can you find calculation problems in this log:
2024-10-06 03:39:41.699 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.699 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.699 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.700 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.700 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.700 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.706 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.706 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.706 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.707 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.707 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.707 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.707 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.707 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.707 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.708 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.708 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.708 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.716 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.716 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.716 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.716 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.716 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.716 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.716 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.716 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.716 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.717 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.717 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.717 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.723 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.723 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.723 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.723 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.723 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.723 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.723 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.723 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.723 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.724 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.724 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.724 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.731 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.731 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.731 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.732 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.732 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.732 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.732 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.732 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.732 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.733 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.733 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.733 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.739 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.739 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.739 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.739 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.739 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.739 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.739 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.739 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.739 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.742 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.742 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.742 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.748 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.748 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.748 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.748 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.748 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.748 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.748 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.748 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.748 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.749 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.749 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.749 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.755 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.755 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.755 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.755 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.755 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.755 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.755 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.755 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.755 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.756 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.756 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.756 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.762 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64]
2024-10-06 03:39:41.762 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.762 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.762 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3]
2024-10-06 03:39:41.762 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.762 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.762 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.763 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.3252804]
2024-10-06 03:39:41.763 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-42.408974], Loss: [42.408974], Mean Loss: [1.3252804]
2024-10-06 03:39:41.763 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [24, 64], Output Shape: [24, 64]
2024-10-06 03:39:41.763 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.012212934, 0.0023932192, 0.054470252, 0.049081367, 0.026759995], Output Sample Values: [0, 0.0023932192, 0.054470252, 0.049081367, 0.026759995]
2024-10-06 03:39:41.763 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed.
2024-10-06 03:39:41.769 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [24, 64], Output Shape: [24, 64]
2024-10-06 03:39:41.769 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.2737577, -0.008846832, -0.03457632, -0.04117969, -0.031483375], Output Sample Values: [0.2737577, 0, 0, 0, 0]
2024-10-06 03:39:41.769 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed.
2024-10-06 03:39:41.769 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [24, 3], Output Shape: [24, 3]
2024-10-06 03:39:41.769 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.3111022, 0.2973977, -0.999465, 0.31288844, 0.29747432], Output Sample Values: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013]
2024-10-06 03:39:41.769 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed.
2024-10-06 03:39:41.769 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed.
2024-10-06 03:39:41.769 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [24, 3], Target Shape: [24, 3], Mean Loss: [1.3245571]
2024-10-06 03:39:41.769 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4432514, 0.43721828, 0.1195303, 0.44367656, 0.43689013], Target Sample: [1, 0, 0, 1, 0], Batch Size: [24], Epsilon: [1E-12], LogSumExp: [1.4429406, 1.4429513, 1.4429564, 1.4429622, 1.4429722], Log Probabilities: [-0.9996892, -1.0057223, -1.3234103, -0.99927473, -1.0060612], Product: [-0, -0, -1.3234103, -0, -0], Loss Sum: [-31.78937], Loss: [31.78937], Mean Loss: [1.3245571]
2024-10-06 03:39:41.769 [Information] HyperAI.Core.Trainings.Trainers.Trainer: Epoch 4/5, Training Loss: 1.0480632, Validation Loss: 1.3252424
2024-10-06 03:39:41.769 [Information] HyperAI.Core.Trainings.Trainers.Trainer: Checkpoint saved at 'checkpoints\model_epoch_4.ckpt' with Validation Loss: 1.3252424
2024-10-06 03:39:41.772 [Information] HyperAI.Core.Trainings.Trainers.Trainer: Epoch 4 completed in 2.11s, Average Training Loss: 1.0480632, Min Loss: 0.97058034, Max Loss: 1.1178614.
2024-10-06 03:39:41.773 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.773 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.12504937, -0.038796697, -0.09838535, -0.14602934, -0.2754949], Output Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.773 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.33080795, -0.22833316, -0.122648, -0.16004086, 0.1203568], Output Sample Values: [0.33080795, 0, 0, 0, 0.1203568] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.42314738, 0.4077367, -1.2768279, 0.3649393, 0.42206043], Output Sample Values: [0.46138325, 0.45432752, 0.0842892, 0.43509343, 0.46067] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.0211021] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.46138325, 0.45432752, 0.0842892, 0.43509343, 0.46067], Target Sample: [0, 0, 1, 0, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4467599, 1.4445882, 1.4477959, 1.4592403, 1.4510381], Log Probabilities: [-0.9853767, -0.9924324, -1.3624707, -1.0094948, -0.9839182], Product: [-0, -0, -1.3624707, -0, -0], Loss Sum: [-32.675266], Loss: [32.675266], Mean Loss: [1.0211021] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Gradient Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient Input Sample Values: 0.46138325, 0.45432752, 0.0842892, 0.43509343, 0.46067, Gradient Output Sample Values: [0, 0, 1, 0, 0], Gradient Sample Values: [0.011665582, 0.011583562, -0.023249142, 0.011387595, 0.011682606] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass completed with Input Shape [32, 3], GradOutput Shape [32, 3], GradInput Shape [32, 3] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.779 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass Input Sample Values: 0.46138325, 0.45432752, 0.0842892, 0.43509343, 0.46067, Gradient Output Sample Values: [0.011665582, 0.011583562, -0.023249142, 0.011387595, 0.011682606], Gradient Input Sample Values: [0.0013750134, 0.001316722, -0.0026917357, 0.0015036215, 0.0017279133] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.780 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.780 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.780 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0.33080795, 0, 0, 0, 0.1203568, Gradient Output Sample Values: [0.0016443905, 0.00027255493, 0.0003415268, 0.00033675303, -0.00022080578], Gradient Input Sample Values: [0.0016443905, 0, 0, 0, -0.00022080578] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.792 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.792 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.792 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0, 0, 0, 0, 0, Gradient Output Sample Values: [-0.0003570733, 0.0008424926, 0.0015217355, 0.0008435354, 0.0008236581], Gradient Input Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.792 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.793 [Debug] HyperAI.Core.Trainings.Trainers.Trainer: Epoch 5, Batch 1/75 completed in 0.02s. Loss: 1.0211021 [Scope: Trainer, Epoch: 4, Batch: 0]
2024-10-06 03:39:41.794 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.794 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.12510987, -0.03935541, -0.0982389, -0.14458524, -0.27499497], Output Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.794 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.3298809, -0.22801863, -0.12391844, -0.1596474, 0.11880636], Output Sample Values: [0.3298809, 0, 0, 0, 0.11880636] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.423407, 0.41274917, -1.275692, 0.36913925, 0.42081052], Output Sample Values: [0.4603528, 0.45547253, 0.084174685, 0.4363738, 0.4595145] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.0677329] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4603528, 0.45547253, 0.084174685, 0.4363738, 0.4595145], Target Sample: [0, 0, 1, 0, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4467708, 1.4445907, 1.4479584, 1.4582613, 1.4515185], Log Probabilities: [-0.986418, -0.99129826, -1.3625962, -1.0082169, -0.9850762], Product: [-0, -0.99129826, -0, -0, -0.9850762], Loss Sum: [-34.167454], Loss: [34.167454], Mean Loss: [1.0677329] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Gradient Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient Input Sample Values: 0.4603528, 0.45547253, 0.084174685, 0.4363738, 0.4595145, Gradient Output Sample Values: [0, 0, 1, 0, 0], Gradient Sample Values: [0.01165344, -0.019653294, 0.007999854, 0.011402156, -0.019580914] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass completed with Input Shape [32, 3], GradOutput Shape [32, 3], GradInput Shape [32, 3] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.800 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass Input Sample Values: 0.4603528, 0.45547253, 0.084174685, 0.4363738, 0.4595145, Gradient Output Sample Values: [0.01165344, -0.019653294, 0.007999854, 0.011402156, -0.019580914], Gradient Input Sample Values: [0.006705912, -0.0076245363, 0.00091862446, 0.0063591725, -0.0075407736] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.801 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.801 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.801 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0.3298809, 0, 0, 0, 0.11880636, Gradient Output Sample Values: [0.0013187716, -0.0003283866, 0.0015893972, 0.00019438927, 0.001658947], Gradient Input Sample Values: [0.0013187716, 0, 0, 0, 0.001658947] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.812 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.812 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.812 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0, 0, 0, 0, 0, Gradient Output Sample Values: [0.0014071909, -0.00085939944, -0.0024694547, -0.0022744418, -0.00031223593], Gradient Input Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.813 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.813 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.814 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.814 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.814 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.814 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.814 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.814 [Debug] HyperAI.Core.Trainings.Trainers.Trainer: Epoch 5, Batch 2/75 completed in 0.02s. Loss: 1.0677329 [Scope: Trainer, Epoch: 4, Batch: 1]
2024-10-06 03:39:41.815 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.815 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.12561908, -0.040314138, -0.09784604, -0.14506426, -0.27559865], Output Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.815 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.33181977, -0.22763681, -0.12644365, -0.1600251, 0.12141337], Output Sample Values: [0.33181977, 0, 0, 0, 0.12141337] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.42013052, 0.42023247, -1.2819939, 0.36386675, 0.431495], Output Sample Values: [0.4582116, 0.4582583, 0.08353006, 0.43319914, 0.463509] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.0621014] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.4582116, 0.4582583, 0.08353006, 0.43319914, 0.463509], Target Sample: [0, 0, 1, 0, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4468434, 1.4447143, 1.4478036, 1.457658, 1.4510784], Log Probabilities: [-0.9886318, -0.9885851, -1.3633133, -1.0115151, -0.98120534], Product: [-0.9886318, -0, -0, -1.0115151, -0], Loss Sum: [-33.987244], Loss: [33.987244], Mean Loss: [1.0621014] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Gradient Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient Input Sample Values: 0.4582116, 0.4582583, 0.08353006, 0.43319914, 0.463509, Gradient Output Sample Values: [0, 0, 1, 0, 0], Gradient Sample Values: [-0.01962233, 0.011628212, 0.007994118, -0.019885391, 0.011714344] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass completed with Input Shape [32, 3], GradOutput Shape [32, 3], GradInput Shape [32, 3] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.821 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass Input Sample Values: 0.4582116, 0.4582583, 0.08353006, 0.43319914, 0.463509, Gradient Output Sample Values: [-0.01962233, 0.011628212, 0.007994118, -0.019885391, 0.011714344], Gradient Input Sample Values: [-0.0076189707, 0.006701073, 0.0009178971, -0.0076003764, 0.0065146056] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.822 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.822 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.822 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0.33181977, 0, 0, 0, 0.12141337, Gradient Output Sample Values: [-0.0024323063, 0.00015941047, -0.001795669, -0.0003851745, -0.0015169203], Gradient Input Sample Values: [-0.0024323063, 0, 0, 0, -0.0015169203] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.833 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.834 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.834 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0, 0, 0, 0, 0, Gradient Output Sample Values: [-0.00096980593, -1.4329555E-06, 0.0016303676, 0.0013224417, -0.0007516198], Gradient Input Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.834 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.835 [Debug] HyperAI.Core.Trainings.Trainers.Trainer: Epoch 5, Batch 3/75 completed in 0.02s. Loss: 1.0621014 [Scope: Trainer, Epoch: 4, Batch: 2]
2024-10-06 03:39:41.836 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.836 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.12461688, -0.039588593, -0.09750693, -0.14608744, -0.2753962], Output Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.836 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.33297926, -0.22827862, -0.12562203, -0.15986237, 0.12017499], Output Sample Values: [0.33297926, 0, 0, 0, 0.12017499] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.42690814, 0.4164054, -1.2858748, 0.37072945, 0.42555085], Output Sample Values: [0.46084744, 0.45603263, 0.0831199, 0.4362778, 0.4608629] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.842 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.0839893] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.46084744, 0.45603263, 0.0831199, 0.4362778, 0.4608629], Target Sample: [0, 0, 1, 0, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4468933, 1.444732, 1.4480193, 1.4579891, 1.4512892], Log Probabilities: [-0.9860459, -0.9908607, -1.3637735, -1.0084541, -0.9838691], Product: [-0, -0.9908607, -0, -1.0084541, -0], Loss Sum: [-34.687656], Loss: [34.687656], Mean Loss: [1.0839893] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Gradient Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient Input Sample Values: 0.46084744, 0.45603263, 0.0831199, 0.4362778, 0.4608629, Gradient Output Sample Values: [0, 0, 1, 0, 0], Gradient Sample Values: [0.011657777, -0.019648219, 0.007990441, -0.019850548, 0.011683182] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass completed with Input Shape [32, 3], GradOutput Shape [32, 3], GradInput Shape [32, 3] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass Input Sample Values: 0.46084744, 0.45603263, 0.0831199, 0.4362778, 0.4608629, Gradient Output Sample Values: [0.011657777, -0.019648219, 0.007990441, -0.019850548, 0.011683182], Gradient Input Sample Values: [0.0067197937, -0.007626969, 0.0009071746, -0.0075976164, 0.006506969] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.843 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.844 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.844 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0.33297926, 0, 0, 0, 0.12017499, Gradient Output Sample Values: [0.001303553, -0.00033907895, 0.0015959481, 0.00018330303, 0.0016702163], Gradient Input Sample Values: [0.001303553, 0, 0, 0, 0.0016702163] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.855 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.855 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.855 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0, 0, 0, 0, 0, Gradient Output Sample Values: [0.0012269446, -0.00055530894, -0.0026717635, -0.0018728056, 0.0002787463], Gradient Input Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.856 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.856 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.858 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.858 [Information] HyperAI.Core.Layers.DenseLayer: Weights updated for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.858 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer1'. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.858 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'HiddenLayer2'. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.858 [Information] HyperAI.Core.Layers.DenseLayer: Gradients cleared for layer 'OutputLayer'. [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.858 [Debug] HyperAI.Core.Trainings.Trainers.Trainer: Epoch 5, Batch 4/75 completed in 0.02s. Loss: 1.0839893 [Scope: Trainer, Epoch: 4, Batch: 3]
2024-10-06 03:39:41.859 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.859 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [-0.12422911, -0.04012105, -0.097553864, -0.14697817, -0.2759332], Output Sample Values: [0, 0, 0, 0, 0] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.859 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer1 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Forward pass completed with Input Shape: [32, 64], Output Shape: [32, 64] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: [0.33053148, -0.22807124, -0.12572509, -0.15983789, 0.12015512], Output Sample Values: [0.33053148, 0, 0, 0, 0.12015512] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass completed with Input Shape: [32, 3], Output Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Forward pass Input Sample Values: [0.42484868, 0.41929266, -1.282793, 0.36970255, 0.42697623], Output Sample Values: [0.45961118, 0.45706466, 0.08332421, 0.4355961, 0.46127257] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Information] HyperAI.Core.NeuralNetworks.NeuralNetwork: Forward pass completed. [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Mean Loss: [1.0293827] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Loss completed with Predictions Sample: [0.45961118, 0.45706466, 0.08332421, 0.4355961, 0.46127257], Target Sample: [0, 0, 1, 0, 0], Batch Size: [32], Epsilon: [1E-12], LogSumExp: [1.4468681, 1.4447078, 1.4481004, 1.4580812, 1.4514778], Log Probabilities: [-0.9872569, -0.98980343, -1.3635439, -1.0091116, -0.98343515], Product: [-0, -0.98980343, -0, -0, -0.98343515], Loss Sum: [-32.940247], Loss: [32.940247], Mean Loss: [1.0293827] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Debug] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient completed with Predictions Shape: [32, 3], Target Shape: [32, 3], Gradient Shape: [32, 3] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.865 [Trace] HyperMath.src.Core.LossFunctions.CrossEntropyLoss: Compute Gradient Input Sample Values: 0.45961118, 0.45706466, 0.08332421, 0.4355961, 0.46127257, Gradient Output Sample Values: [0, 0, 1, 0, 0], Gradient Sample Values: [0.011643668, -0.019635946, 0.007992275, 0.011391959, -0.019561749] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.866 [Debug] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass completed with Input Shape [32, 3], GradOutput Shape [32, 3], GradInput Shape [32, 3] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.866 [Trace] HyperMath.src.Core.ActivationFunctions.SoftmaxActivation: Backward pass Input Sample Values: 0.45961118, 0.45706466, 0.08332421, 0.4355961, 0.46127257, Gradient Output Sample Values: [0.011643668, -0.019635946, 0.007992275, 0.011391959, -0.019561749], Gradient Input Sample Values: [0.006710808, -0.00762318, 0.0009123719, 0.0063642347, -0.007538718] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.866 [Information] HyperAI.Core.Layers.DenseLayer: OutputLayer Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.866 [Debug] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Backward pass completed with Input Shape [32, 64], GradOutput Shape [32, 64], GradInput Shape [32, 64] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.866 [Trace] HyperMath.src.Core.ActivationFunctions.ReLUActivation: Input Sample Values: 0.33053148, 0, 0, 0, 0.12015512, Gradient Output Sample Values: [0.0012751513, -0.00032521403, 0.0016119386, 0.00021389601, 0.001670968], Gradient Input Sample Values: [0.0012751513, 0, 0, 0, 0.001670968] [Scope: Trainer, Epoch: 4, Batch: 4]
2024-10-06 03:39:41.878 [Information] HyperAI.Core.Layers.DenseLayer: HiddenLayer2 Backward pass completed
. [Scope: Trainer, Epoch: 4, Batch: 4]