wehub-resource-sync
140 lines
4.4 KiB
Python
140 lines
4.4 KiB
Python
# Copyright (c) 2020 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_place, is_custom_device
|
|
|
|
import paddle
|
|
import paddle.base.dygraph as dg
|
|
from paddle import base, nn
|
|
from paddle.nn import functional as F
|
|
|
|
|
|
def sigmoid(x):
|
|
return 1.0 / (1.0 + np.exp(-x))
|
|
|
|
|
|
def glu(x, dim=-1):
|
|
a, b = np.split(x, 2, axis=dim)
|
|
out = a * sigmoid(b)
|
|
return out
|
|
|
|
|
|
class TestGLUV2(unittest.TestCase):
|
|
def setUp(self):
|
|
self.x = np.random.randn(5, 20)
|
|
self.dim = -1
|
|
self.out = glu(self.x, self.dim)
|
|
|
|
def check_identity(self, place):
|
|
with dg.guard(place):
|
|
x_var = paddle.to_tensor(self.x)
|
|
y_var = F.glu(x_var, self.dim)
|
|
y_np = y_var.numpy()
|
|
np.testing.assert_allclose(y_np, self.out)
|
|
|
|
y_np = F.glu(input=x_var, axis=self.dim).numpy()
|
|
np.testing.assert_allclose(y_np, self.out)
|
|
|
|
def test_case(self):
|
|
self.check_identity(base.CPUPlace())
|
|
if base.is_compiled_with_cuda() or is_custom_device():
|
|
self.check_identity(get_device_place())
|
|
|
|
|
|
class TestGlu(unittest.TestCase):
|
|
def glu_axis_size(self):
|
|
paddle.enable_static()
|
|
x = paddle.static.data(name='x', shape=[1, 2, 3], dtype='float32')
|
|
paddle.nn.functional.glu(x, axis=256)
|
|
|
|
def test_errors(self):
|
|
self.assertRaises(ValueError, self.glu_axis_size)
|
|
|
|
|
|
class TestnnGLU(unittest.TestCase):
|
|
def setUp(self):
|
|
self.x = np.random.randn(6, 20)
|
|
self.dim = [-1, 0, 1]
|
|
|
|
def check_identity(self, place):
|
|
with dg.guard(place):
|
|
x_var = paddle.to_tensor(self.x)
|
|
for dim in self.dim:
|
|
act1 = nn.GLU(dim)
|
|
y_np1 = act1(x_var).numpy()
|
|
y_np2 = act1(input=x_var).numpy()
|
|
act2 = nn.GLU(dim=1000)
|
|
self.assertEqual(act2.dim, 1000)
|
|
act2.dim = dim
|
|
y_np3 = act2(x_var).numpy()
|
|
out = glu(self.x, dim)
|
|
np.testing.assert_allclose(y_np1, out)
|
|
np.testing.assert_allclose(y_np2, out)
|
|
np.testing.assert_allclose(y_np3, out)
|
|
|
|
def test_case(self):
|
|
self.check_identity(base.CPUPlace())
|
|
if base.is_compiled_with_cuda() or is_custom_device():
|
|
self.check_identity(get_device_place())
|
|
act = nn.GLU(axis=0, name="test")
|
|
self.assertTrue(act.extra_repr() == 'axis=0, name=test')
|
|
|
|
|
|
class TestnnGLUerror(unittest.TestCase):
|
|
def glu_axis_size(self):
|
|
paddle.enable_static()
|
|
x = paddle.static.data(name='x', shape=[1, 2, 3], dtype='float32')
|
|
act = nn.GLU(256)
|
|
act(x)
|
|
|
|
def test_errors(self):
|
|
self.assertRaises(ValueError, self.glu_axis_size)
|
|
act = nn.GLU(256)
|
|
self.assertRaises(TypeError, act, 1)
|
|
# The input dtype must be float16, float32, float64.
|
|
x_int32 = paddle.static.data(
|
|
name='x_int32', shape=[10, 18], dtype='int32'
|
|
)
|
|
self.assertRaises(TypeError, act, x_int32)
|
|
|
|
|
|
class TestGLU_ZeroSize(unittest.TestCase):
|
|
def setUp(self):
|
|
self.x = np.random.randn(5, 0, 20)
|
|
self.dim = -1
|
|
self.out = glu(self.x, self.dim)
|
|
|
|
def check_dygraph(self, place):
|
|
with dg.guard(place):
|
|
x_var = paddle.to_tensor(self.x)
|
|
x_var.stop_gradient = False
|
|
y_var = F.glu(x_var, self.dim)
|
|
y_np = y_var.numpy()
|
|
np.testing.assert_allclose(y_np, self.out)
|
|
|
|
loss = paddle.sum(y_var)
|
|
loss.backward()
|
|
np.testing.assert_allclose(x_var.grad.shape, x_var.shape)
|
|
|
|
def test_case(self):
|
|
self.check_dygraph(base.CPUPlace())
|
|
if base.is_compiled_with_cuda() or is_custom_device():
|
|
self.check_dygraph(get_device_place())
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|