CS348Project/llama.cpp
5
0
Fork 0
mirror of https://github.com/ggml-org/llama.cpp.git synced 2025-11-21 12:16:57 +00:00
Code Issues Packages Projects Releases Wiki Activity

ggml-zdnn: attempt at init bias in init_tensor

Browse Source 
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
This commit is contained in:
Aaron Teo
2025-09-06 20:29:53 +08:00
parent e0bae5dd4a
commit 7de719a45e
2 changed files with 36 additions and 12 deletions
Download Patch File Download Diff File Expand all files Collapse all files

47
ggml/src/ggml-zdnn/ggml-zdnn.cpp
View File

@@ -115,9 +115,7 @@ static void ggml_zdnn_mul_mat_op(ggml_backend_zdnn_context * ctx, const ggml_ten
ggml_backend_zdnn_buffer * weights_extra = (ggml_backend_zdnn_buffer *)weights->extra;
ggml_backend_zdnn_buffer * inputs_extra = (ggml_backend_zdnn_buffer *)inputs->extra;
ggml_backend_zdnn_buffer * output_extra = (ggml_backend_zdnn_buffer *)output->extra;
zdnn_tensor_desc ptd_bias, td_bias;
zdnn_ztensor zt_bias;
ggml_backend_zdnn_buffer * bias_extra = (ggml_backend_zdnn_buffer *)output_extra->extra;
const int64_t weights_rows = ne01;
const int64_t weights_cols = ne00;
@@ -129,12 +127,7 @@ static void ggml_zdnn_mul_mat_op(ggml_backend_zdnn_context * ctx, const ggml_ten
const int64_t output_rows = ne1;
const int64_t output_cols = ne0;
const int64_t bias_dim [GGML_MAX_DIMS] = { 1, 1, 1, output_cols };
ggml_zdnn_create_tensor(ptd_bias, td_bias, zt_bias, output, bias_dim, ZDNN_1D);
void * bias_data = (void *)calloc(ne0, ggml_element_size(output));
if (weights_extra->ztensor.is_transformed == false) ggml_zdnn_load_tensor(weights_extra->ztensor, weights->data);
ggml_zdnn_load_tensor(zt_bias, bias_data);
// GGML_LOG_INFO("%s: tensor '%s' tensor dimensions: [%ld, %ld, %ld, %ld] pre_tfm_desc dimensions: [%ld, %ld, %ld, %ld]\n",
// __func__, weights_extra->name,
@@ -157,13 +150,10 @@ static void ggml_zdnn_mul_mat_op(ggml_backend_zdnn_context * ctx, const ggml_ten
GGML_ASSERT(inputs_extra->pre_tfm_desc.dim1 == inputs->ne[0] && "inputs_extra->pre_tfm_desc.dim1 must match inputs->ne[0]");
GGML_ASSERT(inputs_extra->pre_tfm_desc.dim2 == inputs->ne[1] && "inputs_extra->pre_tfm_desc.dim2 must match inputs->ne[1]");
ZDNN_CHECK(zdnn_matmul_transpose_op(&inputs_extra->ztensor, &weights_extra->ztensor, &zt_bias,
ZDNN_CHECK(zdnn_matmul_transpose_op(&inputs_extra->ztensor, &weights_extra->ztensor, &bias_extra->ztensor,
false, true, MATMUL_OP_ADDITION, &output_extra->ztensor));
// TODO: Remove in the future as we are currently DLF16 -> FP32 then in the next op, FP32 -> DLF16 again. Inefficient.
ZDNN_CHECK(zdnn_transform_origtensor(&output_extra->ztensor, output->data));
ZDNN_CHECK(zdnn_free_ztensor_buffer(&zt_bias));
free(bias_data);
}
static void ggml_zdnn_mul_mat_dispatch(ggml_backend_zdnn_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
@@ -377,6 +367,16 @@ static void ggml_backend_zdnn_buffer_free_buffer(ggml_backend_buffer_t buffer) {
if (ctx->buffers[i]->ztensor.buffer != NULL && ctx->buffers[i]->ztensor.is_transformed) {
ZDNN_CHECK(zdnn_free_ztensor_buffer(&ctx->buffers[i]->ztensor));
}
if (ctx->buffers[i]->extra != nullptr) {
ggml_backend_zdnn_buffer * bias = (ggml_backend_zdnn_buffer *)ctx->buffers[i]->extra;
if (bias->ztensor.buffer != NULL && bias->ztensor.is_transformed) {
ZDNN_CHECK(zdnn_free_ztensor_buffer(&bias->ztensor));
}
free(bias->data);
delete bias;
}
}
delete ctx;
@@ -401,6 +401,7 @@ static enum ggml_status ggml_backend_zdnn_buffer_init_tensor(ggml_backend_buffer
std::unique_ptr<ggml_backend_zdnn_buffer> zdnn_buffer = std::make_unique<ggml_backend_zdnn_buffer>();
zdnn_buffer->data = tensor->data;
zdnn_buffer->size = tsize;
zdnn_buffer->extra = nullptr;
strncpy(zdnn_buffer->name, tensor->name, GGML_MAX_NAME - 1);
ggml_zdnn_init_tensor(zdnn_buffer.get(), tensor);
@@ -409,6 +410,28 @@ static enum ggml_status ggml_backend_zdnn_buffer_init_tensor(ggml_backend_buffer
ctx->buffers.push_back(std::move(zdnn_buffer));
ctx->n_buffers++;
switch (tensor->op) {
case GGML_OP_MUL_MAT:
{
std::unique_ptr<ggml_backend_zdnn_buffer> zdnn_bias_buffer = std::make_unique<ggml_backend_zdnn_buffer>();
zdnn_bias_buffer->data = (void *)calloc(tensor->ne[0], ggml_element_size(tensor));
zdnn_bias_buffer->size = ggml_element_size(tensor) * tensor->ne[0];
snprintf(zdnn_bias_buffer->name, GGML_MAX_NAME - 1, "%s (bias)", tensor->name);
const int64_t bias_dim[GGML_MAX_DIMS] = { 1, 1, 1, tensor->ne[0] };
ggml_zdnn_create_tensor(zdnn_bias_buffer->pre_tfm_desc,
zdnn_bias_buffer->tfm_desc,
zdnn_bias_buffer->ztensor,
tensor, bias_dim, ZDNN_1D);
ggml_zdnn_load_tensor(zdnn_bias_buffer->ztensor, zdnn_bias_buffer->data);
zdnn_buffer->extra = zdnn_bias_buffer.get();
ctx->buffers.push_back(std::move(zdnn_bias_buffer));
ctx->n_buffers++;
} break;
}
// GGML_LOG_INFO("%s: initialised tensor '%s' in buffer %d, size = %8.2f MiB\n",
// __func__, tensor->name, buffer_idx, tsize);