// Copyright 2017 The TensorFlow Authors. All Rights Reserved.
//
// Licensed under the Apache License, Version 2.0 (the "License");
// you may not use this file except in compliance with the License.
// You may obtain a copy of the License at
//
//     http://www.apache.org/licenses/LICENSE-2.0
//
// Unless required by applicable law or agreed to in writing, software
// distributed under the License is distributed on an "AS IS" BASIS,
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
// See the License for the specific language governing permissions and
// limitations under the License.
syntax = "proto2";
import "tensorflow/lite/toco/types.proto";

package toco;

message InputArrayShape {
  repeated int32 dims = 2;
}

// Next ID to USE: 7.
message InputArray {
  // Name of the input arrays, i.e. the arrays from which input activations
  // will be read.
  optional string name = 1;

  // Shape of the input.  For many applications the dimensions are {batch,
  // height, width, depth}.  Often the batch is left "unspecified" by providing
  // a value of -1.
  //
  // The last dimension is typically called 'depth' or 'channels'. For example,
  // for an image model taking RGB images as input, this would have the value 3.
  optional InputArrayShape shape = 6;

  // mean_value and std_value parameters control the interpretation of raw input
  // activation values (elements of the input array) as real numbers. The
  // mapping is given by:
  //
  //    real_value = (raw_input_value - mean_value) / std_value
  //
  // In particular, the defaults (mean_value=0, std_value=1) yield
  // real_value = raw_input_value. Often, non-default values are used in image
  // models. For example, an image model taking uint8 image channel values as
  // its raw inputs, in [0, 255] range, may use mean_value=128, std_value=128 to
  // map them into the interval [-1, 1).
  //
  // Note: this matches exactly the meaning of mean_value and std_value in
  // (TensorFlow via LegacyFedInput).
  optional float mean_value = 3;
  optional float std_value = 4 [default = 1.];

  // Data type of the input.
  //
  // In many graphs, the input arrays already have defined data types,
  // e.g. Placeholder nodes in a TensorFlow GraphDef have a dtype attribute.
  // In those cases, it is not needed to specify this data_type flag.
  // The purpose of this flag is only to define the data type of input
  // arrays whose type isn't defined in the input graph file. For example,
  // when specifying an arbitrary (not Placeholder) --input_array into
  // a TensorFlow GraphDef.
  //
  // When this data_type is quantized (e.g. QUANTIZED_UINT8), the
  // corresponding quantization parameters are the mean_value, std_value
  // fields.
  //
  // It is also important to understand the nuance between this data_type
  // flag and the inference_input_type in TocoFlags. The basic difference
  // is that this data_type (like all ModelFlags) describes a property
  // of the input graph, while inference_input_type (like all TocoFlags)
  // describes an aspect of the toco transformation process and thus of
  // the output file. The types of input arrays may be different between
  // the input and output files if quantization or dequantization occurred.
  // Such differences can only occur for real-number data i.e. only
  // between FLOAT and quantized types (e.g. QUANTIZED_UINT8).
  optional IODataType data_type = 5;
}

message RnnState {
  optional string state_array = 1;
  optional string back_edge_source_array = 2;
  optional bool discardable = 5;
  // size allows to specify a 1-D shape for the RNN state array.
  // Will be expanded with 1's to fit the model.
  // TODO(benoitjacob): should allow a generic, explicit shape.
  optional int32 size = 3;
  optional int32 num_dims = 4;
}

// An ArraysExtraInfo message stores a collection of additional Information
// about arrays in a model, complementing the information in the model itself.
// It is intentionally a separate message so that it may be serialized and
// passed separately from the model. See --arrays_extra_info_file.
//
// A typical use case is to manually specify MinMax for specific arrays in a
// model that does not already contain such MinMax information.
message ArraysExtraInfo {
  message Entry {
    // Next ID to use: 8.
    optional string name = 1;
    optional string name_regexp = 7;
    optional double min = 2;
    optional double max = 3;
    optional IODataType data_type = 4;
    optional InputArrayShape shape = 5;
    optional float constant_float_value = 6;
  }
  repeated Entry entries = 1;
}

// ModelFlags encodes properties of a model that, depending on the file
// format, may or may not be recorded in the model file. The purpose of
// representing these properties in ModelFlags is to allow passing them
// separately from the input model file, for instance as command-line
// parameters, so that we can offer a single uniform interface that can
// handle files from different input formats.
//
// For each of these properties, and each supported file format, we
// detail in comments below whether the property exists in the given file
// format.
//
// Obsolete flags that have been removed:
//   optional int32 input_depth = 3;
//   optional int32 input_width = 4;
//   optional int32 input_height = 5;
//   optional int32 batch = 6 [ default = 1];
//   optional float mean_value = 7;
//   optional float std_value = 8 [default = 1.];
//   optional int32 input_dims = 11 [ default = 4];
//   repeated int32 input_shape = 13;
//
// Next ID to USE: 20.
message ModelFlags {
  // Information about the input arrays, i.e. the arrays from which input
  // activations will be read.
  repeated InputArray input_arrays = 1;

  // Name of the output arrays, i.e. the arrays into which output activations
  // will be written.
  repeated string output_arrays = 2;

  // If true, the model accepts an arbitrary batch size. Mutually exclusive with
  // the 'batch' field: at most one of these two fields can be set.
  optional bool variable_batch = 10;

  repeated RnnState rnn_states = 12;

  // Checks applied to the model, typically after toco's comprehensive
  // graph transformations.
  // Next ID to USE: 4.
  message ModelCheck {
    // Use the name of a type of operator to check its counts.
    // Use "Total" for overall operator counts.
    // Use "Arrays" for overall array counts.
    optional string count_type = 1 [default = "None"];
    // A count of zero is a meaningful check, so negative used to mean disable.
    optional int32 count_min = 2 [default = -1];
    // If count_max < count_min, then count_min is only allowed value.
    optional int32 count_max = 3 [default = -1];
  }
  repeated ModelCheck model_checks = 14;

  // If true, will allow passing inexistent arrays in --input_arrays
  // and --output_arrays. This makes little sense, is only useful to
  // more easily get graph visualizations.
  optional bool allow_nonexistent_arrays = 16;

  // If true, will allow passing non-ascii-printable characters in
  // --input_arrays and --output_arrays. By default (if false), only
  // ascii printable characters are allowed, i.e. character codes
  // ranging from 32 to 127. This is disallowed by default so as to
  // catch common copy-and-paste issues where invisible unicode
  // characters are unwittingly added to these strings.
  optional bool allow_nonascii_arrays = 17;

  // If set, this ArraysExtraInfo allows to pass extra information about arrays
  // not specified in the input model file, such as extra MinMax information.
  optional ArraysExtraInfo arrays_extra_info = 18;

  // When set to false, toco will not change the input ranges and the output
  // ranges of concat operator to the overlap of all input ranges.
  optional bool change_concat_input_ranges = 19 [default = true];
}
