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# SPDX-FileCopyrightText: Copyright 2023, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
"""Tests for module mlia.nn.rewrite.graph_edit.record."""
from pathlib import Path
import numpy as np
import pytest
import tensorflow as tf
from mlia.nn.rewrite.core.extract import ExtractPaths
from mlia.nn.rewrite.core.graph_edit.record import record_model
from mlia.nn.rewrite.core.utils.numpy_tfrecord import numpytf_read
def data_matches_outputs(
name: str,
tensor: tf.Tensor,
model_outputs: list,
dequantized_output: bool,
) -> bool:
"""Check that the name and the tensor match any of the model outputs."""
for model_output in model_outputs:
if model_output["name"] == name:
# If the name is a match, tensor shape and type have to match!
tensor_shape = tensor.shape.as_list()
tensor_type = tensor.dtype.as_numpy_dtype
return all(
(
tensor_shape == model_output["shape"].tolist(),
tensor_type == np.float32
if dequantized_output
else model_output["dtype"],
)
)
return False
def check_record_model(
test_tflite_model: Path,
tmp_path: Path,
test_tfrecord: Path,
batch_size: int,
dequantize_output: bool,
) -> None:
"""Test the function record_model()."""
output_file = ExtractPaths.tfrec.output(tmp_path)
record_model(
input_filename=str(test_tfrecord),
model_filename=str(test_tflite_model),
output_filename=str(output_file),
batch_size=batch_size,
dequantize_output=dequantize_output,
)
output_file = ExtractPaths.tfrec.output(tmp_path, dequantize_output)
assert output_file.is_file()
# Now load model and the data and make sure that the written data matches
# any of the model outputs
interpreter = tf.lite.Interpreter(str(test_tflite_model))
model_outputs = interpreter.get_output_details()
dataset = numpytf_read(str(output_file))
for data in dataset:
for name, tensor in data.items():
assert data_matches_outputs(name, tensor, model_outputs, dequantize_output)
@pytest.mark.parametrize("batch_size", (None, 1, 2))
@pytest.mark.parametrize("dequantize_output", (True, False))
def test_record_model(
test_tflite_model: Path,
tmp_path: Path,
test_tfrecord: Path,
batch_size: int,
dequantize_output: bool,
) -> None:
"""Test the function record_model()."""
check_record_model(
test_tflite_model, tmp_path, test_tfrecord, batch_size, dequantize_output
)
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