Add 'single_index' (#162)

* Add 'single_index' 

Using the same convention as `single_lookup`, I.E:
    - Assumes Tensor needs expanding prior to predict. 
    - Same Method name notation

* Update `single_index` to `index_single`

* Added unit test for `index_single`

Co-authored-by: owenvallis <owensvallis@gmail.com>

tensorflow_similarity/models/similarity_model.py

@@ -247,6 +247,45 @@ def index(self,
                               build=build,
                               verbose=verbose)
 
+    def index_single(self,
+                     x: Tensor,
+                     y: IntTensor = None,
+                     data: Optional[Tensor] = None,
+                     build: bool = True,
+                     verbose: int = 1):
+        """Index data.
+
+        Args:
+            x: Sample to index.
+
+            y: class id associated with the data if any. Defaults to None.
+
+            data: store the data associated with the samples in the key
+            value store. Defaults to None.
+
+            build: Rebuild the index after indexing. This is needed to make the
+            new samples searchable. Set it to false to save processing time
+            when calling indexing repeatidly without the need to search between
+            the indexing requests. Defaults to True.
+
+            verbose: Output indexing progress info. Defaults to 1.
+        """
+
+        if not self._index:
+            raise Exception('You need to compile the model with a valid'
+                            'distance to be able to use the indexing')
+        if verbose:
+            print('[Indexing 1 point]')
+            print('|-Computing embeddings')
+
+        x = tf.expand_dims(x, axis=0)
+        prediction = self.predict(x)
+        self._index.add(prediction=prediction,
+                        label=y,
+                        data=data,
+                        build=build,
+                        verbose=verbose)
+
     def lookup(self,
                x: Tensor,
                k: int = 5,

tests/test_model.py

@@ -32,3 +32,19 @@ def test_save_no_compile(tmp_path):
     model.save(tmp_path)
     model2 = tf.keras.models.load_model(tmp_path)
     assert isinstance(model2, type(model))
+
+
+def test_index_single():
+    """Unit Test for #161 & #162"""
+    inputs = tf.keras.layers.Input(shape=(3,))
+    outputs = tf.keras.layers.Dense(2)(inputs)
+    model = SimilarityModel(inputs, outputs)
+    model.compile(optimizer='adam', loss=TripletLoss())
+
+    # index data
+    x = tf.constant([1, 1, 3], dtype='float32')
+    y = tf.constant([1])
+
+    # run individual sample & index
+    model.index_single(x, y, data=x)
+    assert model._index.size() == 1