wehub-resource-sync
106 lines
3.3 KiB
Python
106 lines
3.3 KiB
Python
# Copyright (c) 2023 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 unittest
|
|
|
|
import numpy as np
|
|
from op_test import get_device, is_custom_device
|
|
|
|
import paddle
|
|
|
|
|
|
class TestTensorApplyAPI(unittest.TestCase):
|
|
def setUp(self):
|
|
self.x = paddle.to_tensor([1, 2, 3, 4, 5], stop_gradient=True)
|
|
self.function = lambda x: 3 * x + 2
|
|
|
|
def test_dtype(self):
|
|
for dtype in ["float64", "float16", "bfloat16"]:
|
|
self.x.to(dtype)
|
|
self.test_dygraph()
|
|
|
|
@unittest.skipIf(
|
|
not (paddle.is_compiled_with_cuda() or is_custom_device()),
|
|
"only support cuda",
|
|
)
|
|
def test_on_gpu(self):
|
|
self.x.to(get_device())
|
|
self.test_dygraph()
|
|
|
|
def test_dygraph(self):
|
|
y = self.x.apply(self.function)
|
|
np.testing.assert_allclose(
|
|
self.function(self.x).numpy(), y.numpy(), rtol=1e-05
|
|
)
|
|
|
|
def test_error(self):
|
|
self.x.stop_gradient = False
|
|
|
|
def fn_inplace(x):
|
|
x.apply_(self.function)
|
|
|
|
def fn_outplace(x, func):
|
|
x.apply(func)
|
|
|
|
def function(x, y, z):
|
|
return x + y + z
|
|
|
|
self.assertRaises(RuntimeError, fn_inplace, self.x)
|
|
self.assertRaises(RuntimeError, fn_outplace, self.x, self.function)
|
|
with paddle.jit.api.sot_mode_guard(False):
|
|
self.assertRaises(
|
|
RuntimeError,
|
|
paddle.jit.to_static(fn_outplace),
|
|
self.x,
|
|
self.function,
|
|
)
|
|
self.x.stop_gradient = True
|
|
self.assertRaises(
|
|
ValueError,
|
|
paddle.jit.to_static(fn_outplace),
|
|
self.x,
|
|
function,
|
|
)
|
|
self.x.stop_gradient = False
|
|
with paddle.pir_utils.IrGuard():
|
|
paddle.disable_static()
|
|
self.assertRaises(
|
|
RuntimeError,
|
|
paddle.jit.to_static(fn_outplace),
|
|
self.x,
|
|
self.function,
|
|
)
|
|
|
|
def test_to_static(self):
|
|
def fn(x, func):
|
|
y = x.apply(func)
|
|
return y
|
|
|
|
with paddle.jit.api.sot_mode_guard(False):
|
|
jit_g = paddle.jit.to_static(fn, full_graph=True)
|
|
out_legacy_ir = jit_g(self.x, self.function)
|
|
with paddle.pir_utils.IrGuard():
|
|
paddle.disable_static()
|
|
jit_g = paddle.jit.to_static(fn, full_graph=True)
|
|
out_pir = jit_g(self.x, self.function)
|
|
np.testing.assert_allclose(
|
|
self.function(self.x).numpy(), out_legacy_ir.numpy(), rtol=1e-05
|
|
)
|
|
np.testing.assert_allclose(
|
|
self.function(self.x).numpy(), out_pir.numpy(), rtol=1e-05
|
|
)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|