From 867f37d643e66c0223457c28f5345f2f21db97f2 Mon Sep 17 00:00:00 2001
From: Annie Tallund <annie.tallund@arm.com>
Date: Wed, 15 Mar 2023 11:27:08 +0100
Subject: Adapt rewrite module to MLIA coding standards

- Fix imports
- Update variable names
- Refactor helper functions
- Add licence headers
- Add docstrings
- Use f-strings rather than % notation
- Create type annotations in rewrite module
- Migrate from tqdm to rich progress bar
- Use logging module in rewrite module: All print statements are
  replaced with logging module

Resolves: MLIA-831, MLIA-842, MLIA-844, MLIA-846
Signed-off-by: Benjamin Klimczak <benjamin.klimczak@arm.com>
Change-Id: Idee37538d72b9f01128a894281a8d10155f7c17c
---
 tests/test_nn_rewrite_core_graph_edit_cut.py    |  4 ++--
 tests/test_nn_rewrite_core_graph_edit_record.py |  4 ++--
 tests/test_nn_rewrite_core_train.py             | 14 +++++++++-----
 3 files changed, 13 insertions(+), 9 deletions(-)

(limited to 'tests')

diff --git a/tests/test_nn_rewrite_core_graph_edit_cut.py b/tests/test_nn_rewrite_core_graph_edit_cut.py
index 914fdfd..7d267ed 100644
--- a/tests/test_nn_rewrite_core_graph_edit_cut.py
+++ b/tests/test_nn_rewrite_core_graph_edit_cut.py
@@ -13,11 +13,11 @@ def test_cut_model(test_tflite_model: Path, tmp_path: Path) -> None:
     """Test the function cut_model()."""
     output_file = tmp_path / "out.tflite"
     cut_model(
-        model_file=test_tflite_model,
+        model_file=str(test_tflite_model),
         input_names=["serving_default_input:0"],
         output_names=["sequential/flatten/Reshape"],
         subgraph_index=0,
-        output_file=output_file,
+        output_file=str(output_file),
     )
     assert output_file.is_file()
 
diff --git a/tests/test_nn_rewrite_core_graph_edit_record.py b/tests/test_nn_rewrite_core_graph_edit_record.py
index 39aeef5..cd728af 100644
--- a/tests/test_nn_rewrite_core_graph_edit_record.py
+++ b/tests/test_nn_rewrite_core_graph_edit_record.py
@@ -7,7 +7,7 @@ import pytest
 import tensorflow as tf
 
 from mlia.nn.rewrite.core.graph_edit.record import record_model
-from mlia.nn.rewrite.core.utils.numpy_tfrecord import NumpyTFReader
+from mlia.nn.rewrite.core.utils.numpy_tfrecord import numpytf_read
 
 
 @pytest.mark.parametrize("batch_size", (None, 1, 2))
@@ -46,7 +46,7 @@ def test_record_model(
     # any of the model outputs
     interpreter = tf.lite.Interpreter(str(test_tflite_model))
     model_outputs = interpreter.get_output_details()
-    dataset = NumpyTFReader(str(output_file))
+    dataset = numpytf_read(str(output_file))
     for data in dataset:
         for name, tensor in data.items():
             assert data_matches_outputs(name, tensor, model_outputs)
diff --git a/tests/test_nn_rewrite_core_train.py b/tests/test_nn_rewrite_core_train.py
index d2bc1e0..3c2ef3e 100644
--- a/tests/test_nn_rewrite_core_train.py
+++ b/tests/test_nn_rewrite_core_train.py
@@ -6,17 +6,21 @@ from __future__ import annotations
 
 from pathlib import Path
 from tempfile import TemporaryDirectory
+from typing import Any
 
 import numpy as np
 import pytest
 import tensorflow as tf
 
 from mlia.nn.rewrite.core.train import augmentation_presets
+from mlia.nn.rewrite.core.train import LearningRateSchedule
 from mlia.nn.rewrite.core.train import mixup
 from mlia.nn.rewrite.core.train import train
 
 
-def replace_fully_connected_with_conv(input_shape, output_shape) -> tf.keras.Model:
+def replace_fully_connected_with_conv(
+    input_shape: Any, output_shape: Any
+) -> tf.keras.Model:
     """Get a replacement model for the fully connected layer."""
     for name, shape in {
         "Input": input_shape,
@@ -43,7 +47,7 @@ def check_train(
     augmentation_preset: tuple[float | None, float | None] = augmentation_presets[
         "none"
     ],
-    lr_schedule: str = "cosine",
+    lr_schedule: LearningRateSchedule = "cosine",
     use_unmodified_model: bool = False,
     num_procs: int = 1,
 ) -> None:
@@ -60,7 +64,7 @@ def check_train(
             output_tensors=["StatefulPartitionedCall:0"],
             augment=augmentation_preset,
             steps=32,
-            lr=1e-3,
+            learning_rate=1e-3,
             batch_size=batch_size,
             verbose=verbose,
             show_progress=show_progress,
@@ -104,7 +108,7 @@ def test_train(
     verbose: bool,
     show_progress: bool,
     augmentation_preset: tuple[float | None, float | None],
-    lr_schedule: str,
+    lr_schedule: LearningRateSchedule,
     use_unmodified_model: bool,
     num_procs: int,
 ) -> None:
@@ -131,7 +135,7 @@ def test_train_invalid_schedule(
         check_train(
             tflite_model=test_tflite_model_fp32,
             tfrecord=test_tfrecord_fp32,
-            lr_schedule="unknown_schedule",
+            lr_schedule="unknown_schedule",  # type: ignore
         )
 
 
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