forked from mindspore-Ecosystem/mindspore
dump graph_kernel_split info
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0a0dc05d51
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3c6c30024c
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@ -14,33 +14,57 @@
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# ============================================================================
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"""GraphKernel splitter"""
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import os
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import json
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import json.decoder as jd
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import traceback
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from mindspore import log as logger
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from . import model
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from . import utils
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def reset_graphmode_for_inplaceassign(graph_list, graph_mode):
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for i, g in enumerate(graph_list):
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if any([op['name'] == 'InplaceAssign' for op in g['op_desc']]):
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graph_mode[i] = 'composite'
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def split_with_json(json_str: str):
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def split_with_json(json_str, flags_str):
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"""Call costmodel to split GraphKernel"""
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try:
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graph_desc = json.loads(json_str)
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flags = json.loads(flags_str)
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target = graph_desc['process']
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comp = model.load_composite(graph_desc)
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graph_split, graph_mode = model.split(comp.graph, target)
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is_multi_graph = len(graph_split) > 1
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graph_list = list(map(comp.dump, graph_split))
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reset_graphmode_for_inplaceassign(graph_list, graph_mode)
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_reset_graphmode_for_inplaceassign(graph_list, graph_mode)
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result = {"multi_graph": is_multi_graph,
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"graph_desc": graph_list,
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"graph_mode": graph_mode}
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_dump_split_info(flags, json_str, comp.graph, graph_split, graph_mode)
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return json.dumps(result)
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except jd.JSONDecodeError:
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logger.error(traceback.format_exc())
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return None
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def _reset_graphmode_for_inplaceassign(graph_list, graph_mode):
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"""Operator with InplaceAssign should always be composite op"""
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for i, g in enumerate(graph_list):
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if any([op['name'] == 'InplaceAssign' for op in g['op_desc']]):
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graph_mode[i] = 'composite'
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def _dump_split_info(flags, graph_json, graph_desc, subgraphs, graph_mode):
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"""Dump split info as text"""
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if not flags.get("dump_as_text", False):
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return
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utils.create_dir(utils.GRAPH_KERNEL_DUMP_PATH)
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filename = os.path.join(utils.GRAPH_KERNEL_DUMP_PATH, "graph_kernel_split_mode.txt")
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with open(filename, "a+") as f:
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f.write("********** main graph: {} **********\n".format(graph_desc.name))
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f.write("input json:\n{}\n".format(graph_json))
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f.write("graph desc:\n{}\n".format(str(graph_desc)))
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if len(subgraphs) > 1:
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for i, g in enumerate(subgraphs):
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f.write("-------- subgraph {}, mode: {} --------\n".format(i, graph_mode[i]))
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f.write("{}\n".format(str(g)))
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else:
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f.write("Graph unchanged.\n")
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f.write("\n")
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@ -0,0 +1,28 @@
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# Copyright 2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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"""GraphKernel utils"""
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import os
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GRAPH_KERNEL_DUMP_PATH = "graph_kernel_dump"
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def create_dir(pathname):
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"""Try to create directory"""
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if os.path.exists(pathname):
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return
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try:
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os.mkdir(pathname)
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except OSError:
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pass
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@ -1,5 +1,5 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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* Copyright 2020-2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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@ -107,7 +107,9 @@ bool GpuKernelMod::Launch(const std::vector<AddressPtr> &inputs, const std::vect
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thread_info[5], 0, reinterpret_cast<CUstream>(stream_ptr),
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reinterpret_cast<void **>(&runtimeargs[0]), 0);
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if (result != CUDA_SUCCESS) {
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MS_LOG(ERROR) << "Launch Kernel failed.";
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const char *msg = nullptr;
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cuGetErrorName(result, &msg);
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MS_LOG(ERROR) << "Launch Kernel failed. error: " << msg;
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return false;
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}
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return true;
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@ -1,5 +1,5 @@
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/**
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* Copyright 2020 Huawei Technologies Co., Ltd
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* Copyright 2020-2021 Huawei Technologies Co., Ltd
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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@ -29,6 +29,7 @@
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#include "backend/kernel_compiler/akg/akg_kernel_json_decoder.h"
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#include "backend/optimizer/graph_kernel/graph_kernel_helper.h"
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#include "debug/anf_ir_dump.h"
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#include "utils/context/graph_kernel_flags.h"
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namespace mindspore {
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namespace opt {
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@ -572,17 +573,19 @@ class CostModelSplitSchemer : public Splitter::SplitSchemer {
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// call costmodel split function.
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auto json_desc_str = json_desc.dump();
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MS_LOG(DEBUG) << "CallPyFn: [" << kGraphKernelSplitFunc << "] with input json:\n" << json_desc_str;
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auto ret = parse::python_adapter::CallPyFn(kGraphKernelModule, kGraphKernelSplitFunc, json_desc_str);
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auto flags_str = CollectSplitFlags();
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MS_LOG(DEBUG) << "CallPyFn: [" << kGraphKernelSplitFunc << "] with input json: " << json_desc_str
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<< ". flag: " << flags_str;
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auto ret = parse::python_adapter::CallPyFn(kGraphKernelModule, kGraphKernelSplitFunc, json_desc_str, flags_str);
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if (py::isinstance<py::none>(ret)) {
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MS_LOG(ERROR) << "CallPyFn: [" << kGraphKernelSplitFunc << "] return invalid result. input json:\n"
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<< json_desc_str;
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<< json_desc_str << ". flag: " << flags_str;
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return false;
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}
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std::string split_graphs_str = py::cast<std::string>(ret);
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if (split_graphs_str.empty()) {
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MS_LOG(ERROR) << "CallPyFn: [" << kGraphKernelSplitFunc << "] return invalid result. input json:\n"
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<< json_desc_str;
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<< json_desc_str << ". flag: " << flags_str;
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return false;
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}
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@ -713,6 +716,13 @@ class CostModelSplitSchemer : public Splitter::SplitSchemer {
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}
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}
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virtual std::string CollectSplitFlags() {
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const auto &flags = context::GraphKernelFlags::GetInstance();
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nlohmann::json flag_json;
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flag_json["dump_as_text"] = flags.dump_as_text;
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return flag_json.dump();
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}
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std::shared_ptr<FuncGraph> func_graph_;
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AnfNodePtrList topo_all_nodes_;
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AnfNodePtrList topo_valid_nodes_;
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@ -49,12 +49,13 @@ class GraphKernelFlags {
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public:
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/**
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* dump_as_text, unsupported now.
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* Dump info as human-readable text.
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* A directory "graph_kernel_dump" will be created, and all information will be dumped in this directory.
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*/
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bool dump_as_text{false};
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/**
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* opt_level, value from 0 to 3.
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* Optimization level, value from 0 to 3.
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* 0: GraphKernel disabled
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* 1: GraphKernel enabled
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* 2 and 3 are not supported now.
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@ -93,17 +94,21 @@ class GraphKernelFlags {
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std::vector<std::string> disable_expand_ops;
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/**
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* enable_cluster_ops, unsupported now.
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* Additional clustering operators (case sensitive).
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* The operators to be added into the default clustering operator list.
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*/
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std::vector<std::string> enable_cluster_ops;
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/**
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* enable_cluster_ops_only, unsupported now.
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* Clustering operators to be enabled (case sensitive).
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* Unlike the "enable_cluster_ops", the default list will be overwritten by this list.
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* Note that the "enable_cluster_ops" and "disable_cluster_ops" will be ignored if this flag is set.
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*/
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std::vector<std::string> enable_cluster_ops_only;
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/**
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* disable_cluster_ops, unsupported now.
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* Clustering operators to be disabled (case sensitive).
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* The behavior is undefined when this list overlaps with "enable_cluster_ops".
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*/
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std::vector<std::string> disable_cluster_ops;
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@ -26,3 +26,5 @@ CUresult cuLaunchKernel(CUfunction f, unsigned int gridDimX, unsigned int gridDi
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}
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CUresult cuModuleUnload(CUmodule hmod) { return CUDA_SUCCESS; }
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CUresult cuGetErrorName(CUresult error, const char **pStr) { return CUDA_SUCCESS; }
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@ -46,5 +46,5 @@ CUresult cuLaunchKernel(CUfunction f, unsigned int gridDimX, unsigned int gridDi
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unsigned int blockDimX, unsigned int blockDimY, unsigned int blockDimZ,
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unsigned int sharedMemBytes, CUstream hStream, void **kernelParams, void **extra);
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CUresult cuModuleUnload(CUmodule hmod);
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CUresult cuGetErrorName(CUresult error, const char **pStr);
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#endif // TESTS_UT_STUB_RUNTIME_INCLUDE_CUDA_H_
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