ikawrakow/ik_llama.cpp
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Cleaned up and improved type/error handling.

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matt23654
2025-01-02 15:53:50 +00:00
committed by Saood Karim
parent 105b40caf7
commit 14f2d8e20c
1 changed files with 22 additions and 35 deletions
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57
ggml/src/ggml-rpc.cpp
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@@ -110,9 +110,9 @@ struct rpc_msg_init_tensor_req {
rpc_tensor tensor;
};
struct rpc_msg_init_tensor_rsp {
uint8_t result; // success/failure
};
//struct rpc_msg_init_tensor_rsp {
// uint8_t result; // success/failure
//};
struct rpc_msg_alloc_buffer_req {
uint64_t size;
@@ -466,16 +466,15 @@ static rpc_tensor serialize_tensor(const ggml_tensor * tensor) {
}
GGML_CALL static void ggml_backend_rpc_buffer_init_tensor(ggml_backend_buffer_t buffer, ggml_tensor * tensor) {
//UNUSED(buffer);
ggml_backend_rpc_buffer_context * ctx = (ggml_backend_rpc_buffer_context *)buffer->context;
// CUDA backend on the server pads everything to 512 due to CUDA limitations.
// Due to bandwidth constraints, we only call the server init tensor functions if necessary.
if (ggml_is_quantized(tensor->type) && (tensor->ne[0] % 512 != 0)) {
// TODO: this check is due to MATRIX_ROW_PADDING in CUDA and should be generalized
//GGML_ASSERT(tensor->ne[0] % 512 == 0 && "unsupported quantized tensor");
rpc_msg_init_tensor_req request;
request.tensor = serialize_tensor(tensor);
//rpc_msg_init_tensor_rsp response;
bool status = send_rpc_cmd(ctx->sock, RPC_CMD_INIT_TENSOR, &request, sizeof(request), nullptr, 0);
GGML_ASSERT(status);
}
@@ -629,13 +628,15 @@ GGML_CALL static size_t ggml_backend_rpc_get_max_size(ggml_backend_buffer_type_t
return buft_ctx->max_size;
}
<<<<<<< HEAD:ggml/src/ggml-rpc.cpp
GGML_CALL static size_t ggml_backend_rpc_buffer_type_get_alloc_size(ggml_backend_buffer_type_t buft, const ggml_tensor * tensor) {
=======
// See comments in init_tensor.
if (ggml_is_quantized(tensor->type) && (tensor->ne[0] % 512 != 0)) {
ggml_backend_rpc_buffer_type_context * buft_ctx = (ggml_backend_rpc_buffer_type_context *)buft->context;
auto sock = get_socket(buft_ctx->endpoint);
rpc_msg_get_alloc_size_req request;
request.tensor = serialize_tensor(tensor);
rpc_msg_get_alloc_size_rsp response;
@@ -874,41 +875,30 @@ private:
};
bool rpc_server::get_alloc_size(const rpc_msg_get_alloc_size_req & request, rpc_msg_get_alloc_size_rsp & response) {
ggml_backend_buffer_type_t buft = ggml_backend_get_default_buffer_type(backend);
ggml_backend_buffer_type_t buft;
struct ggml_init_params params {
/*.mem_size =*/ ggml_tensor_overhead(),
/*.mem_buffer =*/ NULL,
/*.no_alloc =*/ true,
};
struct ggml_context * ctx = ggml_init(params);
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
printf("Got nullptr\n");
fprintf(stderr,"Null tensor pointer passed to server get_alloc_size function.\n");
ggml_free(ctx);
return false;
}
printf("Getting buft\n");
//ggml_backend_buffer_get_alloc_size(tensor->buffer,tensor)
//if (tensor->buffer == nullptr) {
// printf("Got null buffer\n");
// response.alloc_size = 0;
// ggml_free(ctx);
// return true;
//}
if (tensor->buffer == nullptr) {
//No buffer allocated.
buft = ggml_backend_get_default_buffer_type(backend);
} else {
buft = tensor->buffer->buft;
}
response.alloc_size = ggml_backend_buft_get_alloc_size(buft,tensor);
// Call the backend's buffer_type_get_alloc_size function
//ggml_backend_buffer_type_t buft = tensor->buffer->buft;
//if (buft && buft->iface.get_alloc_size) {
// printf("Called buffer type get alloc size\n");
// response.alloc_size = buft->iface.get_alloc_size(buft, tensor);
//} else {
// printf("Called ggml_nbytes");
// response.alloc_size = ggml_nbytes(tensor);
//}
ggml_free(ctx);
return true;
@@ -1088,20 +1078,17 @@ bool rpc_server::init_tensor(const rpc_msg_init_tensor_req & request) {
struct ggml_context * ctx = ggml_init(params);
ggml_tensor * tensor = deserialize_tensor(ctx, &request.tensor);
if (tensor == nullptr) {
printf("Null tensor\n");
fprintf(stderr,"Null tensor pointer passed to server init_tensor function.\n");
ggml_free(ctx);
return false;
}
printf("about to call buffer\n");
//ggml_backend_init_tensor
// Call the backend's buffer_init_tensor function
ggml_backend_buffer_t buffer = tensor->buffer;
if (buffer && buffer->iface.init_tensor) {
printf("Calling buffer iface function\n");
buffer->iface.init_tensor(buffer, tensor);
} else {
fprintf(stderr,"Null buffer for tensor passed to init_tensor function\n");
}
ggml_free(ctx);