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Trying do make the backward to work
This commit is contained in:
Bausager
2026-08-04 21:05:20 +02:00
parent b52c128496
commit 28c1976fb1
6 changed files with 21 additions and 97 deletions
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include/neural_network/activation_loss/activation_softmax_loss_categorical_crossentropy.hpp
+2 -2
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@@ -92,7 +92,7 @@ struct activation_softmax_loss_categorical_crossentropy: loss{
* @param y_true Vector of true label of data.
*
*/
bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::uint_vector& y_true);
bool calculate(const panic::tensor::real_matrix& y_pred, const panic::tensor::uint_vector& y_true) override;
/**
* @brief forward function to calculate losses
@@ -103,7 +103,7 @@ struct activation_softmax_loss_categorical_crossentropy: loss{
* @Note Overloaded if one-shot endcoded
* is used.
*/
bool forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true);
bool calculate(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true) override;
include/neural_network/loss/loss.hpp
+5
View File
@@ -73,6 +73,11 @@ struct loss{
*/
panic::tensor::real_matrix dinputs;
/**
* @brief Matrix for output of loss function
*/
panic::tensor::real_matrix outputs;
/**
* @brief Default de-constructor
include/neural_network/loss/loss_categorical_crossentropy.hpp
+2 -2
View File
@@ -92,7 +92,7 @@ struct loss_categorical_crossentropy: loss{
*/
bool backward(
const panic::tensor::real_matrix& dvalues,
const panic::tensor::uint_vector& y_true);
const panic::tensor::uint_vector& y_true) override;
/**
* @brief backward function to calculate from losses
@@ -105,7 +105,7 @@ struct loss_categorical_crossentropy: loss{
*/
bool backward(
const panic::tensor::real_matrix& dvalues,
const panic::tensor::real_matrix& y_true);
const panic::tensor::real_matrix& y_true) override;
};
src/neural_network/activation_loss/activation_softmax_loss_categorical_crossentropy.cpp
-59
View File
@@ -70,65 +70,6 @@ namespace panic{
activation_softmax_loss_categorical_crossentropy::activation_softmax_loss_categorical_crossentropy() {
}
//--------------------------------------------------------------------------------------------------------------------------
// Function Name : panic::neural_network::activation_softmax_loss_categorical_crossentropy.forward
//
// Description:
// Calculated the forward pass
//--------------------------------------------------------------------------------------------------------------------------
bool activation_softmax_loss_categorical_crossentropy::forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::uint_vector& y_true){
// Output layers activation function
if (!activation.forward(y_pred)){
return false;
}
// Set the output
outputs = activation.outputs;
// calculate the loss value.
if (!loss.calculate(outputs, y_true)){
return false;
}
return true;
}
//--------------------------------------------------------------------------------------------------------------------------
// Function Name : panic::neural_network::activation_softmax_loss_categorical_crossentropy.forward
//
// Description:
// Calculated the forward pass
//--------------------------------------------------------------------------------------------------------------------------
bool activation_softmax_loss_categorical_crossentropy::forward(const panic::tensor::real_matrix& y_pred, const panic::tensor::real_matrix& y_true){
// Output layers activation function
if (!activation.forward(y_pred)){
return false;
}
// Set the output
outputs = activation.outputs;
// calculate the loss value.
if (!loss.calculate(outputs, y_true)){
return false;
}
return true;
}
//--------------------------------------------------------------------------------------------------------------------------
// Function Name : panic::neural_network::activation_softmax_loss_categorical_crossentropy.calculate
//
src/neural_network/loss/loss.cpp
+9 -33
View File
@@ -77,7 +77,10 @@ bool loss::calculate(
// Calculate mean loss
data_loss = panic::math::mean(sample_losses);
//return calculate_mean();
// This is so the model can use every loss functions
// It's a problem to get the output when useing an activation+loss function
outputs = y_pred;
return true;
}
@@ -96,6 +99,11 @@ bool loss::calculate(
}
data_loss = panic::math::mean(sample_losses);
// This is so the model can use every loss functions
// It's a problem to get the output when useing an activation+loss function
outputs = y_pred;
return true;
}
@@ -127,38 +135,6 @@ bool loss::forward(
return false;
}
/*
//--------------------------------------------------------------------------------------------------------------------------
// Function Name : panic::neural_network::loss::calculate_mean
//
// Description:
// Calculates the average of all sample loss values.
//--------------------------------------------------------------------------------------------------------------------------
bool loss::calculate_mean(){
if (sample_losses.size() == 0){
return false;
}
panic::types::real_t sum =
static_cast<panic::types::real_t>(0);
for (
panic::types::uint_t i = 0;
i < sample_losses.size();
++i
){
sum += sample_losses[i];
}
data_loss =
sum /
static_cast<panic::types::real_t>(sample_losses.size());
return true;
}
*/
} // namespace tensor
} // namespace panic
src/neural_network/model/model.cpp
+3 -1
View File
@@ -450,7 +450,7 @@ bool model::train(const panic::tensor::real_matrix& X_train,
}
prediction = panic::math::argmax_rowwise(outputs);
prediction = panic::math::argmax_rowwise(loss_function->outputs);
comparisons = panic::math::equal(prediction, y_train);
@@ -463,6 +463,8 @@ bool model::train(const panic::tensor::real_matrix& X_train,
}
loss_function.backward(loss_function.outputs, y_train);
//backward();
//optimize();