blob: 7639cef63995735e31391cec01b80ad17f284495 [file] [log] [blame]
# Copyright 2020 The IREE Authors
#
# Licensed under the Apache License v2.0 with LLVM Exceptions.
# See https://llvm.org/LICENSE.txt for license information.
# SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
import logging
import os
import sys
import tempfile
import unittest
# TODO: No idea why pytype cannot find names from this module.
# pytype: disable=name-error
import iree.compiler.tools.tf
if not iree.compiler.tools.tf.is_available():
print(
f"Skipping test {__file__} because the IREE TensorFlow compiler "
f"is not installed"
)
sys.exit(0)
import tensorflow as tf
class SimpleArithmeticModule(tf.Module):
@tf.function(
input_signature=[tf.TensorSpec([4], tf.float32), tf.TensorSpec([4], tf.float32)]
)
def simple_mul(self, a, b):
return a * b
@tf.function(
input_signature=[
tf.TensorSpec([128, 3072], tf.float32),
tf.TensorSpec([3072, 256], tf.float32),
]
)
def simple_matmul(self, a, b):
return tf.matmul(a, b)
# TODO(laurenzo): More test cases needed (may need additional files).
# Specifically, figure out how to test v1 models.
class TfCompilerTest(unittest.TestCase):
def testImportSavedModel(self):
import_mlir = iree.compiler.tools.tf.compile_saved_model(
self.smdir, import_only=True, output_generic_mlir=True
)
self.assertIn(b"simple_matmul", import_mlir)
def testCompileSavedModel(self):
binary = iree.compiler.tools.tf.compile_saved_model(
self.smdir, target_backends=iree.compiler.tools.tf.DEFAULT_TESTING_BACKENDS
)
logging.info("Compiled len: %d", len(binary))
self.assertIn(b"simple_matmul", binary)
self.assertIn(b"simple_mul", binary)
def testCompileModule(self):
binary = iree.compiler.tools.tf.compile_module(
self.m, target_backends=iree.compiler.tools.tf.DEFAULT_TESTING_BACKENDS
)
logging.info("Compiled len: %d", len(binary))
self.assertIn(b"simple_matmul", binary)
self.assertIn(b"simple_mul", binary)
@classmethod
def setUpClass(cls):
cls.m = SimpleArithmeticModule()
cls.tempdir = tempfile.TemporaryDirectory()
cls.smdir = os.path.join(cls.tempdir.name, "arith.sm")
tf.saved_model.save(
cls.m, cls.smdir, options=tf.saved_model.SaveOptions(save_debug_info=True)
)
@classmethod
def tearDownClass(cls):
cls.tempdir.cleanup()
if __name__ == "__main__":
logging.basicConfig(level=logging.DEBUG)
unittest.main()