// api.proto
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// Definition of various TensorFlow protobuf messages for use with the TensorFlow API.
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//
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// Assembled from these relevant proto sources:
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// https://github.com/google/protobuf/blob/master/src/google/protobuf/any.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/types.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor_shape.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/attr_value.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/versions.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/graph.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/node_def.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op_def.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/saver.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/meta_graph.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/saved_model.proto
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// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/function.proto
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// https://github.com/tensorflow/tensorboard/blob/master/tensorboard/compat/proto/summary.proto
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// https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/histogram/plugin_data.proto
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// This file is used to generate the api_pb.js file with the JavaScript Protocol
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// Buffers runtime library (https://github.com/protocolbuffers/protobuf/tree/master/js).
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// The protocol compiler (https://github.com/protocolbuffers/protobuf/releases)
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// translated this file (same as proto file in tfjs-converter:
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// https://github.com/tensorflow/tfjs/blob/master/tfjs-converter/src/data/api.proto)
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// into the api_pb.js file with command:
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//
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// ```
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// $ protoc --js_out=import_style=commonjs,binary:. api.proto
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// ```
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syntax = "proto3";
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package tensorflow;
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message Any {
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string type_url = 1;
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bytes value = 2;
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}
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enum DataType {
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// Not a legal value for DataType. Used to indicate a DataType field
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// has not been set.
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DT_INVALID = 0;
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// Data types that all computation devices are expected to be
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// capable to support.
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DT_FLOAT = 1;
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DT_DOUBLE = 2;
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DT_INT32 = 3;
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DT_UINT8 = 4;
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DT_INT16 = 5;
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DT_INT8 = 6;
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DT_STRING = 7;
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DT_COMPLEX64 = 8; // Single-precision complex
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DT_INT64 = 9;
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DT_BOOL = 10;
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DT_QINT8 = 11; // Quantized int8
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DT_QUINT8 = 12; // Quantized uint8
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DT_QINT32 = 13; // Quantized int32
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DT_BFLOAT16 = 14; // Float32 truncated to 16 bits. Only for cast ops.
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// Do not use! These are only for parameters. Every enum above
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// should have a corresponding value below (verified by types_test).
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DT_FLOAT_REF = 101;
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DT_DOUBLE_REF = 102;
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DT_INT32_REF = 103;
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DT_UINT8_REF = 104;
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DT_INT16_REF = 105;
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DT_INT8_REF = 106;
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DT_STRING_REF = 107;
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DT_COMPLEX64_REF = 108;
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DT_INT64_REF = 109;
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DT_BOOL_REF = 110;
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DT_QINT8_REF = 111;
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DT_QUINT8_REF = 112;
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DT_QINT32_REF = 113;
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DT_BFLOAT16_REF = 114;
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}
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message TensorShape {
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// One dimension of the tensor.
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message Dim {
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// Size of the tensor in that dimension.
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int64 size = 1;
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// Optional name of the tensor dimension.
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string name = 2;
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}
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// Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x
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// 40 2D tensor. The names are optional.
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//
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// The order of entries in "dim" matters: It indicates the layout of the
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// values in the tensor in-memory representation.
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//
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// The first entry in "dim" is the outermost dimension used to layout the
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// values, the last entry is the innermost dimension. This matches the
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// in-memory layout of RowMajor Eigen tensors.
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repeated Dim dim = 2;
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bool unknown_rank = 3;
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}
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message Tensor {
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DataType dtype = 1;
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// Shape of the tensor. TODO(touts): sort out the 0-rank issues.
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TensorShape tensor_shape = 2;
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// Only one of the representations below is set, one of "tensor_contents" and
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// the "xxx_val" attributes. We are not using oneof because as oneofs cannot
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// contain repeated fields it would require another extra set of messages.
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// Version number.
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//
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// In version 0, if the "repeated xxx" representations contain only one
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// element, that element is repeated to fill the shape. This makes it easy
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// to represent a constant Tensor with a single value.
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int32 version_number = 3;
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// Serialized content from TensorBase::Serialize() This representation can be
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// used for all tensor types.
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bytes tensor_content = 4;
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// Type specific representations that make it easy to create tensor protos in
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// all languages. Only the representation corresponding to "dtype" can
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// be set. The values hold the flattened representation of the tensor in
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// row major order.
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// DT_FLOAT.
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repeated float float_val = 5 [packed = true];
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// DT_DOUBLE.
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repeated double double_val = 6 [packed = true];
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// DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
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repeated int32 int_val = 7 [packed = true];
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// DT_STRING
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repeated bytes string_val = 8;
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// DT_COMPLEX64. scomplex_val(2*i) and scomplex_val(2*i+1) are real
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// and imaginary parts of i-th single precision complex.
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repeated float scomplex_val = 9 [packed = true];
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// DT_INT64
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repeated int64 int64_val = 10 [packed = true];
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// DT_BOOL
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repeated bool bool_val = 11 [packed = true];
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// DT_UINT32
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repeated uint32 uint32_val = 16 [packed = true];
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// DT_UINT64
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repeated uint64 uint64_val = 17 [packed = true];
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}
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message AttrValue {
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message ListValue {
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repeated bytes s = 2;
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repeated int64 i = 3 [packed = true];
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repeated float f = 4 [packed = true];
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repeated bool b = 5 [packed = true];
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repeated DataType type = 6 [packed = true];
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repeated TensorShape shape = 7;
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repeated Tensor tensor = 8;
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repeated NameAttrList func = 9;
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}
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oneof value {
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ListValue list = 1;
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bytes s = 2;
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int64 i = 3;
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float f = 4;
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bool b = 5;
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DataType type = 6;
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TensorShape shape = 7;
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Tensor tensor = 8;
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string placeholder = 9;
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NameAttrList func = 10;
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}
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}
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message NameAttrList {
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string name = 1;
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map<string, AttrValue> attr = 2;
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}
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message NodeDef {
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string name = 1;
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string op = 2;
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repeated string input = 3;
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string device = 4;
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map<string, AttrValue> attr = 5;
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}
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message VersionDef {
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int32 producer = 1;
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int32 min_consumer = 2;
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repeated int32 bad_consumers = 3;
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}
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message GraphDef {
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repeated NodeDef node = 1;
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VersionDef versions = 4;
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FunctionDefLibrary library = 2;
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}
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message CollectionDef {
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message NodeList {
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repeated string value = 1;
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}
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message BytesList {
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repeated bytes value = 1;
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}
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message Int64List {
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repeated int64 value = 1 [packed = true];
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}
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message FloatList {
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repeated float value = 1 [packed = true];
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}
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message AnyList {
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repeated Any value = 1;
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}
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oneof kind {
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NodeList node_list = 1;
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BytesList bytes_list = 2;
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Int64List int64_list = 3;
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FloatList float_list = 4;
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AnyList any_list = 5;
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}
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}
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message SaverDef {
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string filename_tensor_name = 1;
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string save_tensor_name = 2;
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string restore_op_name = 3;
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int32 max_to_keep = 4;
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bool sharded = 5;
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float keep_checkpoint_every_n_hours = 6;
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enum CheckpointFormatVersion {
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LEGACY = 0;
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V1 = 1;
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V2 = 2;
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}
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CheckpointFormatVersion version = 7;
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}
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message TensorInfo {
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message CooSparse {
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string values_tensor_name = 1;
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string indices_tensor_name = 2;
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string dense_shape_tensor_name = 3;
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}
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oneof encoding {
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string name = 1;
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CooSparse coo_sparse = 4;
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}
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DataType dtype = 2;
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TensorShape tensor_shape = 3;
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}
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message SignatureDef {
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map<string, TensorInfo> inputs = 1;
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map<string, TensorInfo> outputs = 2;
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string method_name = 3;
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}
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message AssetFileDef {
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TensorInfo tensor_info = 1;
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string filename = 2;
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}
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message OpDef {
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string name = 1;
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message ArgDef {
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string name = 1;
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string description = 2;
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DataType type = 3;
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string type_attr = 4; // if specified, attr must have type "type"
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string number_attr = 5; // if specified, attr must have type "int"
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string type_list_attr = 6;
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bool is_ref = 16;
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}
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repeated ArgDef input_arg = 2;
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repeated ArgDef output_arg = 3;
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message AttrDef {
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string name = 1;
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string type = 2;
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AttrValue default_value = 3;
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string description = 4;
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bool has_minimum = 5;
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int64 minimum = 6;
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AttrValue allowed_values = 7;
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}
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repeated AttrDef attr = 4;
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message OpDeprecation {
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int32 version = 1;
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string explanation = 2;
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}
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OpDeprecation deprecation = 8;
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string summary = 5;
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string description = 6;
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bool is_commutative = 18;
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bool is_aggregate = 16; // for things like add
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bool is_stateful = 17; // for things like variables, queue
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bool allows_uninitialized_input = 19; // for Assign, etc.
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}
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message OpList {
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repeated OpDef op = 1;
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}
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message MetaGraphDef {
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message MetaInfoDef {
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string meta_graph_version = 1;
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OpList stripped_op_list = 2;
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Any any_info = 3;
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repeated string tags = 4;
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string tensorflow_version = 5;
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string tensorflow_git_version = 6;
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}
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MetaInfoDef meta_info_def = 1;
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GraphDef graph_def = 2;
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SaverDef saver_def = 3;
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map<string, CollectionDef> collection_def = 4;
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map<string, SignatureDef> signature_def = 5;
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repeated AssetFileDef asset_file_def = 6;
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}
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message SavedModel {
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int64 saved_model_schema_version = 1;
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repeated MetaGraphDef meta_graphs = 2;
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}
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message FunctionDefLibrary {
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repeated FunctionDef function = 1;
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repeated GradientDef gradient = 2;
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}
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message FunctionDef {
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OpDef signature = 1;
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map<string, AttrValue> attr = 5;
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reserved 2;
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repeated NodeDef node_def = 3;
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map<string, string> ret = 4;
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}
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message GradientDef {
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string function_name = 1; // The function name.
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string gradient_func = 2; // The gradient function's name.
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}
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/////////////////
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// Tensorboard //
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/////////////////
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// Metadata associated with a series of Summary data
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message SummaryDescription {
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// Hint on how plugins should process the data in this series.
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// Supported values include "scalar", "histogram", "image", "audio"
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string type_hint = 1;
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}
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// Serialization format for histogram module in
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// core/lib/histogram/histogram.h
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message HistogramProto {
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double min = 1;
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double max = 2;
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double num = 3;
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double sum = 4;
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double sum_squares = 5;
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// Parallel arrays encoding the bucket boundaries and the bucket values.
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// bucket(i) is the count for the bucket i. The range for
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// a bucket is:
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// i == 0: -DBL_MAX .. bucket_limit(0)
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// i != 0: bucket_limit(i-1) .. bucket_limit(i)
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repeated double bucket_limit = 6 [packed = true];
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repeated double bucket = 7 [packed = true];
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}
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// A SummaryMetadata encapsulates information on which plugins are able to make
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// use of a certain summary value.
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message SummaryMetadata {
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message PluginData {
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// The name of the plugin this data pertains to.
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string plugin_name = 1;
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// The content to store for the plugin. The best practice is for this to be
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// a binary serialized protocol buffer.
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bytes content = 2;
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}
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// Data that associates a summary with a certain plugin.
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PluginData plugin_data = 1;
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// Display name for viewing in TensorBoard.
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string display_name = 2;
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// Longform readable description of the summary sequence. Markdown supported.
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string summary_description = 3;
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// Class of data stored in this time series. Required for compatibility with
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// TensorBoard's generic data facilities (`DataProvider`, et al.). This value
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// imposes constraints on the dtype and shape of the corresponding tensor
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// values. See `DataClass` docs for details.
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DataClass data_class = 4;
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}
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enum DataClass {
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// Unknown data class, used (implicitly) for legacy data. Will not be
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// processed by data ingestion pipelines.
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DATA_CLASS_UNKNOWN = 0;
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// Scalar time series. Each `Value` for the corresponding tag must have
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// `tensor` set to a rank-0 tensor of type `DT_FLOAT` (float32).
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DATA_CLASS_SCALAR = 1;
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// Tensor time series. Each `Value` for the corresponding tag must have
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// `tensor` set. The tensor value is arbitrary, but should be small to
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// accommodate direct storage in database backends: an upper bound of a few
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// kilobytes is a reasonable rule of thumb.
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DATA_CLASS_TENSOR = 2;
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// Blob sequence time series. Each `Value` for the corresponding tag must
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// have `tensor` set to a rank-1 tensor of bytestring dtype.
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DATA_CLASS_BLOB_SEQUENCE = 3;
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}
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// A Summary is a set of named values to be displayed by the
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// visualizer.
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//
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// Summaries are produced regularly during training, as controlled by
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// the "summary_interval_secs" attribute of the training operation.
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// Summaries are also produced at the end of an evaluation.
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message Summary {
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message Image {
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// Dimensions of the image.
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int32 height = 1;
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int32 width = 2;
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// Valid colorspace values are
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// 1 - grayscale
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// 2 - grayscale + alpha
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// 3 - RGB
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// 4 - RGBA
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// 5 - DIGITAL_YUV
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// 6 - BGRA
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int32 colorspace = 3;
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// Image data in encoded format. All image formats supported by
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// image_codec::CoderUtil can be stored here.
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bytes encoded_image_string = 4;
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}
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message Audio {
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// Sample rate of the audio in Hz.
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float sample_rate = 1;
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// Number of channels of audio.
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int64 num_channels = 2;
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// Length of the audio in frames (samples per channel).
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int64 length_frames = 3;
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// Encoded audio data and its associated RFC 2045 content type (e.g.
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// "audio/wav").
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bytes encoded_audio_string = 4;
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string content_type = 5;
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}
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message Value {
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// This field is deprecated and will not be set.
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string node_name = 7;
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// Tag name for the data. Used by TensorBoard plugins to organize data. Tags
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// are often organized by scope (which contains slashes to convey
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// hierarchy). For example: foo/bar/0
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string tag = 1;
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// Contains metadata on the summary value such as which plugins may use it.
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// Take note that many summary values may lack a metadata field. This is
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// because the FileWriter only keeps a metadata object on the first summary
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// value with a certain tag for each tag. TensorBoard then remembers which
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// tags are associated with which plugins. This saves space.
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SummaryMetadata metadata = 9;
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// Value associated with the tag.
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oneof value {
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float simple_value = 2;
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bytes obsolete_old_style_histogram = 3;
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Image image = 4;
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HistogramProto histo = 5;
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Audio audio = 6;
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Tensor tensor = 8;
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}
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}
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// Set of values for the summary.
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repeated Value value = 1;
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}
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// Histogram summaries created by the `tensorboard.plugins.histogram.summary`
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// module will include `SummaryMetadata` whose `plugin_data` field has
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// as `content` a binary string that is the encoding of a
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// `HistogramPluginData` proto.
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message HistogramPluginData {
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// Version `0` is the only supported version.
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int32 version = 1;
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}
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