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[INFO] running `Command { std: "git" "clone" "/workspace/cache/git-repos/https%3A%2F%2Fgithub.com%2FTheHuziek%2Fpio-net" "/workspace/builds/worker-5-tc2/source", kill_on_drop: false }`
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[INFO] started tweaking git repo https://github.com/TheHuziek/pio-net
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[INFO] crate git repo https://github.com/TheHuziek/pio-net already has a lockfile, it will not be regenerated
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[INFO] [stdout] warning: variant `gelu` should have an upper camel case name
[INFO] [stdout]  --> src/neuronal_net/types_of_activation.rs:9:5
[INFO] [stdout]   |
[INFO] [stdout] 9 |     gelu, 
[INFO] [stdout]   |     ^^^^ help: convert the identifier to upper camel case: `Gelu`
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(non_camel_case_types)]` (part of `#[warn(nonstandard_style)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `zero`
[INFO] [stdout]  --> src/neuronal_net/neuronal_net.rs:3:10
[INFO] [stdout]   |
[INFO] [stdout] 3 | use na::{zero, DMatrix};
[INFO] [stdout]   |          ^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unnecessary parentheses around function argument
[INFO] [stdout]   --> src/main.rs:31:78
[INFO] [stdout]    |
[INFO] [stdout] 31 |     let expected_output_farenheit = train_input_celsius.iter().map(|x| scale((9.0/5.0 + 32.0),x)).collect::<Vec<DMatrix<f64>>>(); //...
[INFO] [stdout]    |                                                                              ^              ^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_parens)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] help: remove these parentheses
[INFO] [stdout]    |
[INFO] [stdout] 31 -     let expected_output_farenheit = train_input_celsius.iter().map(|x| scale((9.0/5.0 + 32.0),x)).collect::<Vec<DMatrix<f64>>>(); // Ejemplo de salida esperada
[INFO] [stdout] 31 +     let expected_output_farenheit = train_input_celsius.iter().map(|x| scale(9.0/5.0 + 32.0 ,x)).collect::<Vec<DMatrix<f64>>>(); // Ejemplo de salida esperada
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `activations`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:25:14
[INFO] [stdout]    |
[INFO] [stdout] 25 |         let (activations, zs, predicted_output) = self.forward_pass(&input);
[INFO] [stdout]    |              ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_activations`
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `learning_rate`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:27:13
[INFO] [stdout]    |
[INFO] [stdout] 27 |         let learning_rate = if config.learning_rate > 0.0 {
[INFO] [stdout]    |             ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_learning_rate`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `batch_size`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:33:13
[INFO] [stdout]    |
[INFO] [stdout] 33 |         let batch_size = expected_output.ncols().max(1) as f64;
[INFO] [stdout]    |             ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_batch_size`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `output_z`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:35:13
[INFO] [stdout]    |
[INFO] [stdout] 35 |         let output_z = zs.last().expect("Se esperaba al menos una capa de salida");
[INFO] [stdout]    |             ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_output_z`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: variants `LeakyReLU`, `Tanh`, `Softmax`, and `gelu` are never constructed
[INFO] [stdout]  --> src/neuronal_net/types_of_activation.rs:6:5
[INFO] [stdout]   |
[INFO] [stdout] 3 | pub enum ActivationFunctions{
[INFO] [stdout]   |          ------------------- variants in this enum
[INFO] [stdout] ...
[INFO] [stdout] 6 |     LeakyReLU,
[INFO] [stdout]   |     ^^^^^^^^^
[INFO] [stdout] 7 |     Tanh,
[INFO] [stdout]   |     ^^^^
[INFO] [stdout] 8 |     Softmax,
[INFO] [stdout]   |     ^^^^^^^
[INFO] [stdout] 9 |     gelu, 
[INFO] [stdout]   |     ^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `ActivationFunctions` has derived impls for the traits `Clone` and `Debug`, but these are intentionally ignored during dead code analysis
[INFO] [stdout]   = note: `#[warn(dead_code)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: struct `ActivationFunction` is never constructed
[INFO] [stdout]   --> src/neuronal_net/types_of_activation.rs:11:12
[INFO] [stdout]    |
[INFO] [stdout] 11 | pub struct ActivationFunction{}   
[INFO] [stdout]    |            ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: method `derivative` is never used
[INFO] [stdout]   --> src/neuronal_net/types_of_activation.rs:24:12
[INFO] [stdout]    |
[INFO] [stdout] 12 | impl ActivationFunctions {
[INFO] [stdout]    | ------------------------ method in this implementation
[INFO] [stdout] ...
[INFO] [stdout] 24 |     pub fn derivative(&self, x: f64) -> f64 {
[INFO] [stdout]    |            ^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `sigmoid_prime` is never used
[INFO] [stdout]   --> src/neuronal_net/types_of_activation.rs:39:4
[INFO] [stdout]    |
[INFO] [stdout] 39 | fn sigmoid_prime(x: f64) -> f64 {
[INFO] [stdout]    |    ^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: associated function `train` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:16:12
[INFO] [stdout]    |
[INFO] [stdout] 15 | impl NeuralNetCompiled {
[INFO] [stdout]    | ---------------------- associated function in this implementation
[INFO] [stdout] 16 |     pub fn train() {
[INFO] [stdout]    |            ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `multiply` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:65:4
[INFO] [stdout]    |
[INFO] [stdout] 65 | fn multiply(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]    |    ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `subtract` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:87:4
[INFO] [stdout]    |
[INFO] [stdout] 87 | fn subtract(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]    |    ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `add` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:90:4
[INFO] [stdout]    |
[INFO] [stdout] 90 | fn add(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]    |    ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `binary_cross_entropy_loss` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:96:4
[INFO] [stdout]    |
[INFO] [stdout] 96 | fn binary_cross_entropy_loss(predicted: &DMatrix<f64>, actual: &DMatrix<f64>) -> f64 {
[INFO] [stdout]    |    ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `activation_derivative_matrix` is never used
[INFO] [stdout]    --> src/neuronal_net/neural_net_compiled.rs:114:4
[INFO] [stdout]     |
[INFO] [stdout] 114 | fn activation_derivative_matrix(activation: &ActivationFunctions, matrix: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]     |    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `subtract_dismatch` is never used
[INFO] [stdout]    --> src/neuronal_net/neural_net_compiled.rs:117:4
[INFO] [stdout]     |
[INFO] [stdout] 117 | fn subtract_dismatch(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]     |    ^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: variant `gelu` should have an upper camel case name
[INFO] [stdout]  --> src/neuronal_net/types_of_activation.rs:9:5
[INFO] [stdout]   |
[INFO] [stdout] 9 |     gelu, 
[INFO] [stdout]   |     ^^^^ help: convert the identifier to upper camel case: `Gelu`
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(non_camel_case_types)]` (part of `#[warn(nonstandard_style)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused import: `zero`
[INFO] [stdout]  --> src/neuronal_net/neuronal_net.rs:3:10
[INFO] [stdout]   |
[INFO] [stdout] 3 | use na::{zero, DMatrix};
[INFO] [stdout]   |          ^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `#[warn(unused_imports)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unnecessary parentheses around function argument
[INFO] [stdout]   --> src/main.rs:31:78
[INFO] [stdout]    |
[INFO] [stdout] 31 |     let expected_output_farenheit = train_input_celsius.iter().map(|x| scale((9.0/5.0 + 32.0),x)).collect::<Vec<DMatrix<f64>>>(); //...
[INFO] [stdout]    |                                                                              ^              ^
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_parens)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] help: remove these parentheses
[INFO] [stdout]    |
[INFO] [stdout] 31 -     let expected_output_farenheit = train_input_celsius.iter().map(|x| scale((9.0/5.0 + 32.0),x)).collect::<Vec<DMatrix<f64>>>(); // Ejemplo de salida esperada
[INFO] [stdout] 31 +     let expected_output_farenheit = train_input_celsius.iter().map(|x| scale(9.0/5.0 + 32.0 ,x)).collect::<Vec<DMatrix<f64>>>(); // Ejemplo de salida esperada
[INFO] [stdout]    |
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `activations`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:25:14
[INFO] [stdout]    |
[INFO] [stdout] 25 |         let (activations, zs, predicted_output) = self.forward_pass(&input);
[INFO] [stdout]    |              ^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_activations`
[INFO] [stdout]    |
[INFO] [stdout]    = note: `#[warn(unused_variables)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `learning_rate`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:27:13
[INFO] [stdout]    |
[INFO] [stdout] 27 |         let learning_rate = if config.learning_rate > 0.0 {
[INFO] [stdout]    |             ^^^^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_learning_rate`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `batch_size`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:33:13
[INFO] [stdout]    |
[INFO] [stdout] 33 |         let batch_size = expected_output.ncols().max(1) as f64;
[INFO] [stdout]    |             ^^^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_batch_size`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: unused variable: `output_z`
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:35:13
[INFO] [stdout]    |
[INFO] [stdout] 35 |         let output_z = zs.last().expect("Se esperaba al menos una capa de salida");
[INFO] [stdout]    |             ^^^^^^^^ help: if this is intentional, prefix it with an underscore: `_output_z`
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: variants `LeakyReLU`, `Tanh`, `Softmax`, and `gelu` are never constructed
[INFO] [stdout]  --> src/neuronal_net/types_of_activation.rs:6:5
[INFO] [stdout]   |
[INFO] [stdout] 3 | pub enum ActivationFunctions{
[INFO] [stdout]   |          ------------------- variants in this enum
[INFO] [stdout] ...
[INFO] [stdout] 6 |     LeakyReLU,
[INFO] [stdout]   |     ^^^^^^^^^
[INFO] [stdout] 7 |     Tanh,
[INFO] [stdout]   |     ^^^^
[INFO] [stdout] 8 |     Softmax,
[INFO] [stdout]   |     ^^^^^^^
[INFO] [stdout] 9 |     gelu, 
[INFO] [stdout]   |     ^^^^
[INFO] [stdout]   |
[INFO] [stdout]   = note: `ActivationFunctions` has derived impls for the traits `Clone` and `Debug`, but these are intentionally ignored during dead code analysis
[INFO] [stdout]   = note: `#[warn(dead_code)]` (part of `#[warn(unused)]`) on by default
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: struct `ActivationFunction` is never constructed
[INFO] [stdout]   --> src/neuronal_net/types_of_activation.rs:11:12
[INFO] [stdout]    |
[INFO] [stdout] 11 | pub struct ActivationFunction{}   
[INFO] [stdout]    |            ^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: method `derivative` is never used
[INFO] [stdout]   --> src/neuronal_net/types_of_activation.rs:24:12
[INFO] [stdout]    |
[INFO] [stdout] 12 | impl ActivationFunctions {
[INFO] [stdout]    | ------------------------ method in this implementation
[INFO] [stdout] ...
[INFO] [stdout] 24 |     pub fn derivative(&self, x: f64) -> f64 {
[INFO] [stdout]    |            ^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `sigmoid_prime` is never used
[INFO] [stdout]   --> src/neuronal_net/types_of_activation.rs:39:4
[INFO] [stdout]    |
[INFO] [stdout] 39 | fn sigmoid_prime(x: f64) -> f64 {
[INFO] [stdout]    |    ^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: associated function `train` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:16:12
[INFO] [stdout]    |
[INFO] [stdout] 15 | impl NeuralNetCompiled {
[INFO] [stdout]    | ---------------------- associated function in this implementation
[INFO] [stdout] 16 |     pub fn train() {
[INFO] [stdout]    |            ^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `multiply` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:65:4
[INFO] [stdout]    |
[INFO] [stdout] 65 | fn multiply(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]    |    ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `subtract` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:87:4
[INFO] [stdout]    |
[INFO] [stdout] 87 | fn subtract(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]    |    ^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `add` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:90:4
[INFO] [stdout]    |
[INFO] [stdout] 90 | fn add(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]    |    ^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `binary_cross_entropy_loss` is never used
[INFO] [stdout]   --> src/neuronal_net/neural_net_compiled.rs:96:4
[INFO] [stdout]    |
[INFO] [stdout] 96 | fn binary_cross_entropy_loss(predicted: &DMatrix<f64>, actual: &DMatrix<f64>) -> f64 {
[INFO] [stdout]    |    ^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `activation_derivative_matrix` is never used
[INFO] [stdout]    --> src/neuronal_net/neural_net_compiled.rs:114:4
[INFO] [stdout]     |
[INFO] [stdout] 114 | fn activation_derivative_matrix(activation: &ActivationFunctions, matrix: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]     |    ^^^^^^^^^^^^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stdout] warning: function `subtract_dismatch` is never used
[INFO] [stdout]    --> src/neuronal_net/neural_net_compiled.rs:117:4
[INFO] [stdout]     |
[INFO] [stdout] 117 | fn subtract_dismatch(m: &DMatrix<f64>, n: &DMatrix<f64>) -> DMatrix<f64> {
[INFO] [stdout]     |    ^^^^^^^^^^^^^^^^^
[INFO] [stdout] 
[INFO] [stdout] 
[INFO] [stderr]     Finished `dev` profile [unoptimized + debuginfo] target(s) in 24.62s
[INFO] running `Command { std: "docker" "inspect" "194cc60d18240ba59a4ef3350cfc05e43454d9e66c5233f354ccd9947ddeece1", kill_on_drop: false }`
[INFO] running `Command { std: "docker" "rm" "-f" "194cc60d18240ba59a4ef3350cfc05e43454d9e66c5233f354ccd9947ddeece1", kill_on_drop: false }`
[INFO] [stdout] 194cc60d18240ba59a4ef3350cfc05e43454d9e66c5233f354ccd9947ddeece1
