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# SPDX-FileCopyrightText: Copyright 2022-2023, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Test for module utils/test_utils."""
import os
from pathlib import Path
from pathlib import PosixPath
from unittest.mock import MagicMock
import numpy as np
import pytest
import tensorflow as tf
from mlia.nn.tensorflow import tflite_convert
from mlia.nn.tensorflow.tflite_convert import convert_to_tflite
from mlia.nn.tensorflow.tflite_convert import convert_to_tflite_bytes
from mlia.nn.tensorflow.tflite_convert import main
from mlia.nn.tensorflow.tflite_convert import representative_dataset
def test_generate_representative_dataset() -> None:
"""Test function for generating representative dataset."""
dataset = representative_dataset([1, 3, 3], 5)
data = list(dataset())
assert len(data) == 5
for elem in data:
assert isinstance(elem, list)
assert len(elem) == 1
ndarray = elem[0]
assert ndarray.dtype == np.float32
assert isinstance(ndarray, np.ndarray)
def test_convert_saved_model_to_tflite(test_tf_model: Path) -> None:
"""Test converting SavedModel to TensorFlow Lite."""
result = convert_to_tflite_bytes(test_tf_model.as_posix())
assert isinstance(result, bytes)
def test_convert_keras_to_tflite(test_keras_model: Path) -> None:
"""Test converting Keras model to TensorFlow Lite."""
keras_model = tf.keras.models.load_model(str(test_keras_model))
result = convert_to_tflite_bytes(keras_model)
assert isinstance(result, bytes)
def test_save_tflite_model(tmp_path: Path, test_keras_model: Path) -> None:
"""Test saving TensorFlow Lite model."""
keras_model = tf.keras.models.load_model(str(test_keras_model))
temp_file = tmp_path / "test_model_saving.tflite"
convert_to_tflite(keras_model, output_path=temp_file)
interpreter = tf.lite.Interpreter(model_path=str(temp_file))
assert interpreter
def test_convert_unknown_model_to_tflite() -> None:
"""Test that unknown model type cannot be converted to TensorFlow Lite."""
with pytest.raises(
ValueError, match="Unable to create TensorFlow Lite converter for 123"
):
convert_to_tflite(123)
@pytest.mark.parametrize(
"convert_options,expected_args,error",
[
[
{
"input_path": PosixPath("/in"),
"output_path": PosixPath("/out"),
"quantized": True,
"subprocess": True,
},
["/in", "--output", "/out", "--quantize"],
None,
],
[
{
"input_path": None,
"output_path": None,
"quantized": True,
"subprocess": False,
},
[True, None],
None,
],
[
{
"input_path": None,
"output_path": PosixPath("/out"),
"quantized": False,
"subprocess": True,
"model": None,
},
["/in", "/out"],
"Input path is required",
],
[
{
"input_path": PosixPath("/in"),
"output_path": PosixPath("/out"),
"quantized": False,
"subprocess": False,
},
[False, PosixPath("/out")],
None,
],
[
{
"input_path": PosixPath("/in"),
"output_path": PosixPath("/out"),
"quantized": True,
"subprocess": False,
},
[True, PosixPath("/out")],
None,
],
[
{
"input_path": PosixPath("/in"),
"output_path": None,
"quantized": False,
"subprocess": True,
},
["/in"],
None,
],
[
{
"input_path": PosixPath("/in"),
"output_path": PosixPath("/out"),
"quantized": False,
"subprocess": True,
},
["/in", "--output", "/out"],
None,
],
[
{
"input_path": PosixPath("/in"),
"output_path": PosixPath("/out"),
"quantized": True,
"subprocess": True,
},
["/in", "--output", "/out", "--quantize"],
None,
],
[
{
"output_path": PosixPath("/out"),
"quantized": True,
"subprocess": True,
},
["/model_path", "--output", "/out", "--quantize"],
None,
],
],
)
def test_convert_to_tflite_subprocess(
convert_options: dict,
expected_args: str,
error: str,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Test if convert_to_tflite calls the subprocess with the correct args."""
command_mock = MagicMock()
function_mock = MagicMock()
model_path_str = "/model_path"
monkeypatch.setattr(
"mlia.nn.tensorflow.tflite_convert.command_output", command_mock
)
monkeypatch.setattr(
"mlia.nn.tensorflow.tflite_convert._convert_to_tflite", function_mock
)
opts = {"model": model_path_str, **convert_options}
if error:
with pytest.raises(Exception) as exc_info:
convert_to_tflite(**opts)
assert error in str(exc_info.value)
command_mock.assert_not_called()
function_mock.assert_not_called()
return
convert_to_tflite(**opts)
if convert_options["subprocess"]:
command_mock.assert_called_once()
function_mock.assert_not_called()
pyfile = os.path.abspath(tflite_convert.__file__)
assert command_mock.mock_calls[0].args[0].cmd == [
"python",
pyfile,
*expected_args,
]
else:
command_mock.assert_not_called()
function_mock.assert_called_once()
args = function_mock.mock_calls[0].args
assert args == (model_path_str, *expected_args)
@pytest.mark.parametrize(
"args,expected_convert_args",
[
["{}", "{},False,None"],
["{} --quantize", "{},True,None"],
["{} --output {}", "{},False,{}"],
["{} --output {} --quantize", "{},True,{}"],
],
)
def test_main(
args: str,
expected_convert_args: str,
tmp_path: Path,
monkeypatch: pytest.MonkeyPatch,
) -> None:
"""Test main function, the entry point to subprocess mode."""
mock = MagicMock()
monkeypatch.setattr("mlia.nn.tensorflow.tflite_convert._convert_to_tflite", mock)
input_path = tmp_path
output_path = tmp_path / "out"
argv = args.format(input_path, output_path).split()
main(argv)
mock.assert_called_once()
convert_args = mock.mock_calls[0].args
actual = ",".join(str(arg) for arg in convert_args)
expected = expected_convert_args.format(input_path, output_path)
assert actual == expected
def test_main_nonexistent_input() -> None:
"""Test main with missing input model."""
with pytest.raises(ValueError) as excinfo:
main(["/missing"])
assert "Input file doesn't exist: [/missing]" in str(excinfo.value)
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