# Copyright (c) 2018 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.fluid.core as core from paddle.fluid.op import Operator class TestSumOp(OpTest): def setUp(self): self.op_type = "sum" self.use_mkldnn = False self.init_kernel_type() x0 = np.random.random((3, 4)).astype('float32') x1 = np.random.random((3, 4)).astype('float32') x2 = np.random.random((3, 4)).astype('float32') self.inputs = {"X": [("x0", x0), ("x1", x1), ("x2", x2)]} y = x0 + x1 + x2 self.outputs = {'Out': y} self.attrs = {'use_mkldnn': self.use_mkldnn} def test_check_output(self): self.check_output() def test_check_grad(self): self.check_grad(['x0'], 'Out') def init_kernel_type(self): pass class TestSelectedRowsSumOp(OpTest): def check_with_place(self, place): scope = core.Scope() self.check_input_and_optput(scope, place, True, True, True) self.check_input_and_optput(scope, place, False, True, True) self.check_input_and_optput(scope, place, False, False, True) self.check_input_and_optput(scope, place, False, False, False) def check_input_and_optput(self, scope, place, w1=False, w2=False, w3=False): W1 = self.create_selected_rows(scope, place, "W1", w1) W2 = self.create_selected_rows(scope, place, "W2", w2) W3 = self.create_selected_rows(scope, place, "W3", w3) # create Out Variable out = scope.var('Out').get_selected_rows() # create and run sum operator sum_op = Operator("sum", X=["W1", "W2", "W3"], Out='Out') sum_op.run(scope, place) trues = 0 for w in [w1, w2, w3]: if not w: trues += 1 self.assertEqual(7 * trues, len(out.rows())) def create_selected_rows(self, scope, place, var_name, isEmpty): # create and initialize W Variable if not isEmpty: rows = [0, 1, 2, 3, 4, 5, 6] row_numel = 12 else: rows = [] row_numel = 12 var = scope.var(var_name) w_selected_rows = var.get_selected_rows() w_selected_rows.set_height(len(rows)) w_selected_rows.set_rows(rows) w_array = np.ones((len(rows), row_numel)).astype("float32") for i in range(len(rows)): w_array[i] *= i w_tensor = w_selected_rows.get_tensor() w_tensor.set(w_array, place) return var def test_w_is_selected_rows(self): places = [core.CPUPlace()] # currently only support CPU for place in places: self.check_with_place(place) if __name__ == "__main__": unittest.main()