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-rw-r--r--ggml.c158
1 files changed, 142 insertions, 16 deletions
diff --git a/ggml.c b/ggml.c
index d86e594..f4a5a8d 100644
--- a/ggml.c
+++ b/ggml.c
@@ -3472,6 +3472,7 @@ static const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
"ROPE",
"ROPE_BACK",
"ALIBI",
+ "CLAMP",
"CONV_1D_1S",
"CONV_1D_2S",
@@ -3482,7 +3483,8 @@ static const char * GGML_OP_LABEL[GGML_OP_COUNT] = {
"MAP_BINARY",
};
-static_assert(GGML_OP_COUNT == 50, "GGML_OP_COUNT != 50");
+static_assert(GGML_OP_COUNT == 51, "GGML_OP_COUNT != 51");
+
static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
"none",
@@ -3532,6 +3534,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
"rope(x)",
"rope_back(x)",
"alibi(x)",
+ "clamp(x)",
"conv_1d_1s(x)",
"conv_1d_2s(x)",
@@ -3542,7 +3545,7 @@ static const char * GGML_OP_SYMBOL[GGML_OP_COUNT] = {
"f(x,y)",
};
-static_assert(GGML_OP_COUNT == 50, "GGML_OP_COUNT != 50");
+static_assert(GGML_OP_COUNT == 51, "GGML_OP_COUNT != 51");
static_assert(sizeof(struct ggml_object)%GGML_MEM_ALIGN == 0, "ggml_object size must be a multiple of GGML_MEM_ALIGN");
static_assert(sizeof(struct ggml_tensor)%GGML_MEM_ALIGN == 0, "ggml_tensor size must be a multiple of GGML_MEM_ALIGN");
@@ -6214,7 +6217,8 @@ struct ggml_tensor * ggml_alibi(
struct ggml_context * ctx,
struct ggml_tensor * a,
int n_past,
- int n_head) {
+ int n_head,
+ float bias_max) {
GGML_ASSERT(n_past >= 0);
bool is_node = false;
@@ -6233,6 +6237,8 @@ struct ggml_tensor * ggml_alibi(
((int32_t *) b->data)[0] = n_past;
((int32_t *) b->data)[1] = n_head;
+ GGML_ASSERT(sizeof(float) == sizeof(int32_t));
+ (((float *) b->data)[2]) = bias_max;
ggml_scratch_load(ctx);
@@ -6244,6 +6250,40 @@ struct ggml_tensor * ggml_alibi(
return result;
}
+// ggml_clamp
+
+struct ggml_tensor * ggml_clamp(
+ struct ggml_context * ctx,
+ struct ggml_tensor * a,
+ float min,
+ float max) {
+ bool is_node = false;
+
+ if (a->grad) {
+ GGML_ASSERT(false); // TODO: implement backward
+ is_node = true;
+ }
+
+ // TODO: when implement backward, fix this:
+ struct ggml_tensor * result = ggml_view_tensor(ctx, a);
+
+ ggml_scratch_save(ctx);
+
+ struct ggml_tensor * b = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 3);
+
+ ((float *) b->data)[0] = min;
+ ((float *) b->data)[1] = max;
+
+ ggml_scratch_load(ctx);
+
+ result->op = GGML_OP_CLAMP;
+ result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
+ result->src0 = a;
+ result->src1 = b;
+
+ return result;
+}
+
// ggml_conv_1d_1s
struct ggml_tensor * ggml_conv_1d_1s(
@@ -10553,6 +10593,7 @@ static void ggml_compute_forward_diag_mask_f32(
const int n_past = ((int32_t *) src1->data)[0];
const bool inplace = (bool)((int32_t *) src1->data)[1];
+
assert(n_past >= 0);
if (!inplace && (params->type == GGML_TASK_INIT)) {
@@ -10723,14 +10764,15 @@ static void ggml_compute_forward_alibi_f32(
struct ggml_tensor * dst) {
assert(params->ith == 0);
assert(src1->type == GGML_TYPE_I32);
- assert(ggml_nelements(src1) == 2);
+ assert(ggml_nelements(src1) == 3);
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
return;
}
- const int n_past = ((int32_t *) src1->data)[0];
- const int n_head = ((int32_t *) src1->data)[1];
+ const int n_past = ((int32_t *) src1->data)[0];
+ const int n_head = ((int32_t *) src1->data)[1];
+ const float max_bias = ((float *) src1->data)[2];
assert(n_past >= 0);
@@ -10753,8 +10795,8 @@ static void ggml_compute_forward_alibi_f32(
// add alibi to src0 (KQ_scaled)
const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
- const float m0 = powf(2.0f, -8.0f / n_heads_log2_floor);
- const float m1 = powf(2.0f, -4.0f / n_heads_log2_floor);
+ const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor);
+ const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor);
for (int i = 0; i < ne0; i++) {
for (int j = 0; j < ne1; j++) {
@@ -10772,13 +10814,13 @@ static void ggml_compute_forward_alibi_f32(
m_k = powf(m1, 2 * (k - n_heads_log2_floor) + 1);
}
- pdst[0] = i * m_k + src[0];
+ pdst[0] = (i-ne0+1) * m_k + src[0];
+
}
}
}
}
-
static void ggml_compute_forward_alibi_f16(
const struct ggml_compute_params * params,
const struct ggml_tensor * src0,
@@ -10786,14 +10828,15 @@ static void ggml_compute_forward_alibi_f16(
struct ggml_tensor * dst) {
assert(params->ith == 0);
assert(src1->type == GGML_TYPE_I32);
- assert(ggml_nelements(src1) == 2);
+ assert(ggml_nelements(src1) == 3);
if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
return;
}
- const int n_past = ((int32_t *) src1->data)[0];
- const int n_head = ((int32_t *) src1->data)[1];
+ const int n_past = ((int32_t *) src1->data)[0];
+ const int n_head = ((int32_t *) src1->data)[1];
+ const float max_bias = ((float *) src1->data)[2];
assert(n_past >= 0);
@@ -10816,8 +10859,8 @@ static void ggml_compute_forward_alibi_f16(
// add alibi to src0 (KQ_scaled)
const int n_heads_log2_floor = 1 << (int) floor(log2(n_head));
- const float m0 = powf(2.0f, -8.0f / n_heads_log2_floor);
- const float m1 = powf(2.0f, -4.0f / n_heads_log2_floor);
+ const float m0 = powf(2.0f, -(max_bias) / n_heads_log2_floor);
+ const float m1 = powf(2.0f, -(max_bias / 2.0f) / n_heads_log2_floor);
for (int i = 0; i < ne0; i++) {
for (int j = 0; j < ne1; j++) {
@@ -10836,7 +10879,7 @@ static void ggml_compute_forward_alibi_f16(
}
// we return F32
- pdst[0] = i * m_k + GGML_FP16_TO_FP32(src[0]);
+ pdst[0] = (i-ne0+1) * m_k + GGML_FP16_TO_FP32(src[0]);
}
}
}
@@ -10872,6 +10915,77 @@ static void ggml_compute_forward_alibi(
}
}
+
+// ggml_compute_forward_clamp
+
+static void ggml_compute_forward_clamp_f32(
+ const struct ggml_compute_params * params,
+ const struct ggml_tensor * src0,
+ const struct ggml_tensor * src1,
+ struct ggml_tensor * dst) {
+ assert(params->ith == 0);
+ assert(src1->type == GGML_TYPE_I32);
+ assert(ggml_nelements(src1) == 2);
+
+ if (params->type == GGML_TASK_INIT || params->type == GGML_TASK_FINALIZE) {
+ return;
+ }
+
+ const int min = ((float *) src1->data)[0];
+ const int max = ((float *) src1->data)[1];
+
+ const int ith = params->ith;
+ const int nth = params->nth;
+
+ const int n = ggml_nrows(src0);
+ const int nc = src0->ne[0];
+
+ const size_t nb00 = src0->nb[0];
+ const size_t nb01 = src0->nb[1];
+
+ const size_t nb0 = dst->nb[0];
+ const size_t nb1 = dst->nb[1];
+
+ GGML_ASSERT( nb0 == sizeof(float));
+ GGML_ASSERT(nb00 == sizeof(float));
+
+ for (int j = ith; j < n; j += nth) {
+ float * dst_ptr = (float *) ((char *) dst->data + j*nb1);
+ float * src0_ptr = (float *) ((char *) src0->data + j*nb01);
+
+ for (int i = 0; i < nc; i++) {
+ dst_ptr[i] = MAX(MIN(src0_ptr[i], max), min);
+ }
+ }
+}
+
+static void ggml_compute_forward_clamp(
+ const struct ggml_compute_params * params,
+ const struct ggml_tensor * src0,
+ const struct ggml_tensor * src1,
+ struct ggml_tensor * dst) {
+ switch (src0->type) {
+ case GGML_TYPE_F32:
+ {
+ ggml_compute_forward_clamp_f32(params, src0, src1, dst);
+ } break;
+ case GGML_TYPE_F16:
+ case GGML_TYPE_Q4_0:
+ case GGML_TYPE_Q4_1:
+ case GGML_TYPE_Q5_0:
+ case GGML_TYPE_Q5_1:
+ case GGML_TYPE_Q8_0:
+ case GGML_TYPE_Q8_1:
+ case GGML_TYPE_I8:
+ case GGML_TYPE_I16:
+ case GGML_TYPE_I32:
+ case GGML_TYPE_COUNT:
+ {
+ GGML_ASSERT(false);
+ } break;
+ }
+}
+
// ggml_compute_forward_rope
static void ggml_compute_forward_rope_f32(
@@ -12853,6 +12967,10 @@ static void ggml_compute_forward(struct ggml_compute_params * params, struct ggm
{
ggml_compute_forward_alibi(params, tensor->src0, tensor->src1, tensor);
} break;
+ case GGML_OP_CLAMP:
+ {
+ ggml_compute_forward_clamp(params, tensor->src0, tensor->src1, tensor);
+ } break;
case GGML_OP_CONV_1D_1S:
{
ggml_compute_forward_conv_1d_1s(params, tensor->src0, tensor->src1, tensor);
@@ -13160,6 +13278,10 @@ static void ggml_compute_backward(struct ggml_context * ctx, struct ggml_tensor
{
GGML_ASSERT(false); // TODO: not implemented
} break;
+ case GGML_OP_CLAMP:
+ {
+ GGML_ASSERT(false); // TODO: not implemented
+ } break;
case GGML_OP_SILU:
{
// necessary for llama
@@ -14039,6 +14161,10 @@ void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph)
{
node->n_tasks = 1; //TODO
} break;
+ case GGML_OP_CLAMP:
+ {
+ node->n_tasks = 1; //TODO
+ } break;
case GGML_OP_CONV_1D_1S:
case GGML_OP_CONV_1D_2S:
{
generated by cgit v1.2.3 (git 2.25.1) at 2024-10-18 15:32:02 +0000