ExternalVendorCode/whisper.cpp
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rpc : add rpc_msg_set_tensor_hash_req (llama/13353)

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* rpc : add rpc_msg_set_tensor_hash_req

Use a dedicated struct for the request of RPC_CMD_SET_TENSOR_HASH which
makes the code cleaner.

* fix
This commit is contained in:
Radoslav Gerganov 2025-05-09 10:31:07 +03:00 committed by Georgi Gerganov
parent e46df4850f
commit e27c91f6d6
1 changed files with 25 additions and 27 deletions
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52
ggml/src/ggml-rpc/ggml-rpc.cpp
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@ -151,6 +151,12 @@ struct rpc_msg_buffer_clear_req {
uint8_t value;
};
struct rpc_msg_set_tensor_hash_req {
rpc_tensor tensor;
uint64_t offset;
uint64_t hash;
};
struct rpc_msg_set_tensor_hash_rsp {
uint8_t result;
};
@ -548,15 +554,12 @@ static void ggml_backend_rpc_buffer_set_tensor(ggml_backend_buffer_t buffer, ggm
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
rpc_tensor rpc_tensor = serialize_tensor(tensor);
if (size > HASH_THRESHOLD) {
// input serialization format: | rpc_tensor | offset (8 bytes) | hash (8 bytes)
size_t input_size = sizeof(rpc_tensor) + sizeof(uint64_t) + sizeof(uint64_t);
std::vector<uint8_t> input(input_size, 0);
uint64_t hash = fnv_hash((const uint8_t*)data, size);
memcpy(input.data(), &rpc_tensor, sizeof(rpc_tensor));
memcpy(input.data() + sizeof(rpc_tensor), &offset, sizeof(offset));
memcpy(input.data() + sizeof(rpc_tensor) + sizeof(offset), &hash, sizeof(hash));
rpc_msg_set_tensor_hash_req request;
request.tensor = rpc_tensor;
request.offset = offset;
request.hash = fnv_hash((const uint8_t*)data, size);
rpc_msg_set_tensor_hash_rsp response;
bool status = send_rpc_cmd(ctx->sock, RPC_CMD_SET_TENSOR_HASH, input.data(), input.size(), &response, sizeof(response));
bool status = send_rpc_cmd(ctx->sock, RPC_CMD_SET_TENSOR_HASH, &request, sizeof(request), &response, sizeof(response));
GGML_ASSERT(status);
if (response.result) {
// the server has the same data, no need to send it
@ -864,7 +867,7 @@ public:
bool free_buffer(const rpc_msg_free_buffer_req & request);
bool buffer_clear(const rpc_msg_buffer_clear_req & request);
bool set_tensor(const std::vector<uint8_t> & input);
bool set_tensor_hash(const std::vector<uint8_t> & input, rpc_msg_set_tensor_hash_rsp & response);
bool set_tensor_hash(const rpc_msg_set_tensor_hash_req & request, rpc_msg_set_tensor_hash_rsp & response);
bool get_tensor(const rpc_msg_get_tensor_req & request, std::vector<uint8_t> & response);
bool copy_tensor(const rpc_msg_copy_tensor_req & request, rpc_msg_copy_tensor_rsp & response);
bool graph_compute(const std::vector<uint8_t> & input, rpc_msg_graph_compute_rsp & response);
@ -1101,18 +1104,10 @@ bool rpc_server::get_cached_file(uint64_t hash, std::vector<uint8_t> & data) {
return true;
}
bool rpc_server::set_tensor_hash(const std::vector<uint8_t> & input, rpc_msg_set_tensor_hash_rsp & response)
bool rpc_server::set_tensor_hash(const rpc_msg_set_tensor_hash_req & request, rpc_msg_set_tensor_hash_rsp & response)
{
// serialization format: | rpc_tensor | offset (8 bytes) | hash (8 bytes) |
if (input.size() != sizeof(rpc_tensor) + 16) {
return false;
}
const rpc_tensor * in_tensor = (const rpc_tensor *)input.data();
uint64_t offset;
memcpy(&offset, input.data() + sizeof(rpc_tensor), sizeof(offset));
const uint64_t * hash = (const uint64_t *)(input.data() + sizeof(rpc_tensor) + sizeof(offset));
std::vector<uint8_t> cached_file;
if (!get_cached_file(*hash, cached_file)) {
if (!get_cached_file(request.hash, cached_file)) {
response.result = 0;
return true;
}
@ -1125,25 +1120,28 @@ bool rpc_server::set_tensor_hash(const std::vector<uint8_t> & input, rpc_msg_set
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);
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
GGML_LOG_ERROR("[%s] error deserializing tensor\n", __func__);
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);
GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %zu, hash: %" PRIx64 "\n",
__func__, (void*)tensor->buffer, tensor->data, request.offset, size, request.hash);
// sanitize tensor->data
{
const size_t p0 = (size_t) ggml_backend_buffer_get_base(tensor->buffer);
const size_t p1 = p0 + ggml_backend_buffer_get_size(tensor->buffer);
if (in_tensor->data + offset < p0 || in_tensor->data + offset >= p1 || size > (p1 - in_tensor->data - offset)) {
if (request.tensor.data + request.offset < p0
|| request.tensor.data + request.offset >= p1
|| size > (p1 - request.tensor.data - request.offset)) {
GGML_LOG_ERROR("[%s] tensor data region (data=0x%" PRIx64 ", offset=%" PRIu64 ", size=%zu, hash=0x%" PRIx64 ") out of buffer bounds [0x%zx, 0x%zx)\n",
__func__, in_tensor->data, offset, size, *hash, p0, p1);
__func__, request.tensor.data, request.offset, size, request.hash, p0, p1);
return false;
}
}
ggml_backend_tensor_set(tensor, cached_file.data(), offset, size);
ggml_backend_tensor_set(tensor, cached_file.data(), request.offset, size);
response.result = 1;
return true;
}
@ -1503,12 +1501,12 @@ static void rpc_serve_client(ggml_backend_t backend, const char * cache_dir,
break;
}
case RPC_CMD_SET_TENSOR_HASH: {
std::vector<uint8_t> input;
if (!recv_msg(sockfd, input)) {
rpc_msg_set_tensor_hash_req request;
if (!recv_msg(sockfd, &request, sizeof(request))) {
return;
}
rpc_msg_set_tensor_hash_rsp response;
if (!server.set_tensor_hash(input, response)) {
if (!server.set_tensor_hash(request, response)) {
return;
}
if (!send_msg(sockfd, &response, sizeof(response))) {