target_include_directories(${nn_import_common} PUBLIC ${CMAKE_CURRENT_SOURCE_DIR}/include)
set_target_properties(${nn_import_common} PROPERTIES POSITION_INDEPENDENT_CODE ON)
+
+add_subdirectory(tflite)
--- /dev/null
+nncc_find_package(FlatBuffers OPTIONAL)
+
+# Compile flatbuffers schemas
+# Produces FB_GEN_SOURCES and FB_GEN_INCLUDE_DIRS variables
+set(GENERATED_OUTPUT_DIR "${CMAKE_CURRENT_BINARY_DIR}/generated")
+FlatBuffers_Generate(FB_GEN
+ ${GENERATED_OUTPUT_DIR}
+ ${CMAKE_CURRENT_SOURCE_DIR}/schema
+ schema_v3.fbs)
+
+###################
+# TFLITE importer #
+###################
+
+file(GLOB tflite_importer_sources src/*)
+file(GLOB tflite_importer_headers include/*.h)
+list(APPEND tflite_importer_headers ${FB_GEN_SOURCES})
+
+set(tflite_import tflite_import)
+add_library(${tflite_import} SHARED ${tflite_importer_sources} ${tflite_importer_headers})
+
+target_include_directories(${tflite_import} PRIVATE ${FB_GEN_INCLUDE_DIRS})
+target_include_directories(${tflite_import} PRIVATE include)
+
+target_link_libraries(${tflite_import} flatbuffers)
+target_link_libraries(${tflite_import} ${nn_import_common})
+
+###################
+# TFLITE examples #
+###################
+
+file(GLOB tflite_example_sources examples/*)
+
+set(tflite_import_example tflite_import_example)
+add_executable(${tflite_import_example} ${tflite_example_sources})
+
+target_include_directories(${tflite_import_example} PRIVATE ${FB_GEN_INCLUDE_DIRS})
+target_include_directories(${tflite_import_example} PRIVATE include)
+
+target_link_libraries(${tflite_import_example} ${tflite_import})
--- /dev/null
+#include <iostream>
+
+#include "tflite_importer.h"
+
+int main(int argc, char **argv)
+{
+ std::string modelName;
+ if (argc > 1)
+ {
+ modelName = argv[1];
+ }
+ else
+ {
+ modelName = "mobilenet_v1.0.tflite";
+ }
+
+ nncc::contrib::frontend::tflite::TfliteImporter importer{modelName};
+
+ bool success = importer.import();
+
+ if (success)
+ {
+ importer.dump();
+ }
+ else
+ {
+ std::cout << "Could not load model \"" << modelName << "\"" << std::endl;
+ }
+
+ return 0;
+}
--- /dev/null
+#ifndef NNCC_TFLITE_IMPORTER_H
+#define NNCC_TFLITE_IMPORTER_H
+
+#include <memory>
+
+#include "schema_v3_generated.h"
+
+#include "nn_importer.h"
+#include "model_allocation.h"
+
+namespace nncc
+{
+namespace contrib
+{
+namespace frontend
+{
+namespace tflite
+{
+
+using namespace nncc::contrib::frontend::common;
+using namespace ::tflite;
+
+class TfliteImporter : NNImporter
+{
+public:
+ explicit TfliteImporter(std::string filename);
+
+ bool import() override;
+ void *createIR() override;
+ void dump() override;
+
+ bool importUnpacked();
+
+protected:
+ std::unique_ptr<ModelAllocation> modelRaw;
+ std::unique_ptr<ModelT> model;
+ const Model *modelPacked;
+};
+
+} // namespace tflite
+} // namespace frontend
+} // namespace contrib
+} // namespace nncc
+
+#endif // NNCC_TFLITE_IMPORTER_H
--- /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";
+
+// The type of data stored in a tensor.
+enum TensorType : byte {
+ FLOAT32 = 0,
+ FLOAT16 = 1,
+ INT32 = 2,
+ UINT8 = 3,
+ INT64 = 4,
+ STRING = 5,
+}
+
+// Parameters for converting a quantized tensor back to float. Given a
+// quantized value q, the corresponding float value f should be:
+// f = scale * (q - zero_point)
+table QuantizationParameters {
+ min:[float]; // For importing back into tensorflow.
+ max:[float]; // For importing back into tensorflow.
+ scale:[float];
+ zero_point:[long];
+}
+
+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.
+}
+
+// A list of builtin operators. Builtin operators a slighlty 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,
+}
+
+// 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,
+ MeanOptions,
+ SubOptions,
+ DivOptions,
+ SqueezeOptions,
+ SequenceRNNOptions,
+ StridedSliceOptions,
+ ExpOptions,
+ TopKV2Options,
+ SplitOptions,
+ LogSoftmaxOptions,
+ CastOptions,
+ DequantizeOptions,
+ MaximumOptions,
+}
+
+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;
+}
+
+table Pool2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ filter_width:int;
+ filter_height:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DepthwiseConv2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ depth_multiplier:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+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;
+}
+
+// An implementation of TensorFlow fully_connected (a.k.a Dense) layer.
+table FullyConnectedOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+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;
+}
+
+// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
+table LSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+}
+
+table ResizeBilinearOptions {
+ new_height: int (deprecated);
+ new_width: int (deprecated);
+ align_corners: bool;
+}
+
+// A call operation options
+table CallOptions {
+ // The subgraph index that needs to be called.
+ subgraph:uint;
+}
+
+table PadOptions {
+}
+
+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 MeanOptions {
+ keep_dims: bool;
+}
+
+table SqueezeOptions {
+ squeeze_dims:[int];
+}
+
+table SplitOptions {
+ 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 {
+}
+
+table DequantizeOptions {
+}
+
+table MaximumOptions {
+}
+
+// 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;
+}
+
+enum CustomOptionsFormat : byte {
+ FLEXBUFFERS = 0,
+}
+
+// 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;
+}
+
+// The root type, defining a model.
+table SubGraph {
+ // A list of all tensors used in this model.
+ tensors:[Tensor];
+
+ // Indices of the input tensors.
+ inputs:[int];
+
+ // Indices of the output tensors.
+ outputs:[int];
+
+ // All operators, in execution order.
+ operators:[Operator];
+
+ // Name of subgraph (used for debugging).
+ name:string;
+}
+
+// Table of raw data buffers (used for constant tensors). Referenced by tensors
+// by index.
+table Buffer {
+ data:[ubyte];
+}
+
+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
+ buffers:[Buffer];
+
+}
+
+root_type Model;
--- /dev/null
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
--- /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.
+
+namespace tflite;
+
+// The type of data stored in a tensor.
+enum TensorType : byte {
+ FLOAT32 = 0,
+ FLOAT16 = 1,
+ INT32 = 2,
+ UINT8 = 3,
+ INT64 = 4,
+}
+
+// Parameters for converting a quantized tensor back to float. Given a
+// quantized value q, the corresponding float value f should be:
+// f = scale * (q - zero_point)
+table QuantizationParameters {
+ min:[float]; // For importing back into tensorflow.
+ max:[float]; // For importing back into tensorflow.
+ scale:[float];
+ zero_point:[long];
+}
+
+table Tensor {
+ // The tensor shape. The meaning of each entry is operator-specific but
+ // builtin ops use: [batch size, number of channels, height, width] (That's
+ // Tensorflow's NCHW).
+ shape:[int];
+ type:TensorType;
+ // The data_buffer 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*4*3 + j*3 + k].
+ data_buffer:[ubyte];
+ name:string; // For debugging and importing back into tensorflow.
+ quantization:QuantizationParameters; // Optional.
+}
+
+// A list of builtin operators. Builtin operators a slighlty 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 {
+ CUSTOM = 0,
+ CONVOLUTION = 1,
+ DEPTHWISE_CONVOLUTION = 2,
+ CONCAT_EMBEDDINGS = 3,
+ LSH_PROJECTION = 4,
+ TANH = 5,
+ RELU = 6,
+ AVERAGE_POOL = 7,
+ MAX_POOL = 8,
+ L2_POOL = 9,
+ SIGMOID = 10,
+ SVDF = 11,
+ BasicRNN = 12,
+ RELU6 = 13,
+ EMBEDDING_LOOKUP = 14,
+ FULLY_CONNECTED = 15,
+ HASHTABLE_LOOKUP = 16,
+ SOFTMAX = 17,
+ CONCATENATION = 18,
+ LSTM = 19,
+ ADD = 20,
+ L2NORM = 21,
+ LOCAL_RESPONSE_NORM = 22,
+ RESIZE_BILINEAR = 23,
+}
+
+// Options for the builtin operators.
+union BuiltinOptions {
+ ConvolutionOptions,
+ DepthwiseConvolutionOptions,
+ ConcatEmbeddingsOptions,
+ LSHProjectionOptions,
+ PoolOptions,
+ SVDFOptions,
+ BasicRNNOptions,
+ FullyConnectedOptions,
+ SoftmaxOptions,
+ ConcatenationOptions,
+ AddOptions,
+ L2NormOptions,
+ LocalResponseNormOptions,
+ LSTMOptions,
+ ResizeBilinearOptions,
+}
+
+enum Padding : byte { SAME, VALID }
+
+enum ActivationFunctionType : byte {
+ NONE = 0,
+ RELU = 1,
+ RELU1 = 2,
+ RELU6 = 3,
+ TANH = 4,
+ SIGN_BIT = 5,
+}
+
+table ConvolutionOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table PoolOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ filter_width:int;
+ filter_height:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DepthwiseConvolutionOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ depth_multiplier:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+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 BasicRNNCell.
+table BasicRNNOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+// An implementation of TensorFlow fully_connected (a.k.a Dense) layer.
+table FullyConnectedOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table SoftmaxOptions {
+ beta: float;
+}
+
+// An implementation of TensorFlow concat.
+table ConcatenationOptions {
+ axis:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table AddOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table L2NormOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table LocalResponseNormOptions {
+ radius:int;
+ bias:float;
+ alpha:float;
+ beta:float;
+}
+
+// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
+table LSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+}
+
+table ResizeBilinearOptions {
+ new_height:int;
+ new_width:int;
+}
+
+// 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;
+}
+
+// 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:int;
+
+ inputs:[int];
+ outputs:[int];
+
+ builtin_options:BuiltinOptions;
+ custom_options:[ubyte];
+}
+
+// The root type, defining a model.
+table Model {
+ // A list of all tensors used in this model.
+ tensors:[Tensor];
+
+ // Indices of the input tensors.
+ inputs:[int];
+
+ // Indices of the output tensors.
+ outputs:[int];
+
+ // 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 operators, in execution order.
+ operators:[Operator];
+}
+
+root_type Model;
--- /dev/null
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
--- /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.
+
+namespace tflite;
+
+// The type of data stored in a tensor.
+enum TensorType : byte {
+ FLOAT32 = 0,
+ FLOAT16 = 1,
+ INT32 = 2,
+ UINT8 = 3,
+ INT64 = 4,
+ STRING = 5,
+}
+
+// Parameters for converting a quantized tensor back to float. Given a
+// quantized value q, the corresponding float value f should be:
+// f = scale * (q - zero_point)
+table QuantizationParameters {
+ min:[float]; // For importing back into tensorflow.
+ max:[float]; // For importing back into tensorflow.
+ scale:[float];
+ zero_point:[long];
+}
+
+table Tensor {
+ // The tensor shape. The meaning of each entry is operator-specific but
+ // builtin ops use: [batch size, number of channels, height, width] (That's
+ // Tensorflow's NCHW).
+ shape:[int];
+ type:TensorType;
+ // The data_buffer 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*3 + k].
+ data_buffer:[ubyte];
+ name:string; // For debugging and importing back into tensorflow.
+ quantization:QuantizationParameters; // Optional.
+}
+
+// A list of builtin operators. Builtin operators a slighlty 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 {
+ CUSTOM = 0,
+ CONVOLUTION = 1,
+ DEPTHWISE_CONVOLUTION = 2,
+ CONCAT_EMBEDDINGS = 3,
+ LSH_PROJECTION = 4,
+ TANH = 5,
+ RELU = 6,
+ AVERAGE_POOL = 7,
+ MAX_POOL = 8,
+ L2_POOL = 9,
+ SIGMOID = 10,
+ SVDF = 11,
+ BasicRNN = 12,
+ RELU6 = 13,
+ EMBEDDING_LOOKUP = 14,
+ FULLY_CONNECTED = 15,
+ HASHTABLE_LOOKUP = 16,
+ SOFTMAX = 17,
+ CONCATENATION = 18,
+ LSTM = 19,
+ ADD = 20,
+ L2NORM = 21,
+ LOCAL_RESPONSE_NORM = 22,
+ RESIZE_BILINEAR = 23,
+ CALL = 24,
+ RESHAPE = 25,
+ SKIP_GRAM = 26,
+ SPACE_TO_DEPTH = 27,
+}
+
+// Options for the builtin operators.
+union BuiltinOptions {
+ ConvolutionOptions,
+ DepthwiseConvolutionOptions,
+ ConcatEmbeddingsOptions,
+ LSHProjectionOptions,
+ PoolOptions,
+ SVDFOptions,
+ BasicRNNOptions,
+ FullyConnectedOptions,
+ SoftmaxOptions,
+ ConcatenationOptions,
+ AddOptions,
+ L2NormOptions,
+ LocalResponseNormOptions,
+ LSTMOptions,
+ ResizeBilinearOptions,
+ CallOptions,
+ ReshapeOptions,
+ SkipGramOptions,
+ SpaceToDepthOptions,
+}
+
+enum Padding : byte { SAME, VALID }
+
+enum ActivationFunctionType : byte {
+ NONE = 0,
+ RELU = 1,
+ RELU1 = 2,
+ RELU6 = 3,
+ TANH = 4,
+ SIGN_BIT = 5,
+}
+
+table ConvolutionOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table PoolOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ filter_width:int;
+ filter_height:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DepthwiseConvolutionOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ depth_multiplier:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+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 BasicRNNCell.
+table BasicRNNOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+// An implementation of TensorFlow fully_connected (a.k.a Dense) layer.
+table FullyConnectedOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table SoftmaxOptions {
+ beta: float;
+}
+
+// An implementation of TensorFlow concat.
+table ConcatenationOptions {
+ axis:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table AddOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table L2NormOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table LocalResponseNormOptions {
+ radius:int;
+ bias:float;
+ alpha:float;
+ beta:float;
+}
+
+// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
+table LSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+}
+
+table ResizeBilinearOptions {
+ new_height:int;
+ new_width:int;
+}
+
+// A call operation options
+table CallOptions {
+ // The subgraph index that needs to be called.
+ subgraph:int;
+}
+
+table ReshapeOptions {
+ new_shape:[int];
+}
+
+table SkipGramOptions {
+ ngram_size: int;
+ max_skip_size: int;
+ include_all_ngrams: bool;
+}
+
+table SpaceToDepthOptions {
+ block_size: int;
+}
+
+// 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;
+}
+
+// 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:int;
+
+ inputs:[int];
+ outputs:[int];
+
+ builtin_options:BuiltinOptions;
+ custom_options:[ubyte];
+}
+
+// The root type, defining a model.
+table SubGraph {
+ // A list of all tensors used in this model.
+ tensors:[Tensor];
+
+ // Indices of the input tensors.
+ inputs:[int];
+
+ // Indices of the output tensors.
+ outputs:[int];
+
+ // All operators, in execution order.
+ operators:[Operator];
+
+ // Name of subgraph (used for debugging).
+ name:string;
+}
+
+table Model {
+ // Version of the schema.
+ version:int;
+
+ // 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;
+}
+
+root_type Model;
--- /dev/null
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
--- /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.
+
+namespace tflite;
+
+// The type of data stored in a tensor.
+enum TensorType : byte {
+ FLOAT32 = 0,
+ FLOAT16 = 1,
+ INT32 = 2,
+ UINT8 = 3,
+ INT64 = 4,
+ STRING = 5,
+}
+
+// Parameters for converting a quantized tensor back to float. Given a
+// quantized value q, the corresponding float value f should be:
+// f = scale * (q - zero_point)
+table QuantizationParameters {
+ min:[float]; // For importing back into tensorflow.
+ max:[float]; // For importing back into tensorflow.
+ scale:[float];
+ zero_point:[long];
+}
+
+table Tensor {
+ // The tensor shape. The meaning of each entry is operator-specific but
+ // builtin ops use: [batch size, number of channels, height, width] (That's
+ // Tensorflow's NCHW).
+ shape:[int];
+ type:TensorType;
+ // The data_buffer 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*3 + k].
+ data_buffer:[ubyte];
+ name:string; // For debugging and importing back into tensorflow.
+ quantization:QuantizationParameters; // Optional.
+}
+
+// A list of builtin operators. Builtin operators a slighlty 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,
+ // RELU1=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,
+
+}
+
+// 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,
+}
+
+enum Padding : byte { SAME, VALID }
+
+enum ActivationFunctionType : byte {
+ NONE = 0,
+ RELU = 1,
+ RELU1 = 2,
+ RELU6 = 3,
+ TANH = 4,
+ SIGN_BIT = 5,
+}
+
+table Conv2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table Pool2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ filter_width:int;
+ filter_height:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DepthwiseConv2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ depth_multiplier:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+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 fully_connected (a.k.a Dense) layer.
+table FullyConnectedOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table SoftmaxOptions {
+ beta: float;
+}
+
+// An implementation of TensorFlow concat.
+table ConcatenationOptions {
+ axis:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table AddOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table L2NormOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table LocalResponseNormalizationOptions {
+ radius:int;
+ bias:float;
+ alpha:float;
+ beta:float;
+}
+
+// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
+table LSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+}
+
+table ResizeBilinearOptions {
+ new_height:int;
+ new_width:int;
+}
+
+// A call operation options
+table CallOptions {
+ // The subgraph index that needs to be called.
+ subgraph:int;
+}
+
+table ReshapeOptions {
+ new_shape:[int];
+}
+
+table SkipGramOptions {
+ ngram_size: int;
+ max_skip_size: int;
+ include_all_ngrams: bool;
+}
+
+table SpaceToDepthOptions {
+ block_size: int;
+}
+
+// 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;
+}
+
+// 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:int;
+
+ inputs:[int];
+ outputs:[int];
+
+ builtin_options:BuiltinOptions;
+ custom_options:[ubyte];
+}
+
+// The root type, defining a model.
+table SubGraph {
+ // A list of all tensors used in this model.
+ tensors:[Tensor];
+
+ // Indices of the input tensors.
+ inputs:[int];
+
+ // Indices of the output tensors.
+ outputs:[int];
+
+ // All operators, in execution order.
+ operators:[Operator];
+
+ // Name of subgraph (used for debugging).
+ name:string;
+}
+
+table Model {
+ // Version of the schema.
+ version:int;
+
+ // 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;
+}
+
+root_type Model;
--- /dev/null
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
--- /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 (4).
+file_identifier "TFL3";
+// File extension of any written files.
+file_extension "tflite";
+
+// The type of data stored in a tensor.
+enum TensorType : byte {
+ FLOAT32 = 0,
+ FLOAT16 = 1,
+ INT32 = 2,
+ UINT8 = 3,
+ INT64 = 4,
+ STRING = 5,
+}
+
+// Parameters for converting a quantized tensor back to float. Given a
+// quantized value q, the corresponding float value f should be:
+// f = scale * (q - zero_point)
+table QuantizationParameters {
+ min:[float]; // For importing back into tensorflow.
+ max:[float]; // For importing back into tensorflow.
+ scale:[float];
+ zero_point:[long];
+}
+
+table Tensor {
+ // The tensor shape. The meaning of each entry is operator-specific but
+ // builtin ops use: [batch size, number of channels, height, width] (That's
+ // Tensorflow's NCHW).
+ 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 existant 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*3 + k].
+ buffer:uint;
+ name:string; // For debugging and importing back into tensorflow.
+ quantization:QuantizationParameters; // Optional.
+}
+
+// A list of builtin operators. Builtin operators a slighlty 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,
+ // RELU1=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,
+
+}
+
+// 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,
+}
+
+enum Padding : byte { SAME, VALID }
+
+enum ActivationFunctionType : byte {
+ NONE = 0,
+ RELU = 1,
+ RELU1 = 2,
+ RELU6 = 3,
+ TANH = 4,
+ SIGN_BIT = 5,
+}
+
+table Conv2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table Pool2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ filter_width:int;
+ filter_height:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table DepthwiseConv2DOptions {
+ padding:Padding;
+ stride_w:int;
+ stride_h:int;
+ depth_multiplier:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+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 fully_connected (a.k.a Dense) layer.
+table FullyConnectedOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table SoftmaxOptions {
+ beta: float;
+}
+
+// An implementation of TensorFlow concat.
+table ConcatenationOptions {
+ axis:int;
+ fused_activation_function:ActivationFunctionType;
+}
+
+table AddOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table L2NormOptions {
+ fused_activation_function:ActivationFunctionType;
+}
+
+table LocalResponseNormalizationOptions {
+ radius:int;
+ bias:float;
+ alpha:float;
+ beta:float;
+}
+
+// An implementation of TensorFlow LSTMCell and CoupledInputForgetGateLSTMCell
+table LSTMOptions {
+ fused_activation_function:ActivationFunctionType;
+ cell_clip: float; // Optional, 0.0 means no clipping
+ proj_clip: float; // Optional, 0.0 means no clipping
+}
+
+table ResizeBilinearOptions {
+ new_height:int;
+ new_width:int;
+}
+
+// A call operation options
+table CallOptions {
+ // The subgraph index that needs to be called.
+ subgraph:uint;
+}
+
+table ReshapeOptions {
+ new_shape:[int];
+}
+
+table SkipGramOptions {
+ ngram_size: int;
+ max_skip_size: int;
+ include_all_ngrams: bool;
+}
+
+table SpaceToDepthOptions {
+ block_size: int;
+}
+
+// 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;
+}
+
+// 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;
+
+ inputs:[int];
+ outputs:[int];
+
+ builtin_options:BuiltinOptions;
+ custom_options:[ubyte];
+}
+
+// The root type, defining a model.
+table SubGraph {
+ // A list of all tensors used in this model.
+ tensors:[Tensor];
+
+ // Indices of the input tensors.
+ inputs:[int];
+
+ // Indices of the output tensors.
+ outputs:[int];
+
+ // All operators, in execution order.
+ operators:[Operator];
+
+ // Name of subgraph (used for debugging).
+ name:string;
+}
+
+// Table of raw data buffers (used for constant tensors). Referenced by tensors
+// by index.
+table Buffer {
+ data:[ubyte];
+}
+
+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: It is required that the first entry in here is always an empty
+ // buffer. This is so that the default buffer index of zero in Tensor
+ // will always refer to a valid empty buffer.
+ buffers:[Buffer];
+
+}
+
+root_type Model;
--- /dev/null
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
--- /dev/null
+#include "tflite_importer.h"
+
+namespace nncc
+{
+namespace contrib
+{
+namespace frontend
+{
+namespace tflite
+{
+
+TfliteImporter::TfliteImporter(std::string filename)
+{
+ modelRaw.reset(new ModelAllocation{std::move(filename)});
+}
+
+bool TfliteImporter::importUnpacked()
+{
+ bool importSuccess = import();
+
+ if (importSuccess)
+ {
+ model.reset(modelPacked->UnPack());
+ }
+
+ return importSuccess;
+}
+
+bool TfliteImporter::import()
+{
+ const void *modelBuffer = modelRaw->getDataPnt();
+
+ if (!modelBuffer)
+ {
+ return false;
+ }
+
+ auto verifier = flatbuffers::Verifier(reinterpret_cast<const uint8_t *>(modelBuffer),
+ modelRaw->getNumBytes());
+
+ bool importSuccess = VerifyModelBuffer(verifier);
+ if (importSuccess)
+ {
+ modelPacked = GetModel(modelRaw->getDataPnt());
+ }
+
+ return importSuccess;
+}
+
+void *TfliteImporter::createIR()
+{
+ // TODO: implement
+ return nullptr;
+}
+
+void TfliteImporter::dump()
+{
+ // TODO: implement
+}
+
+} // namespace tflite
+} // namespace frontend
+} // namespace contrib
+} // namespace nncc
projects / platform / core / ml / nnfw.git / commitdiff