From a6c50a6c09f99a21caeaff5c9979d5af5cf0b5b1 Mon Sep 17 00:00:00 2001 From: thunder95 <290844930@qq.com> Date: Fri, 29 Jul 2022 15:20:40 +0800 Subject: [PATCH] =?UTF-8?q?=E3=80=90PaddlePaddle=20Hackathon=203=20No.15?= =?UTF-8?q?=E3=80=91=E4=B8=BA=20Paddle=20=E6=96=B0=E5=A2=9E=20count=5Fnonz?= =?UTF-8?q?ero=20(#44169)?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit * add count_nonzero api * remove grad test --- python/paddle/__init__.py | 2 + .../tests/unittests/test_count_nonzero_api.py | 86 +++++++++++++++++++ python/paddle/tensor/__init__.py | 2 + python/paddle/tensor/math.py | 66 ++++++++++++++ 4 files changed, 156 insertions(+) create mode 100644 python/paddle/fluid/tests/unittests/test_count_nonzero_api.py diff --git a/python/paddle/__init__.py b/python/paddle/__init__.py index 6e47f4f9eab..23e1d7551f9 100755 --- a/python/paddle/__init__.py +++ b/python/paddle/__init__.py @@ -220,6 +220,7 @@ from .tensor.math import stanh # noqa: F401 from .tensor.math import sum # noqa: F401 from .tensor.math import nansum # noqa: F401 from .tensor.math import nanmean # noqa: F401 +from .tensor.math import count_nonzero # noqa: F401 from .tensor.math import tanh # noqa: F401 from .tensor.math import tanh_ # noqa: F401 from .tensor.math import add_n # noqa: F401 @@ -560,6 +561,7 @@ __all__ = [ # noqa 'sum', 'nansum', 'nanmean', + 'count_nonzero', 'tile', 'greater_equal', 'isfinite', diff --git a/python/paddle/fluid/tests/unittests/test_count_nonzero_api.py b/python/paddle/fluid/tests/unittests/test_count_nonzero_api.py new file mode 100644 index 00000000000..8f1d4fe8500 --- /dev/null +++ b/python/paddle/fluid/tests/unittests/test_count_nonzero_api.py @@ -0,0 +1,86 @@ +# 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. + +from __future__ import print_function + +import unittest +import numpy as np +import paddle +import paddle.fluid as fluid +import paddle.fluid.core as core +from paddle.fluid import Program, program_guard + +np.random.seed(10) + + +class TestCountNonzeroAPI(unittest.TestCase): + # test paddle.tensor.math.count_nonzero + + def setUp(self): + self.x_shape = [2, 3, 4, 5] + self.x = np.random.uniform(-1, 1, self.x_shape).astype(np.float32) + self.place = paddle.CUDAPlace(0) if core.is_compiled_with_cuda() \ + else paddle.CPUPlace() + + def test_api_static(self): + paddle.enable_static() + with paddle.static.program_guard(paddle.static.Program()): + x = paddle.fluid.data('X', self.x_shape) + out1 = paddle.count_nonzero(x) + out2 = paddle.tensor.count_nonzero(x) + out3 = paddle.tensor.math.count_nonzero(x) + axis = np.arange(len(self.x_shape)).tolist() + out4 = paddle.count_nonzero(x, axis) + out5 = paddle.count_nonzero(x, tuple(axis)) + exe = paddle.static.Executor(self.place) + res = exe.run(feed={'X': self.x}, + fetch_list=[out1, out2, out3, out4, out5]) + out_ref = np.count_nonzero(self.x) + for out in res: + self.assertEqual(np.allclose(out, out_ref), True) + + def test_api_dygraph(self): + paddle.disable_static(self.place) + + def test_case(x, axis=None, keepdim=False): + x_tensor = paddle.to_tensor(x) + out = paddle.count_nonzero(x_tensor, axis=axis, keepdim=keepdim) + if isinstance(axis, list): + axis = tuple(axis) + if len(axis) == 0: + axis = None + + out_ref = np.count_nonzero(x, axis, keepdims=keepdim) + self.assertEqual(np.allclose(out.numpy(), out_ref), True) + + test_case(self.x) + test_case(self.x, None) + test_case(self.x, -1) + test_case(self.x, keepdim=True) + test_case(self.x, 2, keepdim=True) + test_case(self.x, [0, 2]) + test_case(self.x, (0, 2)) + test_case(self.x, (0, 1, 3)) + test_case(self.x, [0, 1, 2, 3]) + paddle.enable_static() + + def test_errors(self): + paddle.enable_static() + with paddle.static.program_guard(paddle.static.Program()): + x = paddle.fluid.data('X', [10, 12], 'int32') + self.assertRaises(ValueError, paddle.count_nonzero, x, axis=10) + + +if __name__ == "__main__": + unittest.main() diff --git a/python/paddle/tensor/__init__.py b/python/paddle/tensor/__init__.py index 08b0af26bd4..f4820bbbbc1 100755 --- a/python/paddle/tensor/__init__.py +++ b/python/paddle/tensor/__init__.py @@ -168,6 +168,7 @@ from .math import stanh # noqa: F401 from .math import sum # noqa: F401 from .math import nansum # noqa: F401 from .math import nanmean # noqa: F401 +from .math import count_nonzero # noqa: F401 from .math import tanh # noqa: F401 from .math import tanh_ # noqa: F401 from .math import add_n # noqa: F401 @@ -343,6 +344,7 @@ tensor_method_func = [ #noqa 'sum', 'nansum', 'nanmean', + 'count_nonzero', 'tanh', 'tanh_', 'add_n', diff --git a/python/paddle/tensor/math.py b/python/paddle/tensor/math.py index 088c5fbeaf8..c85d9226e67 100644 --- a/python/paddle/tensor/math.py +++ b/python/paddle/tensor/math.py @@ -1315,6 +1315,72 @@ def nanmean(x, axis=None, keepdim=False, name=None): return paddle.divide(paddle.nansum(x, axis=axis, keepdim=keepdim, name=name), cnt.astype(x.dtype)) +def count_nonzero(x, axis=None, keepdim=False, name=None): + r""" + Counts the number of non-zero values in the tensor x along the specified axis. + + Args: + x (Tensor): An N-D Tensor, the data type is bool, float16, float32, float64, int32 or int64. + axis (int|list|tuple, optional): The dimensions along which the sum is performed. If + :attr:`None`, sum all elements of :attr:`x` and return a + Tensor with a single element, otherwise must be in the + range :math:`[-rank(x), rank(x))`. If :math:`axis[i] < 0`, + the dimension to reduce is :math:`rank + axis[i]`. + keepdim (bool, optional): Whether to reserve the reduced dimension in the + output Tensor. The result Tensor will have one fewer dimension + than the :attr:`x` unless :attr:`keepdim` is true, default + value is False. + name (str, optional): Name for the operation (optional, default is None). For more information, please refer to :ref:`api_guide_Name`. + + Returns: + Tensor: Results of count operation on the specified axis of input Tensor `x`, it's data type is `'int64'`. + + Examples: + + .. code-block:: python + :name: count_nonzero-example + + import paddle + # x is a 2-D Tensor: + x = paddle.to_tensor([[0., 1.1, 1.2], [0., 0., 1.3], [0., 0., 0.]]) + out1 = paddle.count_nonzero(x) + # [3] + out2 = paddle.count_nonzero(x, axis=0) + # [0, 1, 2] + out3 = paddle.count_nonzero(x, axis=0, keepdim=True) + # [[0, 1, 2]] + out4 = paddle.count_nonzero(x, axis=1) + # [2, 1, 0] + out5 = paddle.count_nonzero(x, axis=1, keepdim=True) + #[[2], + # [1], + # [0]] + + # y is a 3-D Tensor: + y = paddle.to_tensor([[[0., 1.1, 1.2], [0., 0., 1.3], [0., 0., 0.]], + [[0., 2.5, 2.6], [0., 0., 2.4], [2.1, 2.2, 2.3]]]) + out6 = paddle.count_nonzero(y, axis=[1, 2]) + # [3, 6] + out7 = paddle.count_nonzero(y, axis=[0, 1]) + # [1, 3, 5] + """ + + + if axis is not None: + if isinstance(axis, int): + axis = [axis] + dims = len(x.shape) + for i in range(len(axis)): + if not isinstance(axis[i], int) or not (axis[i] < dims and axis[i] >= -dims): + raise ValueError( + "Axis should be None, int, or a list, element should in range [-rank(x), rank(x))." + ) + + bool_tensor = paddle.cast(x, 'bool') + int_tensor = paddle.cast(bool_tensor, 'int64') + return paddle.sum(int_tensor, axis=axis, keepdim=keepdim, name=name) + + @templatedoc(op_type="sum") def add_n(inputs, name=None): """ -- GitLab