--- /dev/null
+// 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.
+
+// Revision History
+// Version 0: Initial version.
+// Version 1: Add subgraphs to schema.
+// Version 2: Rename operators to conform to NN API.
+// Version 3: Move buffer data from Model.Subgraph.Tensors to Model.Buffers.
+
+namespace tflite;
+
+// This corresponds to the version.
+file_identifier "TFL3";
+// File extension of any written files.
+file_extension "tflite";
+
+// IMPORTANT: All new members of tables, enums and unions must be added at the
+// end to ensure backwards compatibility.
+
+// The type of data stored in a tensor.
+enum TensorType : byte {
+ FLOAT32 = 0,
+ FLOAT16 = 1,
+ INT32 = 2,
+ UINT8 = 3,
+ INT64 = 4,
+ STRING = 5,
+ BOOL = 6,
+ INT16 = 7,
+ COMPLEX64 = 8,
+ INT8 = 9,
+}
+
+// Custom quantization parameters for experimenting with new quantization
+// techniques.
+table CustomQuantization {
+ custom:[ubyte] (force_align: 16);
+}
+
+// Represents a specific quantization technique's parameters.
+union QuantizationDetails {
+ CustomQuantization,
+}
+
+// Parameters for converting a quantized tensor back to float.
+table QuantizationParameters {
+ // These four parameters are the asymmetric linear quantization parameters.
+ // Given a quantized value q, the corresponding float value f should be:
+ // f = scale * (q - zero_point)
+ // For other quantization types, the QuantizationDetails below is used.
+ min:[float]; // For importing back into tensorflow.
+ max:[float]; // For importing back into tensorflow.
+ scale:[float]; // For dequantizing the tensor's values.
+ zero_point:[long];
+
+ // If this is not none, the quantization parameters above are ignored and the
+ // value of the QuantizationDetails union below should be used.
+ details:QuantizationDetails;
+}
+
+table Tensor {
+ // The tensor shape. The meaning of each entry is operator-specific but
+ // builtin ops use: [batch size, height, width, number of channels] (That's
+ // Tensorflow's NHWC).
+ shape:[int];
+ type:TensorType;
+ // An index that refers to the buffers table at the root of the model. Or,
+ // if there is no data buffer associated (i.e. intermediate results), then
+ // this is 0 (which refers to an always existent empty buffer).
+ //
+ // The data_buffer itself is an opaque container, with the assumption that the
+ // target device is little-endian. In addition, all builtin operators assume
+ // the memory is ordered such that if `shape` is [4, 3, 2], then index
+ // [i, j, k] maps to data_buffer[i*3*2 + j*2 + k].
+ buffer:uint;
+ name:string; // For debugging and importing back into tensorflow.
+ quantization:QuantizationParameters; // Optional.
+
+ is_variable:bool = false;
+}
+
+// A list of builtin operators. Builtin operators are slightly faster than custom
+// ones, but not by much. Moreover, while custom operators accept an opaque
+// object containing configuration parameters, builtins have a predetermined
+// set of acceptable options.
+enum BuiltinOperator : byte {
+ ADD = 0,
+ AVERAGE_POOL_2D = 1,
+ CONCATENATION = 2,
+ CONV_2D = 3,
+ DEPTHWISE_CONV_2D = 4,
+ // DEPTH_TO_SPACE = 5,
+ DEQUANTIZE = 6,
+ EMBEDDING_LOOKUP = 7,
+ FLOOR = 8,
+ FULLY_CONNECTED = 9,
+ HASHTABLE_LOOKUP = 10,
+ L2_NORMALIZATION = 11,
+ L2_POOL_2D = 12,
+ LOCAL_RESPONSE_NORMALIZATION = 13,
+ LOGISTIC = 14,
+ LSH_PROJECTION = 15,
+ LSTM = 16,
+ MAX_POOL_2D = 17,
+ MUL = 18,
+ RELU = 19,
+ // NOTE(aselle): RELU_N1_TO_1 used to be called RELU1, but it was renamed
+ // since different model developers use RELU1 in different ways. Never
+ // create another op called RELU1.
+ RELU_N1_TO_1 = 20,
+ RELU6 = 21,
+ RESHAPE = 22,
+ RESIZE_BILINEAR = 23,
+ RNN = 24,
+ SOFTMAX = 25,
+ SPACE_TO_DEPTH = 26,
+ SVDF = 27,
+ TANH = 28,
+ // TODO(aselle): Consider rename to CONCATENATE_EMBEDDINGS
+ CONCAT_EMBEDDINGS = 29,
+ SKIP_GRAM = 30,
+ CALL = 31,
+ CUSTOM = 32,
+ EMBEDDING_LOOKUP_SPARSE = 33,
+ PAD = 34,
+ UNIDIRECTIONAL_SEQUENCE_RNN = 35,
+ GATHER = 36,
+ BATCH_TO_SPACE_ND = 37,
+ SPACE_TO_BATCH_ND = 38,
+ TRANSPOSE = 39,
+ MEAN = 40,
+ SUB = 41,
+ DIV = 42,
+ SQUEEZE = 43,
+ UNIDIRECTIONAL_SEQUENCE_LSTM = 44,
+ STRIDED_SLICE = 45,
+ BIDIRECTIONAL_SEQUENCE_RNN = 46,
+ EXP = 47,
+ TOPK_V2 = 48,
+ SPLIT = 49,
+ LOG_SOFTMAX = 50,
+ // DELEGATE is a special op type for the operations which are delegated to
+ // other backends.
+ // WARNING: Experimental interface, subject to change
+ DELEGATE = 51,
+ BIDIRECTIONAL_SEQUENCE_LSTM = 52,
+ CAST = 53,
+ PRELU = 54,
+ MAXIMUM = 55,
+ ARG_MAX = 56,
+ MINIMUM = 57,
+ LESS = 58,
+ NEG = 59,
+ PADV2 = 60,
+ GREATER = 61,
+ GREATER_EQUAL = 62,
+ LESS_EQUAL = 63,
+ SELECT = 64,
+ SLICE = 65,
+ SIN = 66,
+ TRANSPOSE_CONV = 67,
+ SPARSE_TO_DENSE = 68,
+ TILE = 69,
+ EXPAND_DIMS = 70,
+ EQUAL = 71,
+ NOT_EQUAL = 72,
+ LOG = 73,
+ SUM = 74,
+ SQRT = 75,
+ RSQRT = 76,
+ SHAPE = 77,
+ POW = 78,
+ ARG_MIN = 79,
+ FAKE_QUANT = 80,
+ REDUCE_PROD = 81,
+ REDUCE_MAX = 82,
+ PACK = 83,
+ LOGICAL_OR = 84,
+ ONE_HOT = 85,
+ LOGICAL_AND = 86,
+ LOGICAL_NOT = 87,
+ UNPACK = 88,
+ REDUCE_MIN = 89,
+ FLOOR_DIV = 90,
+ REDUCE_ANY = 91,
+ SQUARE = 92,
+ ZEROS_LIKE = 93,
+ FILL = 94,
+ FLOOR_MOD = 95,
+ RANGE = 96,
+ RESIZE_NEAREST_NEIGHBOR = 97,
+ LEAKY_RELU = 98,
+ SQUARED_DIFFERENCE = 99,
+ MIRROR_PAD = 100,
+ ABS = 101,
+ SPLIT_V = 102,
+}
+
+// Options for the builtin operators.
+union BuiltinOptions {
+ Conv2DOptions,
+ DepthwiseConv2DOptions,
+ ConcatEmbeddingsOptions,
+ LSHProjectionOptions,
+ Pool2DOptions,
+ SVDFOptions,
+ RNNOptions,
+ FullyConnectedOptions,
+ SoftmaxOptions,
+ ConcatenationOptions,
+ AddOptions,
+ L2NormOptions,
+ LocalResponseNormalizationOptions,
+ LSTMOptions,
+ ResizeBilinearOptions,
+ CallOptions,
+ ReshapeOptions,
+ SkipGramOptions,
+ SpaceToDepthOptions,
+ EmbeddingLookupSparseOptions,
+ MulOptions,
+ PadOptions,
+ GatherOptions,
+ BatchToSpaceNDOptions,
+ SpaceToBatchNDOptions,
+ TransposeOptions,
+ ReducerOptions,
+ SubOptions,
+ DivOptions,
+ SqueezeOptions,
+ SequenceRNNOptions,
+ StridedSliceOptions,
+ ExpOptions,
+ TopKV2Options,
+ SplitOptions,
+ LogSoftmaxOptions,
+ CastOptions,
+ DequantizeOptions,
+ MaximumMinimumOptions,
+ ArgMaxOptions,
+ LessOptions,
+ NegOptions,
+ PadV2Options,
+ GreaterOptions,
+ GreaterEqualOptions,
+ LessEqualOptions,
+ SelectOptions,
+ SliceOptions,
+ TransposeConvOptions,
+ SparseToDenseOptions,
+ TileOptions,
+ ExpandDimsOptions,
+ EqualOptions,
+ NotEqualOptions,
+ ShapeOptions,
+ PowOptions,
+ ArgMinOptions,
+ FakeQuantOptions,
+ PackOptions,
+ LogicalOrOptions,
+ OneHotOptions,
+ LogicalAndOptions,
+ LogicalNotOptions,
+ UnpackOptions,
+ FloorDivOptions,
+ SquareOptions,
+ ZerosLikeOptions,
+ FillOptions,
+ BidirectionalSequenceLSTMOptions,
+ BidirectionalSequenceRNNOptions,
+ UnidirectionalSequenceLSTMOptions,
+ FloorModOptions,
+ RangeOptions,
+ ResizeNearestNeighborOptions,
+ LeakyReluOptions,
+ SquaredDifferenceOptions,
+ MirrorPadOptions,
+ AbsOptions,
+ SplitVOptions,
+}
+
+enum Padding : byte { SAME, VALID }
+
+enum ActivationFunctionType : byte {
+ NONE = 0,
+ RELU = 1,
+ RELU_N1_TO_1 = 2,
+ RELU6 = 3,
+ TANH = 4,
+ SIGN_BIT = 5,
+}
+
+table Conv2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ fused_activation_function:ActivationFunctionType;
+ dilation_w_factor:int = 1;
+ dilation_h_factor:int = 1;
+}
+
+table Pool2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ filter_width:int;
+ filter_height:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DepthwiseConv2DOptions {
+ // Parameters for DepthwiseConv version 1 or above.
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ depth_multiplier:int;
+ fused_activation_function:ActivationFunctionType;
+ // Parameters for DepthwiseConv version 2 or above.
+ dilation_w_factor:int = 1;
+ dilation_h_factor:int = 1;
+}
+
+table ConcatEmbeddingsOptions {
+ num_channels:int;
+ num_columns_per_channel:[int];
+ embedding_dim_per_channel:[int]; // This could be inferred from parameters.
+}
+
+enum LSHProjectionType: byte {
+ UNKNOWN = 0,
+ SPARSE = 1,
+ DENSE = 2,
+}
+
+table LSHProjectionOptions {
+ type: LSHProjectionType;
+}
+
+table SVDFOptions {
+ rank:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+// An implementation of TensorFlow RNNCell.
+table RNNOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+// An implementation of TensorFlow dynamic_rnn with RNNCell.
+table SequenceRNNOptions {
+ time_major:bool;
+ fused_activation_function:ActivationFunctionType;
+}
+
+// An implementation of TensorFlow bidrectional_dynamic_rnn with RNNCell.
+table BidirectionalSequenceRNNOptions {
+ time_major:bool;
+ fused_activation_function:ActivationFunctionType;
+ merge_outputs: bool;
+}
+
+enum FullyConnectedOptionsWeightsFormat: byte {
+ DEFAULT = 0,
+ SHUFFLED4x16INT8 = 1,
+}
+
+// An implementation of TensorFlow fully_connected (a.k.a Dense) layer.
+table FullyConnectedOptions {
+ // Parameters for FullyConnected version 1 or above.
+ fused_activation_function:ActivationFunctionType;
+
+ // Parameters for FullyConnected version 2 or above.
+ weights_format:FullyConnectedOptionsWeightsFormat = DEFAULT;
+}
+
+table SoftmaxOptions {
+ beta: float;
+}
+
+// An implementation of TensorFlow concat.
+table ConcatenationOptions {
+ axis:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table AddOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table MulOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table L2NormOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table LocalResponseNormalizationOptions {
+ radius:int;
+ bias:float;
+ alpha:float;
+ beta:float;
+}
+
+enum LSTMKernelType : byte {
+ // Full LSTM kernel which supports peephole and projection.
+ FULL = 0,
+ // Basic LSTM kernels. Equivalent to TensorFlow BasicLSTMCell.
+ BASIC = 1,
+}
+
+// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
+table LSTMOptions {
+ // Parameters for LSTM version 1 or above.
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+
+ // Parameters for LSTM version 2 or above.
+ // Basic kernel is only supported in version 2 or above.
+ kernel_type: LSTMKernelType = FULL;
+}
+
+// An implementation of TensorFlow dynamic_rnn with LSTMCell.
+table UnidirectionalSequenceLSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+
+ // If true then first dimension is sequence, otherwise batch.
+ time_major:bool;
+}
+
+table BidirectionalSequenceLSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+
+ // If true, store the outputs of both directions into the first output.
+ merge_outputs: bool;
+}
+
+table ResizeBilinearOptions {
+ new_height: int (deprecated);
+ new_width: int (deprecated);
+ align_corners: bool;
+}
+
+table ResizeNearestNeighborOptions {
+ align_corners: bool;
+}
+
+// A call operation options
+table CallOptions {
+ // The subgraph index that needs to be called.
+ subgraph:uint;
+}
+
+table PadOptions {
+}
+
+table PadV2Options {
+}
+
+table ReshapeOptions {
+ new_shape:[int];
+}
+
+table SpaceToBatchNDOptions {
+}
+
+table BatchToSpaceNDOptions {
+}
+
+table SkipGramOptions {
+ ngram_size: int;
+ max_skip_size: int;
+ include_all_ngrams: bool;
+}
+
+table SpaceToDepthOptions {
+ block_size: int;
+}
+
+table SubOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DivOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table TopKV2Options {
+}
+
+enum CombinerType : byte {
+ SUM = 0,
+ MEAN = 1,
+ SQRTN = 2,
+}
+
+table EmbeddingLookupSparseOptions {
+ combiner:CombinerType;
+}
+
+table GatherOptions {
+ axis: int;
+}
+
+table TransposeOptions {
+}
+
+table ExpOptions {
+}
+
+table ReducerOptions {
+ keep_dims: bool;
+}
+
+table SqueezeOptions {
+ squeeze_dims:[int];
+}
+
+table SplitOptions {
+ num_splits: int;
+}
+
+table SplitVOptions {
+ num_splits: int;
+}
+
+table StridedSliceOptions {
+ begin_mask: int;
+ end_mask: int;
+ ellipsis_mask: int;
+ new_axis_mask: int;
+ shrink_axis_mask: int;
+}
+
+table LogSoftmaxOptions {
+}
+
+table CastOptions {
+ in_data_type: TensorType;
+ out_data_type: TensorType;
+}
+
+table DequantizeOptions {
+}
+
+table MaximumMinimumOptions {
+}
+
+table TileOptions {
+}
+
+table ArgMaxOptions {
+ output_type : TensorType;
+}
+
+table ArgMinOptions {
+ output_type : TensorType;
+}
+
+table GreaterOptions {
+}
+
+table GreaterEqualOptions {
+}
+
+table LessOptions {
+}
+
+table LessEqualOptions {
+}
+
+table NegOptions {
+}
+
+table SelectOptions {
+}
+
+table SliceOptions {
+}
+
+table TransposeConvOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+}
+
+table ExpandDimsOptions {
+}
+
+table SparseToDenseOptions {
+ validate_indices:bool;
+}
+
+table EqualOptions {
+}
+
+table NotEqualOptions {
+}
+
+table ShapeOptions {
+ // Optional output type of the operation (int32 or int64). Defaults to int32.
+ out_type : TensorType;
+}
+
+table PowOptions {
+}
+
+table FakeQuantOptions {
+ // Parameters supported by version 1:
+ min:float;
+ max:float;
+ num_bits:int;
+
+ // Parameters supported by version 2:
+ narrow_range:bool;
+}
+
+table PackOptions {
+ values_count:int;
+ axis:int;
+}
+
+table LogicalOrOptions {
+}
+
+table OneHotOptions {
+ axis:int;
+}
+
+table AbsOptions {
+}
+
+
+table LogicalAndOptions {
+}
+
+table LogicalNotOptions {
+}
+
+table UnpackOptions {
+ num:int;
+ axis:int;
+}
+
+table FloorDivOptions {
+}
+
+table SquareOptions {
+}
+
+table ZerosLikeOptions {
+}
+
+table FillOptions {
+}
+
+table FloorModOptions {
+}
+
+table RangeOptions {
+}
+
+table LeakyReluOptions {
+ alpha:float;
+}
+
+table SquaredDifferenceOptions {
+}
+
+enum MirrorPadMode : byte {
+ // Doesn't include borders.
+ REFLECT = 0,
+ // Includes borders.
+ SYMMETRIC = 1,
+}
+
+table MirrorPadOptions {
+ mode:MirrorPadMode;
+}
+
+// An OperatorCode can be an enum value (BuiltinOperator) if the operator is a
+// builtin, or a string if the operator is custom.
+table OperatorCode {
+ builtin_code:BuiltinOperator;
+ custom_code:string;
+
+ // The version of the operator. The version need to be bumped whenever new
+ // parameters are introduced into an op.
+ version:int = 1;
+}
+
+enum CustomOptionsFormat : byte {
+ FLEXBUFFERS = 0,
+}
+
+enum DataFormat : byte {
+ // For 2D data, NHWC(batch, height, width, channels)
+ // For 3D data, NDHWC(batch, depth, height, width, channels)
+ CHANNELS_LAST = 0,
+ // For 2D data, NCHW(batch, channels, height, width)
+ // For 3D data, NCDHW(batch, channels, depth, height, width)
+ CHANNELS_FIRST = 1,
+}
+
+// An operator takes tensors as inputs and outputs. The type of operation being
+// performed is determined by an index into the list of valid OperatorCodes,
+// while the specifics of each operations is configured using builtin_options
+// or custom_options.
+table Operator {
+ // Index into the operator_codes array. Using an integer here avoids
+ // complicate map lookups.
+ opcode_index:uint;
+
+ // Optional input and output tensors are indicated by -1.
+ inputs:[int];
+ outputs:[int];
+
+ builtin_options:BuiltinOptions;
+ custom_options:[ubyte];
+ custom_options_format:CustomOptionsFormat;
+
+ // A list of booleans indicating the input tensors which are being mutated by
+ // this operator.(e.g. used by RNN and LSTM).
+ // For example, if the "inputs" array refers to 5 tensors and the second and
+ // fifth are mutable variables, then this list will contain
+ // [false, true, false, false, true].
+ //
+ // If the list is empty, no variable is mutated in this operator.
+ // The list either has the same length as `inputs`, or is empty.
+ mutating_variable_inputs:[bool];
+}
+
+// The root type, defining a subgraph, which typically represents an entire
+// model.
+table SubGraph {
+ // A list of all tensors used in this subgraph.
+ tensors:[Tensor];
+
+ // Indices of the tensors that are inputs into this subgraph. Note this is
+ // the list of non-static tensors that feed into the subgraph for inference.
+ inputs:[int];
+
+ // Indices of the tensors that are outputs out of this subgraph. Note this is
+ // the list of output tensors that are considered the product of the
+ // subgraph's inference.
+ outputs:[int];
+
+ // All operators, in execution order.
+ operators:[Operator];
+
+ // Name of this subgraph (used for debugging).
+ name:string;
+
+ // Data format for input/output of SubGraph
+ data_format: DataFormat
+}
+
+// Table of raw data buffers (used for constant tensors). Referenced by tensors
+// by index. The generous alignment accommodates mmap-friendly data structures.
+table Buffer {
+ data:[ubyte] (force_align: 16);
+}
+
+table Model {
+ // Version of the schema.
+ version:uint;
+
+ // A list of all operator codes used in this model. This is
+ // kept in order because operators carry an index into this
+ // vector.
+ operator_codes:[OperatorCode];
+
+ // All the subgraphs of the model. The 0th is assumed to be the main
+ // model.
+ subgraphs:[SubGraph];
+
+ // A description of the model.
+ description:string;
+
+ // Buffers of the model.
+ // Note the 0th entry of this array must be an empty buffer (sentinel).
+ // This is a convention so that tensors without a buffer can provide 0 as
+ // their buffer.
+ buffers:[Buffer];
+
+ // Metadata about the model. Indirects into the existings buffers list.
+ metadata_buffer:[int];
+}
+
+root_type Model;
projects / platform / core / ml / nnfw.git / commitdiff