tensorflow/core/framework/summary.proto

syntax = "proto3";

package tensorflow;

import public "xla/tsl/protobuf/histogram.proto";

import "tensorflow/core/framework/tensor.proto";

option cc_enable_arenas = true;
option java_outer_classname = "SummaryProtos";
option java_multiple_files = true;
option java_package = "org.tensorflow.framework";
option go_package = "github.com/tensorflow/tensorflow/tensorflow/go/core/framework/summary_go_proto";

// Metadata associated with a series of Summary data
message SummaryDescription {
  // Hint on how plugins should process the data in this series.
  // Supported values include "scalar", "histogram", "image", "audio"
  string type_hint = 1;
}

// A SummaryMetadata encapsulates information on which plugins are able to make
// use of a certain summary value.
message SummaryMetadata {
  message PluginData {
    // The name of the plugin this data pertains to.
    string plugin_name = 1;

    // The content to store for the plugin. The best practice is for this to be
    // a binary serialized protocol buffer.
    bytes content = 2;
  }

  // Data that associates a summary with a certain plugin.
  PluginData plugin_data = 1;

  // Display name for viewing in TensorBoard.
  string display_name = 2;

  // Longform readable description of the summary sequence. Markdown supported.
  string summary_description = 3;

  // Class of data stored in this time series. Required for compatibility with
  // TensorBoard's generic data facilities (`DataProvider`, et al.). This value
  // imposes constraints on the dtype and shape of the corresponding tensor
  // values. See `DataClass` docs for details.
  DataClass data_class = 4;
}

enum DataClass {
  // Unknown data class, used (implicitly) for legacy data. Will not be
  // processed by data ingestion pipelines.
  DATA_CLASS_UNKNOWN = 0;
  // Scalar time series. Each `Value` for the corresponding tag must have
  // `tensor` set to a rank-0 tensor of type `DT_FLOAT` (float32).
  DATA_CLASS_SCALAR = 1;
  // Tensor time series. Each `Value` for the corresponding tag must have
  // `tensor` set. The tensor value is arbitrary, but should be small to
  // accommodate direct storage in database backends: an upper bound of a few
  // kilobytes is a reasonable rule of thumb.
  DATA_CLASS_TENSOR = 2;
  // Blob sequence time series. Each `Value` for the corresponding tag must
  // have `tensor` set to a rank-1 tensor of bytestring dtype.
  DATA_CLASS_BLOB_SEQUENCE = 3;
}

// A Summary is a set of named values to be displayed by the
// visualizer.
//
// Summaries are produced regularly during training, as controlled by
// the "summary_interval_secs" attribute of the training operation.
// Summaries are also produced at the end of an evaluation.
message Summary {
  message Image {
    // Dimensions of the image.
    int32 height = 1;
    int32 width = 2;
    // Valid colorspace values are
    //   1 - grayscale
    //   2 - grayscale + alpha
    //   3 - RGB
    //   4 - RGBA
    //   5 - DIGITAL_YUV
    //   6 - BGRA
    int32 colorspace = 3;
    // Image data in encoded format.  All image formats supported by
    // image_codec::CoderUtil can be stored here.
    bytes encoded_image_string = 4;
  }

  message Audio {
    // Sample rate of the audio in Hz.
    float sample_rate = 1;
    // Number of channels of audio.
    int64 num_channels = 2;
    // Length of the audio in frames (samples per channel).
    int64 length_frames = 3;
    // Encoded audio data and its associated RFC 2045 content type (e.g.
    // "audio/wav").
    bytes encoded_audio_string = 4;
    string content_type = 5;
  }

  message Value {
    // This field is deprecated and will not be set.
    string node_name = 7;

    // Tag name for the data. Used by TensorBoard plugins to organize data. Tags
    // are often organized by scope (which contains slashes to convey
    // hierarchy). For example: foo/bar/0
    string tag = 1;

    // Contains metadata on the summary value such as which plugins may use it.
    // Take note that many summary values may lack a metadata field. This is
    // because the FileWriter only keeps a metadata object on the first summary
    // value with a certain tag for each tag. TensorBoard then remembers which
    // tags are associated with which plugins. This saves space.
    SummaryMetadata metadata = 9;

    // Value associated with the tag.
    oneof value {
      float simple_value = 2;
      bytes obsolete_old_style_histogram = 3;
      Image image = 4;
      HistogramProto histo = 5;
      Audio audio = 6;
      TensorProto tensor = 8;
    }
  }

  // Set of values for the summary.
  repeated Value value = 1;
}