public interface
TensorProtoOrBuilder
Known Indirect Subclasses |
Public Methods
abstract boolean |
getBoolVal(int index)
DT_BOOL repeated bool bool_val = 11 [packed = true];
|
abstract int |
getBoolValCount()
DT_BOOL repeated bool bool_val = 11 [packed = true];
|
abstract List<Boolean> |
getBoolValList()
DT_BOOL repeated bool bool_val = 11 [packed = true];
|
abstract double |
getDcomplexVal(int index)
DT_COMPLEX128. |
abstract int |
getDcomplexValCount()
DT_COMPLEX128. |
abstract List<Double> |
getDcomplexValList()
DT_COMPLEX128. |
abstract double |
getDoubleVal(int index)
DT_DOUBLE. |
abstract int |
getDoubleValCount()
DT_DOUBLE. |
abstract List<Double> |
getDoubleValList()
DT_DOUBLE. |
abstract DataType |
getDtype()
.tensorflow.DataType dtype = 1;
|
abstract int |
getDtypeValue()
.tensorflow.DataType dtype = 1;
|
abstract float |
getFloatVal(int index)
DT_FLOAT. |
abstract int |
getFloatValCount()
DT_FLOAT. |
abstract List<Float> |
getFloatValList()
DT_FLOAT. |
abstract int |
getHalfVal(int index)
DT_HALF, DT_BFLOAT16. |
abstract int |
getHalfValCount()
DT_HALF, DT_BFLOAT16. |
abstract List<Integer> |
getHalfValList()
DT_HALF, DT_BFLOAT16. |
abstract long |
getInt64Val(int index)
DT_INT64 repeated int64 int64_val = 10 [packed = true];
|
abstract int |
getInt64ValCount()
DT_INT64 repeated int64 int64_val = 10 [packed = true];
|
abstract List<Long> |
getInt64ValList()
DT_INT64 repeated int64 int64_val = 10 [packed = true];
|
abstract int |
getIntVal(int index)
DT_INT32, DT_INT16, DT_INT8, DT_UINT8. |
abstract int |
getIntValCount()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8. |
abstract List<Integer> |
getIntValList()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8. |
abstract ResourceHandleProto |
getResourceHandleVal(int index)
DT_RESOURCE repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
|
abstract int |
getResourceHandleValCount()
DT_RESOURCE repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
|
abstract List<ResourceHandleProto> |
getResourceHandleValList()
DT_RESOURCE repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
|
abstract ResourceHandleProtoOrBuilder |
getResourceHandleValOrBuilder(int index)
DT_RESOURCE repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
|
abstract List<? extends ResourceHandleProtoOrBuilder> |
getResourceHandleValOrBuilderList()
DT_RESOURCE repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
|
abstract float |
getScomplexVal(int index)
DT_COMPLEX64. |
abstract int |
getScomplexValCount()
DT_COMPLEX64. |
abstract List<Float> |
getScomplexValList()
DT_COMPLEX64. |
abstract com.google.protobuf.ByteString |
getStringVal(int index)
DT_STRING repeated bytes string_val = 8;
|
abstract int |
getStringValCount()
DT_STRING repeated bytes string_val = 8;
|
abstract List<ByteString> |
getStringValList()
DT_STRING repeated bytes string_val = 8;
|
abstract com.google.protobuf.ByteString |
getTensorContent()
Serialized raw tensor content from either Tensor::AsProtoTensorContent or memcpy in tensorflow::grpc::EncodeTensorToByteBuffer. |
abstract TensorShapeProto |
getTensorShape()
Shape of the tensor. |
abstract TensorShapeProtoOrBuilder |
getTensorShapeOrBuilder()
Shape of the tensor. |
abstract int |
getUint32Val(int index)
DT_UINT32 repeated uint32 uint32_val = 16 [packed = true];
|
abstract int |
getUint32ValCount()
DT_UINT32 repeated uint32 uint32_val = 16 [packed = true];
|
abstract List<Integer> |
getUint32ValList()
DT_UINT32 repeated uint32 uint32_val = 16 [packed = true];
|
abstract long |
getUint64Val(int index)
DT_UINT64 repeated uint64 uint64_val = 17 [packed = true];
|
abstract int |
getUint64ValCount()
DT_UINT64 repeated uint64 uint64_val = 17 [packed = true];
|
abstract List<Long> |
getUint64ValList()
DT_UINT64 repeated uint64 uint64_val = 17 [packed = true];
|
abstract VariantTensorDataProto |
getVariantVal(int index)
DT_VARIANT repeated .tensorflow.VariantTensorDataProto variant_val = 15;
|
abstract int |
getVariantValCount()
DT_VARIANT repeated .tensorflow.VariantTensorDataProto variant_val = 15;
|
abstract List<VariantTensorDataProto> |
getVariantValList()
DT_VARIANT repeated .tensorflow.VariantTensorDataProto variant_val = 15;
|
abstract VariantTensorDataProtoOrBuilder |
getVariantValOrBuilder(int index)
DT_VARIANT repeated .tensorflow.VariantTensorDataProto variant_val = 15;
|
abstract List<? extends VariantTensorDataProtoOrBuilder> |
getVariantValOrBuilderList()
DT_VARIANT repeated .tensorflow.VariantTensorDataProto variant_val = 15;
|
abstract int |
getVersionNumber()
Version number. |
abstract boolean |
hasTensorShape()
Shape of the tensor. |
Public Methods
public abstract boolean getBoolVal (int index)
DT_BOOL
repeated bool bool_val = 11 [packed = true];
public abstract int getBoolValCount ()
DT_BOOL
repeated bool bool_val = 11 [packed = true];
public abstract List<Boolean> getBoolValList ()
DT_BOOL
repeated bool bool_val = 11 [packed = true];
public abstract 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];
public abstract 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];
public abstract 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];
public abstract double getDoubleVal (int index)
DT_DOUBLE.
repeated double double_val = 6 [packed = true];
public abstract int getDoubleValCount ()
DT_DOUBLE.
repeated double double_val = 6 [packed = true];
public abstract List<Double> getDoubleValList ()
DT_DOUBLE.
repeated double double_val = 6 [packed = true];
public abstract int getDtypeValue ()
.tensorflow.DataType dtype = 1;
public abstract float getFloatVal (int index)
DT_FLOAT.
repeated float float_val = 5 [packed = true];
public abstract int getFloatValCount ()
DT_FLOAT.
repeated float float_val = 5 [packed = true];
public abstract List<Float> getFloatValList ()
DT_FLOAT.
repeated float float_val = 5 [packed = true];
public abstract 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];
public abstract 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];
public abstract 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];
public abstract long getInt64Val (int index)
DT_INT64
repeated int64 int64_val = 10 [packed = true];
public abstract int getInt64ValCount ()
DT_INT64
repeated int64 int64_val = 10 [packed = true];
public abstract List<Long> getInt64ValList ()
DT_INT64
repeated int64 int64_val = 10 [packed = true];
public abstract int getIntVal (int index)
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
public abstract int getIntValCount ()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
public abstract List<Integer> getIntValList ()
DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
repeated int32 int_val = 7 [packed = true];
public abstract ResourceHandleProto getResourceHandleVal (int index)
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
public abstract int getResourceHandleValCount ()
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
public abstract List<ResourceHandleProto> getResourceHandleValList ()
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
public abstract ResourceHandleProtoOrBuilder getResourceHandleValOrBuilder (int index)
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
public abstract List<? extends ResourceHandleProtoOrBuilder> getResourceHandleValOrBuilderList ()
DT_RESOURCE
repeated .tensorflow.ResourceHandleProto resource_handle_val = 14;
public abstract 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];
public abstract 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];
public abstract 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];
public abstract com.google.protobuf.ByteString getStringVal (int index)
DT_STRING
repeated bytes string_val = 8;
public abstract int getStringValCount ()
DT_STRING
repeated bytes string_val = 8;
public abstract List<ByteString> getStringValList ()
DT_STRING
repeated bytes string_val = 8;
public abstract 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;
public abstract TensorShapeProto getTensorShape ()
Shape of the tensor. TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;
public abstract TensorShapeProtoOrBuilder getTensorShapeOrBuilder ()
Shape of the tensor. TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;
public abstract int getUint32Val (int index)
DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
public abstract int getUint32ValCount ()
DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
public abstract List<Integer> getUint32ValList ()
DT_UINT32
repeated uint32 uint32_val = 16 [packed = true];
public abstract long getUint64Val (int index)
DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
public abstract int getUint64ValCount ()
DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
public abstract List<Long> getUint64ValList ()
DT_UINT64
repeated uint64 uint64_val = 17 [packed = true];
public abstract VariantTensorDataProto getVariantVal (int index)
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
public abstract int getVariantValCount ()
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
public abstract List<VariantTensorDataProto> getVariantValList ()
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
public abstract VariantTensorDataProtoOrBuilder getVariantValOrBuilder (int index)
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
public abstract List<? extends VariantTensorDataProtoOrBuilder> getVariantValOrBuilderList ()
DT_VARIANT
repeated .tensorflow.VariantTensorDataProto variant_val = 15;
public abstract 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;
public abstract boolean hasTensorShape ()
Shape of the tensor. TODO(touts): sort out the 0-rank issues.
.tensorflow.TensorShapeProto tensor_shape = 2;