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https://github.com/ggerganov/whisper.cpp.git
synced 2024-11-07 16:44:13 +01:00
rpc : sanitize tensor data + warnings (llama/0)
Co-authored-by: slaren <slarengh@gmail.com>
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81c999fe0a
commit
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@ -197,6 +197,10 @@ static std::shared_ptr<socket_t> create_server_socket(const char * host, int por
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fprintf(stderr, "Failed to set SO_REUSEADDR\n");
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return nullptr;
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}
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if (inet_addr(host) == INADDR_NONE) {
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fprintf(stderr, "Invalid host address: %s\n", host);
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return nullptr;
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}
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struct sockaddr_in serv_addr;
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serv_addr.sin_family = AF_INET;
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serv_addr.sin_addr.s_addr = inet_addr(host);
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@ -879,6 +883,14 @@ ggml_tensor * rpc_server::deserialize_tensor(struct ggml_context * ctx, const rp
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if (result->buffer && buffers.find(result->buffer) == buffers.end()) {
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return nullptr;
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}
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// require that the tensor data does not go beyond the buffer end
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uint64_t tensor_size = (uint64_t) ggml_nbytes(result);
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uint64_t buffer_start = (uint64_t) ggml_backend_buffer_get_base(result->buffer);
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uint64_t buffer_size = (uint64_t) ggml_backend_buffer_get_size(result->buffer);
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GGML_ASSERT(tensor->data + tensor_size >= tensor->data); // check for overflow
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GGML_ASSERT(tensor->data >= buffer_start && tensor->data + tensor_size <= buffer_start + buffer_size);
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result->op = (ggml_op) tensor->op;
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for (uint32_t i = 0; i < GGML_MAX_OP_PARAMS / sizeof(int32_t); i++) {
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result->op_params[i] = tensor->op_params[i];
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@ -898,7 +910,7 @@ bool rpc_server::set_tensor(const std::vector<uint8_t> & input) {
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const rpc_tensor * in_tensor = (const rpc_tensor *)input.data();
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uint64_t offset;
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memcpy(&offset, input.data() + sizeof(rpc_tensor), sizeof(offset));
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size_t size = input.size() - sizeof(rpc_tensor) - sizeof(offset);
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const size_t size = input.size() - sizeof(rpc_tensor) - sizeof(offset);
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struct ggml_init_params params {
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/*.mem_size =*/ ggml_tensor_overhead(),
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@ -913,6 +925,17 @@ bool rpc_server::set_tensor(const std::vector<uint8_t> & input) {
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return false;
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}
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GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %zu\n", __func__, (void*)tensor->buffer, tensor->data, offset, size);
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// sanitize tensor->data
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{
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const size_t p0 = (size_t) ggml_backend_buffer_get_base(tensor->buffer);
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const size_t p1 = p0 + ggml_backend_buffer_get_size(tensor->buffer);
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if (in_tensor->data + offset < p0 || in_tensor->data + offset >= p1 || size > (p1 - in_tensor->data - offset)) {
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GGML_ABORT("[%s] tensor->data out of bounds\n", __func__);
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}
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}
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const void * data = input.data() + sizeof(rpc_tensor) + sizeof(offset);
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ggml_backend_tensor_set(tensor, data, offset, size);
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ggml_free(ctx);
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@ -943,6 +966,17 @@ bool rpc_server::get_tensor(const std::vector<uint8_t> & input, std::vector<uint
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return false;
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}
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GGML_PRINT_DEBUG("[%s] buffer: %p, data: %p, offset: %" PRIu64 ", size: %" PRIu64 "\n", __func__, (void*)tensor->buffer, tensor->data, offset, size);
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// sanitize tensor->data
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{
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const size_t p0 = (size_t) ggml_backend_buffer_get_base(tensor->buffer);
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const size_t p1 = p0 + ggml_backend_buffer_get_size(tensor->buffer);
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if (in_tensor->data + offset < p0 || in_tensor->data + offset >= p1 || size > (p1 - in_tensor->data - offset)) {
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GGML_ABORT("[%s] tensor->data out of bounds\n", __func__);
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}
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}
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// output serialization format: | data (size bytes) |
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output.resize(size, 0);
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ggml_backend_tensor_get(tensor, output.data(), offset, size);
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@ -3724,7 +3724,8 @@ static struct ggml_tensor * ggml_new_tensor_impl(
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struct ggml_tensor * view_src,
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size_t view_offs) {
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assert(n_dims >= 1 && n_dims <= GGML_MAX_DIMS);
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GGML_ASSERT(type >= 0 && type < GGML_TYPE_COUNT);
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GGML_ASSERT(n_dims >= 1 && n_dims <= GGML_MAX_DIMS);
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// find the base tensor and absolute offset
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if (view_src != NULL && view_src->view_src != NULL) {
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