MLIA-607 Update documentation and comments

Use "TensorFlow Lite" instead of "TFLite" in
documentation and comments

Change-Id: Ie4450d72fb2e5261d152d72ab8bd94c3da914c46

3 files changed, 18 insertions, 18 deletions

diff --git a/src/mlia/nn/tensorflow/config.py b/src/mlia/nn/tensorflow/config.py
index 6ee32e7..03d1d0f 100644
--- a/src/mlia/nn/tensorflow/config.py
+++ b/src/mlia/nn/tensorflow/config.py
@@ -31,7 +31,7 @@ class ModelConfiguration:
     def convert_to_tflite(
         self, tflite_model_path: str | Path, quantized: bool = False
     ) -> TFLiteModel:
-        """Convert model to TFLite format."""
+        """Convert model to TensorFlow Lite format."""
         raise NotImplementedError()
 
     def convert_to_keras(self, keras_model_path: str | Path) -> KerasModel:
@@ -52,8 +52,8 @@ class KerasModel(ModelConfiguration):
     def convert_to_tflite(
         self, tflite_model_path: str | Path, quantized: bool = False
     ) -> TFLiteModel:
-        """Convert model to TFLite format."""
-        logger.info("Converting Keras to TFLite ...")
+        """Convert model to TensorFlow Lite format."""
+        logger.info("Converting Keras to TensorFlow Lite ...")
 
         converted_model = convert_to_tflite(self.get_keras_model(), quantized)
         logger.info("Done\n")
@@ -71,7 +71,7 @@ class KerasModel(ModelConfiguration):
 
 
 class TFLiteModel(ModelConfiguration):  # pylint: disable=abstract-method
-    """TFLite model configuration."""
+    """TensorFlow Lite model configuration."""
 
     def input_details(self) -> list[dict]:
         """Get model's input details."""
@@ -81,7 +81,7 @@ class TFLiteModel(ModelConfiguration):  # pylint: disable=abstract-method
     def convert_to_tflite(
         self, tflite_model_path: str | Path, quantized: bool = False
     ) -> TFLiteModel:
-        """Convert model to TFLite format."""
+        """Convert model to TensorFlow Lite format."""
         return self
 
 
@@ -94,7 +94,7 @@ class TfModel(ModelConfiguration):  # pylint: disable=abstract-method
     def convert_to_tflite(
         self, tflite_model_path: str | Path, quantized: bool = False
     ) -> TFLiteModel:
-        """Convert model to TFLite format."""
+        """Convert model to TensorFlow Lite format."""
         converted_model = convert_tf_to_tflite(self.model_path, quantized)
         save_tflite_model(converted_model, tflite_model_path)
 
@@ -114,12 +114,12 @@ def get_model(model: str | Path) -> ModelConfiguration:
 
     raise Exception(
         "The input model format is not supported"
-        "(supported formats: TFLite, Keras, TensorFlow saved model)!"
+        "(supported formats: TensorFlow Lite, Keras, TensorFlow saved model)!"
     )
 
 
 def get_tflite_model(model: str | Path, ctx: Context) -> TFLiteModel:
-    """Convert input model to TFLite and returns TFLiteModel object."""
+    """Convert input model to TensorFlow Lite and returns TFLiteModel object."""
     tflite_model_path = ctx.get_model_path("converted_model.tflite")
     converted_model = get_model(model)
 
diff --git a/src/mlia/nn/tensorflow/tflite_metrics.py b/src/mlia/nn/tensorflow/tflite_metrics.py
index 0af7500..d7ae2a4 100644
--- a/src/mlia/nn/tensorflow/tflite_metrics.py
+++ b/src/mlia/nn/tensorflow/tflite_metrics.py
@@ -1,7 +1,7 @@
 # SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
 # SPDX-License-Identifier: Apache-2.0
 """
-Contains class TFLiteMetrics to calculate metrics from a TFLite file.
+Contains class TFLiteMetrics to calculate metrics from a TensorFlow Lite file.
 
 These metrics include:
 * Sparsity (per layer and overall)
@@ -102,7 +102,7 @@ class ReportClusterMode(Enum):
 
 
 class TFLiteMetrics:
-    """Helper class to calculate metrics from a TFLite file.
+    """Helper class to calculate metrics from a TensorFlow Lite file.
 
     Metrics include:
     * sparsity (per-layer and overall)
@@ -111,12 +111,12 @@ class TFLiteMetrics:
     """
 
     def __init__(self, tflite_file: str, ignore_list: list[str] | None = None) -> None:
-        """Load the TFLite file and filter layers."""
+        """Load the TensorFlow Lite file and filter layers."""
         self.tflite_file = tflite_file
         if ignore_list is None:
             ignore_list = DEFAULT_IGNORE_LIST
         self.ignore_list = [ignore.casefold() for ignore in ignore_list]
-        # Initialize the TFLite interpreter with the model file
+        # Initialize the TensorFlow Lite interpreter with the model file
         self.interpreter = tf.lite.Interpreter(
             model_path=tflite_file, experimental_preserve_all_tensors=True
         )
@@ -218,7 +218,7 @@ class TFLiteMetrics:
         """Print a summary of all the model information."""
         print(f"Model file: {self.tflite_file}")
         print("#" * 80)
-        print(" " * 28 + "### TFLITE SUMMARY ###")
+        print(" " * 28 + "### TENSORFLOW LITE SUMMARY ###")
         print(f"File: {os.path.abspath(self.tflite_file)}")
         print("Input(s):")
         self._print_in_outs(self.interpreter.get_input_details(), verbose)
diff --git a/src/mlia/nn/tensorflow/utils.py b/src/mlia/nn/tensorflow/utils.py
index 6250f56..7970329 100644
--- a/src/mlia/nn/tensorflow/utils.py
+++ b/src/mlia/nn/tensorflow/utils.py
@@ -63,7 +63,7 @@ def representative_tf_dataset(model: str) -> Callable:
 
 
 def convert_to_tflite(model: tf.keras.Model, quantized: bool = False) -> Interpreter:
-    """Convert Keras model to TFLite."""
+    """Convert Keras model to TensorFlow Lite."""
     if not isinstance(model, tf.keras.Model):
         raise Exception("Invalid model type")
 
@@ -83,7 +83,7 @@ def convert_to_tflite(model: tf.keras.Model, quantized: bool = False) -> Interpr
 
 
 def convert_tf_to_tflite(model: str, quantized: bool = False) -> Interpreter:
-    """Convert TensorFlow model to TFLite."""
+    """Convert TensorFlow model to TensorFlow Lite."""
     if not isinstance(model, str):
         raise Exception("Invalid model type")
 
@@ -109,15 +109,15 @@ def save_keras_model(model: tf.keras.Model, save_path: str | Path) -> None:
 
 
 def save_tflite_model(model: tf.lite.TFLiteConverter, save_path: str | Path) -> None:
-    """Save TFLite model at provided path."""
+    """Save TensorFlow Lite model at provided path."""
     with open(save_path, "wb") as file:
         file.write(model)
 
 
 def is_tflite_model(model: str | Path) -> bool:
-    """Check if model type is supported by TFLite API.
+    """Check if model type is supported by TensorFlow Lite API.
 
-    TFLite model is indicated by the model file extension .tflite
+    TensorFlow Lite model is indicated by the model file extension .tflite
     """
     model_path = Path(model)
     return model_path.suffix == ".tflite"