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[EISW-89824] [master] Rename VPUX to NPU (#19004)

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* Change `VPUX`/`VPU` occurrences to `NPU`

* Switch `HARDWARE_AWARE_IGNORED_PATTERNS` VPU to NPU

* Rename `MYRIAD plugin`

* Rename vpu_patterns to npu_patterns in tools/pot

* Rename vpu.json to npu.json in tools/pot

* Rename restrict_for_vpu to restrict_for_npu in tools/pot

* Change keembayOptimalBatchNum to npuOptimalBatchNum

---------

Co-authored-by: Dan <mircea-aurelian.dan@intel.com>
This commit is contained in:
Stefania Hergane
2023-08-10 00:20:07 +04:00
committed by GitHub
co-authored by Dan
parent dafe437833
commit 24f8c4105e
42 changed files with 711 additions and 711 deletions
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src/plugins/auto/src/auto_compiled_model.cpp
+1 -1
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@@ -201,7 +201,7 @@ ov::Any AutoCompiledModel::get_property(const std::string& name) const {
LOG_WARNING_TAG("deduce optimal infer requset num for auto-batch failed :%s", iie.what());
}
real = (std::max)(requests, optimal_batch_size);
} else if (device_info.device_name.find("VPU") != std::string::npos) {
} else if (device_info.device_name.find("NPU") != std::string::npos) {
real = 8u;
} else {
real = upper_bound_streams_num ? 2 * upper_bound_streams_num : default_num_for_tput;
src/plugins/auto/src/auto_schedule.cpp
+4 -4
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@@ -301,10 +301,10 @@ void AutoSchedule::try_to_compile_model(AutoCompileContext& context, const std::
}
// need to recompile model, unregister it's priority
// there maybe potential issue.
// for example they are dGPU, VPU, iGPU, customer want to compile model with
// configure 0 dGPU, 1 VPU, if dGPU compile failed,
// the result will be not sure, maybe two models are compiled into VPU,
// maybe 0 is compiled to VPU, 1 is compiled to iGPU
// for example they are dGPU, NPU, iGPU, customer want to compile model with
// configure 0 dGPU, 1 NPU, if dGPU compile failed,
// the result will be not sure, maybe two models are compiled into NPU,
// maybe 0 is compiled to NPU, 1 is compiled to iGPU
m_plugin->unregister_priority(m_context->m_model_priority, context.m_device_info.unique_name);
// remove the current device from device_list
auto erase_device = deviceChecker().check_and_return_if_device_in_list(device, device_list, true);
src/plugins/auto/src/plugin_config.cpp
+1 -1
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@@ -8,7 +8,7 @@ namespace auto_plugin {
// AUTO will enable the blocklist if
// 1.No device priority passed to AUTO/MULTI.(eg. core.compile_model(model, "AUTO", configs);)
// 2.No valid device parsed out from device priority (eg. core.compile_model(model, "AUTO:-CPU,-GPU", configs);).
const std::set<std::string> PluginConfig::device_block_list = {"VPU", "GNA", "notIntelGPU"};
const std::set<std::string> PluginConfig::device_block_list = {"NPU", "GNA", "notIntelGPU"};
PluginConfig::PluginConfig() {
set_default();
src/plugins/auto/tests/unit/compile_model_metric_test.cpp
+2 -2
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@@ -192,13 +192,13 @@ TEST_P(ExecNetworkget_propertyOptimalNumInferReq, OPTIMAL_NUMBER_OF_INFER_REQUES
metaDevices.push_back({actualDeviceName, metaConfig, actualCustomerNum, ""});
// enable autoBatch
unsigned int gpuOptimalBatchNum = 8;
unsigned int keembayOptimalBatchNum = 1;
unsigned int npuOptimalBatchNum = 1;
ov::hint::PerformanceMode mode = ov::hint::PerformanceMode::THROUGHPUT;
std::tuple<unsigned int, unsigned int> rangeOfStreams = std::make_tuple<unsigned int, unsigned int>(1, 3);
ON_CALL(*core, get_property(StrEq(ov::test::utils::DEVICE_GPU), StrEq(ov::optimal_batch_size.name()), _))
.WillByDefault(RETURN_MOCK_VALUE(gpuOptimalBatchNum));
ON_CALL(*core, get_property(StrEq(ov::test::utils::DEVICE_KEEMBAY), StrEq(ov::optimal_batch_size.name()), _))
.WillByDefault(RETURN_MOCK_VALUE(keembayOptimalBatchNum));
.WillByDefault(RETURN_MOCK_VALUE(npuOptimalBatchNum));
ON_CALL(*core, get_property(_, StrEq(ov::range_for_streams.name()), _))
.WillByDefault(RETURN_MOCK_VALUE(rangeOfStreams));
ON_CALL(*core, get_property(_, StrEq(ov::hint::performance_mode.name()), _))
src/plugins/auto/tests/unit/get_device_list.cpp
+9 -9
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@@ -7,8 +7,8 @@
using Config = std::map<std::string, std::string>;
using namespace ov::mock_auto_plugin;
const std::vector<std::string> availableDevs = {"CPU", "GPU", "VPU"};
const std::vector<std::string> availableDevsWithId = {"CPU", "GPU.0", "GPU.1", "VPU"};
const std::vector<std::string> availableDevs = {"CPU", "GPU", "NPU"};
const std::vector<std::string> availableDevsWithId = {"CPU", "GPU.0", "GPU.1", "NPU"};
using Params = std::tuple<std::string, std::string>;
using ConfigParams = std::tuple<
std::vector<std::string>, // Available devices retrieved from Core
@@ -96,8 +96,8 @@ const std::vector<Params> testConfigsWithId = {Params{" ", " "},
Params{"CPU,,GPU", "CPU,GPU.0,GPU.1"},
Params{"CPU, ,GPU", "CPU, ,GPU.0,GPU.1"},
Params{"CPU,GPU,GPU.1", "CPU,GPU.0,GPU.1"},
Params{"CPU,GPU,VPU,INVALID_DEVICE", "CPU,GPU.0,GPU.1,VPU,INVALID_DEVICE"},
Params{"VPU,GPU,CPU,-GPU.0", "VPU,GPU.1,CPU"},
Params{"CPU,GPU,NPU,INVALID_DEVICE", "CPU,GPU.0,GPU.1,NPU,INVALID_DEVICE"},
Params{"NPU,GPU,CPU,-GPU.0", "NPU,GPU.1,CPU"},
Params{"-GPU.0,GPU,CPU", "GPU.1,CPU"},
Params{"-GPU.0,GPU", "GPU.1"},
Params{"-GPU,GPU.0", "GPU.0"},
@@ -131,13 +131,13 @@ const std::vector<Params> testConfigs = {Params{" ", " "},
Params{"CPU,GPU,GPU.0", "CPU,GPU"},
Params{"CPU,GPU,GPU.1", "CPU,GPU,GPU.1"},
Params{"CPU,GPU.1,GPU", "CPU,GPU.1,GPU"},
Params{"CPU,VPU", "CPU,VPU"},
Params{"CPU,-VPU", "CPU"},
Params{"CPU,NPU", "CPU,NPU"},
Params{"CPU,-NPU", "CPU"},
Params{"INVALID_DEVICE", "INVALID_DEVICE"},
Params{"CPU,-INVALID_DEVICE", "CPU"},
Params{"CPU,INVALID_DEVICE", "CPU,INVALID_DEVICE"},
Params{"-CPU,INVALID_DEVICE", "INVALID_DEVICE"},
Params{"CPU,GPU,VPU", "CPU,GPU,VPU"}};
Params{"CPU,GPU,NPU", "CPU,GPU,NPU"}};
const std::vector<Params> testConfigsWithIdNotInteldGPU = {Params{" ", " "},
Params{"", "CPU,GPU.0"},
@@ -147,8 +147,8 @@ const std::vector<Params> testConfigsWithIdNotInteldGPU = {Params{" ", " "},
Params{"CPU,,GPU", "CPU,GPU.0,GPU.1"},
Params{"CPU, ,GPU", "CPU, ,GPU.0,GPU.1"},
Params{"CPU,GPU,GPU.1", "CPU,GPU.0,GPU.1"},
Params{"CPU,GPU,VPU,INVALID_DEVICE", "CPU,GPU.0,GPU.1,VPU,INVALID_DEVICE"},
Params{"VPU,GPU,CPU,-GPU.0", "VPU,GPU.1,CPU"},
Params{"CPU,GPU,NPU,INVALID_DEVICE", "CPU,GPU.0,GPU.1,NPU,INVALID_DEVICE"},
Params{"NPU,GPU,CPU,-GPU.0", "NPU,GPU.1,CPU"},
Params{"-GPU.0,GPU,CPU", "GPU.1,CPU"},
Params{"-GPU.0,GPU", "GPU.1"},
Params{"-GPU,GPU.0", "GPU.0"},
src/plugins/auto/tests/unit/select_device_failed_test.cpp
+5 -5
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@@ -127,7 +127,7 @@ TEST_P(AutoLoadFailedTest, LoadCNNetWork) {
metaDevices.push_back(std::move(devInfo));
// set the return value of SelectDevice
// for example if there are three device, if will return GPU on the first call, and then MYRIAD
// for example if there are three device, if will return GPU on the first call, and then NPU
// at last CPU
ON_CALL(*plugin, select_device(Property(&std::vector<DeviceInformation>::size, Eq(selDevsSize)), _, _))
.WillByDefault(Return(metaDevices[deviceConfigs.size() - selDevsSize]));
@@ -181,12 +181,12 @@ TEST_P(AutoLoadFailedTest, LoadCNNetWork) {
// { true, false, GENERAL, 3 device, 2, 3, 2}
//
// there are three devices for loading
// CPU load for accelerator success, but GPU will load faild and then select MYRIAD and load again
// CPU load for accelerator success, but GPU will load faild and then select NPU and load again
// LoadExeNetworkImpl will not throw exception and can continue to run,
// it will select twice, first select GPU, second select MYRIAD
// it will load network three times(CPU, GPU, MYRIAD)
// it will select twice, first select GPU, second select NPU
// it will load network three times(CPU, GPU, NPU)
// the inference request num is loadSuccessCount * optimalNum, in this test case optimalNum is 2
// so inference request num is 4 (CPU 2, MYRIAD 2)
// so inference request num is 4 (CPU 2, NPU 2)
//
const std::vector<ConfigParams> testConfigs = {
ConfigParams{true,