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Paddle/python/paddle/fluid/tests/unittests/test_randperm_op.py

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3.9 KiB

# 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 OpTest
import paddle
import paddle.fluid.core as core
from paddle.static import program_guard, Program
def check_randperm_out(n, data_np):
assert isinstance(data_np, np.ndarray), \
"The input data_np should be np.ndarray."
gt_sorted = np.arange(n)
out_sorted = np.sort(data_np)
return list(gt_sorted == out_sorted)
def error_msg(data_np):
return "The sorted ground truth and sorted out should " + \
"be equal, out = " + str(data_np)
def convert_dtype(dtype_str):
dtype_str_list = ["int32", "int64", "float32", "float64"]
dtype_num_list = [
core.VarDesc.VarType.INT32, core.VarDesc.VarType.INT64,
core.VarDesc.VarType.FP32, core.VarDesc.VarType.FP64
]
assert dtype_str in dtype_str_list, dtype_str + \
" should in " + str(dtype_str_list)
return dtype_num_list[dtype_str_list.index(dtype_str)]
class TestRandpermOp(OpTest):
""" Test randperm op."""
def setUp(self):
self.op_type = "randperm"
self.n = 200
self.dtype = "int64"
self.inputs = {}
self.outputs = {"Out": np.zeros((self.n)).astype(self.dtype)}
self.init_attrs()
self.attrs = {
"n": self.n,
"dtype": convert_dtype(self.dtype),
}
def init_attrs(self):
pass
def test_check_output(self):
self.check_output_customized(self.verify_output)
def verify_output(self, outs):
out_np = np.array(outs[0])
self.assertTrue(
check_randperm_out(self.n, out_np), msg=error_msg(out_np))
class TestRandpermOpN(TestRandpermOp):
def init_attrs(self):
self.n = 10000
class TestRandpermOpInt32(TestRandpermOp):
def init_attrs(self):
self.dtype = "int32"
class TestRandpermOpFloat32(TestRandpermOp):
def init_attrs(self):
self.dtype = "float32"
class TestRandpermOpFloat64(TestRandpermOp):
def init_attrs(self):
self.dtype = "float64"
class TestRandpermOpError(unittest.TestCase):
def test_errors(self):
with program_guard(Program(), Program()):
self.assertRaises(ValueError, paddle.randperm, -3)
self.assertRaises(TypeError, paddle.randperm, 10, 'int8')
class TestRandpermAPI(unittest.TestCase):
def test_out(self):
n = 10
place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
) else paddle.CPUPlace()
with program_guard(Program(), Program()):
x1 = paddle.randperm(n)
x2 = paddle.randperm(n, 'float32')
exe = paddle.static.Executor(place)
res = exe.run(fetch_list=[x1, x2])
self.assertEqual(res[0].dtype, np.int64)
self.assertEqual(res[1].dtype, np.float32)
self.assertTrue(check_randperm_out(n, res[0]))
self.assertTrue(check_randperm_out(n, res[1]))
class TestRandpermImperative(unittest.TestCase):
def test_out(self):
paddle.disable_static()
n = 10
for dtype in ['int32', np.int64, 'float32', 'float64']:
data_p = paddle.randperm(n, dtype)
data_np = data_p.numpy()
self.assertTrue(
check_randperm_out(n, data_np), msg=error_msg(data_np))
paddle.enable_static()
if __name__ == "__main__":
unittest.main()