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// Generated by the protocol buffer compiler.  DO NOT EDIT!
// source: tensorflow/core/framework/tensor.proto

package org.tensorflow.framework;

public interface TensorProtoOrBuilder extends
    // @@protoc_insertion_point(interface_extends:tensorflow.TensorProto)
    org.nd4j.shade.protobuf.MessageOrBuilder {

  /**
   * .tensorflow.DataType dtype = 1;
   */
  int getDtypeValue();
  /**
   * .tensorflow.DataType dtype = 1;
   */
  org.tensorflow.framework.DataType getDtype();

  /**
   * 
   * Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
   * 
* * .tensorflow.TensorShapeProto tensor_shape = 2; */ boolean hasTensorShape(); /** *
   * Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
   * 
* * .tensorflow.TensorShapeProto tensor_shape = 2; */ org.tensorflow.framework.TensorShapeProto getTensorShape(); /** *
   * Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
   * 
* * .tensorflow.TensorShapeProto tensor_shape = 2; */ org.tensorflow.framework.TensorShapeProtoOrBuilder getTensorShapeOrBuilder(); /** *
   * 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; */ int getVersionNumber(); /** *
   * 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; */ org.nd4j.shade.protobuf.ByteString getTensorContent(); /** *
   * 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]; */ java.util.List 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_FLOAT.
   * 
* * repeated float float_val = 5 [packed = true]; */ java.util.List 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_DOUBLE.
   * 
* * repeated double double_val = 6 [packed = true]; */ java.util.List 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_INT32, DT_INT16, DT_INT8, DT_UINT8.
   * 
* * repeated int32 int_val = 7 [packed = true]; */ java.util.List 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_STRING
   * 
* * repeated bytes string_val = 8; */ java.util.List getStringValList(); /** *
   * DT_STRING
   * 
* * repeated bytes string_val = 8; */ int getStringValCount(); /** *
   * DT_STRING
   * 
* * repeated bytes string_val = 8; */ org.nd4j.shade.protobuf.ByteString getStringVal(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]; */ java.util.List 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_INT64
   * 
* * repeated int64 int64_val = 10 [packed = true]; */ java.util.List 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_BOOL
   * 
* * repeated bool bool_val = 11 [packed = true]; */ java.util.List getBoolValList(); /** *
   * DT_BOOL
   * 
* * repeated bool bool_val = 11 [packed = true]; */ int getBoolValCount(); /** *
   * DT_BOOL
   * 
* * repeated bool bool_val = 11 [packed = true]; */ boolean getBoolVal(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]; */ java.util.List 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_RESOURCE
   * 
* * repeated .tensorflow.ResourceHandleProto resource_handle_val = 14; */ java.util.List getResourceHandleValList(); /** *
   * DT_RESOURCE
   * 
* * repeated .tensorflow.ResourceHandleProto resource_handle_val = 14; */ org.tensorflow.framework.ResourceHandleProto getResourceHandleVal(int index); /** *
   * DT_RESOURCE
   * 
* * repeated .tensorflow.ResourceHandleProto resource_handle_val = 14; */ int getResourceHandleValCount(); /** *
   * DT_RESOURCE
   * 
* * repeated .tensorflow.ResourceHandleProto resource_handle_val = 14; */ java.util.List getResourceHandleValOrBuilderList(); /** *
   * DT_RESOURCE
   * 
* * repeated .tensorflow.ResourceHandleProto resource_handle_val = 14; */ org.tensorflow.framework.ResourceHandleProtoOrBuilder getResourceHandleValOrBuilder( int index); /** *
   * DT_VARIANT
   * 
* * repeated .tensorflow.VariantTensorDataProto variant_val = 15; */ java.util.List getVariantValList(); /** *
   * DT_VARIANT
   * 
* * repeated .tensorflow.VariantTensorDataProto variant_val = 15; */ org.tensorflow.framework.VariantTensorDataProto getVariantVal(int index); /** *
   * DT_VARIANT
   * 
* * repeated .tensorflow.VariantTensorDataProto variant_val = 15; */ int getVariantValCount(); /** *
   * DT_VARIANT
   * 
* * repeated .tensorflow.VariantTensorDataProto variant_val = 15; */ java.util.List getVariantValOrBuilderList(); /** *
   * DT_VARIANT
   * 
* * repeated .tensorflow.VariantTensorDataProto variant_val = 15; */ org.tensorflow.framework.VariantTensorDataProtoOrBuilder getVariantValOrBuilder( int index); /** *
   * DT_UINT32
   * 
* * repeated uint32 uint32_val = 16 [packed = true]; */ java.util.List 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_UINT64
   * 
* * repeated uint64 uint64_val = 17 [packed = true]; */ java.util.List 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); }




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