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# SPDX-FileCopyrightText: Copyright 2022, Arm Limited and/or its affiliates.
# SPDX-License-Identifier: Apache-2.0
import os
import pytest
import tensorflow as tf
import tempfile
import tosa_checker
@pytest.fixture(scope="module")
def build_tosa_non_compat_model():
num_boxes = 6
max_output_size = 5
iou_threshold = 0.5
score_threshold = 0.1
def non_max_suppression(x):
boxes = x[0]
scores = x[1]
output = tf.image.non_max_suppression_with_scores(
boxes[0],
scores[0],
max_output_size=max_output_size,
iou_threshold=iou_threshold,
score_threshold=score_threshold,
soft_nms_sigma=1.0,
)
return output
boxes_in = tf.keras.layers.Input(
shape=(num_boxes, 4), batch_size=1, dtype=tf.float32, name="boxes"
)
scores_in = tf.keras.layers.Input(
shape=(num_boxes), batch_size=1, dtype=tf.float32, name="scores"
)
outputs = tf.keras.layers.Lambda(non_max_suppression, name="nms")(
[boxes_in, scores_in]
)
model = tf.keras.models.Model(inputs=[boxes_in, scores_in], outputs=outputs)
return model
@pytest.fixture(scope="module")
def build_tosa_non_compat_model_custom_op():
@tf.function(
experimental_implements='name: "exp_log" \
attr { \
key: "tfl_fusable_op" \
value { b: true } \
}'
)
def exp_log(x):
x = tf.math.exp(x)
x = tf.math.log(x)
return x
input = tf.keras.layers.Input(shape=(16,), name="input")
x = tf.keras.layers.Lambda(exp_log, name="exp_log")(input)
x = tf.keras.layers.Dense(8, activation="relu", name="dense")(x)
model = tf.keras.models.Model(inputs=[input], outputs=x)
return model
@pytest.fixture(scope="module")
def build_tosa_compat_model():
input = tf.keras.layers.Input(shape=(16,), name="input")
x = tf.keras.layers.Dense(8, activation="relu", name="dense")(input)
model = tf.keras.models.Model(inputs=[input], outputs=x)
return model
def create_tflite(model):
converter = tf.lite.TFLiteConverter.from_keras_model(model)
tflite_model = converter.convert()
return tflite_model
@pytest.fixture(scope="module")
def non_compat_file(build_tosa_non_compat_model):
tflite_model = create_tflite(build_tosa_non_compat_model)
with tempfile.TemporaryDirectory() as tmp_dir:
file = os.path.join(tmp_dir, "test.tflite")
open(file, "wb").write(tflite_model)
yield file
@pytest.fixture(scope="module")
def non_compat_file_custom_op(build_tosa_non_compat_model_custom_op):
tflite_model = create_tflite(build_tosa_non_compat_model_custom_op)
with tempfile.TemporaryDirectory() as tmp_dir:
file = os.path.join(tmp_dir, "test.tflite")
open(file, "wb").write(tflite_model)
yield file
@pytest.fixture(scope="module")
def compat_file(build_tosa_compat_model):
tflite_model = create_tflite(build_tosa_compat_model)
with tempfile.TemporaryDirectory() as tmp_dir:
file = os.path.join(tmp_dir, "test.tflite")
open(file, "wb").write(tflite_model)
yield file
class TestTosaCompatibilityTool:
def test_bad_tflite_file(self):
make_bad_tfile = os.path.join(tempfile.mkdtemp(), "test.tflite")
open(make_bad_tfile, "wb").write("bad tflite file".encode("ASCII"))
with pytest.raises(RuntimeError):
checker = tosa_checker.TOSAChecker(model_path=make_bad_tfile)
def test_tosa_non_compat_model(self, non_compat_file):
checker = tosa_checker.TOSAChecker(model_path=non_compat_file)
tosa_compatible = checker.is_tosa_compatible()
assert tosa_compatible == False
ops = checker._get_tosa_compatibility_for_ops()
assert type(ops) == list
assert [[op.name, op.is_tosa_compatible] for op in ops] == [
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.strided_slice", True],
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.strided_slice", True],
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.pseudo_const", True],
["tfl.non_max_suppression_v5", False],
]
tosa_ops = checker._get_used_tosa_ops()
assert type(tosa_ops) == list
assert [[op.name, op.is_tosa_compatible] for op in tosa_ops] == [
["tosa.const", True],
["tosa.const", True],
["tosa.const", True],
["tosa.const", True],
["tosa.reshape", True],
["tosa.reshape", True],
]
def test_tosa_non_compat_model_with_custom_op(self, non_compat_file_custom_op):
checker = tosa_checker.TOSAChecker(model_path=non_compat_file_custom_op)
tosa_compatible = checker.is_tosa_compatible()
assert tosa_compatible == False
ops = checker._get_tosa_compatibility_for_ops()
assert type(ops) == list
assert [[op.name, op.is_tosa_compatible] for op in ops] == [
["tfl.custom", False],
["tfl.pseudo_const", True],
["tfl.no_value", True],
["tfl.fully_connected", True],
]
tosa_ops = checker._get_used_tosa_ops()
assert type(tosa_ops) == list
assert [[op.name, op.is_tosa_compatible] for op in tosa_ops] == [
["tosa.const", True],
["tosa.const", True],
["tosa.custom", False],
["tosa.fully_connected", True],
["tosa.clamp", True],
]
def test_tosa_compat_model(self, compat_file):
checker = tosa_checker.TOSAChecker(model_path=compat_file)
tosa_compatible = checker.is_tosa_compatible()
assert tosa_compatible == True
ops = checker._get_tosa_compatibility_for_ops()
assert type(ops) == list
assert [[op.name, op.is_tosa_compatible] for op in ops] == [
["tfl.pseudo_const", True],
["tfl.no_value", True],
["tfl.fully_connected", True],
]
tosa_ops = checker._get_used_tosa_ops()
assert type(tosa_ops) == list
assert [[op.name, op.is_tosa_compatible] for op in tosa_ops] == [
["tosa.const", True],
["tosa.const", True],
["tosa.fully_connected", True],
["tosa.clamp", True],
]
def test_tosa_non_compat_model_mlir_representation(self, non_compat_file):
checker = tosa_checker.TOSAChecker(model_path=non_compat_file)
tfl_mlir_representation = checker._get_mlir_model_representation(
elide_large_elements_attrs=True
)
assert "non_max_suppression_v5" in tfl_mlir_representation
tosa_mlir_representation = checker._get_mlir_tosa_model_representation(
elide_large_elements_attrs=True
)
assert "non_max_suppression_v5" in tosa_mlir_representation
def test_tosa_compat_model_mlir_representation(self, compat_file):
checker = tosa_checker.TOSAChecker(model_path=compat_file)
tfl_mlir_representation = checker._get_mlir_model_representation(
elide_large_elements_attrs=True
)
assert "fully_connected" in tfl_mlir_representation
tosa_mlir_representation = checker._get_mlir_tosa_model_representation(
elide_large_elements_attrs=True
)
assert "fully_connected" in tosa_mlir_representation
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