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Added U32 precision (#1297)

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Ilya Churaev 2020-07-14 10:27:10 +03:00 committed by GitHub
parent 91ec946865
commit 32d7959b92
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GPG Key ID: 4AEE18F83AFDEB23
26 changed files with 129 additions and 45 deletions
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2
inference-engine/ie_bridges/c/docs/api_overview.md
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@ -136,6 +136,8 @@ enum precision_e{
​ U64 = 73, /**< 64bit unsigned integer value */
​ U32 = 74, /**< 32bit unsigned integer value */
​ BIN = 71, /**< 1bit integer value */
​ CUSTOM = 80 /**< custom precision has it's own name and size of elements */

1
inference-engine/ie_bridges/c/include/c_api/ie_c_api.h
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@ -182,6 +182,7 @@ typedef enum {
I32 = 70, /**< 32bit signed integer value */
I64 = 72, /**< 64bit signed integer value */
U64 = 73, /**< 64bit unsigned integer value */
U32 = 74, /**< 32bit unsigned integer value */
BIN = 71, /**< 1bit integer value */
CUSTOM = 80 /**< custom precision has it's own name and size of elements */
}precision_e;

6
inference-engine/ie_bridges/c/src/ie_c_api.cpp
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@ -86,6 +86,7 @@ std::map<IE::Precision, precision_e> precision_map = {{IE::Precision::UNSPECIFIE
{IE::Precision::I8, precision_e::I8},
{IE::Precision::U16, precision_e::U16},
{IE::Precision::I32, precision_e::I32},
{IE::Precision::U32, precision_e::U32},
{IE::Precision::I64, precision_e::I64},
{IE::Precision::U64, precision_e::U64},
{IE::Precision::BIN, precision_e::BIN},
@ -1424,6 +1425,8 @@ IEStatusCode ie_blob_make_memory(const tensor_desc_t *tensorDesc, ie_blob_t **bl
_blob->object = IE::make_shared_blob<int16_t>(tensor);
} else if (prec == IE::Precision::I32) {
_blob->object = IE::make_shared_blob<int32_t>(tensor);
} else if (prec == IE::Precision::U32) {
_blob->object = IE::make_shared_blob<uint32_t>(tensor);
} else if (prec == IE::Precision::I64) {
_blob->object = IE::make_shared_blob<int64_t>(tensor);
} else if (prec == IE::Precision::U64) {
@ -1490,6 +1493,9 @@ IEStatusCode ie_blob_make_memory_from_preallocated(const tensor_desc_t *tensorDe
} else if (prec == IE::Precision::I32) {
int32_t *p = reinterpret_cast<int32_t *>(ptr);
_blob->object = IE::make_shared_blob(tensor, p, size);
} else if (prec == IE::Precision::U32) {
uint32_t *p = reinterpret_cast<uint32_t *>(ptr);
_blob->object = IE::make_shared_blob(tensor, p, size);
} else if (prec == IE::Precision::I64) {
int64_t *p = reinterpret_cast<int64_t *>(ptr);
_blob->object = IE::make_shared_blob(tensor, p, size);

2
inference-engine/ie_bridges/python/src/openvino/inference_engine/constants.pyx
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@ -18,7 +18,7 @@ from .cimport ie_api_impl_defs as C
import numpy as np
from enum import Enum
supported_precisions = ["FP32", "FP16", "I64", "U64", "I32", "I16", "I8", "U16", "U8"]
supported_precisions = ["FP32", "FP16", "I64", "U64", "I32", "U32", "I16", "I8", "U16", "U8"]
known_plugins = ['CPU', 'GPU', 'FPGA', 'MYRIAD', 'HETERO', 'HDDL', 'MULTI']

3
inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api.pyx
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@ -1687,8 +1687,9 @@ cdef class BlobBuffer:
'I8': 'b', # signed char
'I16': 'h', # signed short
'I32': 'i', # signed int
'U32': 'I', # unsigned int
'I64': 'q', # signed long int
'U64': 'Q', # signed long int
'U64': 'Q', # unsigned long int
}
if name not in precision_to_format:
raise ValueError("Unknown Blob precision: {}".format(name))

5
inference-engine/ie_bridges/python/src/openvino/inference_engine/ie_api_impl.cpp
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@ -14,9 +14,10 @@ std::map <std::string, InferenceEngine::Precision> precision_map = {{"FP32", Inf
{"I16", InferenceEngine::Precision::I16},
{"I32", InferenceEngine::Precision::I32},
{"I64", InferenceEngine::Precision::I64},
{"U64", InferenceEngine::Precision::U64},
{"U8", InferenceEngine::Precision::U8},
{"U16", InferenceEngine::Precision::U16},
{"U8", InferenceEngine::Precision::U8}};
{"U32", InferenceEngine::Precision::U32},
{"U64", InferenceEngine::Precision::U64}};
std::map <std::string, InferenceEngine::Layout> layout_map = {{"ANY", InferenceEngine::Layout::ANY},
{"NCHW", InferenceEngine::Layout::NCHW},

10
inference-engine/include/ie_blob.h
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@ -761,14 +761,16 @@ protected:
#ifdef __clang__
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<float>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<double>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<int16_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<uint16_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<int8_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<uint8_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<int>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<int16_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<uint16_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<int32_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<uint32_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<long>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<long long>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<uint64_t>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<unsigned long>);
extern template class INFERENCE_ENGINE_API_CLASS(InferenceEngine::TBlob<unsigned long long>);
#endif // __clang__
/**

25
inference-engine/include/ie_precision.hpp
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@ -34,6 +34,7 @@ public:
I8 = 50, /**< 8bit signed integer value */
U16 = 60, /**< 16bit unsigned integer value */
I32 = 70, /**< 32bit signed integer value */
U32 = 74, /**< 32bit unsigned integer value */
I64 = 72, /**< 64bit signed integer value */
U64 = 73, /**< 64bit unsigned integer value */
BIN = 71, /**< 1bit integer value */
@ -108,13 +109,14 @@ public:
CASE(FP32, float);
CASE2(FP16, int16_t, uint16_t);
CASE2(BF16, int16_t, uint16_t);
CASE(I8, int8_t);
CASE(I16, int16_t);
CASE(I32, int32_t);
CASE(I64, int64_t);
CASE(U64, uint64_t);
CASE(U16, uint16_t);
CASE(U8, uint8_t);
CASE(I8, int8_t);
CASE(U16, uint16_t);
CASE(U32, uint32_t);
CASE(U64, uint64_t);
CASE(BOOL, uint8_t);
CASE2(Q78, int16_t, uint16_t);
CASE2(BIN, int8_t, uint8_t);
@ -182,10 +184,10 @@ public:
static Precision FromStr(const std::string& str) {
static std::unordered_map<std::string, ePrecision> names = {
#define PRECISION_NAME(s) {#s, s}
PRECISION_NAME(Q78), PRECISION_NAME(U8), PRECISION_NAME(I8), PRECISION_NAME(I16),
PRECISION_NAME(I32), PRECISION_NAME(I64), PRECISION_NAME(U64), PRECISION_NAME(U16),
PRECISION_NAME(Q78), PRECISION_NAME(BOOL), PRECISION_NAME(BF16),
PRECISION_NAME(I8), PRECISION_NAME(I16), PRECISION_NAME(I32), PRECISION_NAME(I64),
PRECISION_NAME(U8), PRECISION_NAME(U16), PRECISION_NAME(U32), PRECISION_NAME(U64),
PRECISION_NAME(FP32), PRECISION_NAME(FP16), PRECISION_NAME(MIXED), PRECISION_NAME(BIN),
PRECISION_NAME(BOOL), PRECISION_NAME(BF16),
#undef PRECISION_NAME
};
auto i = names.find(str);
@ -263,13 +265,14 @@ protected:
CASE(FP32);
CASE(FP16);
CASE(BF16);
CASE(I8);
CASE(I16);
CASE(I32);
CASE(I64);
CASE(U64);
CASE(U16);
CASE(U8);
CASE(I8);
CASE(U16);
CASE(U32);
CASE(U64);
CASE(Q78);
CASE(MIXED);
CASE(BIN);
@ -330,6 +333,10 @@ struct PrecisionTrait<Precision::I32> {
using value_type = int32_t;
};
template <>
struct PrecisionTrait<Precision::U32> {
using value_type = uint32_t;
};
template <>
struct PrecisionTrait<Precision::I64> {
using value_type = int64_t;
};

1
inference-engine/samples/common/samples/classification_results.h
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@ -103,6 +103,7 @@ private:
TBLOB_TOP_RESULT(I8);
TBLOB_TOP_RESULT(U16);
TBLOB_TOP_RESULT(I32);
TBLOB_TOP_RESULT(U32);
TBLOB_TOP_RESULT(U64);
TBLOB_TOP_RESULT(I64);
default:

5
inference-engine/src/cldnn_engine/cldnn_program.cpp
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@ -4626,6 +4626,11 @@ void Program::CreateCumSumPrimitive(cldnn::topology& topology, InferenceEngine::
axis = data[0];
break;
}
case InferenceEngine::Precision::U32: {
auto data = constantBlob->buffer().as<uint32_t*>();
axis = static_cast<int32_t>(data[0]);
break;
}
case InferenceEngine::Precision::U64: {
auto data = constantBlob->buffer().as<uint64_t*>();
axis = static_cast<int32_t>(data[0]);

1
inference-engine/src/gna_plugin/gna_executable_network.hpp
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@ -33,6 +33,7 @@ class GNAExecutableNetwork : public InferenceEngine::ExecutableNetworkThreadSafe
: plg(plg) {
InferenceEngine::NetPass::ConvertPrecision(network, InferenceEngine::Precision::I64, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(network, InferenceEngine::Precision::U64, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(network, InferenceEngine::Precision::U32, InferenceEngine::Precision::I32);
plg->LoadNetwork(network);
}

2
inference-engine/src/inference_engine/blob_transform.cpp
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@ -126,6 +126,7 @@ static inline void blob_copy_4d(Blob::Ptr src, Blob::Ptr dst) {
switch (src->getTensorDesc().getPrecision()) {
case Precision::FP32:
case Precision::I32:
case Precision::U32:
blob_copy_4d_t<Precision::FP32>(src, dst);
break;
@ -263,6 +264,7 @@ static inline void blob_copy_5d(Blob::Ptr src, Blob::Ptr dst) {
switch (src->getTensorDesc().getPrecision()) {
case Precision::FP32:
case Precision::I32:
case Precision::U32:
blob_copy_5d_t<Precision::FP32>(src, dst);
break;

10
inference-engine/src/inference_engine/ie_rtti.cpp
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@ -109,12 +109,14 @@ TBlob<T, U>::~TBlob() {
template class InferenceEngine::TBlob<float>;
template class InferenceEngine::TBlob<double>;
template class InferenceEngine::TBlob<int16_t>;
template class InferenceEngine::TBlob<uint16_t>;
template class InferenceEngine::TBlob<int8_t>;
template class InferenceEngine::TBlob<uint8_t>;
template class InferenceEngine::TBlob<int>;
template class InferenceEngine::TBlob<int16_t>;
template class InferenceEngine::TBlob<uint16_t>;
template class InferenceEngine::TBlob<int32_t>;
template class InferenceEngine::TBlob<uint32_t>;
template class InferenceEngine::TBlob<long>;
template class InferenceEngine::TBlob<long long>;
template class InferenceEngine::TBlob<uint64_t>;
template class InferenceEngine::TBlob<unsigned long>;
template class InferenceEngine::TBlob<unsigned long long>;
#endif // __clang__

12
inference-engine/src/legacy_api/include/ie_ngraph_utils.hpp
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@ -33,6 +33,8 @@ inline ::ngraph::element::Type convertPrecision(const Precision& precision) {
return ::ngraph::element::Type(::ngraph::element::Type_t::i16);
case Precision::I32:
return ::ngraph::element::Type(::ngraph::element::Type_t::i32);
case Precision::U32:
return ::ngraph::element::Type(::ngraph::element::Type_t::u32);
case Precision::I64:
return ::ngraph::element::Type(::ngraph::element::Type_t::i64);
case Precision::U64:
@ -103,14 +105,16 @@ inline Precision convertPrecision(const ::ngraph::element::Type& precision) {
return Precision(Precision::I32);
case ::ngraph::element::Type_t::i64:
return Precision(Precision::I64);
case ::ngraph::element::Type_t::u64:
return Precision(Precision::U64);
case ::ngraph::element::Type_t::u1:
return Precision(Precision::BIN);
case ::ngraph::element::Type_t::u8:
return Precision(Precision::U8);
case ::ngraph::element::Type_t::u16:
return Precision(Precision::U16);
case ::ngraph::element::Type_t::u32:
return Precision(Precision::U32);
case ::ngraph::element::Type_t::u64:
return Precision(Precision::U64);
case ::ngraph::element::Type_t::u1:
return Precision(Precision::BIN);
case ::ngraph::element::Type_t::boolean:
return Precision(Precision::BOOL);
default:

9
inference-engine/src/legacy_api/src/ie_cnn_layer_builder_ngraph.cpp
View File

@ -401,15 +401,18 @@ CNNLayer::Ptr NodeConverter<ngraph::op::Convert>::createLayer(const std::shared_
case Precision::I64:
precision_str = "I64";
break;
case Precision::U64:
precision_str = "U64";
break;
case Precision::U8:
precision_str = "U8";
break;
case Precision::U16:
precision_str = "U16";
break;
case Precision::U32:
precision_str = "U32";
break;
case Precision::U64:
precision_str = "U64";
break;
case Precision::BOOL:
precision_str = "BOOL";
break;

3
inference-engine/src/legacy_api/src/net_pass.cpp
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@ -1471,6 +1471,9 @@ details::CNNSubnet GetInternalSubnet(const CNNLayerPtr &layer) {
void ConvertPrecision(ICNNNetwork& net, Precision from, Precision to) {
auto compare = getPrecisionMask(from, to);
switch (compare) {
case getPrecisionMask(Precision::U32, Precision::I32):
convertPrecisionForAll<Precision::U32, Precision::I32>(net);
break;
case getPrecisionMask(Precision::U64, Precision::I32):
convertPrecisionForAll<Precision::U64, Precision::I32>(net);
break;

4
inference-engine/src/low_precision_transformations/src/network_helper.cpp
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@ -647,6 +647,9 @@ std::shared_ptr<float> CNNNetworkHelper::getFloatData(const Blob::Ptr& srcBlob)
} else if (precision == Precision::I32) {
const auto* srcData = srcBlob->buffer().as<PrecisionTrait<Precision::I32>::value_type*>();
std::copy(srcData, srcData + dataSize, floatPtr.get());
} else if (precision == Precision::U32) {
const auto* srcData = srcBlob->buffer().as<PrecisionTrait<Precision::U32>::value_type*>();
std::copy(srcData, srcData + dataSize, floatPtr.get());
} else if (precision == Precision::I64) {
const auto* srcData = srcBlob->buffer().as<PrecisionTrait<Precision::I64>::value_type*>();
std::copy(srcData, srcData + dataSize, floatPtr.get());
@ -666,6 +669,7 @@ bool CNNNetworkHelper::isBlobPrecisionSupported(const Precision precision) {
(precision == Precision::I8) ||
(precision == Precision::U8) ||
(precision == Precision::I32) ||
(precision == Precision::U32) ||
(precision == Precision::I64) ||
(precision == Precision::U64);
}

1
inference-engine/src/mkldnn_plugin/mkldnn_exec_network.cpp
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@ -52,6 +52,7 @@ MKLDNNExecNetwork::MKLDNNExecNetwork(const InferenceEngine::ICNNNetwork &network
// Default int64->int32 conversion is already applied in IE common module.
NetPass::ConvertPrecision(*_clonedNetwork, Precision::I64, Precision::I32);
NetPass::ConvertPrecision(*_clonedNetwork, Precision::U64, Precision::I32);
NetPass::ConvertPrecision(*_clonedNetwork, Precision::U32, Precision::I32);
NetPass::ConvertPrecision(*_clonedNetwork, Precision::FP16, Precision::FP32);
NetPass::ConvertPrecision(*_clonedNetwork, Precision::BOOL, Precision::U8);
NetPass::ConvertPrecision(*_clonedNetwork, Precision::U16, Precision::I32);

27
inference-engine/src/plugin_api/blob_factory.hpp
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@ -48,7 +48,7 @@ InferenceEngine::Blob::Ptr make_shared_blob2(Args&&... args) {
/**
* @brief Creates Blob::Ptr with precision.
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
*
* @param[in] desc The TensorDesc object
* @return A Blob::Ptr pointer
@ -58,7 +58,7 @@ make_blob_with_precision(const InferenceEngine::TensorDesc& desc);
/**
* @brief Makes a blob with precision.
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
*
* @param[in] desc The TensorDesc object
* @param ptr The pointer to a raw memory
@ -69,7 +69,7 @@ make_blob_with_precision(const InferenceEngine::TensorDesc& desc, void* ptr);
/**
* @brief Makes a blob with precision.
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
*
* @param[in] desc The description
* @param[in] alloc The IAllocator object
@ -81,7 +81,7 @@ make_blob_with_precision(const InferenceEngine::TensorDesc& desc,
/**
* @brief Creates a plain Blob::Ptr
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
*
* @param[in] prec The Precision value
* @param[in] dims The dims
@ -92,7 +92,7 @@ make_plain_blob(InferenceEngine::Precision prec, const InferenceEngine::SizeVect
/**
* @brief Creates Blob::Ptr with precision
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
*
* @param[in] precision The precision
* @param args The arguments
@ -109,12 +109,13 @@ InferenceEngine::Blob::Ptr make_blob_with_precision(InferenceEngine::Precision p
USE_FACTORY(FP32);
USE_FACTORY(FP16);
USE_FACTORY(Q78);
USE_FACTORY(I16);
USE_FACTORY(U8);
USE_FACTORY(I8);
USE_FACTORY(U16);
USE_FACTORY(I16);
USE_FACTORY(I32);
USE_FACTORY(I64);
USE_FACTORY(U8);
USE_FACTORY(U16);
USE_FACTORY(U32);
USE_FACTORY(U64);
USE_FACTORY(BIN);
USE_FACTORY(BF16);
@ -127,7 +128,7 @@ InferenceEngine::Blob::Ptr make_blob_with_precision(InferenceEngine::Precision p
/**
* @brief Create blob with custom precision
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
* @tparam T - type off underlined elements
* @tparam Args Variadic template type arguments
* @param args Arguments
@ -140,7 +141,7 @@ InferenceEngine::Blob::Ptr make_custom_blob(Args&&... args) {
/**
* @brief Create blob with custom precision
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
* @tparam T A type off underlined elements
* @param layout A blob layout
* @param size A blob size
@ -154,7 +155,7 @@ InferenceEngine::Blob::Ptr make_custom_blob(InferenceEngine::Layout layout, Infe
/**
* @brief Creates a TBlob<> object from a Data node
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
* @param data A reference to a smart pointer of the Data node
* @return Smart pointer to TBlob<> with the relevant C type to the precision of the data node
*/
@ -162,10 +163,10 @@ INFERENCE_ENGINE_API_CPP(InferenceEngine::Blob::Ptr) CreateBlobFromData(const In
/**
* @brief Copy data from std::vector to Blob
* @ingroup ie_dev_api_memory
* @ingroup ie_dev_api_memory
* @tparam T type of data in std::vector
* @param outputBlob An output blob to copy to
* @param inputVector An input std::vector to copy from
* @param inputVector An input std::vector to copy from
*/
template <typename T>
void CopyVectorToBlob(const InferenceEngine::Blob::Ptr outputBlob, const std::vector<T>& inputVector) {

1
inference-engine/src/vpu/graph_transformer/src/frontend/frontend.cpp
View File

@ -394,6 +394,7 @@ ModelPtr FrontEnd::runCommonPasses(ie::ICNNNetwork& network, const UnsupportedLa
}
ie::NetPass::ConvertPrecision(*originalOrConvertNetwork, ie::Precision::I64, ie::Precision::I32);
ie::NetPass::ConvertPrecision(*originalOrConvertNetwork, ie::Precision::U32, ie::Precision::I32);
ie::NetPass::ConvertPrecision(*originalOrConvertNetwork, ie::Precision::U64, ie::Precision::I32);
ie::NetPass::ConvertPrecision(*originalOrConvertNetwork, ie::Precision::BOOL, ie::Precision::I32);

27
inference-engine/tests/functional/inference_engine/blob_copy_test.cpp
View File

@ -52,6 +52,8 @@ InferenceEngine::Blob::Ptr createBlob(InferenceEngine::Precision precision, Size
return make_shared_blob<int16_t>(tensorDesc);
case InferenceEngine::Precision::I32:
return make_shared_blob<int32_t>(tensorDesc);
case InferenceEngine::Precision::U32:
return make_shared_blob<uint32_t>(tensorDesc);
case InferenceEngine::Precision::I64:
return make_shared_blob<int64_t>(tensorDesc);
case InferenceEngine::Precision::U64:
@ -121,6 +123,8 @@ void FillBlob(Blob::Ptr& inputBlob) {
return FillBlobRandom<int16_t>(inputBlob);
case InferenceEngine::Precision::I32:
return FillBlobRandom<int32_t>(inputBlob);
case InferenceEngine::Precision::U32:
return FillBlobRandom<uint32_t>(inputBlob);
case InferenceEngine::Precision::I64:
return FillBlobRandom<int64_t>(inputBlob);
case InferenceEngine::Precision::U64:
@ -206,7 +210,9 @@ bool IsCorrectBlobCopy(Blob::Ptr& srcBlob, Blob::Ptr& dstBlob) {
case InferenceEngine::Precision::Q78:
return IsCorrectBlobCopy_Impl<int16_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::I32:
IsCorrectBlobCopy_Impl<int32_t>(srcBlob, dstBlob);
return IsCorrectBlobCopy_Impl<int32_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::U32:
return IsCorrectBlobCopy_Impl<uint32_t >(srcBlob, dstBlob);
case InferenceEngine::Precision::I64:
return IsCorrectBlobCopy_Impl<int64_t >(srcBlob, dstBlob);
case InferenceEngine::Precision::U64:
@ -286,7 +292,7 @@ std::vector<Dims> BlobCopy_Dims = {
};
// The 'blob_copy(4/5)_d' function is a template with the parameter-list <InferenceEngine::Precision::ePrecision PRC>
// FP32 is used for cases with the following accuracy: FP32, I32
// FP32 is used for cases with the following accuracy: FP32, I32, U32
// FP16 is used for cases with the following accuracy: FP16, U16, I16
// U8 is used for cases with the following accuracy: U8, I8
// Cases with other precision are not supported
@ -294,6 +300,11 @@ std::vector<PrecisionType> BlobCopy_PrecisionParams = {
InferenceEngine::Precision::FP32,
InferenceEngine::Precision::FP16,
InferenceEngine::Precision::U8,
InferenceEngine::Precision::I8,
InferenceEngine::Precision::U16,
InferenceEngine::Precision::I16,
InferenceEngine::Precision::U32,
InferenceEngine::Precision::I32,
};
} // namespace
@ -325,17 +336,21 @@ bool IsEqualBlobCopy(Blob::Ptr& srcBlob, Blob::Ptr& dstBlob) {
case InferenceEngine::Precision::I16:
case InferenceEngine::Precision::Q78:
return IsEqualBlobCopy_Impl<int16_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::U32:
IsEqualBlobCopy_Impl<uint32_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::I32:
IsEqualBlobCopy_Impl<int32_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::U64:
return IsEqualBlobCopy_Impl<uint64_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::I64:
return IsEqualBlobCopy_Impl<int64_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::U16:
return IsEqualBlobCopy_Impl<uint16_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::I8:
case InferenceEngine::Precision::BIN:
return IsEqualBlobCopy_Impl<int8_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::U8:
return IsEqualBlobCopy_Impl<uint8_t>(srcBlob, dstBlob);
case InferenceEngine::Precision::U16:
return IsEqualBlobCopy_Impl<uint16_t>(srcBlob, dstBlob);
default:
return false;
}
@ -372,6 +387,10 @@ void copy3DBlobsAllBytesWithReLayoutWrapper(const Blob::Ptr& srcLayoutBlob, Blob
return copy3DBlobsAllBytesWithReLayout<int16_t>(srcLayoutBlob, trgLayoutBlob);
case InferenceEngine::Precision::I32:
return copy3DBlobsAllBytesWithReLayout<int32_t>(srcLayoutBlob, trgLayoutBlob);
case InferenceEngine::Precision::U32:
return copy3DBlobsAllBytesWithReLayout<uint32_t>(srcLayoutBlob, trgLayoutBlob);
case InferenceEngine::Precision::U64:
return copy3DBlobsAllBytesWithReLayout<uint64_t>(srcLayoutBlob, trgLayoutBlob);
case InferenceEngine::Precision::I64:
return copy3DBlobsAllBytesWithReLayout<int64_t>(srcLayoutBlob, trgLayoutBlob);
case InferenceEngine::Precision::U16:

4
inference-engine/tests/functional/inference_engine/ie_precision_test.cpp
View File

@ -19,6 +19,7 @@ TEST_F(PrecisionTests, ShowsCorrectPrecisionNames) {
ASSERT_STREQ(Precision(Precision::FP32).name(), "FP32");
ASSERT_STREQ(Precision(Precision::I16).name(), "I16");
ASSERT_STREQ(Precision(Precision::I32).name(), "I32");
ASSERT_STREQ(Precision(Precision::U32).name(), "U32");
ASSERT_STREQ(Precision(Precision::U16).name(), "U16");
ASSERT_STREQ(Precision(Precision::I8).name(), "I8");
ASSERT_STREQ(Precision(Precision::Q78).name(), "Q78");
@ -35,6 +36,7 @@ TEST_F(PrecisionTests, sizeIsCorrect) {
ASSERT_EQ(Precision(Precision::FP16).size(), 2);
ASSERT_EQ(Precision(Precision::FP32).size(), 4);
ASSERT_EQ(Precision(Precision::I32).size(), 4);
ASSERT_EQ(Precision(Precision::U32).size(), 4);
ASSERT_EQ(Precision(Precision::I16).size(), 2);
ASSERT_EQ(Precision(Precision::U16).size(), 2);
ASSERT_EQ(Precision(Precision::I8).size(), 1);
@ -51,6 +53,7 @@ TEST_F(PrecisionTests, is_float) {
ASSERT_FALSE(Precision(Precision::I64).is_float());
ASSERT_FALSE(Precision(Precision::U64).is_float());
ASSERT_FALSE(Precision(Precision::I32).is_float());
ASSERT_FALSE(Precision(Precision::U32).is_float());
ASSERT_FALSE(Precision(Precision::I16).is_float());
ASSERT_FALSE(Precision(Precision::U16).is_float());
ASSERT_FALSE(Precision(Precision::I8).is_float());
@ -68,6 +71,7 @@ TEST_F(PrecisionTests, constructFromSTR) {
ASSERT_EQ(Precision(Precision::FP16), Precision::FromStr("FP16"));
ASSERT_EQ(Precision(Precision::FP32), Precision::FromStr("FP32"));
ASSERT_EQ(Precision(Precision::I32), Precision::FromStr("I32"));
ASSERT_EQ(Precision(Precision::U32), Precision::FromStr("U32"));
ASSERT_EQ(Precision(Precision::I16), Precision::FromStr("I16"));
ASSERT_EQ(Precision(Precision::U16), Precision::FromStr("U16"));
ASSERT_EQ(Precision(Precision::I8), Precision::FromStr("I8"));

2
inference-engine/tests/functional/plugin/cpu/shared_tests_instances/low_precision_transformations/layer_transformation.cpp
View File

@ -93,6 +93,7 @@ InferenceEngine::CNNNetwork LayerTransformation::transform(InferenceEngine::deta
InferenceEngine::NetPass::ConvertPrecision(*implNetwork, InferenceEngine::Precision::I64, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(*implNetwork, InferenceEngine::Precision::U64, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(*implNetwork, InferenceEngine::Precision::U32, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(*implNetwork, InferenceEngine::Precision::FP16, InferenceEngine::Precision::FP32);
InferenceEngine::NetPass::ConvertPrecision(*implNetwork, InferenceEngine::Precision::BOOL, InferenceEngine::Precision::U8);
@ -115,6 +116,7 @@ InferenceEngine::CNNNetwork LayerTransformation::transform(const InferenceEngine
InferenceEngine::NetPass::ConvertPrecision(*cnnNetworkImp, InferenceEngine::Precision::I64, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(*cnnNetworkImp, InferenceEngine::Precision::U64, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(*cnnNetworkImp, InferenceEngine::Precision::U32, InferenceEngine::Precision::I32);
InferenceEngine::NetPass::ConvertPrecision(*cnnNetworkImp, InferenceEngine::Precision::FP16, InferenceEngine::Precision::FP32);
InferenceEngine::NetPass::ConvertPrecision(*cnnNetworkImp, InferenceEngine::Precision::BOOL, InferenceEngine::Precision::U8);

7
inference-engine/tests_deprecated/unit/inference_engine_tests/util_const_infer_test.cpp
View File

@ -170,6 +170,13 @@ IE::BlobMap RemoveLayerTests::fillConstDataDiffPrec (const std::vector<std::stri
}
break;
}
case IE::Precision::U32: {
auto *buffer = blob->buffer().as<unsigned int *>();
for (int i = 0; i < blob->size(); i++) {
buffer[i] = i + 2;
}
break;
}
case IE::Precision::I64: {
auto *buffer = blob->buffer().as<long long int *>();
for (int i = 0; i < blob->size(); i++) {

1
ngraph/test/runtime/ie/ie_executable.cpp
View File

@ -60,6 +60,7 @@ namespace
case element::Type_t::i8: blob = MAKE_IE_TBLOB(int8_t, I8, shape, layout); break;
case element::Type_t::u16: blob = MAKE_IE_TBLOB(uint16_t, U16, shape, layout); break;
case element::Type_t::i32: blob = MAKE_IE_TBLOB(int32_t, I32, shape, layout); break;
case element::Type_t::u32: blob = MAKE_IE_TBLOB(uint32_t, U32, shape, layout); break;
case element::Type_t::i64: blob = MAKE_IE_TBLOB(int64_t, I64, shape, layout); break;
case element::Type_t::u64: blob = MAKE_IE_TBLOB(uint64_t, U64, shape, layout); break;
case element::Type_t::boolean: blob = MAKE_IE_TBLOB(uint8_t, BOOL, shape, layout); break;

3
ngraph/test/util/engine/ie_engines.cpp
View File

@ -105,6 +105,9 @@ namespace
case InferenceEngine::Precision::U16:
return compare_blobs<uint16_t>(computed, expected, tolerance_bits);
break;
case InferenceEngine::Precision::U32:
return compare_blobs<uint32_t>(computed, expected, tolerance_bits);
break;
case InferenceEngine::Precision::U64:
return compare_blobs<uint64_t>(computed, expected, tolerance_bits);
break;