mirror of
https://git.adityakumar.xyz/llama.cpp.git
synced 2024-11-09 15:29:43 +00:00
ggml : sync cgraph import / export API
This commit is contained in:
Georgi Gerganov
parent
5d1830b99d
commit
7552ac5863
2 changed files with 491 additions and 3 deletions
482
ggml.c
482
ggml.c
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@ -4030,6 +4030,14 @@ void ggml_set_no_alloc(struct ggml_context * ctx, bool no_alloc) {
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ctx->no_alloc = no_alloc;
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}
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void * ggml_get_mem_buffer(struct ggml_context * ctx) {
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return ctx->mem_buffer;
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}
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size_t ggml_get_mem_size(struct ggml_context * ctx) {
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return ctx->mem_size;
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}
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// IMPORTANT:
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// when creating "opt" tensors, always save and load the scratch buffer
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// this is an error prone process, but it is necessary to support inplace
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@ -4523,6 +4531,23 @@ struct ggml_tensor * ggml_view_tensor(
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return result;
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}
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struct ggml_tensor * ggml_get_tensor(struct ggml_context * ctx, const char * name) {
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struct ggml_object * obj = ctx->objects_begin;
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char * const mem_buffer = ctx->mem_buffer;
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while (obj != NULL) {
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struct ggml_tensor * cur = (struct ggml_tensor *)(mem_buffer + obj->offs);
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if (strcmp(cur->name, name) == 0) {
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return cur;
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}
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obj = obj->next;
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}
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return NULL;
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}
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////////////////////////////////////////////////////////////////////////////////
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// ggml_dup
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@ -14532,7 +14557,7 @@ void ggml_graph_reset(struct ggml_cgraph * cgraph) {
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}
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}
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struct ggml_tensor * ggml_get_tensor_by_name(struct ggml_cgraph * cgraph, const char * name) {
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struct ggml_tensor * ggml_graph_get_tensor(struct ggml_cgraph * cgraph, const char * name) {
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for (int i = 0; i < cgraph->n_leafs; i++) {
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struct ggml_tensor * leaf = cgraph->leafs[i];
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@ -14552,6 +14577,461 @@ struct ggml_tensor * ggml_get_tensor_by_name(struct ggml_cgraph * cgraph, const
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return NULL;
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}
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static void ggml_graph_export_leaf(const struct ggml_tensor * tensor, FILE * fout) {
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const int64_t * ne = tensor->ne;
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const size_t * nb = tensor->nb;
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fprintf(fout, "%-6s %-12s %8d %8lld %8lld %8lld %8lld %16zu %16zu %16zu %16zu %16p %16s\n",
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ggml_type_name(tensor->type),
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ggml_op_name (tensor->op),
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tensor->n_dims,
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ne[0], ne[1], ne[2], ne[3],
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nb[0], nb[1], nb[2], nb[3],
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tensor->data,
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tensor->name);
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}
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static void ggml_graph_export_node(const struct ggml_tensor * tensor, const char * arg, FILE * fout) {
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const int64_t * ne = tensor->ne;
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const size_t * nb = tensor->nb;
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fprintf(fout, "%-6s %-6s %-12s %8d %8lld %8lld %8lld %8lld %16zu %16zu %16zu %16zu %8d %16p %16s\n",
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arg,
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ggml_type_name(tensor->type),
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ggml_op_name (tensor->op),
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tensor->n_dims,
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ne[0], ne[1], ne[2], ne[3],
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nb[0], nb[1], nb[2], nb[3],
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tensor->n_tasks,
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tensor->data,
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tensor->name);
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}
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void ggml_graph_export(const struct ggml_cgraph * cgraph, const char * fname) {
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assert(cgraph->work == NULL);
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assert(cgraph->work_size == 0);
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uint64_t size_eval = 0;
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// compute size of intermediate results
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// TODO: does not take into account scratch buffers !!!!
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for (int i = 0; i < cgraph->n_nodes; ++i) {
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size_eval += ggml_nbytes(cgraph->nodes[i]);
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}
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// print
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{
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FILE * fout = stdout;
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fprintf(fout, "\n");
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fprintf(fout, "%-16s %8x\n", "magic", GGML_FILE_MAGIC);
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fprintf(fout, "%-16s %8d\n", "version", GGML_FILE_VERSION);
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fprintf(fout, "%-16s %8d\n", "leafs", cgraph->n_leafs);
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fprintf(fout, "%-16s %8d\n", "nodes", cgraph->n_nodes);
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fprintf(fout, "%-16s %8llu\n", "eval", size_eval);
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// header
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fprintf(fout, "\n");
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fprintf(fout, "%-6s %-12s %8s %8s %8s %8s %8s %16s %16s %16s %16s %16s %16s\n",
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"TYPE", "OP", "NDIMS", "NE0", "NE1", "NE2", "NE3", "NB0", "NB1", "NB2", "NB3", "DATA", "NAME");
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for (int i = 0; i < cgraph->n_leafs; ++i) {
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ggml_graph_export_leaf(cgraph->leafs[i], fout);
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GGML_ASSERT(cgraph->leafs[i]->op == GGML_OP_NONE);
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GGML_ASSERT(cgraph->leafs[i]->src0 == NULL);
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GGML_ASSERT(cgraph->leafs[i]->src1 == NULL);
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}
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// header
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fprintf(fout, "\n");
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fprintf(fout, "%-6s %-6s %-12s %8s %8s %8s %8s %8s %16s %16s %16s %16s %8s %16s %16s\n",
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"ARG", "TYPE", "OP", "NDIMS", "NE0", "NE1", "NE2", "NE3", "NB0", "NB1", "NB2", "NB3", "NTASKS", "DATA", "NAME");
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for (int i = 0; i < cgraph->n_nodes; ++i) {
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ggml_graph_export_node(cgraph->nodes[i], "DST", fout);
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if (cgraph->nodes[i]->src0) {
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ggml_graph_export_node(cgraph->nodes[i]->src0, "SRC0", fout);
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}
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if (cgraph->nodes[i]->src1) {
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ggml_graph_export_node(cgraph->nodes[i]->src1, "SRC1", fout);
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}
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for (int j = 0; j < GGML_MAX_OPT; ++j) {
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if (cgraph->nodes[i]->opt[j]) {
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ggml_graph_export_node(cgraph->nodes[i]->opt[j], "OPT", fout);
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}
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}
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fprintf(fout, "\n");
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}
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fprintf(fout, "\n");
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}
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// write binary data
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{
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FILE * fout = fopen(fname, "wb");
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if (!fout) {
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fprintf(stderr, "%s: failed to open %s\n", __func__, fname);
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return;
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}
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// header
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{
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const uint32_t magic = GGML_FILE_MAGIC;
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const uint32_t version = GGML_FILE_VERSION;
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const uint32_t n_leafs = cgraph->n_leafs;
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const uint32_t nodes = cgraph->n_nodes;
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fwrite(&magic, sizeof(uint32_t), 1, fout);
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fwrite(&version, sizeof(uint32_t), 1, fout);
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fwrite(&n_leafs, sizeof(uint32_t), 1, fout);
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fwrite(&nodes, sizeof(uint32_t), 1, fout);
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fwrite(&size_eval, sizeof(uint64_t), 1, fout);
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}
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// leafs
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{
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for (int i = 0; i < cgraph->n_leafs; ++i) {
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const struct ggml_tensor * tensor = cgraph->leafs[i];
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const uint32_t type = tensor->type;
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const uint32_t op = tensor->op;
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const uint32_t n_dims = tensor->n_dims;
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fwrite(&type, sizeof(uint32_t), 1, fout);
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fwrite(&op, sizeof(uint32_t), 1, fout);
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fwrite(&n_dims, sizeof(uint32_t), 1, fout);
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for (int j = 0; j < GGML_MAX_DIMS; ++j) {
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const uint64_t ne = tensor->ne[j];
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const uint64_t nb = tensor->nb[j];
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fwrite(&ne, sizeof(uint64_t), 1, fout);
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fwrite(&nb, sizeof(uint64_t), 1, fout);
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}
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// store the pointer address
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{
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const uint64_t ptr = (uint64_t) tensor->data;
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fwrite(&ptr, sizeof(uint64_t), 1, fout);
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}
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fwrite(tensor->name, sizeof(char), GGML_MAX_NAME, fout);
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// dump the data
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// TODO: pad this to 32 byte boundary
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{
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const size_t size = ggml_nbytes(tensor);
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fwrite(tensor->data, sizeof(char), size, fout);
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}
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}
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}
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// nodes
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{
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for (int i = 0; i < cgraph->n_nodes; ++i) {
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const struct ggml_tensor * tensor = cgraph->nodes[i];
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const uint32_t type = tensor->type;
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const uint32_t op = tensor->op;
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const uint32_t n_dims = tensor->n_dims;
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fwrite(&type, sizeof(uint32_t), 1, fout);
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fwrite(&op, sizeof(uint32_t), 1, fout);
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fwrite(&n_dims, sizeof(uint32_t), 1, fout);
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for (int j = 0; j < GGML_MAX_DIMS; ++j) {
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const uint64_t ne = tensor->ne[j];
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const uint64_t nb = tensor->nb[j];
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fwrite(&ne, sizeof(uint64_t), 1, fout);
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fwrite(&nb, sizeof(uint64_t), 1, fout);
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}
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// store the pointer address
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{
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const uint64_t ptr = (uint64_t) tensor->data;
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fwrite(&ptr, sizeof(uint64_t), 1, fout);
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}
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fwrite(tensor->name, sizeof(char), GGML_MAX_NAME, fout);
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// output the op arguments
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{
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struct ggml_tensor * args[2 + GGML_MAX_OPT] = { NULL };
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args[0] = tensor->src0;
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args[1] = tensor->src1;
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for (int j = 0; j < GGML_MAX_OPT; ++j) {
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args[2 + j] = tensor->opt[j];
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}
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for (int j = 0; j < 2 + GGML_MAX_OPT; ++j) {
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if (args[j]) {
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int32_t idx = -1;
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// check if leaf
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{
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for (int k = 0; k < cgraph->n_leafs; ++k) {
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if (args[j] == cgraph->leafs[k]) {
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idx = k;
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break;
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}
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}
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}
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// check if node
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if (idx == -1) {
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for (int k = 0; k < cgraph->n_nodes; ++k) {
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if (args[j] == cgraph->nodes[k]) {
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idx = GGML_MAX_NODES + k;
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break;
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}
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}
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}
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if (idx == -1) {
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fprintf(stderr, "%s: failed to find tensor, arg = %d, node = %d\n", __func__, j, i);
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return;
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}
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fwrite(&idx, sizeof(int32_t), 1, fout);
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} else {
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const int32_t nul = -1;
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fwrite(&nul, sizeof(int32_t), 1, fout);
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}
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}
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}
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}
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}
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fclose(fout);
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}
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}
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struct ggml_cgraph ggml_graph_import(const char * fname, struct ggml_context ** ctx_data, struct ggml_context ** ctx_eval) {
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assert(*ctx_data == NULL);
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assert(*ctx_eval == NULL);
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struct ggml_cgraph result = { 0 };
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struct ggml_tensor * data = NULL;
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// read file into data
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{
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FILE * fin = fopen(fname, "rb");
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if (!fin) {
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fprintf(stderr, "%s: failed to open %s\n", __func__, fname);
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return result;
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}
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size_t fsize = 0;
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fseek(fin, 0, SEEK_END);
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fsize = ftell(fin);
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fseek(fin, 0, SEEK_SET);
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// create the data context
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{
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const size_t overhead = 1*ggml_tensor_overhead();
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struct ggml_init_params params = {
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.mem_size = fsize + overhead,
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.mem_buffer = NULL,
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.no_alloc = false,
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};
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*ctx_data = ggml_init(params);
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if (!*ctx_data) {
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fprintf(stderr, "%s: failed to create ggml context\n", __func__);
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return result;
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}
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}
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data = ggml_new_tensor_1d(*ctx_data, GGML_TYPE_I8, fsize);
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fread(data->data, sizeof(char), fsize, fin);
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fclose(fin);
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}
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// populate result
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{
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char * ptr = (char *) data->data;
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const uint32_t magic = *(const uint32_t *) ptr; ptr += sizeof(magic);
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if (magic != GGML_FILE_MAGIC) {
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fprintf(stderr, "%s: invalid magic number, got %08x\n", __func__, magic);
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return result;
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}
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const uint32_t version = *(const uint32_t *) ptr; ptr += sizeof(version);
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if (version != GGML_FILE_VERSION) {
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fprintf(stderr, "%s: invalid version number\n", __func__);
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return result;
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}
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const uint32_t n_leafs = *(const uint32_t *) ptr; ptr += sizeof(n_leafs);
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const uint32_t n_nodes = *(const uint32_t *) ptr; ptr += sizeof(n_nodes);
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const uint64_t size_eval = *(const uint64_t *) ptr; ptr += sizeof(size_eval);
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result.n_leafs = n_leafs;
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result.n_nodes = n_nodes;
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// create the data context
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{
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const size_t overhead = (n_leafs + n_nodes)*ggml_tensor_overhead();
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struct ggml_init_params params = {
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.mem_size = size_eval + overhead,
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.mem_buffer = NULL,
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.no_alloc = true,
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};
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*ctx_eval = ggml_init(params);
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if (!*ctx_eval) {
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fprintf(stderr, "%s: failed to create ggml context\n", __func__);
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return result;
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}
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}
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// leafs
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{
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uint32_t type;
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uint32_t op;
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uint32_t n_dims;
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for (uint32_t i = 0; i < n_leafs; ++i) {
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type = *(const uint32_t *) ptr; ptr += sizeof(type);
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op = *(const uint32_t *) ptr; ptr += sizeof(op);
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n_dims = *(const uint32_t *) ptr; ptr += sizeof(n_dims);
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int64_t ne[GGML_MAX_DIMS];
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size_t nb[GGML_MAX_DIMS];
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for (int j = 0; j < GGML_MAX_DIMS; ++j) {
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uint64_t ne_cur;
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uint64_t nb_cur;
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ne_cur = *(const uint64_t *) ptr; ptr += sizeof(ne_cur);
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nb_cur = *(const uint64_t *) ptr; ptr += sizeof(nb_cur);
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ne[j] = ne_cur;
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nb[j] = nb_cur;
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}
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struct ggml_tensor * tensor = ggml_new_tensor(*ctx_eval, (enum ggml_type) type, n_dims, ne);
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tensor->op = (enum ggml_op) op;
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uint64_t ptr_cur = *(const uint64_t *) ptr; ptr += sizeof(ptr_cur);
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memcpy(tensor->name, ptr, GGML_MAX_NAME); ptr += GGML_MAX_NAME;
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tensor->data = (void *) ptr;
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for (int j = 0; j < GGML_MAX_DIMS; ++j) {
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tensor->nb[j] = nb[j];
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}
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result.leafs[i] = tensor;
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ptr += ggml_nbytes(tensor);
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fprintf(stderr, "%s: loaded leaf %d: '%16s', %3d dims, %9zu bytes\n", __func__, i, tensor->name, n_dims, ggml_nbytes(tensor));
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}
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}
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ggml_set_no_alloc(*ctx_eval, false);
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// nodes
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{
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uint32_t type;
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uint32_t op;
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uint32_t n_dims;
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for (uint32_t i = 0; i < n_nodes; ++i) {
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type = *(const uint32_t *) ptr; ptr += sizeof(type);
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op = *(const uint32_t *) ptr; ptr += sizeof(op);
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n_dims = *(const uint32_t *) ptr; ptr += sizeof(n_dims);
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int64_t ne[GGML_MAX_DIMS];
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size_t nb[GGML_MAX_DIMS];
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for (int j = 0; j < GGML_MAX_DIMS; ++j) {
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uint64_t ne_cur;
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uint64_t nb_cur;
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ne_cur = *(const uint64_t *) ptr; ptr += sizeof(ne_cur);
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nb_cur = *(const uint64_t *) ptr; ptr += sizeof(nb_cur);
|
||||
|
||||
ne[j] = ne_cur;
|
||||
nb[j] = nb_cur;
|
||||
}
|
||||
|
||||
struct ggml_tensor * tensor = ggml_new_tensor(*ctx_eval, (enum ggml_type) type, n_dims, ne);
|
||||
|
||||
tensor->op = (enum ggml_op) op;
|
||||
|
||||
uint64_t ptr_cur = *(const uint64_t *) ptr; ptr += sizeof(ptr_cur);
|
||||
|
||||
memcpy(tensor->name, ptr, GGML_MAX_NAME); ptr += GGML_MAX_NAME;
|
||||
|
||||
for (int j = 0; j < GGML_MAX_DIMS; ++j) {
|
||||
tensor->nb[j] = nb[j];
|
||||
}
|
||||
|
||||
// parse args
|
||||
{
|
||||
struct ggml_tensor ** args[2 + GGML_MAX_OPT] = {
|
||||
&tensor->src0,
|
||||
&tensor->src1,
|
||||
};
|
||||
|
||||
for (int j = 0; j < GGML_MAX_OPT; ++j) {
|
||||
args[2 + j] = &tensor->opt[j];
|
||||
}
|
||||
|
||||
for (int j = 0; j < 2 + GGML_MAX_OPT; ++j) {
|
||||
const int32_t arg_idx = *(const int32_t *) ptr; ptr += sizeof(arg_idx);
|
||||
|
||||
if (arg_idx == -1) {
|
||||
continue;
|
||||
}
|
||||
|
||||
if (arg_idx < GGML_MAX_NODES) {
|
||||
*args[j] = result.leafs[arg_idx];
|
||||
} else {
|
||||
*args[j] = result.nodes[arg_idx - GGML_MAX_NODES];
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
result.nodes[i] = tensor;
|
||||
|
||||
fprintf(stderr, "%s: loaded node %d: '%16s', %3d dims, %9zu bytes\n", __func__, i, tensor->name, n_dims, ggml_nbytes(tensor));
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
void ggml_graph_print(const struct ggml_cgraph * cgraph) {
|
||||
int64_t perf_total_per_op_us[GGML_OP_COUNT] = {0};
|
||||
|
||||
|
|
|
|||
12
ggml.h
12
ggml.h
|
|
@ -451,9 +451,12 @@ extern "C" {
|
|||
|
||||
GGML_API size_t ggml_used_mem(const struct ggml_context * ctx);
|
||||
|
||||
GGML_API size_t ggml_set_scratch(struct ggml_context * ctx, struct ggml_scratch scratch);
|
||||
GGML_API size_t ggml_set_scratch (struct ggml_context * ctx, struct ggml_scratch scratch);
|
||||
GGML_API void ggml_set_no_alloc(struct ggml_context * ctx, bool no_alloc);
|
||||
|
||||
GGML_API void * ggml_get_mem_buffer(struct ggml_context * ctx);
|
||||
GGML_API size_t ggml_get_mem_size (struct ggml_context * ctx);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_new_tensor(
|
||||
struct ggml_context * ctx,
|
||||
enum ggml_type type,
|
||||
|
|
@ -492,6 +495,8 @@ extern "C" {
|
|||
GGML_API struct ggml_tensor * ggml_dup_tensor (struct ggml_context * ctx, const struct ggml_tensor * src);
|
||||
GGML_API struct ggml_tensor * ggml_view_tensor(struct ggml_context * ctx, const struct ggml_tensor * src);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_get_tensor(struct ggml_context * ctx, const char * name);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_set_zero(struct ggml_tensor * tensor);
|
||||
GGML_API struct ggml_tensor * ggml_set_i32 (struct ggml_tensor * tensor, int32_t value);
|
||||
GGML_API struct ggml_tensor * ggml_set_f32 (struct ggml_tensor * tensor, float value);
|
||||
|
|
@ -978,7 +983,10 @@ extern "C" {
|
|||
GGML_API void ggml_graph_compute(struct ggml_context * ctx, struct ggml_cgraph * cgraph);
|
||||
GGML_API void ggml_graph_reset (struct ggml_cgraph * cgraph);
|
||||
|
||||
GGML_API struct ggml_tensor * ggml_get_tensor_by_name(struct ggml_cgraph * cgraph, const char * name);
|
||||
GGML_API struct ggml_tensor * ggml_graph_get_tensor(struct ggml_cgraph * cgraph, const char * name);
|
||||
|
||||
GGML_API void ggml_graph_export(const struct ggml_cgraph * cgraph, const char * fname);
|
||||
GGML_API struct ggml_cgraph ggml_graph_import(const char * fname, struct ggml_context ** ctx_data, struct ggml_context ** ctx_eval);
|
||||
|
||||
// print info and performance information for the graph
|
||||
GGML_API void ggml_graph_print(const struct ggml_cgraph * cgraph);
|
||||
|
|
|
|||
Loading…
Reference in a new issue