From: Dmitry Mozolev/SRR-AI Tools Lab/./삼성전자 <d.mozolev@samsung.com>
Date: Tue, 22 May 2018 23:00:59 +0000 (+0300)
Subject: Add TFLite v3 format parser (#169)
X-Git-Tag: nncc_backup~2681
X-Git-Url: http://review.tizen.org/git/?a=commitdiff_plain;h=4377d0f845aedd687e8172cacf15de94b8be6783;p=platform%2Fcore%2Fml%2Fnnfw.git

Add TFLite v3 format parser (#169)

* Add TFLite v3 format parser

Just using flatbuffers library to get access
to the handle for .tflite version 3 model contents.

Signed-off-by: Dmitry Mozolev <d.mozolev@samsung.com>

* Add meta info about flatbuffers schemas

Signed-off-by: Dmitry Mozolev <d.mozolev@samsung.com>
---

diff --git a/contrib/nnc/libs/frontend/CMakeLists.txt b/contrib/nnc/libs/frontend/CMakeLists.txt
index 672e864..62c171a 100644
--- a/contrib/nnc/libs/frontend/CMakeLists.txt
+++ b/contrib/nnc/libs/frontend/CMakeLists.txt
@@ -10,3 +10,5 @@ add_library(${nn_import_common} STATIC ${common_sources} ${common_headers})
 
 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)
diff --git a/contrib/nnc/libs/frontend/tflite/CMakeLists.txt b/contrib/nnc/libs/frontend/tflite/CMakeLists.txt
new file mode 100644
index 0000000..4f2a39f
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/CMakeLists.txt
@@ -0,0 +1,40 @@
+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})
diff --git a/contrib/nnc/libs/frontend/tflite/examples/sanity_check.cpp b/contrib/nnc/libs/frontend/tflite/examples/sanity_check.cpp
new file mode 100644
index 0000000..a92e794
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/examples/sanity_check.cpp
@@ -0,0 +1,31 @@
+#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;
+}
diff --git a/contrib/nnc/libs/frontend/tflite/include/tflite_importer.h b/contrib/nnc/libs/frontend/tflite/include/tflite_importer.h
new file mode 100644
index 0000000..89e2f8b
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/include/tflite_importer.h
@@ -0,0 +1,45 @@
+#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
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema.fbs b/contrib/nnc/libs/frontend/tflite/schema/schema.fbs
new file mode 100644
index 0000000..7d2e00f
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema.fbs
@@ -0,0 +1,466 @@
+// 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;
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema.meta b/contrib/nnc/libs/frontend/tflite/schema/schema.meta
new file mode 100644
index 0000000..74668ab
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema.meta
@@ -0,0 +1,2 @@
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v0.fbs b/contrib/nnc/libs/frontend/tflite/schema/schema_v0.fbs
new file mode 100644
index 0000000..852ea98
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v0.fbs
@@ -0,0 +1,247 @@
+// 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;
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v0.meta b/contrib/nnc/libs/frontend/tflite/schema/schema_v0.meta
new file mode 100644
index 0000000..74668ab
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v0.meta
@@ -0,0 +1,2 @@
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v1.fbs b/contrib/nnc/libs/frontend/tflite/schema/schema_v1.fbs
new file mode 100644
index 0000000..06cd940
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v1.fbs
@@ -0,0 +1,295 @@
+// 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;
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v1.meta b/contrib/nnc/libs/frontend/tflite/schema/schema_v1.meta
new file mode 100644
index 0000000..74668ab
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v1.meta
@@ -0,0 +1,2 @@
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v2.fbs b/contrib/nnc/libs/frontend/tflite/schema/schema_v2.fbs
new file mode 100644
index 0000000..96731c8
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v2.fbs
@@ -0,0 +1,303 @@
+// 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;
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v2.meta b/contrib/nnc/libs/frontend/tflite/schema/schema_v2.meta
new file mode 100644
index 0000000..74668ab
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v2.meta
@@ -0,0 +1,2 @@
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v3.fbs b/contrib/nnc/libs/frontend/tflite/schema/schema_v3.fbs
new file mode 100644
index 0000000..cedefe0
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v3.fbs
@@ -0,0 +1,326 @@
+// 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;
diff --git a/contrib/nnc/libs/frontend/tflite/schema/schema_v3.meta b/contrib/nnc/libs/frontend/tflite/schema/schema_v3.meta
new file mode 100644
index 0000000..74668ab
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/schema/schema_v3.meta
@@ -0,0 +1,2 @@
+REPO=https://github.com/tensorflow/tensorflow.git
+COMMIT=c7a04561fb8
diff --git a/contrib/nnc/libs/frontend/tflite/src/tflite_importer.cpp b/contrib/nnc/libs/frontend/tflite/src/tflite_importer.cpp
new file mode 100644
index 0000000..dbe2122
--- /dev/null
+++ b/contrib/nnc/libs/frontend/tflite/src/tflite_importer.cpp
@@ -0,0 +1,64 @@
+#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