Loss CCE

This function block computes the Categorical Cross Entropy (CCE) loss function, commonly used in classification tasks for machine learning applications.

📥 Inputs

This function block does not have any inputs.

📤 Outputs

This block outputs the computed loss function, which can be utilized in evaluating the performance of classification models.

🕹️ Controls

No specific controls are available for this block as it automatically computes the loss function when executed.

🎨 Features

Machine Learning Loss Calculation Automatically calculates the Categorical Cross Entropy loss for model training.

📝 Usage Instructions

1. Integrate with Training Pipeline: Place this block within your AI training pipeline where the loss needs to be computed.

2. Execution: The CCE loss function will be computed automatically when the training scenario is executed.

📊 Evaluation

When run, this function block computes the Categorical Cross Entropy loss, typically used to evaluate how well the predicted classifications match the true labels.

🛠️ Troubleshooting

Loss Function Not Returning Expected Values

Ensure that the expected input shapes and labels are compatible with the CCE loss function. Check that the model output configurations and logits settings are correct.