | ||
101 | invalid number of inputs | Number of inputs must be between 0 and 2,073,600 (1080 x 1920). |
102 | invalid number of layers | Number of layer must be between 0 and 1,000. |
Layer error | ||
201 | invalid number of neurons | Neurons by layer must be between 1 and 1,000,000. |
202 | invalid number of outputs | Number of outputs must be equal to number of neurons inside layer. |
203 | invalid weight neurons | neurons created with wrong number of weights |
Neuron error | ||
301 | wrong bias | Bias must be equal to 1. |
302 | wrong number of weights | Number of weights must be between 1 and 1,000,000. |
303 | wrong weight | Weights must be stay between -10,000 and +10,000. |
304 | wrong weight | Error during the creation of a recurrent neuron. |
Data error | ||
401 | wrong value | A value after normalization is not in range [-1;1]. |
402 | null set | A composite have a null set. |
403 | bad data | Data is badly created. |
404 | bad temporal data | Temporal data is badly created. |
405 | wrong size | Error in size of data. |
406 | wrong number of labels | Data type classification must have at least 2 labels. |
Optimizer | ||
501 | invalid learning rate | Learning rate must be between 0 and 1. |
502 | invalid momentum | Momentum must be between 0 and 1. |
503 | invalid beta1 | Momentum must be between 0 and 1. |
504 | invalid beta2 | Momentum must be between 0 and 1. |
505 | invalid epsilon | Momentum must be between 0 and 1. |
isValid method don't throw error because the method is always supposed to be valid, otherwise it is an error in the library code.