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ggml : GGML_ASSERT() instead of assert() where appropriate

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gq
Georgi Gerganov 1 year ago
parent 11295af7a6
commit e052167772
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GPG Key ID: 449E073F9DC10735
1 changed files with 106 additions and 107 deletions
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213
src/ggml.c
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@ -2413,7 +2413,7 @@ struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value) {
} break;
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
@ -2473,7 +2473,7 @@ struct ggml_tensor * ggml_set_f32(struct ggml_tensor * tensor, float value) {
} break;
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
@ -2710,7 +2710,7 @@ struct ggml_tensor * ggml_add_impl(
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
assert(ggml_are_same_shape(a, b));
GGML_ASSERT(ggml_are_same_shape(a, b));
bool is_node = false;
@ -2749,7 +2749,7 @@ struct ggml_tensor * ggml_sub_impl(
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
assert(ggml_are_same_shape(a, b));
GGML_ASSERT(ggml_are_same_shape(a, b));
bool is_node = false;
@ -2788,7 +2788,7 @@ struct ggml_tensor * ggml_mul_impl(
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
assert(ggml_are_same_shape(a, b));
GGML_ASSERT(ggml_are_same_shape(a, b));
bool is_node = false;
@ -2797,7 +2797,7 @@ struct ggml_tensor * ggml_mul_impl(
}
if (inplace) {
assert(is_node == false);
GGML_ASSERT(is_node == false);
}
struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
@ -2831,7 +2831,7 @@ struct ggml_tensor * ggml_div_impl(
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
assert(ggml_are_same_shape(a, b));
GGML_ASSERT(ggml_are_same_shape(a, b));
bool is_node = false;
@ -2840,7 +2840,7 @@ struct ggml_tensor * ggml_div_impl(
}
if (inplace) {
assert(is_node == false);
GGML_ASSERT(is_node == false);
}
struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
@ -2964,7 +2964,7 @@ struct ggml_tensor * ggml_mean(
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement
GGML_ASSERT(false); // TODO: implement
is_node = true;
}
@ -2985,7 +2985,7 @@ struct ggml_tensor * ggml_repeat(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
assert(ggml_can_repeat(a, b));
GGML_ASSERT(ggml_can_repeat(a, b));
bool is_node = false;
@ -3221,7 +3221,7 @@ struct ggml_tensor * ggml_norm_impl(
bool is_node = false;
if (!inplace && (a->grad)) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3253,7 +3253,7 @@ struct ggml_tensor * ggml_mul_mat(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
assert(ggml_can_mul_mat(a, b));
GGML_ASSERT(ggml_can_mul_mat(a, b));
bool is_node = false;
@ -3279,13 +3279,13 @@ struct ggml_tensor * ggml_scale_impl(
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
assert(ggml_is_scalar(b));
assert(ggml_is_padded_1d(a));
GGML_ASSERT(ggml_is_scalar(b));
GGML_ASSERT(ggml_is_padded_1d(a));
bool is_node = false;
if (!inplace && (a->grad || b->grad)) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3322,12 +3322,12 @@ struct ggml_tensor * ggml_cpy_impl(
struct ggml_tensor * a,
struct ggml_tensor * b,
bool inplace) {
assert(ggml_nelements(a) == ggml_nelements(b));
GGML_ASSERT(ggml_nelements(a) == ggml_nelements(b));
bool is_node = false;
if (!inplace && (a->grad || b->grad)) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3362,14 +3362,14 @@ struct ggml_tensor * ggml_reshape(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
assert(ggml_is_contiguous(a));
assert(ggml_is_contiguous(b));
assert(ggml_nelements(a) == ggml_nelements(b));
GGML_ASSERT(ggml_is_contiguous(a));
GGML_ASSERT(ggml_is_contiguous(b));
GGML_ASSERT(ggml_nelements(a) == ggml_nelements(b));
bool is_node = false;
if (a->grad || b->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3388,13 +3388,13 @@ struct ggml_tensor * ggml_reshape_2d(
struct ggml_tensor * a,
int ne0,
int ne1) {
assert(ggml_is_contiguous(a));
assert(ggml_nelements(a) == ne0*ne1);
GGML_ASSERT(ggml_is_contiguous(a));
GGML_ASSERT(ggml_nelements(a) == ne0*ne1);
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3415,13 +3415,13 @@ struct ggml_tensor * ggml_reshape_3d(
int ne0,
int ne1,
int ne2) {
assert(ggml_is_contiguous(a));
assert(ggml_nelements(a) == ne0*ne1*ne2);
GGML_ASSERT(ggml_is_contiguous(a));
GGML_ASSERT(ggml_nelements(a) == ne0*ne1*ne2);
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3444,7 +3444,7 @@ struct ggml_tensor * ggml_view_1d(
int ne0,
size_t offset) {
if (a->grad) {
assert(false); // gradient propagation is not supported
GGML_ASSERT(false); // gradient propagation is not supported
}
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 1, &ne0, (char *) a->data + offset);
@ -3467,7 +3467,7 @@ struct ggml_tensor * ggml_view_2d(
size_t nb1,
size_t offset) {
if (a->grad) {
assert(false); // gradient propagation is not supported
GGML_ASSERT(false); // gradient propagation is not supported
}
const int ne[GGML_MAX_DIMS] = { ne0, ne1, 1, 1 };
@ -3495,22 +3495,22 @@ struct ggml_tensor * ggml_permute(
int axis1,
int axis2,
int axis3) {
assert(axis0 >= 0 && axis0 < GGML_MAX_DIMS);
assert(axis1 >= 0 && axis1 < GGML_MAX_DIMS);
assert(axis2 >= 0 && axis2 < GGML_MAX_DIMS);
assert(axis3 >= 0 && axis3 < GGML_MAX_DIMS);
assert(axis0 != axis1);
assert(axis0 != axis2);
assert(axis0 != axis3);
assert(axis1 != axis2);
assert(axis1 != axis3);
assert(axis2 != axis3);
GGML_ASSERT(axis0 >= 0 && axis0 < GGML_MAX_DIMS);
GGML_ASSERT(axis1 >= 0 && axis1 < GGML_MAX_DIMS);
GGML_ASSERT(axis2 >= 0 && axis2 < GGML_MAX_DIMS);
GGML_ASSERT(axis3 >= 0 && axis3 < GGML_MAX_DIMS);
GGML_ASSERT(axis0 != axis1);
GGML_ASSERT(axis0 != axis2);
GGML_ASSERT(axis0 != axis3);
GGML_ASSERT(axis1 != axis2);
GGML_ASSERT(axis1 != axis3);
GGML_ASSERT(axis2 != axis3);
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3555,7 +3555,7 @@ struct ggml_tensor * ggml_transpose(
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3581,12 +3581,12 @@ struct ggml_tensor * ggml_get_rows(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
assert(ggml_is_matrix(a) && ggml_is_vector(b) && b->type == GGML_TYPE_I32);
GGML_ASSERT(ggml_is_matrix(a) && ggml_is_vector(b) && b->type == GGML_TYPE_I32);
bool is_node = false;
if (a->grad || b->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3611,7 +3611,7 @@ struct ggml_tensor * ggml_diag_mask_inf(
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3636,7 +3636,7 @@ struct ggml_tensor * ggml_soft_max(
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3660,11 +3660,11 @@ struct ggml_tensor * ggml_rope(
int n_past,
int n_dims,
int mode) {
assert(n_past >= 0);
GGML_ASSERT(n_past >= 0);
bool is_node = false;
if (a->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3691,13 +3691,13 @@ struct ggml_tensor * ggml_conv_1d_1s(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
assert(ggml_is_matrix(b));
assert(a->ne[1] == b->ne[1]);
assert(a->ne[3] == 1);
GGML_ASSERT(ggml_is_matrix(b));
GGML_ASSERT(a->ne[1] == b->ne[1]);
GGML_ASSERT(a->ne[3] == 1);
bool is_node = false;
if (a->grad || b->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3718,13 +3718,13 @@ struct ggml_tensor * ggml_conv_1d_2s(
struct ggml_context * ctx,
struct ggml_tensor * a,
struct ggml_tensor * b) {
assert(ggml_is_matrix(b));
assert(a->ne[1] == b->ne[1]);
assert(a->ne[3] == 1);
GGML_ASSERT(ggml_is_matrix(b));
GGML_ASSERT(a->ne[1] == b->ne[1]);
GGML_ASSERT(a->ne[3] == 1);
bool is_node = false;
if (a->grad || b->grad) {
assert(false); // TODO: implement backward
GGML_ASSERT(false); // TODO: implement backward
is_node = true;
}
@ -3747,7 +3747,7 @@ struct ggml_tensor * ggml_flash_attn(
struct ggml_tensor * k,
struct ggml_tensor * v,
bool masked) {
assert(ggml_can_mul_mat(k, q));
GGML_ASSERT(ggml_can_mul_mat(k, q));
// TODO: check if vT can be multiplied by (k*qT)
bool is_node = false;
@ -3779,7 +3779,7 @@ struct ggml_tensor * ggml_flash_ff(
struct ggml_tensor * b1,
struct ggml_tensor * c0,
struct ggml_tensor * c1) {
assert(ggml_can_mul_mat(b0, a));
GGML_ASSERT(ggml_can_mul_mat(b0, a));
// TODO: more checks
bool is_node = false;
@ -3810,7 +3810,7 @@ void ggml_set_param(
struct ggml_tensor * tensor) {
tensor->is_param = true;
assert(tensor->grad == NULL);
GGML_ASSERT(tensor->grad == NULL);
tensor->grad = ggml_dup_tensor(ctx, tensor);
}
@ -3820,9 +3820,9 @@ static void ggml_compute_forward_dup_f16(
const struct ggml_compute_params * params,
const struct ggml_tensor * src0,
struct ggml_tensor * dst) {
assert(params->ith == 0);
assert(ggml_is_contiguous(dst));
assert(ggml_nelements(dst) == ggml_nelements(src0));
GGML_ASSERT(params->ith == 0);
GGML_ASSERT(ggml_is_contiguous(dst));
GGML_ASSERT(ggml_nelements(dst) == ggml_nelements(src0));
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
return;
@ -4122,7 +4122,7 @@ static void ggml_compute_forward_add(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4174,7 +4174,7 @@ static void ggml_compute_forward_sub(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4226,7 +4226,7 @@ static void ggml_compute_forward_mul(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4278,7 +4278,7 @@ static void ggml_compute_forward_div(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4326,7 +4326,7 @@ static void ggml_compute_forward_sqr(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4374,7 +4374,7 @@ static void ggml_compute_forward_sqrt(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4432,7 +4432,7 @@ static void ggml_compute_forward_sum(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4509,7 +4509,7 @@ static void ggml_compute_forward_mean(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4573,7 +4573,7 @@ static void ggml_compute_forward_repeat(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4621,7 +4621,7 @@ static void ggml_compute_forward_abs(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4669,7 +4669,7 @@ static void ggml_compute_forward_sgn(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4717,7 +4717,7 @@ static void ggml_compute_forward_neg(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4765,7 +4765,7 @@ static void ggml_compute_forward_step(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4813,7 +4813,7 @@ static void ggml_compute_forward_relu(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4878,7 +4878,7 @@ static void ggml_compute_forward_gelu(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
@ -4964,7 +4964,7 @@ static void ggml_compute_forward_norm(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -4986,10 +4986,9 @@ static bool ggml_compute_forward_mul_mat_use_blas(
const int ne1 = dst->ne[1];
// TODO: find the optimal values for these
if (ggml_is_contiguous(src0) && ggml_is_contiguous(src1) && (
(ne0 >= 32 && ne1 >= 32 && ne10 >= 32)
)) {
printf("BLAS: %d %d %d\n", ne0, ne1, ne10);
if (ggml_is_contiguous(src0) &&
ggml_is_contiguous(src1) && ((ne0 >= 32 && ne1 >= 32 && ne10 >= 32))) {
//printf("BLAS: %d %d %d\n", ne0, ne1, ne10);
return true;
}
@ -6175,7 +6174,7 @@ static void ggml_compute_forward_mul_mat(
case GGML_TYPE_I32:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
@ -6263,7 +6262,7 @@ static void ggml_compute_forward_scale(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -6457,7 +6456,7 @@ static void ggml_compute_forward_get_rows(
case GGML_TYPE_I32:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
@ -6536,7 +6535,7 @@ static void ggml_compute_forward_diag_mask_inf(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -6630,7 +6629,7 @@ static void ggml_compute_forward_soft_max(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -6712,7 +6711,7 @@ static void ggml_compute_forward_rope(
case GGML_TYPE_F16:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -7733,7 +7732,7 @@ static void ggml_compute_forward_flash_attn(
case GGML_TYPE_I32:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -7944,7 +7943,7 @@ static void ggml_compute_forward_flash_ff(
case GGML_TYPE_I32:
case GGML_TYPE_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
@ -7952,7 +7951,7 @@ static void ggml_compute_forward_flash_ff(
/////////////////////////////////
static void ggml_compute_forward(struct ggml_compute_params * params, struct ggml_tensor * tensor) {
assert(params);
GGML_ASSERT(params);
switch (tensor->op) {
case GGML_OP_DUP:
@ -8200,7 +8199,7 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
} break;
case GGML_OP_MEAN:
{
assert(false); // TODO: implement
GGML_ASSERT(false); // TODO: implement
} break;
case GGML_OP_REPEAT:
{
@ -8255,17 +8254,17 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
} break;
case GGML_OP_GELU:
{
assert(false); // TODO: not implemented
GGML_ASSERT(false); // TODO: not implemented
} break;
case GGML_OP_NORM:
{
assert(false); // TODO: not implemented
GGML_ASSERT(false); // TODO: not implemented
} break;
case GGML_OP_MUL_MAT:
{
if (src0->grad) {
// TODO: this requires outer product - ggml_out_prod(ctx, src1, tensor->grad);
assert(false);
GGML_ASSERT(false);
}
if (src1->grad) {
src1->grad =
@ -8381,12 +8380,12 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
if (node->op == GGML_OP_NONE && node->grad == NULL) {
// reached a leaf node, not part of the gradient graph (e.g. a constant)
assert(cgraph->n_leafs < GGML_MAX_NODES);
GGML_ASSERT(cgraph->n_leafs < GGML_MAX_NODES);
cgraph->leafs[cgraph->n_leafs] = node;
cgraph->n_leafs++;
} else {
assert(cgraph->n_nodes < GGML_MAX_NODES);
GGML_ASSERT(cgraph->n_nodes < GGML_MAX_NODES);
cgraph->nodes[cgraph->n_nodes] = node;
cgraph->grads[cgraph->n_nodes] = node->grad;
@ -8410,7 +8409,7 @@ static void ggml_build_forward_impl(struct ggml_cgraph * cgraph, struct ggml_ten
if (n_new > 0) {
// the last added node should always be starting point
assert(cgraph->nodes[cgraph->n_nodes - 1] == tensor);
GGML_ASSERT(cgraph->nodes[cgraph->n_nodes - 1] == tensor);
}
}
@ -8441,7 +8440,7 @@ struct ggml_cgraph ggml_build_forward(struct ggml_tensor * tensor) {
struct ggml_cgraph ggml_build_backward(struct ggml_context * ctx, struct ggml_cgraph * gf, bool keep) {
struct ggml_cgraph result = *gf;
assert(gf->n_nodes > 0);
GGML_ASSERT(gf->n_nodes > 0);
// if we are keeping the gradient graph, we have to detach the gradient nodes from the original graph
if (keep) {
@ -8640,7 +8639,7 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
};
int rc = ggml_thread_create(&workers[j].thrd, NULL, ggml_graph_compute_thread, &workers[j]);
assert(rc == 0);
GGML_ASSERT(rc == 0);
UNUSED(rc);
}
}
@ -8850,13 +8849,13 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
} break;
case GGML_OP_COUNT:
{
assert(false);
GGML_ASSERT(false);
} break;
}
}
if (cgraph->work != NULL && work_size > cgraph->work_size) {
assert(false); // TODO: better handling
GGML_ASSERT(false); // TODO: better handling
}
if (work_size > 0 && cgraph->work == NULL) {
@ -9022,7 +9021,7 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
for (int j = 0; j < n_threads - 1; j++) {
int rc = ggml_thread_join(workers[j].thrd, NULL);
assert(rc == 0);
GGML_ASSERT(rc == 0);
UNUSED(rc);
}
@ -9129,7 +9128,7 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
char color[16];
FILE * fp = fopen(filename, "w");
assert(fp);
GGML_ASSERT(fp);
fprintf(fp, "digraph G {\n");
fprintf(fp, " newrank = true;\n");
@ -9287,7 +9286,7 @@ static enum ggml_opt_result ggml_opt_adam(
struct ggml_tensor * f,
struct ggml_cgraph * gf,
struct ggml_cgraph * gb) {
assert(ggml_is_scalar(f));
GGML_ASSERT(ggml_is_scalar(f));
gf->n_threads = params.n_threads;
gb->n_threads = params.n_threads;
@ -9301,7 +9300,7 @@ static enum ggml_opt_result ggml_opt_adam(
if (gf->nodes[i]->is_param) {
GGML_PRINT_DEBUG("found param %d: grad->op = %d\n", np, gf->nodes[i]->grad->op);
assert(np < GGML_MAX_PARAMS);
GGML_ASSERT(np < GGML_MAX_PARAMS);
ps[np++] = gf->nodes[i];
nx += ggml_nelements(gf->nodes[i]);
@ -9601,7 +9600,7 @@ static enum ggml_opt_result ggml_opt_lbfgs(
if (gf->nodes[i]->is_param) {
GGML_PRINT_DEBUG("found param %d: grad->op = %d\n", np, gf->nodes[i]->grad->op);
assert(np < GGML_MAX_PARAMS);
GGML_ASSERT(np < GGML_MAX_PARAMS);
ps[np++] = gf->nodes[i];
nx += ggml_nelements(gf->nodes[i]);

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