mirror of
https://github.com/ggerganov/llama.cpp.git
synced 2024-12-24 10:24:35 +00:00
ggml : improve ggml_graph_dump_dot, add ggml_format_name (#1978)
* Improve ggml_graph_dump_dot, add ggml_format_name * add more automatic names to view ops * fix name of copies
This commit is contained in:
slaren
GitHub
parent
11da1a85cd
commit
f2c754e1c3
135
ggml.c
135
ggml.c
@ -24,6 +24,7 @@
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#include <stdio.h>
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#include <float.h>
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#include <limits.h>
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#include <stdarg.h>
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#ifdef GGML_USE_METAL
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#include <unistd.h>
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@ -4734,10 +4735,19 @@ struct ggml_tensor * ggml_set_name(struct ggml_tensor * tensor, const char * nam
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return tensor;
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}
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struct ggml_tensor * ggml_format_name(struct ggml_tensor * tensor, const char * fmt, ...) {
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va_list args;
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va_start(args, fmt);
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vsnprintf(tensor->name, sizeof(tensor->name), fmt, args);
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va_end(args);
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return tensor;
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}
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struct ggml_tensor * ggml_view_tensor(
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struct ggml_context * ctx,
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const struct ggml_tensor * src) {
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, src->type, src->n_dims, src->ne, src->data);
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ggml_format_name(result, "%s (view)", src->name);
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result->nb[0] = src->nb[0];
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result->nb[1] = src->nb[1];
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@ -5899,6 +5909,11 @@ struct ggml_tensor * ggml_cpy_impl(
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// make a view of the destination
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struct ggml_tensor * result = ggml_view_tensor(ctx, b);
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if (strlen(b->name) > 0) {
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ggml_format_name(result, "%s (copy of %s)", b->name, a->name);
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} else {
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ggml_format_name(result, "%s (copy)", a->name);
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}
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result->op = GGML_OP_CPY;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -5935,6 +5950,7 @@ struct ggml_tensor * ggml_cont_impl(
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}
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struct ggml_tensor * result = inplace ? ggml_view_tensor(ctx, a) : ggml_dup_tensor(ctx, a);
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ggml_format_name(result, "%s (cont)", a->name);
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result->op = GGML_OP_CONT;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -5978,6 +5994,7 @@ struct ggml_tensor * ggml_reshape(
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}
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, b->n_dims, b->ne, a->data);
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ggml_format_name(result, "%s (reshaped)", a->name);
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result->op = GGML_OP_RESHAPE;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -6002,6 +6019,7 @@ struct ggml_tensor * ggml_reshape_1d(
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const int64_t ne[1] = { ne0 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 1, ne, a->data);
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ggml_format_name(result, "%s (reshaped)", a->name);
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result->op = GGML_OP_RESHAPE;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -6027,6 +6045,7 @@ struct ggml_tensor * ggml_reshape_2d(
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const int64_t ne[2] = { ne0, ne1 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 2, ne, a->data);
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ggml_format_name(result, "%s (reshaped)", a->name);
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result->op = GGML_OP_RESHAPE;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -6053,6 +6072,7 @@ struct ggml_tensor * ggml_reshape_3d(
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const int64_t ne[3] = { ne0, ne1, ne2 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 3, ne, a->data);
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ggml_format_name(result, "%s (reshaped)", a->name);
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result->op = GGML_OP_RESHAPE;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -6081,6 +6101,7 @@ struct ggml_tensor * ggml_reshape_4d(
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const int64_t ne[4] = { ne0, ne1, ne2, ne3 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 4, ne, a->data);
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ggml_format_name(result, "%s (reshaped)", a->name);
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result->op = GGML_OP_RESHAPE;
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result->grad = is_node ? ggml_dup_tensor(ctx, result) : NULL;
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@ -6105,10 +6126,12 @@ struct ggml_tensor * ggml_view_1d(
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}
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 1, &ne0, (char *) a->data + offset);
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ggml_format_name(result, "%s (view)", a->name);
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ggml_scratch_save(ctx);
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struct ggml_tensor * offs = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 2);
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ggml_set_name(offs, "offset");
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memcpy(offs->data, &offset, 2*sizeof(int32_t));
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ggml_scratch_load(ctx);
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@ -6141,10 +6164,12 @@ struct ggml_tensor * ggml_view_2d(
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const int64_t ne[GGML_MAX_DIMS] = { ne0, ne1, 1, 1 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 2, ne, (char *) a->data + offset);
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ggml_format_name(result, "%s (view)", a->name);
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ggml_scratch_save(ctx);
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struct ggml_tensor * offs = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 2);
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ggml_set_name(offs, "offset");
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memcpy(offs->data, &offset, 2*sizeof(int32_t));
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ggml_scratch_load(ctx);
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@ -6183,10 +6208,12 @@ struct ggml_tensor * ggml_view_3d(
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const int64_t ne[GGML_MAX_DIMS] = { ne0, ne1, ne2, 1 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 3, ne, (char *) a->data + offset);
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ggml_format_name(result, "%s (view)", a->name);
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ggml_scratch_save(ctx);
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struct ggml_tensor * offs = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 2);
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ggml_set_name(offs, "offset");
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memcpy(offs->data, &offset, 2*sizeof(int32_t));
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ggml_scratch_load(ctx);
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@ -6227,10 +6254,12 @@ struct ggml_tensor * ggml_view_4d(
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const int64_t ne[GGML_MAX_DIMS] = { ne0, ne1, ne2, ne3 };
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struct ggml_tensor * result = ggml_new_tensor_impl(ctx, a->type, 4, ne, (char *) a->data + offset);
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ggml_format_name(result, "%s (view)", a->name);
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ggml_scratch_save(ctx);
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struct ggml_tensor * offs = ggml_new_tensor_1d(ctx, GGML_TYPE_I32, 2);
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ggml_set_name(offs, "offset");
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memcpy(offs->data, &offset, 2*sizeof(int32_t));
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ggml_scratch_load(ctx);
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@ -6276,6 +6305,7 @@ struct ggml_tensor * ggml_permute(
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}
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struct ggml_tensor * result = ggml_view_tensor(ctx, a);
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ggml_format_name(result, "%s (permuted)", a->name);
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int ne[GGML_MAX_DIMS];
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int nb[GGML_MAX_DIMS];
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@ -6335,6 +6365,7 @@ struct ggml_tensor * ggml_transpose(
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}
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struct ggml_tensor * result = ggml_view_tensor(ctx, a);
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ggml_format_name(result, "%s (transposed)", a->name);
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result->ne[0] = a->ne[1];
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result->ne[1] = a->ne[0];
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@ -16004,7 +16035,7 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
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GGML_ASSERT(cgraph->n_leafs < GGML_MAX_NODES);
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if (strlen(node->name) == 0) {
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snprintf(node->name, sizeof(node->name), "leaf_%d", cgraph->n_leafs);
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ggml_format_name(node, "leaf_%d", cgraph->n_leafs);
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}
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cgraph->leafs[cgraph->n_leafs] = node;
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@ -16013,7 +16044,7 @@ static void ggml_visit_parents(struct ggml_cgraph * cgraph, struct ggml_tensor *
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GGML_ASSERT(cgraph->n_nodes < GGML_MAX_NODES);
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if (strlen(node->name) == 0) {
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snprintf(node->name, sizeof(node->name), "node_%d", cgraph->n_nodes);
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ggml_format_name(node, "node_%d", cgraph->n_nodes);
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}
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cgraph->nodes[cgraph->n_nodes] = node;
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@ -17397,6 +17428,26 @@ static struct ggml_tensor * ggml_graph_get_parent(const struct ggml_cgraph * cgr
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return NULL;
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}
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static void ggml_graph_dump_dot_node_edge(FILE * fp, const struct ggml_cgraph * gb, struct ggml_tensor * node, struct ggml_tensor * parent, const char * label) {
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struct ggml_tensor * gparent = ggml_graph_get_parent(gb, node);
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struct ggml_tensor * gparent0 = ggml_graph_get_parent(gb, parent);
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fprintf(fp, " \"%p\":%s -> \"%p\":%s [ arrowhead = %s; style = %s; label = \"%s\"; ]\n",
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gparent0 ? (void *) gparent0 : (void *) parent,
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gparent0 ? "g" : "x",
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gparent ? (void *) gparent : (void *) node,
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gparent ? "g" : "x",
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gparent ? "empty" : "vee",
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gparent ? "dashed" : "solid",
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label);
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}
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static void ggml_graph_dump_dot_leaf_edge(FILE * fp, struct ggml_tensor * node, struct ggml_tensor * parent, const char * label) {
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fprintf(fp, " \"%p\":%s -> \"%p\":%s [ label = \"%s\"; ]\n",
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(void *) parent, "x",
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(void *) node, "x",
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label);
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}
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void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph * gf, const char * filename) {
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char color[16];
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@ -17432,7 +17483,9 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
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(void *) node, color);
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if (strlen(node->name) > 0) {
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fprintf(fp, "%s |", node->name);
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fprintf(fp, "%s (%s)|", node->name, ggml_type_name(node->type));
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} else {
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fprintf(fp, "(%s)|", ggml_type_name(node->type));
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}
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if (node->n_dims == 2) {
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@ -17441,7 +17494,6 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
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fprintf(fp, "%d [%" PRId64 ", %" PRId64 ", %" PRId64 "] | <x>%s", i, node->ne[0], node->ne[1], node->ne[2], GGML_OP_SYMBOL[node->op]);
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}
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if (node->grad) {
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fprintf(fp, " | <g>%s\"; ]\n", GGML_OP_SYMBOL[node->grad->op]);
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} else {
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@ -17460,18 +17512,29 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
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(void *) node, color);
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if (strlen(node->name) > 0) {
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fprintf(fp, "%s | ", node->name);
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fprintf(fp, "%s (%s)|", node->name, ggml_type_name(node->type));
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} else {
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fprintf(fp, "(%s)|", ggml_type_name(node->type));
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}
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if (ggml_nelements(node) == 1) {
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if (node->type == GGML_TYPE_I8 || node->type == GGML_TYPE_I16 || node->type == GGML_TYPE_I32) {
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fprintf(fp, "%d", ggml_get_i32_1d(node, 0));
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fprintf(fp, "CONST %d [%" PRId64 ", %" PRId64 "]", i, node->ne[0], node->ne[1]);
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if (ggml_nelements(node) < 5) {
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fprintf(fp, " | (");
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for (int j = 0; j < ggml_nelements(node); j++) {
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if (node->type == GGML_TYPE_I8 || node->type == GGML_TYPE_I16 || node->type == GGML_TYPE_I32) {
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fprintf(fp, "%d", ggml_get_i32_1d(node, j));
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}
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else if (node->type == GGML_TYPE_F32 || node->type == GGML_TYPE_F16) {
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fprintf(fp, "%.1e", (double)ggml_get_f32_1d(node, j));
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}
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else {
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fprintf(fp, "#");
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}
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if (j < ggml_nelements(node) - 1) {
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fprintf(fp, ", ");
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}
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}
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else {
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fprintf(fp, "%.1e", (double)ggml_get_f32_1d(node, 0));
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}
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}
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else {
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fprintf(fp, "CONST %d [%" PRId64 ", %" PRId64 "]", i, node->ne[0], node->ne[1]);
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fprintf(fp, ")");
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}
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fprintf(fp, "\"; ]\n");
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}
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@ -17479,30 +17542,20 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
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for (int i = 0; i < gb->n_nodes; i++) {
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struct ggml_tensor * node = gb->nodes[i];
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struct ggml_tensor * parent = ggml_graph_get_parent(gb, node);
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if (node->src0) {
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struct ggml_tensor * parent0 = ggml_graph_get_parent(gb, node->src0);
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fprintf(fp, " \"%p\":%s -> \"%p\":%s [ arrowhead = %s; style = %s; label = \"x\"; ]\n",
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parent0 ? (void *) parent0 : (void *) node->src0,
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parent0 ? "g" : "x",
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parent ? (void *) parent : (void *) node,
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parent ? "g" : "x",
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parent ? "empty" : "vee",
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parent ? "dashed" : "solid");
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ggml_graph_dump_dot_node_edge(fp, gb, node, node->src0, "x");
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}
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if (node->src1) {
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struct ggml_tensor * parent1 = ggml_graph_get_parent(gb, node->src1);
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ggml_graph_dump_dot_node_edge(fp, gb, node, node->src1, "y");
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}
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fprintf(fp, " \"%p\":%s -> \"%p\":%s [ arrowhead = %s; style = %s; label = \"y\"; ]\n",
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parent1 ? (void *) parent1 : (void *) node->src1,
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parent1 ? "g" : "x",
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parent ? (void *) parent : (void *) node,
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parent ? "g" : "x",
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parent ? "empty" : "vee",
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parent ? "dashed" : "solid");
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for (int j = 0; j < GGML_MAX_OPT; j++) {
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if (node->opt[j]) {
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char label[16];
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snprintf(label, sizeof(label), "opt %d", j);
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ggml_graph_dump_dot_node_edge(fp, gb, node, node->opt[j], label);
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}
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}
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}
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@ -17510,15 +17563,19 @@ void ggml_graph_dump_dot(const struct ggml_cgraph * gb, const struct ggml_cgraph
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struct ggml_tensor * node = gb->leafs[i];
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if (node->src0) {
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fprintf(fp, " \"%p\":%s -> \"%p\":%s [ label = \"x\"; ]\n",
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(void *) node->src0, "x",
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(void *) node, "x");
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ggml_graph_dump_dot_leaf_edge(fp, node, node->src0, "x");
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}
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if (node->src1) {
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fprintf(fp, " \"%p\":%s -> \"%p\":%s [ label = \"y\"; ]\n",
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(void *) node->src1, "x",
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(void *) node, "x");
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ggml_graph_dump_dot_leaf_edge(fp, node, node->src1, "y");
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}
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for (int j = 0; j < GGML_MAX_OPT; j++) {
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if (node->opt[j]) {
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char label[16];
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snprintf(label, sizeof(label), "opt %d", j);
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ggml_graph_dump_dot_leaf_edge(fp, node, node->opt[j], label);
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}
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}
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}
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1
ggml.h
1
ggml.h
@ -563,6 +563,7 @@ extern "C" {
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GGML_API const char * ggml_get_name(const struct ggml_tensor * tensor);
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GGML_API struct ggml_tensor * ggml_set_name(struct ggml_tensor * tensor, const char * name);
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GGML_API struct ggml_tensor * ggml_format_name(struct ggml_tensor * tensor, const char * fmt, ...);
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//
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// operations on tensors with backpropagation
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