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ggml-zdnn: bring back working matmul

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Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
This commit is contained in:
Aaron Teo
2025-07-28 18:14:44 +08:00
parent 4cc62cb693
commit 03ec5d3ed3
1 changed files with 62 additions and 58 deletions
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120
ggml/src/ggml-zdnn/ggml-zdnn-rewrite.cpp
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@@ -8,7 +8,46 @@
#include <csignal>
#include <unistd.h>
static bool ggml_zdnn_op_mul_mat(struct ggml_backend_zdnn_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
inline zdnn_data_types ggml_zdnn_type_mapping(ggml_type type) {
switch (type) {
case GGML_TYPE_F32:
return FP32;
case GGML_TYPE_F16:
return FP16;
case GGML_TYPE_BF16:
return BFLOAT;
case GGML_TYPE_I8:
return INT8;
case GGML_TYPE_I32:
return INT32;
case GGML_TYPE_Q8_0:
return INT8;
default:
GGML_ABORT("%s: fatal: unable to determine zTensor data type",
__func__);
break;
}
}
inline void ggml_zdnn_create_tensor(zdnn_tensor_desc & pre_tfm_desc,
zdnn_tensor_desc & tfm_desc,
zdnn_ztensor & ztensor,
const ggml_tensor * src,
const int64_t * ne,
const zdnn_data_layouts layout) {
zdnn_init_pre_transformed_desc(
layout,
ggml_zdnn_type_mapping(src->type),
&pre_tfm_desc,
ne[3], ne[2], ne[1], ne[0]
);
ZDNN_CHECK(zdnn_generate_transformed_desc(&pre_tfm_desc, &tfm_desc));
ZDNN_CHECK(zdnn_init_ztensor_with_malloc(&pre_tfm_desc, &tfm_desc, &ztensor));
}
static void ggml_backend_zdnn_mul_mat(ggml_backend_zdnn_context * ctx, const ggml_tensor * src0, const ggml_tensor * src1, ggml_tensor * dst) {
GGML_TENSOR_BINARY_OP_LOCALS
const enum ggml_type type = src0->type;
@@ -32,10 +71,15 @@ static bool ggml_zdnn_op_mul_mat(struct ggml_backend_zdnn_context * ctx, const g
const ggml_tensor * inputs = src1;
ggml_tensor * output = dst;
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;
ggml_backend_zdnn_buffer * bias_extra = (ggml_backend_zdnn_buffer *)output_extra->extra;
const zdnn_extra * inputs_extra = (const zdnn_extra *)inputs->extra;
const zdnn_extra * weights_extra = (const zdnn_extra *)weights->extra;
zdnn_extra * output_extra = ( zdnn_extra *)output->extra;
zdnn_extra * output_bias_extra = ( zdnn_extra *)output_extra->extra;
zdnn_tensor_desc pre_tfm_desc_weights, tfm_desc_weights;
zdnn_tensor_desc pre_tfm_desc_bias, tfm_desc_bias;
zdnn_ztensor ztensor_weights, ztensor_bias;
const int64_t weights_rows = ne01;
const int64_t weights_cols = ne00;
@@ -47,66 +91,26 @@ static bool ggml_zdnn_op_mul_mat(struct ggml_backend_zdnn_context * ctx, const g
const int64_t output_rows = ne1;
const int64_t output_cols = ne0;
zdnn_tensor_desc pre_tfm_desc_inputs, tfm_desc_inputs;
zdnn_tensor_desc pre_tfm_desc_weights, tfm_desc_weights;
zdnn_tensor_desc pre_tfm_desc_bias, tfm_desc_bias;
zdnn_tensor_desc pre_tfm_desc_output, tfm_desc_output;
zdnn_ztensor ztensor_inputs, ztensor_weights, ztensor_bias, ztensor_output;
const int64_t inputs_dim [GGML_MAX_DIMS] = { 1, 1, inputs_cols, inputs_rows };
const int64_t weights_dim[GGML_MAX_DIMS] = { 1, 1, weights_cols, weights_rows };
const int64_t bias_dim [GGML_MAX_DIMS] = { 1, 1, 1, output_cols };
const int64_t output_dim[GGML_MAX_DIMS] = { 1, 1, output_cols, output_rows };
// have to do this because weights apparently do not go through set_tensor
zdnn_init_pre_transformed_desc(
ZDNN_2D,
FP32,
&pre_tfm_desc_weights,
weights_dim[3], weights_dim[2], weights_dim[1], weights_dim[0]
);
ZDNN_CHECK(zdnn_generate_transformed_desc(&pre_tfm_desc_weights, &tfm_desc_weights));
ZDNN_CHECK(zdnn_init_ztensor_with_malloc(&pre_tfm_desc_weights, &tfm_desc_weights, &ztensor_weights));
ZDNN_CHECK(zdnn_transform_ztensor(&ztensor_weights, weights->data));
// have to do this here because although it was transformed, the shape is wrong
zdnn_init_pre_transformed_desc(
ZDNN_2D,
FP32,
&pre_tfm_desc_inputs,
inputs_dim[3], inputs_dim[2], inputs_dim[1], inputs_dim[0]
);
ZDNN_CHECK(zdnn_generate_transformed_desc(&pre_tfm_desc_inputs, &tfm_desc_inputs));
ZDNN_CHECK(zdnn_init_ztensor_with_malloc(&pre_tfm_desc_inputs, &tfm_desc_inputs, &ztensor_inputs));
ZDNN_CHECK(zdnn_transform_ztensor(&ztensor_inputs, inputs->data));
// have to transform the bias ztensor here because only GGML_OP_NONE goes through set_tensor
zdnn_init_pre_transformed_desc(
ZDNN_1D,
FP32,
&pre_tfm_desc_bias,
bias_dim[3], bias_dim[2], bias_dim[1], bias_dim[0]
);
ZDNN_CHECK(zdnn_generate_transformed_desc(&pre_tfm_desc_bias, &tfm_desc_bias));
ZDNN_CHECK(zdnn_init_ztensor_with_malloc(&pre_tfm_desc_bias, &tfm_desc_bias, &ztensor_bias));
//! Something to do with these 2 lines that we can't remove
//! If we remove it, the entire computation will throw an error
//! Even though we don't use these tensors lol
ggml_zdnn_create_tensor(pre_tfm_desc_weights, tfm_desc_weights, ztensor_weights, src0, weights_dim, ZDNN_2D);
ggml_zdnn_create_tensor(pre_tfm_desc_bias, tfm_desc_bias, ztensor_bias, dst, bias_dim, ZDNN_1D);
void * bias_data = (void *)calloc(ne0, sizeof(ggml_element_size(output)));
ZDNN_CHECK(zdnn_transform_ztensor(&ztensor_bias, bias_data));
ZDNN_CHECK(zdnn_transform_ztensor(&output_bias_extra->ztensor, bias_data));
zdnn_init_pre_transformed_desc(
ZDNN_2D,
FP32,
&pre_tfm_desc_output,
output_dim[3], output_dim[2], output_dim[1], output_dim[0]
);
ZDNN_CHECK(zdnn_generate_transformed_desc(&pre_tfm_desc_output, &tfm_desc_output));
ZDNN_CHECK(zdnn_init_ztensor_with_malloc(&pre_tfm_desc_output, &tfm_desc_output, &ztensor_output));
ZDNN_CHECK(zdnn_transform_ztensor(&ztensor_output, output->data));
ZDNN_CHECK(zdnn_matmul_transpose_op(&inputs_extra->ztensor, &weights_extra->ztensor, &ztensor_bias,
false, true, MATMUL_OP_ADDITION, &output_extra->ztensor));
ZDNN_CHECK(zdnn_transform_origtensor(&output_extra->ztensor, output->data));
std::raise(SIGINT);
ZDNN_CHECK(zdnn_matmul_transpose_op(&ztensor_inputs, &ztensor_weights, &ztensor_bias,
false, true, MATMUL_OP_ADDITION, &ztensor_output));
ZDNN_CHECK(zdnn_transform_origtensor(&ztensor_output, output->data));
ZDNN_CHECK(zdnn_free_ztensor_buffer(&ztensor_weights));
ZDNN_CHECK(zdnn_free_ztensor_buffer(&ztensor_bias));
free(bias_data);
}
static bool ggml_backend_zdnn_compute_forward(struct ggml_backend_zdnn_context * ctx, struct ggml_tensor * dst) {