pub fn check_theoretical_grads<'g, 't, 'v, F: Float, A>(
    objective: A,
    gradients: &'t [A],
    variables: &'t [A],
    feeder: Feeder<'v, F>,
    eps: F,
    tol: F,
    g: &'g Context<F>,
) where
    A: AsRef<Tensor<'g, F>> + Copy,
{
    let objective = sum_all(objective);
    // backprop
    let theoretical_grads = g
        .evaluator()
        .extend(gradients)
        .set_feeder(feeder.clone())
        .run();

    // for each variable nodes
    for (var_node, th_grad) in variables.iter().zip(theoretical_grads) {
        // Copy gradient array if needed
        let th_copied = if th_grad.as_ref().unwrap().is_standard_layout() {
            None
        } else {
            Some(ndarray_ext::deep_copy(&th_grad.as_ref().unwrap().view()))
        };
        let th_ptr = if let Some(ref inner) = th_copied {
            inner.as_ptr()
        } else {
            th_grad.as_ref().unwrap().as_ptr()
        };

        // for each values
        let v_len = g
            .env()
            .get_array_by_id(
                var_node
                    .as_ref()
                    .get_variable_id()
                    .expect("This is not a variable"),
            )
            .expect("variable array not found")
            .borrow()
            .len();

        for i in 0..v_len as isize {
            let evacuated;
            // +
            unsafe {
                let mut guard_mut = g
                    .env()
                    .get_array_by_id(
                        var_node
                            .as_ref()
                            .get_variable_id()
                            .expect("This is not a variable"),
                    )
                    .expect("variable array not found")
                    .borrow_mut();
                let head = guard_mut.as_mut_ptr();
                evacuated = *head.offset(i);
                *head.offset(i) = evacuated + eps;
            }

            // eval
            let obj_pos_orig = g
                .evaluator()
                .push(objective)
                .set_feeder(feeder.clone())
                .run()
                .remove(0)
                .unwrap();
            let obj_pos = if obj_pos_orig.is_standard_layout() {
                obj_pos_orig
            } else {
                ndarray_ext::deep_copy(&obj_pos_orig.view())
            };

            unsafe {
                let mut guard_mut = g
                    .env()
                    .get_array_by_id(
                        var_node
                            .as_ref()
                            .get_variable_id()
                            .expect("This is not a variable"),
                    )
                    .expect("variable array not found")
                    .borrow_mut();

                let head = guard_mut.as_mut_ptr();
                *head.offset(i) = evacuated - eps;
            }

            // eval
            let obj_neg_orig = g
                .evaluator()
                .push(objective)
                .set_feeder(feeder.clone())
                .run()
                .remove(0)
                .unwrap();
            let obj_neg = if obj_neg_orig.is_standard_layout() {
                obj_neg_orig
            } else {
                ndarray_ext::deep_copy(&obj_neg_orig.view())
            };

            // restore
            unsafe {
                let mut guard_mut = g
                    .env()
                    .get_array_by_id(
                        var_node
                            .as_ref()
                            .get_variable_id()
                            .expect("This is not a variable"),
                    )
                    .expect("variable array not found")
                    .borrow_mut();
                let head = guard_mut.as_mut_ptr();
                *head.offset(i) = evacuated;
            }

            let two = F::one() + F::one();
            let g_num = (obj_pos - obj_neg).scalar_sum() / (two * eps);
            let g_th = unsafe { *th_ptr.offset(i) };

            // compare
            let diff = (g_num - g_th).abs();
            if diff > tol {
                panic!(
                    "Gradient checking failed with too large error: numerical={}, theoretical={}",
                    g_num, g_th
                );
            }
        }
    }
}
/// Checks the validity of `gradients` with finite difference trick.
/// For this test only, `variables` must be *shared* variables.
Checks the validity of `gradients` with finite difference trick.
For this test only, `variables` must be *shared* variables.
Checks the validity of ` gradients ` with finite difference trick . For this test only ` variables ` must be * shared * variables .
pub fn check_theoretical_grads<'g, 't, 'v, F: Float, A>(
    objective: A,
    gradients: &'t [A],
    variables: &'t [A],
    feeder: Feeder<'v, F>,
    eps: F,
    tol: F,
    g: &'g Context<F>,
) where
    A: AsRef<Tensor<'g, F>> + Copy,
{
    let objective = sum_all(objective);
    // backprop
    let theoretical_grads = g
        .evaluator()
        .extend(gradients)
        .set_feeder(feeder.clone())
        .run();
    // for each variable nodes
    for (var_node, th_grad) in variables.iter().zip(theoretical_grads) {
        // Copy gradient array if needed
        let th_copied = if th_grad.as_ref().unwrap().is_standard_layout() {
            None
        } else {
            Some(ndarray_ext::deep_copy(&th_grad.as_ref().unwrap().view()))
        };
        let th_ptr = if let Some(ref inner) = th_copied {
            inner.as_ptr()
        } else {
            th_grad.as_ref().unwrap().as_ptr()
        };
        // for each values
        let v_len = g
            .env()
            .get_array_by_id(
                var_node
                    .as_ref()
                    .get_variable_id()
                    .expect("This is not a variable"),
            )
            .expect("variable array not found")
            .borrow()
            .len();
        for i in 0..v_len as isize {
            let evacuated;
            // +
            unsafe {
                let mut guard_mut = g
                    .env()
                    .get_array_by_id(
                        var_node
                            .as_ref()
                            .get_variable_id()
                            .expect("This is not a variable"),
                    )
                    .expect("variable array not found")
                    .borrow_mut();
                let head = guard_mut.as_mut_ptr();
                evacuated = *head.offset(i);
                *head.offset(i) = evacuated + eps;
            }
            // eval
            let obj_pos_orig = g
                .evaluator()
                .push(objective)
                .set_feeder(feeder.clone())
                .run()
                .remove(0)
                .unwrap();
            let obj_pos = if obj_pos_orig.is_standard_layout() {
                obj_pos_orig
            } else {
                ndarray_ext::deep_copy(&obj_pos_orig.view())
            };
            unsafe {
                let mut guard_mut = g
                    .env()
                    .get_array_by_id(
                        var_node
                            .as_ref()
                            .get_variable_id()
                            .expect("This is not a variable"),
                    )
                    .expect("variable array not found")
                    .borrow_mut();
                let head = guard_mut.as_mut_ptr();
                *head.offset(i) = evacuated - eps;
            }
            // eval
            let obj_neg_orig = g
                .evaluator()
                .push(objective)
                .set_feeder(feeder.clone())
                .run()
                .remove(0)
                .unwrap();
            let obj_neg = if obj_neg_orig.is_standard_layout() {
                obj_neg_orig
            } else {
                ndarray_ext::deep_copy(&obj_neg_orig.view())
            };
            // restore
            unsafe {
                let mut guard_mut = g
                    .env()
                    .get_array_by_id(
                        var_node
                            .as_ref()
                            .get_variable_id()
                            .expect("This is not a variable"),
                    )
                    .expect("variable array not found")
                    .borrow_mut();
                let head = guard_mut.as_mut_ptr();
                *head.offset(i) = evacuated;
            }
            let two = F::one() + F::one();
            let g_num = (obj_pos - obj_neg).scalar_sum() / (two * eps);
            let g_th = unsafe { *th_ptr.offset(i) };
            // compare
            let diff = (g_num - g_th).abs();
            if diff > tol {
                panic!(
                    "Gradient checking failed with too large error: numerical={}, theoretical={}",
                    g_num, g_th
                );
            }
        }
    }
}
pub fn check_theoretical_grads < ' g , ' t , ' v , F : Float , A > ( objective : A , gradients : & ' t [ A ] , variables : & ' t [ A ] , feeder : Feeder < ' v , F > , eps : F , tol : F , g : & ' g Context < F > , ) where A : AsRef < Tensor < ' g , F > > + Copy , { let objective = sum_all ( objective ) ; // backprop let theoretical_grads = g . evaluator ( ) . extend ( gradients ) . set_feeder ( feeder . clone ( ) ) . run ( ) ; // for each variable nodes for ( var_node , th_grad ) in variables . iter ( ) . zip ( theoretical_grads ) { // Copy gradient array if needed let th_copied = if th_grad . as_ref ( ) . unwrap ( ) . is_standard_layout ( ) { None } else { Some ( ndarray_ext :: deep_copy ( & th_grad . as_ref ( ) . unwrap ( ) . view ( ) ) ) } ; let th_ptr = if let Some ( ref inner ) = th_copied { inner . as_ptr ( ) } else { th_grad . as_ref ( ) . unwrap ( ) . as_ptr ( ) } ; // for each values let v_len = g . env ( ) . get_array_by_id ( var_node . as_ref ( ) . get_variable_id ( ) . expect ( " " ) , ) . expect ( " " ) . borrow ( ) . len ( ) ; for i in 0 .. v_len as isize { let evacuated ; // + unsafe { let mut guard_mut = g . env ( ) . get_array_by_id ( var_node . as_ref ( ) . get_variable_id ( ) . expect ( " " ) , ) . expect ( " " ) . borrow_mut ( ) ; let head = guard_mut . as_mut_ptr ( ) ; evacuated = * head . offset ( i ) ; * head . offset ( i ) = evacuated + eps ; } // eval let obj_pos_orig = g . evaluator ( ) . push ( objective ) . set_feeder ( feeder . clone ( ) ) . run ( ) . remove ( 0 ) . unwrap ( ) ; let obj_pos = if obj_pos_orig . is_standard_layout ( ) { obj_pos_orig } else { ndarray_ext :: deep_copy ( & obj_pos_orig . view ( ) ) } ; unsafe { let mut guard_mut = g . env ( ) . get_array_by_id ( var_node . as_ref ( ) . get_variable_id ( ) . expect ( " " ) , ) . expect ( " " ) . borrow_mut ( ) ; let head = guard_mut . as_mut_ptr ( ) ; * head . offset ( i ) = evacuated - eps ; } // eval let obj_neg_orig = g . evaluator ( ) . push ( objective ) . set_feeder ( feeder . clone ( ) ) . run ( ) . remove ( 0 ) . unwrap ( ) ; let obj_neg = if obj_neg_orig . is_standard_layout ( ) { obj_neg_orig } else { ndarray_ext :: deep_copy ( & obj_neg_orig . view ( ) ) } ; // restore unsafe { let mut guard_mut = g . env ( ) . get_array_by_id ( var_node . as_ref ( ) . get_variable_id ( ) . expect ( " " ) , ) . expect ( " " ) . borrow_mut ( ) ; let head = guard_mut . as_mut_ptr ( ) ; * head . offset ( i ) = evacuated ; } let two = F :: one ( ) + F :: one ( ) ; let g_num = ( obj_pos - obj_neg ) . scalar_sum ( ) / ( two * eps ) ; let g_th = unsafe { * th_ptr . offset ( i ) } ; // compare let diff = ( g_num - g_th ) . abs ( ) ; if diff > tol { panic ! ( " " g_num g_th ) ; } } } }
Checks the validity of `gradients` with finite difference trick.
Checks the validity of ` gradients ` with finite difference trick .
objective
A
gradients
&'t [A]
variables
&'t [A]
feeder
Feeder<'v, F>
eps
F
tol
F
g
&'g Context<F>
objective
A
gradients
&'t [A]
variables
&'t [A]
feeder
Feeder<'v, F>
eps
F
tol
F
g
&'g Context<F>