From 9456bba1210a6ec95f96adf92ff8b263d7786253 Mon Sep 17 00:00:00 2001 From: hongruichen Date: Mon, 17 Jun 2024 18:44:19 +0800 Subject: [PATCH] rename --- ggml-qnn.cpp | 68 ++++++++++++++++++++++++++-------------------------- 1 file changed, 34 insertions(+), 34 deletions(-) diff --git a/ggml-qnn.cpp b/ggml-qnn.cpp index c23d67bb3..b97b20245 100644 --- a/ggml-qnn.cpp +++ b/ggml-qnn.cpp @@ -2077,8 +2077,8 @@ private: void operator=(ggml_qnn_tensor_readwrite&&) = delete; }; -using ggml_qnn_tensor_reader = ggml_qnn_tensor_readwrite; -using ggml_qnn_tensor_writer = ggml_qnn_tensor_readwrite; +using ggml_qnn_tensor_output = ggml_qnn_tensor_readwrite; +using ggml_qnn_tensor_input = ggml_qnn_tensor_readwrite; //TODO: this function can be removed later because there are duplicated codes with ggml_qnn_mul_mat // keep it for illustrate how to implement a specified GGMPL OP using QNN API + QNN RPC @@ -2164,22 +2164,22 @@ static void ggml_qnn_add(ggml_backend_qnn_context * ctx, const ggml_tensor * src QNN_LOG_INFO("create qnn graph handle with graph name %s ok\n", graph_name.c_str()); } - ggml_qnn_tensor_writer tensor_writer0(src0, graph_handle, ctx); - if (!tensor_writer0.is_valid()) { + ggml_qnn_tensor_input tensor_input0(src0, graph_handle, ctx); + if (!tensor_input0.is_valid()) { goto failure; } - ggml_qnn_tensor_writer tensor_writer1(src1, graph_handle, ctx); - if (!tensor_writer1.is_valid()) { + ggml_qnn_tensor_input tensor_input1(src1, graph_handle, ctx); + if (!tensor_input1.is_valid()) { QNN_LOG_INFO("error = %d\n", error); goto failure; } - ggml_qnn_tensor_reader tensor_reader(dst, graph_handle, ctx); - if (!tensor_reader.is_valid()) { + ggml_qnn_tensor_output tensor_output(dst, graph_handle, ctx); + if (!tensor_output.is_valid()) { goto failure; } - Qnn_Tensor_t tensor_inputs[] = {*tensor_writer0.get_qnn_tensor(), *tensor_writer1.get_qnn_tensor()}; - Qnn_Tensor_t tensor_outputs[] = {*tensor_reader.get_qnn_tensor()}; + Qnn_Tensor_t tensor_inputs[] = {*tensor_input0.get_qnn_tensor(), *tensor_input1.get_qnn_tensor()}; + Qnn_Tensor_t tensor_outputs[] = {*tensor_output.get_qnn_tensor()}; Qnn_OpConfig_t op_config = { (Qnn_OpConfigVersion_t) 1, .v1 = {"ggml_op_add", @@ -2215,18 +2215,18 @@ static void ggml_qnn_add(ggml_backend_qnn_context * ctx, const ggml_tensor * src } auto graph_item = std::make_tuple(graph_handle, - tensor_writer0.get_qnn_tensor(), - tensor_writer1.get_qnn_tensor(), - tensor_reader.get_qnn_tensor()); + tensor_input0.get_qnn_tensor(), + tensor_input1.get_qnn_tensor(), + tensor_output.get_qnn_tensor()); instance->_qnn_graph_map[map_entry] = graph_item; } else { auto & graph_item = instance->_qnn_graph_map[map_entry]; - ggml_qnn_tensor_writer tensor_writer0(src0, std::get<1>(graph_item), ctx); - ggml_qnn_tensor_writer tensor_writer1(src1, std::get<2>(graph_item), ctx); - ggml_qnn_tensor_reader tensor_reader(dst, std::get<3>(graph_item), ctx); + ggml_qnn_tensor_input tensor_input0(src0, std::get<1>(graph_item), ctx); + ggml_qnn_tensor_input tensor_input1(src1, std::get<2>(graph_item), ctx); + ggml_qnn_tensor_output tensor_output(dst, std::get<3>(graph_item), ctx); - Qnn_Tensor_t tensor_inputs[] = {*tensor_writer0.get_qnn_tensor(), *tensor_writer1.get_qnn_tensor()}; - Qnn_Tensor_t tensor_outputs[] = {*tensor_reader.get_qnn_tensor()}; + Qnn_Tensor_t tensor_inputs[] = {*tensor_input0.get_qnn_tensor(), *tensor_input1.get_qnn_tensor()}; + Qnn_Tensor_t tensor_outputs[] = {*tensor_output.get_qnn_tensor()}; error = qnn_raw_interface.graphExecute(graph_handle, tensor_inputs,2, tensor_outputs,1, @@ -2360,21 +2360,21 @@ static void ggml_qnn_mul_mat(ggml_backend_qnn_context * ctx, goto failure; } - ggml_qnn_tensor_writer tensor_writer0(src0, graph_handle, ctx); - if (!tensor_writer0.is_valid()) { + ggml_qnn_tensor_input tensor_input0(src0, graph_handle, ctx); + if (!tensor_input0.is_valid()) { goto failure; } - ggml_qnn_tensor_writer tensor_writer1(src1, graph_handle, ctx); - if (!tensor_writer1.is_valid()) { + ggml_qnn_tensor_input tensor_input1(src1, graph_handle, ctx); + if (!tensor_input1.is_valid()) { goto failure; } - ggml_qnn_tensor_reader tensor_reader(dst, graph_handle, ctx); - if (!tensor_reader.is_valid()) { + ggml_qnn_tensor_output tensor_output(dst, graph_handle, ctx); + if (!tensor_output.is_valid()) { goto failure; } - Qnn_Tensor_t tensor_inputs[] = {*tensor_writer0.get_qnn_tensor(), *tensor_writer1.get_qnn_tensor()}; - Qnn_Tensor_t tensor_outputs[] = {*tensor_reader.get_qnn_tensor()}; + Qnn_Tensor_t tensor_inputs[] = {*tensor_input0.get_qnn_tensor(), *tensor_input1.get_qnn_tensor()}; + Qnn_Tensor_t tensor_outputs[] = {*tensor_output.get_qnn_tensor()}; Qnn_OpConfig_t op_config = { (Qnn_OpConfigVersion_t) 1, .v1 = {"ggml_op_mul_mat", @@ -2410,18 +2410,18 @@ static void ggml_qnn_mul_mat(ggml_backend_qnn_context * ctx, } auto graph_item = std::make_tuple(graph_handle, - tensor_writer0.get_qnn_tensor(), - tensor_writer1.get_qnn_tensor(), - tensor_reader.get_qnn_tensor()); + tensor_input0.get_qnn_tensor(), + tensor_input1.get_qnn_tensor(), + tensor_output.get_qnn_tensor()); instance->_qnn_graph_map[map_entry] = graph_item; } else { auto & graph_item= instance->_qnn_graph_map[map_entry]; - ggml_qnn_tensor_writer tensor_writer0(src0, std::get<1>(graph_item), ctx); - ggml_qnn_tensor_writer tensor_writer1(src1, std::get<2>(graph_item), ctx); - ggml_qnn_tensor_reader tensor_reader(dst, std::get<3>(graph_item), ctx); + ggml_qnn_tensor_input tensor_input0(src0, std::get<1>(graph_item), ctx); + ggml_qnn_tensor_input tensor_input1(src1, std::get<2>(graph_item), ctx); + ggml_qnn_tensor_output tensor_output(dst, std::get<3>(graph_item), ctx); - Qnn_Tensor_t tensor_inputs[] = {*tensor_writer0.get_qnn_tensor(), *tensor_writer1.get_qnn_tensor()}; - Qnn_Tensor_t tensor_outputs[] = {*tensor_reader.get_qnn_tensor()}; + Qnn_Tensor_t tensor_inputs[] = {*tensor_input0.get_qnn_tensor(), *tensor_input1.get_qnn_tensor()}; + Qnn_Tensor_t tensor_outputs[] = {*tensor_output.get_qnn_tensor()}; error = qnn_raw_interface.graphExecute(graph_handle, tensor_inputs, 2, tensor_outputs, 1,