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Merged
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Apr 14, 2025
Merged

rpc : use ggml_context_ptr #12938

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45 changes: 23 additions & 22 deletions ggml/src/ggml-rpc/ggml-rpc.cpp
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Original file line number Diff line number Diff line change
@@ -1,6 +1,7 @@
#include "ggml-rpc.h"
#include "ggml-impl.h"
#include "ggml-backend-impl.h"
#include "ggml-cpp.h"

#include <cinttypes>
#include <string>
Expand Down Expand Up @@ -853,12 +854,13 @@ bool rpc_server::get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_
/*.no_alloc =*/ true,
};

struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);

if (tensor == nullptr) {
GGML_LOG_ERROR("Null tensor pointer passed to server get_alloc_size function.\n");
ggml_free(ctx);
return false;
}

Expand All @@ -871,7 +873,6 @@ bool rpc_server::get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_

response.alloc_size = ggml_backend_buft_get_alloc_size(buft,tensor);

ggml_free(ctx);
return true;
}

Expand Down Expand Up @@ -985,11 +986,12 @@ bool rpc_server::set_tensor(const std::vector<uint8_t> & input) {
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
ggml_tensor * tensor = deserialize_tensor(ctx, in_tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("[%s] error deserializing tensor\n", __func__);
ggml_free(ctx);
return false;
}
GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %zu\n", __func__, (void*)tensor->buffer, tensor->data, offset, size);
Expand All @@ -1016,7 +1018,6 @@ bool rpc_server::set_tensor(const std::vector<uint8_t> & input) {
printf("[%s] saved to '%s'\n", __func__, cache_file.c_str());
}
ggml_backend_tensor_set(tensor, data, offset, size);
ggml_free(ctx);
return true;
}

Expand Down Expand Up @@ -1060,11 +1061,12 @@ bool rpc_server::set_tensor_hash(const std::vector<uint8_t> & input, rpc_msg_set
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
ggml_tensor * tensor = deserialize_tensor(ctx, in_tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("[%s] error deserializing tensor\n", __func__);
ggml_free(ctx);
return false;
}
GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %zu, hash: %" PRIx64 "\n", __func__, (void*)tensor->buffer, tensor->data, offset, size, *hash);
Expand All @@ -1080,7 +1082,6 @@ bool rpc_server::set_tensor_hash(const std::vector<uint8_t> & input, rpc_msg_set
}
ggml_backend_tensor_set(tensor, cached_file.data(), offset, size);
response.result = 1;
ggml_free(ctx);
return true;
}

Expand All @@ -1090,11 +1091,12 @@ bool rpc_server::init_tensor(const rpc_msg_init_tensor_req & request) {
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("Null tensor pointer passed to server init_tensor function.\n");
ggml_free(ctx);
return false;
}

Expand All @@ -1110,11 +1112,9 @@ bool rpc_server::init_tensor(const rpc_msg_init_tensor_req & request) {
// This pointer can either be passed around client/server, or probably better stored server-side and kept track of.
// Currently unimplemented.
GGML_LOG_ERROR("tensor->extra populated by the backend, this is currently unsupported.\n");
ggml_free(ctx);
return false;
}

ggml_free(ctx);
return true;
}

Expand All @@ -1124,11 +1124,12 @@ bool rpc_server::get_tensor(const rpc_msg_get_tensor_req & request, std::vector<
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("[%s] error deserializing tensor\n", __func__);
ggml_free(ctx);
return false;
}
GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %" PRIu64 "\n", __func__, (void*)tensor->buffer, tensor->data, request.offset, request.size);
Expand All @@ -1147,7 +1148,6 @@ bool rpc_server::get_tensor(const rpc_msg_get_tensor_req & request, std::vector<

response.resize(request.size, 0);
ggml_backend_tensor_get(tensor, response.data(), request.offset, request.size);
ggml_free(ctx);
return true;
}

Expand All @@ -1157,12 +1157,14 @@ bool rpc_server::copy_tensor(const rpc_msg_copy_tensor_req & request, rpc_msg_co
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();

ggml_tensor * src = deserialize_tensor(ctx, &request.src);
ggml_tensor * dst = deserialize_tensor(ctx, &request.dst);
if (src == nullptr || dst == nullptr) {
GGML_LOG_ERROR("[%s] error deserializing tensors\n", __func__);
ggml_free(ctx);
return false;
}

Expand All @@ -1180,15 +1182,13 @@ bool rpc_server::copy_tensor(const rpc_msg_copy_tensor_req & request, rpc_msg_co
dst_data + src_size,
dst_base,
dst_base + dst_buf_sz);
ggml_free(ctx);
return false;
}

GGML_PRINT_DEBUG("[%s] src->buffer: %p, dst->buffer: %p\n",
__func__, (void*) src->buffer, (void*) dst->buffer);

response.result = ggml_backend_buffer_copy_tensor(src, dst);
ggml_free(ctx);
return true;
}

Expand Down Expand Up @@ -1242,7 +1242,9 @@ bool rpc_server::graph_compute(const std::vector<uint8_t> & input, rpc_msg_graph
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_context_ptr ctx_ptr { ggml_init(params) };
GGML_ASSERT(ctx_ptr != nullptr);
ggml_context * ctx = ctx_ptr.get();
struct ggml_cgraph * graph = ggml_new_graph_custom(ctx, n_nodes, false);
graph->n_nodes = n_nodes;
std::unordered_map<uint64_t, const rpc_tensor*> tensor_ptrs;
Expand All @@ -1257,7 +1259,6 @@ bool rpc_server::graph_compute(const std::vector<uint8_t> & input, rpc_msg_graph
}
ggml_status status = ggml_backend_graph_compute(backend, graph);
response.result = status;
ggml_free(ctx);
return true;
}

Expand Down