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Paddle/python/paddle/fluid/tests/custom_op/test_dispatch_jit.py

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3.4 KiB

# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import os
import unittest
import paddle
import numpy as np
from paddle.utils.cpp_extension import load, get_build_directory
from utils import paddle_includes, extra_cc_args
from paddle.utils.cpp_extension.extension_utils import run_cmd
# Because Windows don't use docker, the shared lib already exists in the
# cache dir, it will not be compiled again unless the shared lib is removed.
file = '{}\\dispatch_op\\dispatch_op.pyd'.format(get_build_directory())
if os.name == 'nt' and os.path.isfile(file):
cmd = 'del {}'.format(file)
run_cmd(cmd, True)
dispatch_op = load(
name='dispatch_op',
sources=['dispatch_test_op.cc'],
extra_include_paths=paddle_includes, # add for Coverage CI
extra_cxx_cflags=extra_cc_args,
verbose=True)
class TestJitDispatch(unittest.TestCase):
def setUp(self):
paddle.set_device('cpu')
def run_dispatch_test(self, func, dtype):
np_x = np.ones([2, 2]).astype(dtype)
x = paddle.to_tensor(np_x)
out = func(x)
np_x = x.numpy()
np_out = out.numpy()
self.assertTrue(dtype in str(np_out.dtype))
self.assertTrue(
np.array_equal(np_x, np_out),
"custom op x: {},\n custom op out: {}".format(np_x, np_out))
def test_dispatch_integer(self):
dtypes = ["int32", "int64", "int8", "uint8", "int16"]
for dtype in dtypes:
self.run_dispatch_test(dispatch_op.dispatch_test_integer, dtype)
def test_dispatch_complex(self):
dtypes = ["complex64", "complex128"]
for dtype in dtypes:
self.run_dispatch_test(dispatch_op.dispatch_test_complex, dtype)
def test_dispatch_float_and_integer(self):
dtypes = [
"float32", "float64", "int32", "int64", "int8", "uint8", "int16"
]
for dtype in dtypes:
self.run_dispatch_test(dispatch_op.dispatch_test_float_and_integer,
dtype)
def test_dispatch_float_and_complex(self):
dtypes = ["float32", "float64", "complex64", "complex128"]
for dtype in dtypes:
self.run_dispatch_test(dispatch_op.dispatch_test_float_and_complex,
dtype)
def test_dispatch_float_and_integer_and_complex(self):
dtypes = [
"float32", "float64", "int32", "int64", "int8", "uint8", "int16",
"complex64", "complex128"
]
for dtype in dtypes:
self.run_dispatch_test(
dispatch_op.dispatch_test_float_and_integer_and_complex, dtype)
def test_dispatch_float_and_half(self):
dtypes = ["float32", "float64", "float16"]
for dtype in dtypes:
self.run_dispatch_test(dispatch_op.dispatch_test_float_and_half,
dtype)
if __name__ == '__main__':
unittest.main()