You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
197 lines
7.2 KiB
197 lines
7.2 KiB
# Copyright (c) 2018 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.
|
|
|
|
from __future__ import print_function
|
|
|
|
import unittest
|
|
import numpy as np
|
|
import paddle
|
|
import paddle.fluid as fluid
|
|
from op_test import OpTest
|
|
paddle.enable_static()
|
|
|
|
|
|
# Correct: General.
|
|
class TestUnsqueezeOp(OpTest):
|
|
def setUp(self):
|
|
self.init_test_case()
|
|
self.op_type = "unsqueeze"
|
|
self.inputs = {"X": np.random.random(self.ori_shape).astype("float64")}
|
|
self.init_attrs()
|
|
self.outputs = {"Out": self.inputs["X"].reshape(self.new_shape)}
|
|
|
|
def test_check_output(self):
|
|
self.check_output()
|
|
|
|
def test_check_grad(self):
|
|
self.check_grad(["X"], "Out")
|
|
|
|
def init_test_case(self):
|
|
self.ori_shape = (3, 40)
|
|
self.axes = (1, 2)
|
|
self.new_shape = (3, 1, 1, 40)
|
|
|
|
def init_attrs(self):
|
|
self.attrs = {"axes": self.axes}
|
|
|
|
|
|
# Correct: Single input index.
|
|
class TestUnsqueezeOp1(TestUnsqueezeOp):
|
|
def init_test_case(self):
|
|
self.ori_shape = (20, 5)
|
|
self.axes = (-1, )
|
|
self.new_shape = (20, 5, 1)
|
|
|
|
|
|
# Correct: Mixed input axis.
|
|
class TestUnsqueezeOp2(TestUnsqueezeOp):
|
|
def init_test_case(self):
|
|
self.ori_shape = (20, 5)
|
|
self.axes = (0, -1)
|
|
self.new_shape = (1, 20, 5, 1)
|
|
|
|
|
|
# Correct: There is duplicated axis.
|
|
class TestUnsqueezeOp3(TestUnsqueezeOp):
|
|
def init_test_case(self):
|
|
self.ori_shape = (10, 2, 5)
|
|
self.axes = (0, 3, 3)
|
|
self.new_shape = (1, 10, 2, 1, 1, 5)
|
|
|
|
|
|
# Correct: Reversed axes.
|
|
class TestUnsqueezeOp4(TestUnsqueezeOp):
|
|
def init_test_case(self):
|
|
self.ori_shape = (10, 2, 5)
|
|
self.axes = (3, 1, 1)
|
|
self.new_shape = (10, 1, 1, 2, 5, 1)
|
|
|
|
|
|
class API_TestUnsqueeze(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.program_guard(fluid.Program(), fluid.Program()):
|
|
data1 = fluid.layers.data('data1', shape=[-1, 10], dtype='float64')
|
|
result_squeeze = paddle.unsqueeze(data1, axis=[1])
|
|
place = fluid.CPUPlace()
|
|
exe = fluid.Executor(place)
|
|
input1 = np.random.random([5, 1, 10]).astype('float64')
|
|
input = np.squeeze(input1, axis=1)
|
|
result, = exe.run(feed={"data1": input},
|
|
fetch_list=[result_squeeze])
|
|
self.assertTrue(np.allclose(input1, result))
|
|
|
|
|
|
class TestUnsqueezeOpError(unittest.TestCase):
|
|
def test_errors(self):
|
|
with fluid.program_guard(fluid.Program(), fluid.Program()):
|
|
# The type of axis in split_op should be int or Variable.
|
|
def test_axes_type():
|
|
x6 = fluid.layers.data(
|
|
shape=[-1, 10], dtype='float16', name='x3')
|
|
paddle.unsqueeze(x6, axis=3.2)
|
|
|
|
self.assertRaises(TypeError, test_axes_type)
|
|
|
|
|
|
class API_TestUnsqueeze2(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.program_guard(fluid.Program(), fluid.Program()):
|
|
data1 = fluid.data('data1', shape=[-1, 10], dtype='float64')
|
|
data2 = fluid.data('data2', shape=[1], dtype='int32')
|
|
result_squeeze = paddle.unsqueeze(data1, axis=data2)
|
|
place = fluid.CPUPlace()
|
|
exe = fluid.Executor(place)
|
|
input1 = np.random.random([5, 1, 10]).astype('float64')
|
|
input2 = np.array([1]).astype('int32')
|
|
input = np.squeeze(input1, axis=1)
|
|
result1, = exe.run(feed={"data1": input,
|
|
"data2": input2},
|
|
fetch_list=[result_squeeze])
|
|
self.assertTrue(np.allclose(input1, result1))
|
|
|
|
|
|
class API_TestUnsqueeze3(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.program_guard(fluid.Program(), fluid.Program()):
|
|
data1 = fluid.data('data1', shape=[-1, 10], dtype='float64')
|
|
data2 = fluid.data('data2', shape=[1], dtype='int32')
|
|
result_squeeze = paddle.unsqueeze(data1, axis=[data2, 3])
|
|
place = fluid.CPUPlace()
|
|
exe = fluid.Executor(place)
|
|
input1 = np.random.random([5, 1, 10, 1]).astype('float64')
|
|
input2 = np.array([1]).astype('int32')
|
|
input = np.squeeze(input1)
|
|
result1, = exe.run(feed={"data1": input,
|
|
"data2": input2},
|
|
fetch_list=[result_squeeze])
|
|
self.assertTrue(np.array_equal(input1, result1))
|
|
self.assertEqual(input1.shape, result1.shape)
|
|
|
|
|
|
class API_TestDyUnsqueeze(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.dygraph.guard():
|
|
input_1 = np.random.random([5, 1, 10]).astype("int32")
|
|
input1 = np.expand_dims(input_1, axis=1)
|
|
input = fluid.dygraph.to_variable(input_1)
|
|
output = paddle.unsqueeze(input, axis=[1])
|
|
out_np = output.numpy()
|
|
self.assertTrue(np.array_equal(input1, out_np))
|
|
self.assertEqual(input1.shape, out_np.shape)
|
|
|
|
|
|
class API_TestDyUnsqueeze2(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.dygraph.guard():
|
|
input1 = np.random.random([5, 10]).astype("int32")
|
|
out1 = np.expand_dims(input1, axis=1)
|
|
input = fluid.dygraph.to_variable(input1)
|
|
output = paddle.unsqueeze(input, axis=1)
|
|
out_np = output.numpy()
|
|
self.assertTrue(np.array_equal(out1, out_np))
|
|
self.assertEqual(out1.shape, out_np.shape)
|
|
|
|
|
|
class API_TestDyUnsqueezeAxisTensor(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.dygraph.guard():
|
|
input1 = np.random.random([5, 10]).astype("int32")
|
|
out1 = np.expand_dims(input1, axis=1)
|
|
out1 = np.expand_dims(out1, axis=2)
|
|
input = fluid.dygraph.to_variable(input1)
|
|
output = paddle.unsqueeze(input, axis=paddle.to_tensor([1, 2]))
|
|
out_np = output.numpy()
|
|
self.assertTrue(np.array_equal(out1, out_np))
|
|
self.assertEqual(out1.shape, out_np.shape)
|
|
|
|
|
|
class API_TestDyUnsqueezeAxisTensorList(unittest.TestCase):
|
|
def test_out(self):
|
|
with fluid.dygraph.guard():
|
|
input1 = np.random.random([5, 10]).astype("int32")
|
|
# Actually, expand_dims supports tuple since version 1.18.0
|
|
out1 = np.expand_dims(input1, axis=1)
|
|
out1 = np.expand_dims(out1, axis=2)
|
|
input = fluid.dygraph.to_variable(input1)
|
|
output = paddle.unsqueeze(
|
|
fluid.dygraph.to_variable(input1),
|
|
axis=[paddle.to_tensor([1]), paddle.to_tensor([2])])
|
|
out_np = output.numpy()
|
|
self.assertTrue(np.array_equal(out1, out_np))
|
|
self.assertEqual(out1.shape, out_np.shape)
|
|
|
|
|
|
if __name__ == "__main__":
|
|
unittest.main()
|