Skip to content

Commit 9dc809e

Browse files
author
zhouwg
committed
ggml: fix typo in ggml.c
1 parent 67d1ef2 commit 9dc809e

File tree

1 file changed

+58
-58
lines changed

1 file changed

+58
-58
lines changed

‎ggml/src/ggml.c‎

Lines changed: 58 additions & 58 deletions
Original file line numberDiff line numberDiff line change
@@ -330,7 +330,7 @@ void * ggml_aligned_malloc(size_t size) {
330330
#endif
331331
if (result != 0) {
332332
// Handle allocation failure
333-
const char *error_desc = "unknown allocation error";
333+
const char * error_desc = "unknown allocation error";
334334
switch (result) {
335335
case EINVAL:
336336
error_desc = "invalid alignment value";
@@ -1174,13 +1174,13 @@ void ggml_print_objects(const struct ggml_context * ctx) {
11741174
int64_t ggml_nelements(const struct ggml_tensor * tensor) {
11751175
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
11761176

1177-
return tensor->ne[0]*tensor->ne[1]*tensor->ne[2]*tensor->ne[3];
1177+
return tensor->ne[0] * tensor->ne[1] * tensor->ne[2] * tensor->ne[3];
11781178
}
11791179

11801180
int64_t ggml_nrows(const struct ggml_tensor * tensor) {
11811181
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
11821182

1183-
return tensor->ne[1]*tensor->ne[2]*tensor->ne[3];
1183+
return tensor->ne[1] * tensor->ne[2] * tensor->ne[3];
11841184
}
11851185

11861186
size_t ggml_nbytes(const struct ggml_tensor * tensor) {
@@ -1194,14 +1194,14 @@ size_t ggml_nbytes(const struct ggml_tensor * tensor) {
11941194
const size_t blck_size = ggml_blck_size(tensor->type);
11951195
if (blck_size == 1) {
11961196
nbytes = ggml_type_size(tensor->type);
1197-
for (int i = 0; i < GGML_MAX_DIMS; ++i) {
1198-
nbytes += (tensor->ne[i] - 1)*tensor->nb[i];
1197+
for (size_t i = 0; i < GGML_MAX_DIMS; ++i) {
1198+
nbytes += (tensor->ne[i] - 1) * tensor->nb[i];
11991199
}
12001200
}
12011201
else {
1202-
nbytes = tensor->ne[0]*tensor->nb[0]/blck_size;
1203-
for (int i = 1; i < GGML_MAX_DIMS; ++i) {
1204-
nbytes += (tensor->ne[i] - 1)*tensor->nb[i];
1202+
nbytes = tensor->ne[0] * tensor->nb[0] / blck_size;
1203+
for (size_t i = 1; i < GGML_MAX_DIMS; ++i) {
1204+
nbytes += (tensor->ne[i] - 1) * tensor->nb[i];
12051205
}
12061206
}
12071207

@@ -1222,11 +1222,11 @@ size_t ggml_type_size(enum ggml_type type) {
12221222

12231223
size_t ggml_row_size(enum ggml_type type, int64_t ne) {
12241224
assert(ne % ggml_blck_size(type) == 0);
1225-
return ggml_type_size(type)*ne/ggml_blck_size(type);
1225+
return ggml_type_size(type) * ne / ggml_blck_size(type);
12261226
}
12271227

12281228
double ggml_type_sizef(enum ggml_type type) {
1229-
return ((double)(type_traits[type].type_size))/type_traits[type].blck_size;
1229+
return ((double)(type_traits[type].type_size)) / type_traits[type].blck_size;
12301230
}
12311231

12321232
const char * ggml_type_name(enum ggml_type type) {
@@ -1304,19 +1304,19 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
13041304
enum ggml_type wtype = GGML_TYPE_COUNT;
13051305

13061306
switch (ftype) {
1307-
case GGML_FTYPE_ALL_F32: wtype = GGML_TYPE_F32; break;
1308-
case GGML_FTYPE_MOSTLY_F16: wtype = GGML_TYPE_F16; break;
1309-
case GGML_FTYPE_MOSTLY_BF16: wtype = GGML_TYPE_BF16; break;
1310-
case GGML_FTYPE_MOSTLY_Q4_0: wtype = GGML_TYPE_Q4_0; break;
1311-
case GGML_FTYPE_MOSTLY_Q4_1: wtype = GGML_TYPE_Q4_1; break;
1312-
case GGML_FTYPE_MOSTLY_Q5_0: wtype = GGML_TYPE_Q5_0; break;
1313-
case GGML_FTYPE_MOSTLY_Q5_1: wtype = GGML_TYPE_Q5_1; break;
1314-
case GGML_FTYPE_MOSTLY_Q8_0: wtype = GGML_TYPE_Q8_0; break;
1315-
case GGML_FTYPE_MOSTLY_Q2_K: wtype = GGML_TYPE_Q2_K; break;
1316-
case GGML_FTYPE_MOSTLY_Q3_K: wtype = GGML_TYPE_Q3_K; break;
1317-
case GGML_FTYPE_MOSTLY_Q4_K: wtype = GGML_TYPE_Q4_K; break;
1318-
case GGML_FTYPE_MOSTLY_Q5_K: wtype = GGML_TYPE_Q5_K; break;
1319-
case GGML_FTYPE_MOSTLY_Q6_K: wtype = GGML_TYPE_Q6_K; break;
1307+
case GGML_FTYPE_ALL_F32: wtype = GGML_TYPE_F32; break;
1308+
case GGML_FTYPE_MOSTLY_F16: wtype = GGML_TYPE_F16; break;
1309+
case GGML_FTYPE_MOSTLY_BF16: wtype = GGML_TYPE_BF16; break;
1310+
case GGML_FTYPE_MOSTLY_Q4_0: wtype = GGML_TYPE_Q4_0; break;
1311+
case GGML_FTYPE_MOSTLY_Q4_1: wtype = GGML_TYPE_Q4_1; break;
1312+
case GGML_FTYPE_MOSTLY_Q5_0: wtype = GGML_TYPE_Q5_0; break;
1313+
case GGML_FTYPE_MOSTLY_Q5_1: wtype = GGML_TYPE_Q5_1; break;
1314+
case GGML_FTYPE_MOSTLY_Q8_0: wtype = GGML_TYPE_Q8_0; break;
1315+
case GGML_FTYPE_MOSTLY_Q2_K: wtype = GGML_TYPE_Q2_K; break;
1316+
case GGML_FTYPE_MOSTLY_Q3_K: wtype = GGML_TYPE_Q3_K; break;
1317+
case GGML_FTYPE_MOSTLY_Q4_K: wtype = GGML_TYPE_Q4_K; break;
1318+
case GGML_FTYPE_MOSTLY_Q5_K: wtype = GGML_TYPE_Q5_K; break;
1319+
case GGML_FTYPE_MOSTLY_Q6_K: wtype = GGML_TYPE_Q6_K; break;
13201320
case GGML_FTYPE_MOSTLY_IQ2_XXS: wtype = GGML_TYPE_IQ2_XXS; break;
13211321
case GGML_FTYPE_MOSTLY_IQ2_XS: wtype = GGML_TYPE_IQ2_XS; break;
13221322
case GGML_FTYPE_MOSTLY_IQ3_XXS: wtype = GGML_TYPE_IQ3_XXS; break;
@@ -1326,8 +1326,8 @@ enum ggml_type ggml_ftype_to_ggml_type(enum ggml_ftype ftype) {
13261326
case GGML_FTYPE_MOSTLY_IQ4_XS: wtype = GGML_TYPE_IQ4_XS; break;
13271327
case GGML_FTYPE_MOSTLY_IQ3_S: wtype = GGML_TYPE_IQ3_S; break;
13281328
case GGML_FTYPE_MOSTLY_IQ2_S: wtype = GGML_TYPE_IQ2_S; break;
1329-
case GGML_FTYPE_UNKNOWN: wtype = GGML_TYPE_COUNT; break;
1330-
case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16: wtype = GGML_TYPE_COUNT; break;
1329+
case GGML_FTYPE_UNKNOWN: wtype = GGML_TYPE_COUNT; break;
1330+
case GGML_FTYPE_MOSTLY_Q4_1_SOME_F16: wtype = GGML_TYPE_COUNT; break;
13311331
}
13321332

13331333
GGML_ASSERT(wtype != GGML_TYPE_COUNT);
@@ -1348,7 +1348,7 @@ static bool ggml_is_contiguous_n(const struct ggml_tensor * tensor, int n) {
13481348
if (tensor->ne[0] != ggml_blck_size(tensor->type) && tensor->nb[0] != next_nb) {
13491349
return false;
13501350
}
1351-
next_nb *= tensor->ne[0]/ggml_blck_size(tensor->type);
1351+
next_nb *= tensor->ne[0] / ggml_blck_size(tensor->type);
13521352
for (int i = 1; i < GGML_MAX_DIMS; i++) {
13531353
if (tensor->ne[i] != 1) {
13541354
if (i > n) {
@@ -1358,7 +1358,7 @@ static bool ggml_is_contiguous_n(const struct ggml_tensor * tensor, int n) {
13581358
next_nb *= tensor->ne[i];
13591359
} else {
13601360
// this dimension does not need to be contiguous
1361-
next_nb = tensor->ne[i]*tensor->nb[i];
1361+
next_nb = tensor->ne[i] * tensor->nb[i];
13621362
}
13631363
}
13641364
}
@@ -1382,7 +1382,7 @@ bool ggml_is_contiguous_2(const struct ggml_tensor * tensor) {
13821382
}
13831383

13841384
bool ggml_is_contiguously_allocated(const struct ggml_tensor * tensor) {
1385-
return ggml_nbytes(tensor) == ggml_nelements(tensor) * ggml_type_size(tensor->type)/ggml_blck_size(tensor->type);
1385+
return ggml_nbytes(tensor) == ggml_nelements(tensor) * ggml_type_size(tensor->type) / ggml_blck_size(tensor->type);
13861386
}
13871387

13881388
bool ggml_is_permuted(const struct ggml_tensor * tensor) {
@@ -1409,8 +1409,8 @@ static inline bool ggml_is_padded_1d(const struct ggml_tensor * tensor) {
14091409

14101410
return
14111411
tensor->nb[0] == ggml_type_size(tensor->type) &&
1412-
tensor->nb[2] == tensor->nb[1]*tensor->ne[1] &&
1413-
tensor->nb[3] == tensor->nb[2]*tensor->ne[2];
1412+
tensor->nb[2] == tensor->nb[1] * tensor->ne[1] &&
1413+
tensor->nb[3] == tensor->nb[2] * tensor->ne[2];
14141414
}
14151415

14161416
bool ggml_is_empty(const struct ggml_tensor * tensor) {
@@ -1675,9 +1675,9 @@ static struct ggml_tensor * ggml_new_tensor_impl(
16751675
}
16761676

16771677
result->nb[0] = ggml_type_size(type);
1678-
result->nb[1] = result->nb[0]*(result->ne[0]/ggml_blck_size(type));
1679-
for (int i = 2; i < GGML_MAX_DIMS; i++) {
1680-
result->nb[i] = result->nb[i - 1]*result->ne[i - 1];
1678+
result->nb[1] = result->nb[0] * (result->ne[0] / ggml_blck_size(type));
1679+
for (size_t i = 2; i < GGML_MAX_DIMS; i++) {
1680+
result->nb[i] = result->nb[i - 1] * result->ne[i - 1];
16811681
}
16821682

16831683
ctx->n_objects++;
@@ -1745,22 +1745,22 @@ void ggml_unravel_index(const struct ggml_tensor * tensor, int64_t i, int64_t *
17451745
const int64_t ne1 = tensor->ne[1];
17461746
const int64_t ne0 = tensor->ne[0];
17471747

1748-
const int64_t i3_ = (i/(ne2*ne1*ne0));
1749-
const int64_t i2_ = (i - i3_*ne2*ne1*ne0)/(ne1*ne0);
1750-
const int64_t i1_ = (i - i3_*ne2*ne1*ne0 - i2_*ne1*ne0)/ne0;
1751-
const int64_t i0_ = (i - i3_*ne2*ne1*ne0 - i2_*ne1*ne0 - i1_*ne0);
1748+
const int64_t i3_ = (i / (ne2 * ne1 * ne0));
1749+
const int64_t i2_ = (i - i3_ * ne2 * ne1 * ne0) / (ne1 * ne0);
1750+
const int64_t i1_ = (i - i3_ * ne2 * ne1 * ne0 - i2_ * ne1 * ne0) / ne0;
1751+
const int64_t i0_ = (i - i3_ * ne2 * ne1 * ne0 - i2_ * ne1 * ne0 - i1_ * ne0);
17521752

17531753
if (i0) {
1754-
* i0 = i0_;
1754+
*i0 = i0_;
17551755
}
17561756
if (i1) {
1757-
* i1 = i1_;
1757+
*i1 = i1_;
17581758
}
17591759
if (i2) {
1760-
* i2 = i2_;
1760+
*i2 = i2_;
17611761
}
17621762
if (i3) {
1763-
* i3 = i3_;
1763+
*i3 = i3_;
17641764
}
17651765
}
17661766

@@ -1810,7 +1810,7 @@ struct ggml_tensor * ggml_view_tensor(
18101810
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, src->type, GGML_MAX_DIMS, src->ne, src, 0);
18111811
ggml_format_name(result, "%s (view)", src->name);
18121812

1813-
for (int i = 0; i < GGML_MAX_DIMS; i++) {
1813+
for (size_t i = 0; i < GGML_MAX_DIMS; i++) {
18141814
result->nb[i] = src->nb[i];
18151815
}
18161816

@@ -2290,7 +2290,7 @@ struct ggml_tensor * ggml_sum_rows(
22902290
struct ggml_context * ctx,
22912291
struct ggml_tensor * a) {
22922292
int64_t ne[GGML_MAX_DIMS] = { 1 };
2293-
for (int i = 1; i < GGML_MAX_DIMS; ++i) {
2293+
for (size_t i = 1; i < GGML_MAX_DIMS; ++i) {
22942294
ne[i] = a->ne[i];
22952295
}
22962296

@@ -2678,7 +2678,7 @@ static struct ggml_tensor * ggml_glu_impl(
26782678
GGML_ASSERT(a->type == b->type);
26792679
}
26802680

2681-
int64_t ne[GGML_MAX_DIMS] = { a->ne[0] / 2 }; for (int i = 1; i < GGML_MAX_DIMS; i++) ne[i] = a->ne[i];
2681+
int64_t ne[GGML_MAX_DIMS] = { a->ne[0] / 2 }; for (size_t i = 1; i < GGML_MAX_DIMS; i++) ne[i] = a->ne[i];
26822682
struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, GGML_MAX_DIMS, b ? a->ne : ne, NULL, 0);
26832683

26842684
ggml_set_op_params_i32(result, 0, (int32_t) op);
@@ -2963,9 +2963,9 @@ struct ggml_tensor * ggml_l2_norm_inplace(
29632963
static inline bool ggml_can_mul_mat(const struct ggml_tensor * t0, const struct ggml_tensor * t1) {
29642964
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
29652965

2966-
return (t0->ne[0] == t1->ne[0]) &&
2967-
(t1->ne[2]%t0->ne[2] == 0) && // verify t0 is broadcastable
2968-
(t1->ne[3]%t0->ne[3] == 0);
2966+
return (t0->ne[0] == t1->ne[0]) &&
2967+
(t1->ne[2] % t0->ne[2] == 0) && // verify t0 is broadcastable
2968+
(t1->ne[3] % t0->ne[3] == 0);
29692969
}
29702970

29712971
struct ggml_tensor * ggml_mul_mat(
@@ -3040,9 +3040,9 @@ struct ggml_tensor * ggml_mul_mat_id(
30403040
static inline bool ggml_can_out_prod(const struct ggml_tensor * t0, const struct ggml_tensor * t1) {
30413041
static_assert(GGML_MAX_DIMS == 4, "GGML_MAX_DIMS is not 4 - update this function");
30423042

3043-
return (t0->ne[1] == t1->ne[1]) &&
3044-
(t1->ne[2]%t0->ne[2] == 0) && // verify t0 is broadcastable
3045-
(t1->ne[3]%t0->ne[3] == 0);
3043+
return (t0->ne[1] == t1->ne[1]) &&
3044+
(t1->ne[2] % t0->ne[2] == 0) && // verify t0 is broadcastable
3045+
(t1->ne[3] % t0->ne[3] == 0);
30463046
}
30473047

30483048
struct ggml_tensor * ggml_out_prod(
@@ -3720,8 +3720,8 @@ static struct ggml_tensor * ggml_soft_max_impl(
37203720
GGML_ASSERT(ggml_is_contiguous(mask));
37213721
GGML_ASSERT(mask->ne[0] == a->ne[0]);
37223722
GGML_ASSERT(mask->ne[1] >= a->ne[1]);
3723-
GGML_ASSERT(a->ne[2]%mask->ne[2] == 0);
3724-
GGML_ASSERT(a->ne[3]%mask->ne[3] == 0);
3723+
GGML_ASSERT(a->ne[2] % mask->ne[2] == 0);
3724+
GGML_ASSERT(a->ne[3] % mask->ne[3] == 0);
37253725
}
37263726

37273727
if (max_bias > 0.0f) {
@@ -4418,7 +4418,7 @@ struct ggml_tensor * ggml_conv_transpose_2d_p0(
44184418
a->ne[2], b->ne[3],
44194419
};
44204420

4421-
struct ggml_tensor* result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne);
4421+
struct ggml_tensor * result = ggml_new_tensor(ctx, GGML_TYPE_F32, 4, ne);
44224422

44234423
ggml_set_op_params_i32(result, 0, stride);
44244424

@@ -5043,8 +5043,8 @@ static struct ggml_tensor * ggml_add_rel_pos_impl(
50435043
GGML_ASSERT(ph->type == GGML_TYPE_F32);
50445044
GGML_ASSERT(pw->type == GGML_TYPE_F32);
50455045
GGML_ASSERT(pw->ne[3] == a->ne[2]);
5046-
GGML_ASSERT(pw->ne[0]*pw->ne[0] == a->ne[0]);
5047-
GGML_ASSERT(pw->ne[1]*pw->ne[2] == a->ne[1]);
5046+
GGML_ASSERT(pw->ne[0] * pw->ne[0] == a->ne[0]);
5047+
GGML_ASSERT(pw->ne[1] * pw->ne[2] == a->ne[1]);
50485048

50495049
struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
50505050
ggml_set_op_params_i32(result, 0, inplace ? 1 : 0);
@@ -5544,7 +5544,7 @@ size_t ggml_hash_size(size_t min_sz) {
55445544
size_t l = 0;
55455545
size_t r = n_primes;
55465546
while (l < r) {
5547-
size_t m = (l + r)/2;
5547+
size_t m = (l + r) / 2;
55485548
if (primes[m] < min_sz) {
55495549
l = m + 1;
55505550
} else {
@@ -6138,7 +6138,7 @@ static size_t ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor
61386138
return node_hash_pos;
61396139
}
61406140

6141-
for (int i = 0; i < GGML_MAX_SRC; ++i) {
6141+
for (size_t i = 0; i < GGML_MAX_SRC; ++i) {
61426142
const int k =
61436143
(cgraph->order == GGML_CGRAPH_EVAL_ORDER_LEFT_TO_RIGHT) ? i :
61446144
(cgraph->order == GGML_CGRAPH_EVAL_ORDER_RIGHT_TO_LEFT) ? (GGML_MAX_SRC-1-i) :
@@ -6260,7 +6260,7 @@ void ggml_build_backward_expand(
62606260
default:
62616261
break;
62626262
}
6263-
for (int j = 0; j < GGML_MAX_SRC; ++j) {
6263+
for (size_t j = 0; j < GGML_MAX_SRC; ++j) {
62646264
if (!node->src[j] || ignore_src[j] || !grads_needed[ggml_hash_find(&cgraph->visited_hash_set, node->src[j])]) {
62656265
continue;
62666266
}

0 commit comments

Comments
 (0)