From 94bef03539da14527b448f56fc42f910a074bba9 Mon Sep 17 00:00:00 2001 From: ruri Date: Tue, 3 Dec 2019 13:02:43 +0800 Subject: [PATCH] Revert "Add masked select api (#21172)" (#21456) This reverts commit 007c9975727ca6ab28b253bc8bdee0dfae832073. --- python/paddle/fluid/layers/nn.py | 63 +------------------ .../fluid/tests/unittests/test_layers.py | 11 ---- .../tests/unittests/test_masked_select.py | 54 ---------------- 3 files changed, 1 insertion(+), 127 deletions(-) delete mode 100644 python/paddle/fluid/tests/unittests/test_masked_select.py diff --git a/python/paddle/fluid/layers/nn.py b/python/paddle/fluid/layers/nn.py index 0386159b5bf..322fd65cc7d 100644 --- a/python/paddle/fluid/layers/nn.py +++ b/python/paddle/fluid/layers/nn.py @@ -28,7 +28,7 @@ from ..framework import Variable, OpProtoHolder, in_dygraph_mode from ..dygraph import base from ..param_attr import ParamAttr from .layer_function_generator import autodoc, templatedoc, _generate_doc_string_ -from .tensor import concat, assign, fill_constant, zeros, cast +from .tensor import concat, assign, fill_constant, zeros from . import utils from .. import unique_name from functools import reduce @@ -183,7 +183,6 @@ __all__ = [ 'hard_swish', 'gather_tree', 'uniform_random', - 'masked_select', ] @@ -13620,63 +13619,3 @@ def uniform_random(shape, dtype='float32', min=-1.0, max=1.0, seed=0): outputs={"Out": out}) return helper.append_activation(out) - - -def masked_select(input, mask): - """ - This OP selects elements of the input tensor according to the mask tensor. - The shapes of the mask tensor don't have to match shapes of input tensor, but they must be broadcastable, and the result is a new 1-D tensor. - - NOTE: The meaning of broadcastable is consistent with expand_as. - - Parameters: - - input(Variable): The input tensor, the data type should be int32, float32, float64. - mask(Variable): The boolean mask tensor, the data type should be bool. - - Returns: - Variable: masked select tensor, its data type is same as the input. - - Examples: - .. code-block:: python - - import paddle.fluid as fluid - import numpy as np - mask_shape = [4,1] - shape = [4,4] - data = np.random.random(mask_shape).astype("float32") - input_data = np.random.randint(5,size=shape).astype("float32") - mask_data = data > 0.5 - - # print(input_data) - # [[0.38972723 0.36218056 0.7892614 0.50122297] - # [0.14408113 0.85540855 0.30984417 0.7577004 ] - # [0.97263193 0.5248062 0.07655851 0.75549215] - # [0.26214206 0.32359877 0.6314582 0.2128865 ]] - - # print(mask_data) - # [[ True] - # [ True] - # [False] - # [ True]] - - input = fluid.data(name="input",shape=[4,4],dtype="float32") - mask = fluid.data(name="mask",shape=[4,1],dtype="bool") - result = fluid.layers.masked_select(input=input, mask=mask) - place = fluid.CPUPlace() - exe = fluid.Executor(place) - start = fluid.default_startup_program() - main = fluid.default_main_program() - exe.run(start) - masked_select_result= exe.run(main, feed={'input':input_data, 'mask':mask_data}, fetch_list=[result]) - # print(masked_select_result) - # [0.38972723 0.36218056 0.7892614 0.50122297 0.14408113 0.85540855 - # 0.30984417 0.7577004 0.26214206 0.32359877 0.6314582 0.2128865 ] - - """ - mask_cast = cast(x=mask, dtype=input.dtype) - mask_expand = expand_as(x=mask_cast, target_tensor=input) - mask_expand_cast_back_bool = cast(x=mask_expand, dtype="bool") - select = where(mask_expand_cast_back_bool) - result = gather_nd(input, select) - return result diff --git a/python/paddle/fluid/tests/unittests/test_layers.py b/python/paddle/fluid/tests/unittests/test_layers.py index e1803f0ca38..ca7efebfb79 100644 --- a/python/paddle/fluid/tests/unittests/test_layers.py +++ b/python/paddle/fluid/tests/unittests/test_layers.py @@ -1640,9 +1640,6 @@ class TestBook(LayerTest): elif dtype == 'int64': return np.random.randint(self._low_data_bound, self._high_data_bound, shape).astype(dtype) - elif dtype == 'bool': - return np.random.randint(self._low_data_bound, - self._high_data_bound, shape).astype(dtype) def _get_data(self, name, @@ -2574,14 +2571,6 @@ class TestBook(LayerTest): out = layers.square_error_cost(input=x, label=y) return (out) - def make_masked_select(self): - with program_guard(fluid.default_main_program(), - fluid.default_startup_program()): - x = self._get_data(name="X", shape=[4, 4], dtype="float32") - y = self._get_data(name="Y", shape=[1, 4], dtype="bool") - out = layers.masked_select(input=x, mask=y) - return (out) - def test_dynamic_lstmp(self): # TODO(minqiyang): dygraph do not support lod now with self.static_graph(): diff --git a/python/paddle/fluid/tests/unittests/test_masked_select.py b/python/paddle/fluid/tests/unittests/test_masked_select.py deleted file mode 100644 index c2e087fdd9a..00000000000 --- a/python/paddle/fluid/tests/unittests/test_masked_select.py +++ /dev/null @@ -1,54 +0,0 @@ -# Copyright (c) 2019 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 sys -import paddle.fluid.core as core -import paddle.fluid as fluid -import paddle.fluid.layers as layers -from paddle.fluid.executor import Executor - - -class TestMaskedSelect(unittest.TestCase): - def test_masked_select(self): - - mask_shape = [4, 1] - shape = [4, 4] - data = np.random.random(mask_shape).astype("float32") - input_data = np.random.random(shape).astype("float32") - mask_data = data > 0.5 - mask_data_b = np.broadcast_to(mask_data, shape) - npresult = input_data[np.where(mask_data_b)] - - input_var = layers.create_tensor(dtype="float32", name="input") - mask_var = layers.create_tensor(dtype="bool", name="mask") - - output = layers.masked_select(input=input_var, mask=mask_var) - for use_cuda in ([False, True] - if core.is_compiled_with_cuda() else [False]): - place = fluid.CUDAPlace(0) if use_cuda else fluid.CPUPlace() - exe = Executor(place) - result = exe.run(fluid.default_main_program(), - feed={"input": input_data, - "mask": mask_data}, - fetch_list=[output]) - - self.assertTrue(np.isclose(npresult, result).all()) - - -if __name__ == "__main__": - unittest.main() -- GitLab