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134 lines
3.9 KiB
134 lines
3.9 KiB
# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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from op_test import OpTest
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import paddle
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import paddle.fluid.core as core
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from paddle.static import program_guard, Program
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def check_randperm_out(n, data_np):
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assert isinstance(data_np, np.ndarray), \
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"The input data_np should be np.ndarray."
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gt_sorted = np.arange(n)
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out_sorted = np.sort(data_np)
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return list(gt_sorted == out_sorted)
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def error_msg(data_np):
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return "The sorted ground truth and sorted out should " + \
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"be equal, out = " + str(data_np)
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def convert_dtype(dtype_str):
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dtype_str_list = ["int32", "int64", "float32", "float64"]
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dtype_num_list = [
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core.VarDesc.VarType.INT32, core.VarDesc.VarType.INT64,
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core.VarDesc.VarType.FP32, core.VarDesc.VarType.FP64
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]
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assert dtype_str in dtype_str_list, dtype_str + \
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" should in " + str(dtype_str_list)
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return dtype_num_list[dtype_str_list.index(dtype_str)]
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class TestRandpermOp(OpTest):
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""" Test randperm op."""
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def setUp(self):
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self.op_type = "randperm"
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self.n = 200
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self.dtype = "int64"
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self.inputs = {}
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self.outputs = {"Out": np.zeros((self.n)).astype(self.dtype)}
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self.init_attrs()
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self.attrs = {
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"n": self.n,
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"dtype": convert_dtype(self.dtype),
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}
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def init_attrs(self):
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pass
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def test_check_output(self):
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self.check_output_customized(self.verify_output)
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def verify_output(self, outs):
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out_np = np.array(outs[0])
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self.assertTrue(
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check_randperm_out(self.n, out_np), msg=error_msg(out_np))
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class TestRandpermOpN(TestRandpermOp):
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def init_attrs(self):
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self.n = 10000
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class TestRandpermOpInt32(TestRandpermOp):
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def init_attrs(self):
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self.dtype = "int32"
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class TestRandpermOpFloat32(TestRandpermOp):
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def init_attrs(self):
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self.dtype = "float32"
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class TestRandpermOpFloat64(TestRandpermOp):
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def init_attrs(self):
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self.dtype = "float64"
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class TestRandpermOpError(unittest.TestCase):
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def test_errors(self):
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with program_guard(Program(), Program()):
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self.assertRaises(ValueError, paddle.randperm, -3)
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self.assertRaises(TypeError, paddle.randperm, 10, 'int8')
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class TestRandpermAPI(unittest.TestCase):
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def test_out(self):
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n = 10
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place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda(
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) else paddle.CPUPlace()
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with program_guard(Program(), Program()):
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x1 = paddle.randperm(n)
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x2 = paddle.randperm(n, 'float32')
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exe = paddle.static.Executor(place)
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res = exe.run(fetch_list=[x1, x2])
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self.assertEqual(res[0].dtype, np.int64)
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self.assertEqual(res[1].dtype, np.float32)
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self.assertTrue(check_randperm_out(n, res[0]))
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self.assertTrue(check_randperm_out(n, res[1]))
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class TestRandpermImperative(unittest.TestCase):
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def test_out(self):
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paddle.disable_static()
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n = 10
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for dtype in ['int32', np.int64, 'float32', 'float64']:
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data_p = paddle.randperm(n, dtype)
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data_np = data_p.numpy()
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self.assertTrue(
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check_randperm_out(n, data_np), msg=error_msg(data_np))
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paddle.enable_static()
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if __name__ == "__main__":
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unittest.main()
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