add Neural Network as classifier

Author: mkaliberda

src/server/codegen/knowledgepack_model_graph_mixin.py

@@ -614,7 +614,7 @@ def get_classifier_init(self, knowledgepack):
         elif classifier_config["classifier"] in [
             "TF Micro",
             "TensorFlow Lite for Microcontrollers",
-            "Neural Network"
+            "Neural Network",
         ]:
             return {"classifier": "Neural Network"}
 
@@ -1618,5 +1618,7 @@ def get_classifier_type(knowledgepack):
 
     if classifier_type == "tensorflow_lite_for_microcontrollers":
         classifier_type = "tf_micro"
+    if classifier_type == "neural_network":
+        classifier_type = "tf_micro"
 
     return classifier_type

src/server/codegen/model_gen/model_gen.py

@@ -24,7 +24,7 @@
     linear_regression,
     pme,
     tf_micro,
-    nnom
+    nnom,
 )
 from django.core.exceptions import ValidationError
 
@@ -35,12 +35,13 @@
     "bonsai",
     "pme",
     "linear_regression",
-    "nnom"
+    "nnom",
 ]
 
 CLASSIFER_MAP = {
     "decision tree ensemble": "decision_tree_ensemble",
     "tensorflow lite for microcontrollers": "tf_micro",
+    "Neural Network": "tf_micro",
     "nnom": "nnom",
     "pme": "pme",
     "boosted tree ensemble": "boosted_tree_ensemble",
@@ -61,7 +62,7 @@ def get_classifier_type(model_configuration):
     return classifier_type.lower()
 
 
-#TODO: Make this an interface that returns the object instead of having all of these if statements
+# TODO: Make this an interface that returns the object instead of having all of these if statements
 class ModelGen:
     @staticmethod
     def create_classifier_structures(classifier_type, kb_models):
@@ -82,10 +83,10 @@ def create_classifier_structures(classifier_type, kb_models):
 
         if classifier_type == "linear_regression":
             return linear_regression.create_classifier_structures(kb_models)
-        
+
         if classifier_type == "nnom":
             return nnom.create_classifier_structures(kb_models)
-        
+
         return ""
 
     @staticmethod
@@ -107,7 +108,7 @@ def create_max_tmp_parameters(classifier_type, kb_models):
 
         if classifier_type == "linear_regression":
             return linear_regression.create_max_tmp_parameters(kb_models)
-        
+
         if classifier_type == "nnom":
             return nnom.create_max_tmp_parameters(kb_models)
 
@@ -151,7 +152,7 @@ def validate_model_parameters(model_parameters, model_configuration):
 
         if classifier_type == "linear_regression":
             return linear_regression.validate_model_parameters(model_parameters)
-        
+
         if classifier_type == "nnom":
             return nnom.validate_model_parameters(model_parameters)
 
@@ -180,8 +181,7 @@ def validate_model_configuration(model_configuration):
 
         if classifier_type == "linear_regression":
             return linear_regression.validate_model_configuration(model_configuration)
-        
-    
+
         if classifier_type == "nnom":
             return nnom.validate_model_configuration(model_configuration)
 
@@ -204,7 +204,7 @@ def get_output_tensor_size(classifier_type, model):
 
         if classifier_type == "linear_regression":
             return linear_regression.get_output_tensor_size(model)
-        
+
         if classifier_type == "nnom":
             return nnom.get_output_tensor_size(model)
 
@@ -232,7 +232,7 @@ def get_input_feature_type(model):
 
         if classifier_type == "linear_regression":
             return FLOAT
-        
+
         if classifier_type == "nnom":
             return UINT8_T
 
@@ -263,7 +263,7 @@ def get_input_feature_def(model):
 
         if classifier_type == "nnom":
             return UINT8_T
-        
+
         raise ValueError("No classifier type found")
 
     @staticmethod
@@ -273,7 +273,7 @@ def get_model_type(model):
         CLASSIFICATION = 1
         if classifier_type == "tf_micro":
             return CLASSIFICATION
-        
+
         if classifier_type == "nnom":
             return CLASSIFICATION
 

src/server/library/core_functions/mg_contracts.py

@@ -1274,6 +1274,23 @@ def tensorflow_micro():
 tensorflow_micro_contracts = {"input_contract": [], "output_contract": []}
 
 
+def neural_network():
+    """
+    The Neural Network uses Tensorflow Lite for Microcontrollers, an inference engine
+    from Google optimized run machine learning models on embedded devices.
+
+    Tensorflow Lite for Microcontrollers supports a subset of all Tensorflow functions. For a full
+    list see `all_ops_resolver.cc <https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/micro/all_ops_resolver.cc>`_.
+
+    For additional documentation on Tensorflow Lite for Microcontrollers see `here <https://www.tensorflow.org/lite/microcontrollers>`_.
+    """
+
+    return None
+
+
+neural_network_contracts = {"input_contract": [], "output_contract": []}
+
+
 def load_model_tensorflow_micro(
     input_data,
     label_column,
@@ -1433,7 +1450,9 @@ def load_model_tensorflow_micro(
         "type": "list",
         "element_type": "str",
         "handle_by_set": True,
-        "options": [{"name": "TensorFlow Lite for Microcontrollers"}],
+        "options": [
+            {"name": "TensorFlow Lite for Microcontrollers", "name": "Neural Network"}
+        ],
     },
     {"name": "class_map", "type": "dict", "handle_by_set": True, "default": None},
     {

src/server/library/fixtures/functions_prod.yml

@@ -831,6 +831,23 @@
     automl_available: False
   model: library.transform
 
+- fields:
+    core: True
+    name: Neural Network
+    version: 1
+    type: Classifier
+    subtype: NN
+    path: core_functions/mg_contracts.py
+    function_in_file: neural_network
+    has_c_version: False
+    c_file_name:
+    c_function_name:
+    deprecated: False
+    dcl_executable: False
+    uuid: 3994d48f-7b8a-4807-b919-284bbe045928
+    automl_available: False
+  model: library.transform
+
 - fields:
     core: True
     name: Load Model TensorFlow Lite for Microcontrollers

src/server/library/fixtures/parameter_inventory.yml

@@ -322,3 +322,16 @@
     binary_classifiers: 0
     allow_unknown: 1
   model: library.parameterinventory
+
+- fields:
+    uuid: e040c660-45c2-4e48-92fc-2a22310076c9
+    function: 3994d48f-7b8a-4807-b919-284bbe045928
+    function_name: Neural Network
+    pipeline_key: classifiers
+    variable_name: null
+    variable_type: null
+    variable_values: null
+    classifiers_optimizers_group: 4
+    binary_classifiers: 0
+    allow_unknown: 1
+  model: library.parameterinventory

src/server/library/fixtures/pipeline_schema.json

@@ -312,7 +312,8 @@
         "TransformList": null,
         "Set": false,
         "Exclude": [
-            "TF Micro"
+            "TF Micro",
+            "TensorFlow Lite for Microcontrollers"
         ],
         "Limit": 1
     },