public interface TensorProtoOrBuilder
extends com.google.protobuf.MessageOrBuilder
Modifier and Type | Method and Description |
---|---|
boolean |
getBoolVal(int index)
DT_BOOL
|
int |
getBoolValCount()
DT_BOOL
|
List<Boolean> |
getBoolValList()
DT_BOOL
|
double |
getDcomplexVal(int index)
DT_COMPLEX128.
|
int |
getDcomplexValCount()
DT_COMPLEX128.
|
List<Double> |
getDcomplexValList()
DT_COMPLEX128.
|
double |
getDoubleVal(int index)
DT_DOUBLE.
|
int |
getDoubleValCount()
DT_DOUBLE.
|
List<Double> |
getDoubleValList()
DT_DOUBLE.
|
DataType |
getDtype()
.tensorflow.DataType dtype = 1; |
int |
getDtypeValue()
.tensorflow.DataType dtype = 1; |
float |
getFloatVal(int index)
DT_FLOAT.
|
int |
getFloatValCount()
DT_FLOAT.
|
List<Float> |
getFloatValList()
DT_FLOAT.
|
int |
getHalfVal(int index)
DT_HALF, DT_BFLOAT16.
|
int |
getHalfValCount()
DT_HALF, DT_BFLOAT16.
|
List<Integer> |
getHalfValList()
DT_HALF, DT_BFLOAT16.
|
long |
getInt64Val(int index)
DT_INT64
|
int |
getInt64ValCount()
DT_INT64
|
List<Long> |
getInt64ValList()
DT_INT64
|
int |
getIntVal(int index)
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
|
int |
getIntValCount()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
|
List<Integer> |
getIntValList()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
|
ResourceHandleProto |
getResourceHandleVal(int index)
DT_RESOURCE
|
int |
getResourceHandleValCount()
DT_RESOURCE
|
List<ResourceHandleProto> |
getResourceHandleValList()
DT_RESOURCE
|
ResourceHandleProtoOrBuilder |
getResourceHandleValOrBuilder(int index)
DT_RESOURCE
|
List<? extends ResourceHandleProtoOrBuilder> |
getResourceHandleValOrBuilderList()
DT_RESOURCE
|
float |
getScomplexVal(int index)
DT_COMPLEX64.
|
int |
getScomplexValCount()
DT_COMPLEX64.
|
List<Float> |
getScomplexValList()
DT_COMPLEX64.
|
com.google.protobuf.ByteString |
getStringVal(int index)
DT_STRING
|
int |
getStringValCount()
DT_STRING
|
List<com.google.protobuf.ByteString> |
getStringValList()
DT_STRING
|
com.google.protobuf.ByteString |
getTensorContent()
Serialized raw tensor content from either Tensor::AsProtoTensorContent or
memcpy in tensorflow::grpc::EncodeTensorToByteBuffer.
|
TensorShapeProto |
getTensorShape()
Shape of the tensor.
|
TensorShapeProtoOrBuilder |
getTensorShapeOrBuilder()
Shape of the tensor.
|
int |
getUint32Val(int index)
DT_UINT32
|
int |
getUint32ValCount()
DT_UINT32
|
List<Integer> |
getUint32ValList()
DT_UINT32
|
long |
getUint64Val(int index)
DT_UINT64
|
int |
getUint64ValCount()
DT_UINT64
|
List<Long> |
getUint64ValList()
DT_UINT64
|
VariantTensorDataProto |
getVariantVal(int index)
DT_VARIANT
|
int |
getVariantValCount()
DT_VARIANT
|
List<VariantTensorDataProto> |
getVariantValList()
DT_VARIANT
|
VariantTensorDataProtoOrBuilder |
getVariantValOrBuilder(int index)
DT_VARIANT
|
List<? extends VariantTensorDataProtoOrBuilder> |
getVariantValOrBuilderList()
DT_VARIANT
|
int |
getVersionNumber()
Version number.
|
boolean |
hasTensorShape()
Shape of the tensor.
|
findInitializationErrors, getAllFields, getDefaultInstanceForType, getDescriptorForType, getField, getInitializationErrorString, getOneofFieldDescriptor, getRepeatedField, getRepeatedFieldCount, getUnknownFields, hasField, hasOneof
int getDtypeValue()
.tensorflow.DataType dtype = 1;
DataType getDtype()
.tensorflow.DataType dtype = 1;
boolean hasTensorShape()
Shape of the tensor. TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;
TensorShapeProto getTensorShape()
Shape of the tensor. TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;
TensorShapeProtoOrBuilder getTensorShapeOrBuilder()
Shape of the tensor. TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;
int getVersionNumber()
Version number. In version 0, if the "repeated xxx" representations contain only one element, that element is repeated to fill the shape. This makes it easy to represent a constant Tensor with a single value.
int32 version_number = 3;
com.google.protobuf.ByteString getTensorContent()
Serialized raw tensor content from either Tensor::AsProtoTensorContent or memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. This representation can be used for all tensor types. The purpose of this representation is to reduce serialization overhead during RPC call by avoiding serialization of many repeated small items.
bytes tensor_content = 4;
List<Integer> getHalfValList()
DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];
int getHalfValCount()
DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];
int getHalfVal(int index)
DT_HALF, DT_BFLOAT16. Note that since protobuf has no int16 type, we'll have some pointless zero padding for each value here.
repeated int32 half_val = 13 [packed = true];
List<Float> getFloatValList()
DT_FLOAT.
repeated float float_val = 5 [packed = true];
int getFloatValCount()
DT_FLOAT.
repeated float float_val = 5 [packed = true];
float getFloatVal(int index)
DT_FLOAT.
repeated float float_val = 5 [packed = true];
List<Double> getDoubleValList()
DT_DOUBLE.
repeated double double_val = 6 [packed = true];
int getDoubleValCount()
DT_DOUBLE.
repeated double double_val = 6 [packed = true];
double getDoubleVal(int index)
DT_DOUBLE.
repeated double double_val = 6 [packed = true];
List<Integer> getIntValList()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
int getIntValCount()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
int getIntVal(int index)
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
List<com.google.protobuf.ByteString> getStringValList()
DT_STRING
repeated bytes string_val = 8;
int getStringValCount()
DT_STRING
repeated bytes string_val = 8;
com.google.protobuf.ByteString getStringVal(int index)
DT_STRING
repeated bytes string_val = 8;
List<Float> getScomplexValList()
DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];
int getScomplexValCount()
DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];
float getScomplexVal(int index)
DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real and imaginary parts of i-th single precision complex.
repeated float scomplex_val = 9 [packed = true];
List<Long> getInt64ValList()
DT_INT64
repeated int64 int64_val = 10 [packed = true];
int getInt64ValCount()
DT_INT64
repeated int64 int64_val = 10 [packed = true];
long getInt64Val(int index)
DT_INT64
repeated int64 int64_val = 10 [packed = true];
int getBoolValCount()
DT_BOOL
repeated bool bool_val = 11 [packed = true];
boolean getBoolVal(int index)
DT_BOOL
repeated bool bool_val = 11 [packed = true];
List<Double> getDcomplexValList()
DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];
int getDcomplexValCount()
DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];
double getDcomplexVal(int index)
DT_COMPLEX128. dcomplex_val(2*i) and dcomplex_val(2*i+1) are real and imaginary parts of i-th double precision complex.
repeated double dcomplex_val = 12 [packed = true];
List<ResourceHandleProto> getResourceHandleValList()
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProto getResourceHandleVal(int index)
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
int getResourceHandleValCount()
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
List<? extends ResourceHandleProtoOrBuilder> getResourceHandleValOrBuilderList()
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
ResourceHandleProtoOrBuilder getResourceHandleValOrBuilder(int index)
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
List<VariantTensorDataProto> getVariantValList()
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProto getVariantVal(int index)
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
int getVariantValCount()
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
List<? extends VariantTensorDataProtoOrBuilder> getVariantValOrBuilderList()
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
VariantTensorDataProtoOrBuilder getVariantValOrBuilder(int index)
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
List<Integer> getUint32ValList()
DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
int getUint32ValCount()
DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
int getUint32Val(int index)
DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
List<Long> getUint64ValList()
DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
int getUint64ValCount()
DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
long getUint64Val(int index)
DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
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