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fix a bug: When x is a scalar, the dtype returned by paddle.where is … #74496

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6 changes: 3 additions & 3 deletions python/paddle/tensor/search.py
Original file line number Diff line number Diff line change
Expand Up @@ -796,7 +796,7 @@ def where(
name (str|None, optional): For details, please refer to :ref:`api_guide_Name`. Generally, no setting is required. Default: None.

Returns:
Tensor, A Tensor with the same shape as :attr:`condition` and same data type as :attr:`x` and :attr:`y`.
Tensor, A Tensor with the same shape as :attr:`condition` and same data type as :attr:`x` and :attr:`y`. If :attr:`x` and :attr:`y` have different data types, type promotion rules will be applied (see `Auto Type Promotion <https://www.paddlepaddle.org.cn/documentation/docs/en/develop/guides/advanced/auto_type_promotion_en.html#introduction-to-data-type-promotion>`_).

Examples:

Expand All @@ -819,10 +819,10 @@ def where(
[3]]),)
"""
if np.isscalar(x):
x = paddle.full([1], x, np.array([x]).dtype.name)
x = paddle.to_tensor(x)

if np.isscalar(y):
y = paddle.full([1], y, np.array([y]).dtype.name)
y = paddle.to_tensor(y)

if x is None and y is None:
return nonzero(condition, as_tuple=True)
Expand Down
137 changes: 137 additions & 0 deletions test/tensor/test_search.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,137 @@
# Copyright (c) 2022 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 paddle


class TestSearchAPIs(unittest.TestCase):
def __init__(self, method_name='runTest'):
super().__init__(method_name)
self.con = None
self.con_2D = None

def setUp(self):
self.con = paddle.to_tensor([0.4, 0.3, 0.6, 0.7], dtype="float32")
self.con_2D = paddle.rand([4, 4], dtype='float32')

def test_where_with_float16_scalar(self):
# TODO(hanchoa): Do not support float16 with cpu.
pass

def test_where_with_bfloat16_scalar(self):
# TODO(hanchoa): Do not support bfloat16 with cpu.
pass

def test_where_with_float32_scalar(self):
x = paddle.to_tensor([0.0, 0.0, 0.0, 0.0], dtype="float32")
y = paddle.to_tensor([0.1, 0.1, 0.1, 0.1], dtype="float32")

res = paddle.where(self.con > 0.5, x, y)
self.assertEqual(res.dtype, paddle.float32)

res = paddle.where(self.con > 0.5, 0.5, y)
self.assertEqual(res.dtype, paddle.float32)

res = paddle.where(self.con > 0.5, x, 0.6)
self.assertEqual(res.dtype, paddle.float32)

res = paddle.where(self.con > 0.5, 0.5, 0.6)
self.assertEqual(res.dtype, paddle.float32)

def test_where_with_float64_scalar(self):
x = paddle.to_tensor([0.0, 0.0, 0.0, 0.0], dtype="float64")
y = paddle.to_tensor([0.1, 0.1, 0.1, 0.1], dtype="float64")

res = paddle.where(self.con > 0.5, x, y)
self.assertEqual(res.dtype, paddle.float64)

res = paddle.where(self.con > 0.5, 0.5, y)
self.assertEqual(res.dtype, paddle.float64)

res = paddle.where(self.con > 0.5, x, 0.6)
self.assertEqual(res.dtype, paddle.float64)

res = paddle.where(self.con > 0.5, 0.5, 0.6)
self.assertEqual(res.dtype, paddle.float32)

def test_where_with_complex64_scalar(self):
x = paddle.to_tensor([0.0, 0.0, 0.0, 0.0], dtype="complex64")
y = paddle.to_tensor([0.1, 0.1, 0.1, 0.1], dtype="complex64")

res = paddle.where(self.con > 0.5, x, y)
self.assertEqual(res.dtype, paddle.complex64)

res = paddle.where(self.con > 0.5, 0.5, y)
self.assertEqual(res.dtype, paddle.complex64)

res = paddle.where(self.con > 0.5, x, 0.6)
self.assertEqual(res.dtype, paddle.complex64)

res = paddle.where(self.con > 0.5, 0.5, 0.6)
self.assertEqual(res.dtype, paddle.float32)

def test_where_with_complex128_scalar(self):
x = paddle.to_tensor([0.0, 0.0, 0.0, 0.0], dtype="complex128")
y = paddle.to_tensor([0.1, 0.1, 0.1, 0.1], dtype="complex128")

res = paddle.where(self.con > 0.5, x, y)
self.assertEqual(res.dtype, paddle.complex128)

res = paddle.where(self.con > 0.5, 0.5, y)
self.assertEqual(res.dtype, paddle.complex128)

res = paddle.where(self.con > 0.5, x, 0.6)
self.assertEqual(res.dtype, paddle.complex128)

res = paddle.where(self.con > 0.5, 0.5, 0.6)
self.assertEqual(res.dtype, paddle.float32)

def test_where_with_int_scalar(self):
x = paddle.to_tensor([2, 2, 2, 2], dtype="int32")
y = paddle.to_tensor([3, 3, 3, 3], dtype="int32")

res = paddle.where(self.con > 0.5, x, y)
self.assertEqual(res.dtype, paddle.int32)

# TODO(hanchao): Do not support int type promotion yet.
# res = paddle.where(self.con > 0.5, 3, y)
# self.assertEqual(res.dtype, paddle.int32)

# res = paddle.where(self.con > 0.5, x, 4)
# self.assertEqual(res.dtype, paddle.int32)
#
# res = paddle.where(self.con > 0.5, 3, 4)
# self.assertEqual(res.dtype, paddle.int32)

def test_where_with_float32_scalar_2D(self):
x = paddle.to_tensor([0.0, 0.0, 0.0, 0.0], dtype="float32")
y = paddle.to_tensor([0.1, 0.1, 0.1, 0.1], dtype="float32")

res = paddle.where(self.con_2D > 0.5, x, y)
self.assertEqual(res.dtype, paddle.float32)

res = paddle.where(self.con_2D > 0.5, 0.5, y)
self.assertEqual(res.dtype, paddle.float32)

res = paddle.where(self.con_2D > 0.5, x, 0.6)
self.assertEqual(res.dtype, paddle.float32)

res = paddle.where(self.con_2D > 0.5, 0.5, 0.6)
self.assertEqual(res.dtype, paddle.float32)


if __name__ == '__main__':
unittest.main()
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