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#include "ggml-backend.h"
#include "ggml-cpu.h"
#include "ggml.h"
#ifdef GGML_USE_CUDA
#include "ggml-cuda.h"
#endif
#include <stdlib.h>
#include <string.h>
struct model {
struct ggml_context* ctx;
struct ggml_context* ctx0;
ggml_backend_t backend;
ggml_backend_buffer_t buffer;
struct ggml_cgraph* gf;
ggml_gallocr_t allocr;
uint8_t* buf;
};
struct ggml_context* make_ctx(void) {
struct ggml_init_params params = {
.mem_size = ggml_tensor_overhead() * 3,
.mem_buffer = NULL,
.no_alloc = true,
};
return ggml_init(params);
}
ggml_backend_t make_backend(void) {
ggml_backend_t backend = NULL;
#ifdef GGML_USE_CUDA
backend = ggml_backend_cuda_init(0);
GGML_ASSERT(backend != NULL);
#endif
if (!backend) {
backend = ggml_backend_cpu_init();
}
return backend;
}
void model_init(struct model* m) {
m->ctx = make_ctx();
m->backend = make_backend();
size_t buf_size = ggml_tensor_overhead() * GGML_DEFAULT_GRAPH_SIZE + ggml_graph_overhead();
m->buf = calloc(buf_size, sizeof(uint8_t));
struct ggml_init_params params0 = {
.mem_size = buf_size,
.mem_buffer = m->buf,
.no_alloc = true,
};
m->ctx0 = ggml_init(params0);
m->gf = ggml_new_graph(m->ctx0);
}
void model_alloc(struct model* m) {
m->buffer = ggml_backend_alloc_ctx_tensors(m->ctx, m->backend);
m->allocr = ggml_gallocr_new(ggml_backend_get_default_buffer_type(m->backend));
}
void model_compute(struct model* m) {
ggml_gallocr_alloc_graph(m->allocr, m->gf);
ggml_backend_graph_compute(m->backend, m->gf);
}
void model_free(struct model* m) {
ggml_free(m->ctx0);
free(m->buf);
ggml_gallocr_free(m->allocr);
ggml_free(m->ctx);
ggml_backend_buffer_free(m->buffer);
ggml_backend_free(m->backend);
}
void check_tensor(struct ggml_tensor* t,
const float* expected_t_d,
const int ne0,
const int ne1,
const int ne2) {
GGML_ASSERT(t->ne[0] == ne0);
GGML_ASSERT(t->ne[1] == ne1);
GGML_ASSERT(t->ne[2] == ne2);
const size_t bsize = ggml_nbytes(t);
if (t->type == GGML_TYPE_F32) {
float* buffer = malloc(bsize);
ggml_backend_tensor_get(t, buffer, 0, bsize);
for (int i = 0; i < bsize / sizeof(float); ++i) {
float expected = expected_t_d[i];
float actual = buffer[i];
if (expected != actual) {
printf("expected %.1f, got %.1f\n", expected, actual);
}
GGML_ASSERT(expected == actual);
}
free(buffer);
} else if (t->type == GGML_TYPE_F16) {
ggml_fp16_t* buffer = malloc(bsize);
ggml_backend_tensor_get(t, buffer, 0, bsize);
for (int i = 0; i < bsize / sizeof(ggml_fp16_t); ++i) {
float expected = expected_t_d[i];
float actual = ggml_fp16_to_fp32(buffer[i]);
if (expected != actual) {
printf("expected %.1f, got %.1f\n", expected, actual);
}
GGML_ASSERT(expected == actual);
}
free(buffer);
//} else if (t->type == GGML_TYPE_BF16) {
// ggml_bf16_t* buffer = malloc(bsize);
// ggml_backend_tensor_get(t, buffer, 0, bsize);
// for (int i = 0; i < bsize / sizeof(ggml_bf16_t); ++i) {
// float expected = expected_t_d[i];
// float actual = ggml_bf16_to_fp32(buffer[i]);
// if (expected != actual) {
// printf("expected %.1f, got %.1f\n", expected, actual);
// }
// GGML_ASSERT(expected == actual);
// }
// free(buffer);
} else {
GGML_ABORT("unknown type");
}
}
void test_cont(void) {
float buf_f32[] = {1.0, 2.0};
ggml_fp16_t buf_f16[] = {ggml_fp32_to_fp16(buf_f32[0]), ggml_fp32_to_fp16(buf_f32[1])};
ggml_bf16_t buf_bf16[] = {ggml_fp32_to_bf16(buf_f32[0]), ggml_fp32_to_bf16(buf_f32[1])};
float expected_out[] = {1.0, 2.0};
struct model m;
model_init(&m);
struct ggml_tensor* in_1 = ggml_new_tensor_1d(m.ctx, GGML_TYPE_F32, 2);
struct ggml_tensor* in_2 = ggml_new_tensor_1d(m.ctx, GGML_TYPE_F16, 2);
//struct ggml_tensor* in_3 = ggml_new_tensor_1d(m.ctx, GGML_TYPE_BF16, 2);
model_alloc(&m);
ggml_backend_tensor_set(in_1, buf_f32, 0, ggml_nbytes(in_1));
ggml_backend_tensor_set(in_2, buf_f16, 0, ggml_nbytes(in_2));
//ggml_backend_tensor_set(in_3, buf_bf16, 0, ggml_nbytes(in_3));
struct ggml_tensor* out_1 = ggml_cont(m.ctx0, ggml_transpose(m.ctx0, in_1));
struct ggml_tensor* out_2 = ggml_cont(m.ctx0, ggml_transpose(m.ctx0, in_2));
//struct ggml_tensor* out_3 = ggml_cont(m.ctx0, ggml_transpose(m.ctx0, in_3));
ggml_build_forward_expand(m.gf, out_1);
ggml_build_forward_expand(m.gf, out_2);
//ggml_build_forward_expand(m.gf, out_3);
model_compute(&m);
check_tensor(out_1, expected_out, 1, 2, 1);
check_tensor(out_2, expected_out, 1, 2, 1);
//check_tensor(out_3, expected_out, 1, 2, 1);
model_free(&m);
}
int main(int argc, const char* argv[]) {
test_cont();
return 0;
}
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