wehub-resource-sync
231 lines
6.6 KiB
Python
231 lines
6.6 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 OpTest, get_places
|
|
from scipy import special
|
|
|
|
import paddle
|
|
|
|
np.random.seed(100)
|
|
paddle.seed(100)
|
|
|
|
|
|
def output_i0(x):
|
|
return special.i0(x)
|
|
|
|
|
|
def ref_i0_grad(x, dout):
|
|
gradx = special.i1(x)
|
|
return dout * gradx
|
|
|
|
|
|
class TestI0API(unittest.TestCase):
|
|
DTYPE = "float64"
|
|
DATA = [0, 1, 2, 3, 4, 5]
|
|
|
|
def setUp(self):
|
|
self.x = np.array(self.DATA).astype(self.DTYPE)
|
|
self.out_ref = output_i0(self.x)
|
|
self.place = get_places()
|
|
|
|
def test_api_static(self):
|
|
def run(place):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(paddle.static.Program()):
|
|
x = paddle.static.data(
|
|
name="x", shape=self.x.shape, dtype=self.DTYPE
|
|
)
|
|
out = paddle.i0(x)
|
|
exe = paddle.static.Executor(place)
|
|
res = exe.run(
|
|
paddle.static.default_main_program(),
|
|
feed={"x": self.x},
|
|
fetch_list=[out],
|
|
)
|
|
np.testing.assert_allclose(res[0], self.out_ref, rtol=1e-5)
|
|
paddle.disable_static()
|
|
|
|
for place in self.place:
|
|
run(place)
|
|
|
|
def test_api_dygraph(self):
|
|
def run(place):
|
|
paddle.disable_static(place)
|
|
x = paddle.to_tensor(self.x)
|
|
out = paddle.i0(x)
|
|
|
|
out_ref = output_i0(self.x)
|
|
np.testing.assert_allclose(out.numpy(), out_ref, rtol=1e-5)
|
|
paddle.enable_static()
|
|
|
|
for place in self.place:
|
|
run(place)
|
|
|
|
def test_empty_input_error(self):
|
|
for place in self.place:
|
|
paddle.disable_static(place)
|
|
x = None
|
|
self.assertRaises(ValueError, paddle.i0, x)
|
|
paddle.enable_static()
|
|
|
|
|
|
class TestI0Float32Zero2EightCase(TestI0API):
|
|
DTYPE = "float32"
|
|
DATA = [0, 1, 2, 3, 4, 5, 6, 7, 8]
|
|
|
|
|
|
class TestI0Float32OverEightCase(TestI0API):
|
|
DTYPE = "float32"
|
|
DATA = [9, 10, 11, 12]
|
|
|
|
|
|
class TestI0Float64Zero2EightCase(TestI0API):
|
|
DTYPE = "float64"
|
|
DATA = [0, 1, 2, 3, 4, 5, 6, 7, 8]
|
|
|
|
|
|
class TestI0Float64OverEightCase(TestI0API):
|
|
DTYPE = "float64"
|
|
DATA = [9, 10, 11, 12]
|
|
|
|
|
|
class TestI0Op(OpTest):
|
|
def setUp(self) -> None:
|
|
self.op_type = "i0"
|
|
self.python_api = paddle.i0
|
|
self.init_config()
|
|
self.outputs = {"out": self.target}
|
|
|
|
def init_config(self):
|
|
self.dtype = np.float64
|
|
zero_case = np.zeros(1).astype(self.dtype)
|
|
rand_case = np.random.randn(100).astype(self.dtype)
|
|
one2eight_case = np.random.uniform(low=1, high=8, size=100).astype(
|
|
self.dtype
|
|
)
|
|
over_eight_case = np.random.uniform(low=9, high=15, size=100).astype(
|
|
self.dtype
|
|
)
|
|
self.case = np.concatenate(
|
|
[zero_case, rand_case, one2eight_case, over_eight_case]
|
|
)
|
|
self.inputs = {'x': self.case}
|
|
self.target = output_i0(self.inputs['x'])
|
|
|
|
def test_check_output(self):
|
|
self.check_output(check_pir=True, check_symbol_infer=False)
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(
|
|
['x'],
|
|
'out',
|
|
user_defined_grads=[ref_i0_grad(self.case, 1 / self.case.size)],
|
|
check_pir=True,
|
|
)
|
|
|
|
|
|
class TestI0Op_ZeroSize(OpTest):
|
|
def setUp(self) -> None:
|
|
self.__class__.op_type = "i0"
|
|
self.op_type = "i0"
|
|
self.python_api = paddle.i0
|
|
self.init_config()
|
|
x = np.random.randn(3, 4, 0)
|
|
self.inputs = {'x': x.astype(self.dtype)}
|
|
self.attrs = {}
|
|
self.outputs = {'out': special.i0(x)}
|
|
|
|
def init_config(self):
|
|
self.dtype = np.float32
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(['x'], 'out')
|
|
|
|
|
|
class TestI0API_Compatibility(unittest.TestCase):
|
|
DTYPE = "float64"
|
|
DATA = [0, 1, 2, 3, 4, 5]
|
|
|
|
def setUp(self):
|
|
self.x = np.array(self.DATA).astype(self.DTYPE)
|
|
self.out = output_i0(self.x)
|
|
self.place = get_places()
|
|
|
|
def test_dygraph_Compatibility(self):
|
|
paddle.disable_static()
|
|
x = paddle.to_tensor(self.x)
|
|
paddle_dygraph_out = []
|
|
# Position args (args)
|
|
out1 = paddle.i0(x)
|
|
paddle_dygraph_out.append(out1)
|
|
# Key words args (kwargs) for paddle
|
|
out2 = paddle.i0(x=x)
|
|
paddle_dygraph_out.append(out2)
|
|
# Key words args for torch
|
|
out3 = paddle.i0(input=x)
|
|
paddle_dygraph_out.append(out3)
|
|
|
|
# Tensor method kwargs
|
|
out4 = x.i0()
|
|
paddle_dygraph_out.append(out4)
|
|
# Test out
|
|
out5 = paddle.empty([])
|
|
paddle.i0(x, out=out5)
|
|
paddle_dygraph_out.append(out5)
|
|
# scipy reference out
|
|
ref_out = output_i0(self.x)
|
|
# Check
|
|
for out in paddle_dygraph_out:
|
|
np.testing.assert_allclose(out.numpy(), ref_out, rtol=1e-5)
|
|
paddle.enable_static()
|
|
|
|
def test_static_Compatibility(self):
|
|
def run(place):
|
|
paddle.enable_static()
|
|
with paddle.static.program_guard(paddle.static.Program()):
|
|
x = paddle.static.data(
|
|
name="x", shape=self.x.shape, dtype=self.DTYPE
|
|
)
|
|
# Position args (args)
|
|
out1 = paddle.i0(x)
|
|
# Key words args (kwargs) for paddle
|
|
out2 = paddle.i0(x=x)
|
|
# Key words args for torch
|
|
out3 = paddle.i0(input=x)
|
|
# Tensor method args
|
|
out4 = x.i0()
|
|
|
|
exe = paddle.static.Executor(place)
|
|
fetches = exe.run(
|
|
paddle.static.default_main_program(),
|
|
feed={"x": self.x},
|
|
fetch_list=[out1, out2, out3, out4],
|
|
)
|
|
for out in fetches:
|
|
np.testing.assert_allclose(out, self.out, rtol=1e-5)
|
|
paddle.disable_static()
|
|
|
|
for place in self.place:
|
|
run(place)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|