+
diff --git a/ggml-sycl.cpp b/ggml-sycl.cpp
index 86091cfbf..f5bb7da86 100644
--- a/ggml-sycl.cpp
+++ b/ggml-sycl.cpp
@@ -15996,73 +15996,76 @@ static void ggml_sycl_mul_mat_id_sycl(ggml_tensor * dst) {
static void ggml_sycl_mul_mat_id(const ggml_tensor *src0,
const ggml_tensor *src1,
ggml_tensor *dst) try {
-#if 0
- ggml_sycl_mul_mat_id_sycl(dst);
- // TODO: mmq/mmv support
-#endif
-
- const int64_t nb11 = src1->nb[1];
- const int64_t nb1 = dst->nb[1];
-
- const struct ggml_tensor * ids = src0;
- const int32_t id = ((int32_t *) dst->op_params)[0];
- const int32_t n_as = ((int32_t *) dst->op_params)[1];
-
- std::vector ids_host(ggml_nbytes(ids));
-
+ GGML_ASSERT(src0->backend != GGML_BACKEND_TYPE_GPU_SPLIT &&
+ "mul_mat_id does not support split buffers");
+ const ggml_tensor *ids = dst->src[2];
const dpct::queue_ptr stream = g_syclStreams[g_main_device][0];
- if (ids->backend == GGML_BACKEND_TYPE_GPU) {
- const char * ids_dev = (const char *)((const ggml_tensor_extra_gpu *)ids->extra)->data_device[g_main_device];
- SYCL_CHECK(CHECK_TRY_ERROR(
- stream->memcpy(ids_host.data(), ids_dev, ggml_nbytes(ids)).wait()));
- // SYCL_CHECK(CHECK_TRY_ERROR(stream->wait()));
- } else {
- memcpy(ids_host.data(), ids->data, ggml_nbytes(ids));
- }
+ const size_t nb11 = src1->nb[1];
+ const size_t nb1 = dst->nb[1];
- const ggml_tensor_extra_gpu * src1_extra = (const ggml_tensor_extra_gpu *) src1->extra;
- const ggml_tensor_extra_gpu * dst_extra = (const ggml_tensor_extra_gpu *) dst->extra;
+ const int32_t id = ((int32_t *)dst->op_params)[0];
+ const int32_t n_as = src0->ne[2];
+ std::vector ids_host(ggml_nbytes(ids));
+ const char *ids_dev = (const char *)ids->data;
+
+ SYCL_CHECK(CHECK_TRY_ERROR(
+ stream->memcpy(ids_host.data(), ids_dev, ggml_nbytes(ids))));
+ SYCL_CHECK(CHECK_TRY_ERROR(stream->wait()));
+
+ const ggml_tensor_extra_gpu *src0_extra =
+ (const ggml_tensor_extra_gpu *)src0->extra;
+ const ggml_tensor_extra_gpu *src1_extra =
+ (const ggml_tensor_extra_gpu *)src1->extra;
+ const ggml_tensor_extra_gpu *dst_extra =
+ (const ggml_tensor_extra_gpu *)dst->extra;
+
+ ggml_tensor_extra_gpu src0_row_extra;
ggml_tensor_extra_gpu src1_row_extra;
ggml_tensor_extra_gpu dst_row_extra;
+ ggml_tensor src0_row = *src0;
ggml_tensor src1_row = *src1;
ggml_tensor dst_row = *dst;
src1_row.backend = GGML_BACKEND_TYPE_GPU;
dst_row.backend = GGML_BACKEND_TYPE_GPU;
+ src0_row.extra = &src0_row_extra;
src1_row.extra = &src1_row_extra;
dst_row.extra = &dst_row_extra;
- char * src1_original = src1->backend == GGML_BACKEND_TYPE_CPU ?
- (char *) src1->data : (char *) src1_extra->data_device[g_main_device];
- char * dst_original = dst->backend == GGML_BACKEND_TYPE_CPU ?
- (char *) dst->data : (char *) dst_extra->data_device[g_main_device];
+ char *src0_original = src1->backend == GGML_BACKEND_TYPE_CPU
+ ? (char *)src0->data
+ : (char *)src0_extra->data_device[g_main_device];
+ char *src1_original = src1->backend == GGML_BACKEND_TYPE_CPU
+ ? (char *)src1->data
+ : (char *)src1_extra->data_device[g_main_device];
+ char *dst_original = dst->backend == GGML_BACKEND_TYPE_CPU
+ ? (char *)dst->data
+ : (char *)dst_extra->data_device[g_main_device];
+
+ src0_row.ne[2] = 1;
+ src0_row.ne[3] = 1;
+ src0_row.nb[3] = src0->nb[2];
if (src1->ne[1] == 1) {
- GGML_ASSERT(src1->backend == GGML_BACKEND_TYPE_GPU);
- GGML_ASSERT(dst->backend == GGML_BACKEND_TYPE_GPU);
-
for (int64_t i01 = 0; i01 < ids->ne[1]; i01++) {
- //int32_t row_id;
- //SYCL_CHECK(syclMemcpyAsync(&row_id, ids_dev + i01*ids->nb[1] + id*ids->nb[0], sizeof(int32_t), syclMemcpyDeviceToHost, g_syclStreams[g_main_device][0]));
- //SYCL_CHECK(syclStreamSynchronize(g_syclStreams[g_main_device][0]));
-
- const int32_t row_id = *(const int32_t *) (ids_host.data() + i01*ids->nb[1] + id*ids->nb[0]);
+ const int32_t row_id =
+ *(const int32_t *)(ids_host.data() + i01 * ids->nb[1] +
+ id * ids->nb[0]);
GGML_ASSERT(row_id >= 0 && row_id < n_as);
- const struct ggml_tensor * src0_row = dst->src[row_id + 2];
+ src0_row_extra.data_device[g_main_device] =
+ src0_original + row_id * src0->nb[2];
+ src1_row_extra.data_device[g_main_device] =
+ src1_original + i01 * src1->nb[1];
+ dst_row_extra.data_device[g_main_device] =
+ dst_original + i01 * dst->nb[1];
- src1_row_extra.data_device[g_main_device] = src1_original + i01*src1->nb[1];
- src1_row.data = (char *) src1->data + i01*src1->nb[1]; // TODO why is this set?
-
- dst_row_extra.data_device[g_main_device] = dst_original + i01*dst->nb[1];
- dst_row.data = (char *) dst->data + i01*dst->nb[1]; // TODO why is this set?
-
- ggml_sycl_mul_mat(src0_row, &src1_row, &dst_row);
+ ggml_sycl_mul_mat(&src0_row, &src1_row, &dst_row);
}
} else {
sycl_pool_alloc src1_contiguous(sizeof(float)*ggml_nelements(src1));
@@ -16072,8 +16075,6 @@ static void ggml_sycl_mul_mat_id(const ggml_tensor *src0,
dst_row_extra.data_device[g_main_device] = dst_contiguous.get();
for (int32_t row_id = 0; row_id < n_as; ++row_id) {
- const struct ggml_tensor * src0_row = dst->src[row_id + 2];
-
int64_t num_src1_rows = 0;
for (int64_t i01 = 0; i01 < ids->ne[1]; i01++) {
const int32_t row_id_i = *(const int32_t *) (ids_host.data() + i01*ids->nb[1] + id*ids->nb[0]);
@@ -16086,7 +16087,7 @@ static void ggml_sycl_mul_mat_id(const ggml_tensor *src0,
SYCL_CHECK(CHECK_TRY_ERROR(
stream->memcpy(src1_contiguous.get() + num_src1_rows * nb11,
- src1_original + i01 * nb11, nb11).wait()));
+ src1_original + i01 * nb11, nb11)));
num_src1_rows++;
}
@@ -16094,6 +16095,9 @@ static void ggml_sycl_mul_mat_id(const ggml_tensor *src0,
continue;
}
+ src0_row_extra.data_device[g_main_device] =
+ src0_original + row_id * src0->nb[2];
+
src1_row.ne[1] = num_src1_rows;
dst_row.ne[1] = num_src1_rows;
@@ -16105,7 +16109,7 @@ static void ggml_sycl_mul_mat_id(const ggml_tensor *src0,
dst_row.nb[2] = num_src1_rows*nb1;
dst_row.nb[3] = num_src1_rows*nb1;
- ggml_sycl_mul_mat(src0_row, &src1_row, &dst_row);
+ ggml_sycl_mul_mat(&src0_row, &src1_row, &dst_row);
num_src1_rows = 0;
for (int64_t i01 = 0; i01 < ids->ne[1]; i01++) {
@@ -16119,7 +16123,7 @@ static void ggml_sycl_mul_mat_id(const ggml_tensor *src0,
SYCL_CHECK(CHECK_TRY_ERROR(stream->memcpy(
dst_original + i01 * nb1,
- dst_contiguous.get() + num_src1_rows * nb1, nb1).wait()));
+ dst_contiguous.get() + num_src1_rows * nb1, nb1)));
num_src1_rows++;
}
}
diff --git a/llama.cpp b/llama.cpp
index 9f24bbfa1..d66df77fb 100644
--- a/llama.cpp
+++ b/llama.cpp
@@ -13378,6 +13378,11 @@ struct llama_beam_search_data {
}
llama_logit_info logit_info(ctx);
std::vector next_tokens = logit_info.top_k(n_beams);
+
+ // Clear the kv slot so that other beams may try different tokens at this position. The llama_decode()
+ // call in loop() will conclusively fill in the kv slot once the beams converge at this position.
+ llama_kv_cache_seq_rm(ctx, 0, n_past, -1);
+
size_t i=0;
if (next_beams.size() < n_beams) {
for (; next_beams.size() < n_beams ; ++i) {
@@ -15778,6 +15783,8 @@ size_t llama_state_set_data(struct llama_context * ctx, const uint8_t * src) {
GGML_ASSERT((uint32_t) id < ctx->cparams.n_batch);
ctx->output_ids[id] = i;
}
+
+ ctx->n_outputs = n_outputs;
}
}
@@ -16946,6 +16953,21 @@ static int32_t llama_chat_apply_template_internal(
if (add_ass) {
ss << "### Response:\n";
}
+ } else if (tmpl == "command-r" || (tmpl.find("<|START_OF_TURN_TOKEN|>") != std::string::npos && tmpl.find("<|USER_TOKEN|>") != std::string::npos)) {
+ // CohereForAI/c4ai-command-r-plus
+ for (auto message : chat) {
+ std::string role(message->role);
+ if (role == "system") {
+ ss << "<|START_OF_TURN_TOKEN|><|SYSTEM_TOKEN|>" << trim(message->content) << "<|END_OF_TURN_TOKEN|>";
+ } else if (role == "user") {
+ ss << "<|START_OF_TURN_TOKEN|><|USER_TOKEN|>" << trim(message->content) << "<|END_OF_TURN_TOKEN|>";
+ } else if (role == "assistant") {
+ ss << "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>" << trim(message->content) << "<|END_OF_TURN_TOKEN|>";
+ }
+ }
+ if (add_ass) {
+ ss << "<|START_OF_TURN_TOKEN|><|CHATBOT_TOKEN|>";
+ }
} else {
// template not supported
return -1;