// api.proto
// Definition of various TensorFlow protobuf messages for use with the TensorFlow API.
//
// Assembled from these relevant proto sources:
// https://github.com/google/protobuf/blob/master/src/google/protobuf/any.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/types.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/tensor_shape.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/attr_value.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/versions.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/graph.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/node_def.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/op_def.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/saver.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/meta_graph.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/protobuf/saved_model.proto
// https://github.com/tensorflow/tensorflow/blob/master/tensorflow/core/framework/function.proto
// https://github.com/tensorflow/tensorboard/blob/master/tensorboard/compat/proto/summary.proto
// https://github.com/tensorflow/tensorboard/blob/master/tensorboard/plugins/histogram/plugin_data.proto


// This file is used to generate the api_pb.js file with the JavaScript Protocol
// Buffers runtime library (https://github.com/protocolbuffers/protobuf/tree/master/js).
// The protocol compiler (https://github.com/protocolbuffers/protobuf/releases)
// translated this file (same as proto file in tfjs-converter:
// https://github.com/tensorflow/tfjs/blob/master/tfjs-converter/src/data/api.proto)
// into the api_pb.js file with command:
//
// ```
// $ protoc --js_out=import_style=commonjs,binary:. api.proto
// ```


syntax = "proto3";
package tensorflow;

message Any {
  string type_url = 1;
  bytes value = 2;
}

enum DataType {
  // Not a legal value for DataType.  Used to indicate a DataType field
  // has not been set.
  DT_INVALID = 0;

  // Data types that all computation devices are expected to be
  // capable to support.
  DT_FLOAT = 1;
  DT_DOUBLE = 2;
  DT_INT32 = 3;
  DT_UINT8 = 4;
  DT_INT16 = 5;
  DT_INT8 = 6;
  DT_STRING = 7;
  DT_COMPLEX64 = 8;  // Single-precision complex
  DT_INT64 = 9;
  DT_BOOL = 10;
  DT_QINT8 = 11;     // Quantized int8
  DT_QUINT8 = 12;    // Quantized uint8
  DT_QINT32 = 13;    // Quantized int32
  DT_BFLOAT16 = 14;  // Float32 truncated to 16 bits.  Only for cast ops.

  // Do not use!  These are only for parameters.  Every enum above
  // should have a corresponding value below (verified by types_test).
  DT_FLOAT_REF = 101;
  DT_DOUBLE_REF = 102;
  DT_INT32_REF = 103;
  DT_UINT8_REF = 104;
  DT_INT16_REF = 105;
  DT_INT8_REF = 106;
  DT_STRING_REF = 107;
  DT_COMPLEX64_REF = 108;
  DT_INT64_REF = 109;
  DT_BOOL_REF = 110;
  DT_QINT8_REF = 111;
  DT_QUINT8_REF = 112;
  DT_QINT32_REF = 113;
  DT_BFLOAT16_REF = 114;
}

message TensorShape {
  // One dimension of the tensor.
  message Dim {
    // Size of the tensor in that dimension.
    int64 size = 1;

    // Optional name of the tensor dimension.
    string name = 2;
  }

  // Dimensions of the tensor, such as {"input", 30}, {"output", 40} for a 30 x
  // 40 2D tensor.  The names are optional.
  //
  // The order of entries in "dim" matters: It indicates the layout of the
  // values in the tensor in-memory representation.
  //
  // The first entry in "dim" is the outermost dimension used to layout the
  // values, the last entry is the innermost dimension.  This matches the
  // in-memory layout of RowMajor Eigen tensors.
  repeated Dim dim = 2;

  bool unknown_rank = 3;
}

message Tensor {
  DataType dtype = 1;

  // Shape of the tensor.  TODO(touts): sort out the 0-rank issues.
  TensorShape tensor_shape = 2;

  // Only one of the representations below is set, one of "tensor_contents" and
  // the "xxx_val" attributes.  We are not using oneof because as oneofs cannot
  // contain repeated fields it would require another extra set of messages.

  // 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;

  // Serialized content from TensorBase::Serialize() This representation can be
  // used for all tensor types.
  bytes tensor_content = 4;

  // Type specific representations that make it easy to create tensor protos in
  // all languages.  Only the representation corresponding to "dtype" can
  // be set.  The values hold the flattened representation of the tensor in
  // row major order.

  // DT_FLOAT.
  repeated float float_val = 5 [packed = true];

  // DT_DOUBLE.
  repeated double double_val = 6 [packed = true];

  // DT_INT32, DT_INT16, DT_INT8, DT_UINT8.
  repeated int32 int_val = 7 [packed = true];

  // DT_STRING
  repeated bytes string_val = 8;

  // 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];

  // DT_INT64
  repeated int64 int64_val = 10 [packed = true];

  // DT_BOOL
  repeated bool bool_val = 11 [packed = true];

  // DT_UINT32
  repeated uint32 uint32_val = 16 [packed = true];

  // DT_UINT64
  repeated uint64 uint64_val = 17 [packed = true];
}

message AttrValue {
  message ListValue {
    repeated bytes s = 2;
    repeated int64 i = 3 [packed = true];
    repeated float f = 4 [packed = true];
    repeated bool b = 5 [packed = true];
    repeated DataType type = 6 [packed = true];
    repeated TensorShape shape = 7;
    repeated Tensor tensor = 8;
    repeated NameAttrList func = 9;
  }

  oneof value {
    ListValue list = 1;
    bytes s = 2;
    int64 i = 3;
    float f = 4;
    bool b = 5;
    DataType type = 6;
    TensorShape shape = 7;
    Tensor tensor = 8;
    string placeholder = 9;
    NameAttrList func = 10;
  }
}

message NameAttrList {
  string name = 1;
  map<string, AttrValue> attr = 2;
}

message NodeDef {
  string name = 1;
  string op = 2;
  repeated string input = 3;
  string device = 4;
  map<string, AttrValue> attr = 5;
}

message VersionDef {
  int32 producer = 1;
  int32 min_consumer = 2;
  repeated int32 bad_consumers = 3;
}

message GraphDef {
  repeated NodeDef node = 1;
  VersionDef versions = 4;
  FunctionDefLibrary library = 2;
}

message CollectionDef {
  message NodeList {
    repeated string value = 1;
  }
  message BytesList {
    repeated bytes value = 1;
  }
  message Int64List {
    repeated int64 value = 1 [packed = true];
  }
  message FloatList {
    repeated float value = 1 [packed = true];
  }
  message AnyList {
    repeated Any value = 1;
  }

  oneof kind {
    NodeList node_list = 1;
    BytesList bytes_list = 2;
    Int64List int64_list = 3;
    FloatList float_list = 4;
    AnyList any_list = 5;
  }
}

message SaverDef {
  string filename_tensor_name = 1;
  string save_tensor_name = 2;
  string restore_op_name = 3;
  int32 max_to_keep = 4;
  bool sharded = 5;
  float keep_checkpoint_every_n_hours = 6;

  enum CheckpointFormatVersion {
    LEGACY = 0;
    V1 = 1;
    V2 = 2;
  }
  CheckpointFormatVersion version = 7;
}

message TensorInfo {
  message CooSparse {
    string values_tensor_name = 1;
    string indices_tensor_name = 2;
    string dense_shape_tensor_name = 3;
  }

  oneof encoding {
    string name = 1;
    CooSparse coo_sparse = 4;
  }
  DataType dtype = 2;
  TensorShape tensor_shape = 3;
}

message SignatureDef {
  map<string, TensorInfo> inputs = 1;
  map<string, TensorInfo> outputs = 2;
  string method_name = 3;
}

message AssetFileDef {
  TensorInfo tensor_info = 1;
  string filename = 2;
}

message OpDef {
  string name = 1;

  message ArgDef {
    string name = 1;
    string description = 2;
    DataType type = 3;
    string type_attr = 4;    // if specified, attr must have type "type"
    string number_attr = 5;  // if specified, attr must have type "int"
    string type_list_attr = 6;
    bool is_ref = 16;
  }
  repeated ArgDef input_arg = 2;
  repeated ArgDef output_arg = 3;

  message AttrDef {
    string name = 1;
    string type = 2;
    AttrValue default_value = 3;
    string description = 4;
    bool has_minimum = 5;
    int64 minimum = 6;
    AttrValue allowed_values = 7;
  }
  repeated AttrDef attr = 4;

  message OpDeprecation {
    int32 version = 1;
    string explanation = 2;
  }
  OpDeprecation deprecation = 8;

  string summary = 5;
  string description = 6;
  bool is_commutative = 18;
  bool is_aggregate = 16;  // for things like add
  bool is_stateful = 17;  // for things like variables, queue
  bool allows_uninitialized_input = 19;  // for Assign, etc.
}

message OpList {
  repeated OpDef op = 1;
}

message MetaGraphDef {
  message MetaInfoDef {
    string meta_graph_version = 1;
    OpList stripped_op_list = 2;
    Any any_info = 3;
    repeated string tags = 4;
    string tensorflow_version = 5;
    string tensorflow_git_version = 6;
  }
  MetaInfoDef meta_info_def = 1;
  GraphDef graph_def = 2;
  SaverDef saver_def = 3;
  map<string, CollectionDef> collection_def = 4;
  map<string, SignatureDef> signature_def = 5;
  repeated AssetFileDef asset_file_def = 6;
}

message SavedModel {
  int64 saved_model_schema_version = 1;
  repeated MetaGraphDef meta_graphs = 2;
}

message FunctionDefLibrary {
  repeated FunctionDef function = 1;
  repeated GradientDef gradient = 2;
}

message FunctionDef {
  OpDef signature = 1;
  map<string, AttrValue> attr = 5;
  reserved 2;
  repeated NodeDef node_def = 3;
  map<string, string> ret = 4;
}

message GradientDef {
  string function_name = 1;  // The function name.
  string gradient_func = 2;  // The gradient function's name.
}

/////////////////
// Tensorboard //
/////////////////

// 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;
}

// Serialization format for histogram module in
// core/lib/histogram/histogram.h
message HistogramProto {
  double min = 1;
  double max = 2;
  double num = 3;
  double sum = 4;
  double sum_squares = 5;

  // Parallel arrays encoding the bucket boundaries and the bucket values.
  // bucket(i) is the count for the bucket i.  The range for
  // a bucket is:
  //   i == 0:  -DBL_MAX .. bucket_limit(0)
  //   i != 0:  bucket_limit(i-1) .. bucket_limit(i)
  repeated double bucket_limit = 6 [packed = true];
  repeated double bucket = 7 [packed = true];
}

// 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;
      Tensor tensor = 8;
    }
  }

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

// Histogram summaries created by the `tensorboard.plugins.histogram.summary`
// module will include `SummaryMetadata` whose `plugin_data` field has
// as `content` a binary string that is the encoding of a
// `HistogramPluginData` proto.
message HistogramPluginData {
  // Version `0` is the only supported version.
  int32 version = 1;
}