提交 ab8cc401 编写于 作者: Q qijun

add sparse sgd operator unittest

上级 330c509b
...@@ -37,7 +37,8 @@ class SGDOpKernel : public framework::OpKernel<T> { ...@@ -37,7 +37,8 @@ class SGDOpKernel : public framework::OpKernel<T> {
auto* learning_rate = ctx.Input<framework::Tensor>("LearningRate"); auto* learning_rate = ctx.Input<framework::Tensor>("LearningRate");
auto* grad_var = ctx.InputVar("Grad"); auto* grad_var = ctx.InputVar("Grad");
if (grad_var->IsType<framework::Tensor>()) { // Actually, all tensors are LoDTensor except SelectedRows.
if (grad_var->IsType<framework::LoDTensor>()) {
param_out->mutable_data<T>(ctx.GetPlace()); param_out->mutable_data<T>(ctx.GetPlace());
auto* grad = ctx.Input<framework::Tensor>("Grad"); auto* grad = ctx.Input<framework::Tensor>("Grad");
......
...@@ -186,6 +186,11 @@ All parameter, weight, gradient are variables in Paddle. ...@@ -186,6 +186,11 @@ All parameter, weight, gradient are variables in Paddle.
return self.GetMutable<LoDTensor>(); return self.GetMutable<LoDTensor>();
}, },
py::return_value_policy::reference) py::return_value_policy::reference)
.def("get_selected_rows",
[](Variable &self) -> SelectedRows * {
return self.GetMutable<SelectedRows>();
},
py::return_value_policy::reference)
.def("get_net", .def("get_net",
[](Variable &self) -> operators::NetOp * { [](Variable &self) -> operators::NetOp * {
return self.GetMutable<operators::NetOp>(); return self.GetMutable<operators::NetOp>();
......
...@@ -8,29 +8,30 @@ class TestSelectedRows(unittest.TestCase): ...@@ -8,29 +8,30 @@ class TestSelectedRows(unittest.TestCase):
place = core.CPUPlace() place = core.CPUPlace()
height = 10 height = 10
rows = [0, 4, 7] rows = [0, 4, 7]
row_numel = 10 row_numel = 12
selcted_rows = core.SelectedRows(rows, row_numel) selected_rows = core.SelectedRows(rows, height)
np_array = np.ones((len(rows), height)).astype("float32") np_array = np.ones((len(rows), row_numel)).astype("float32")
np_array[0, 0] = 2.0 np_array[0, 0] = 2.0
np_array[2, 8] = 4.0 np_array[2, 8] = 4.0
tensor = selcted_rows.get_tensor() tensor = selected_rows.get_tensor()
tensor.set(np_array, place) tensor.set(np_array, place)
# compare rows # compare rows
self.assertEqual(0, selcted_rows.rows()[0]) self.assertEqual(0, selected_rows.rows()[0])
self.assertEqual(4, selcted_rows.rows()[1]) self.assertEqual(4, selected_rows.rows()[1])
self.assertEqual(7, selcted_rows.rows()[2]) self.assertEqual(7, selected_rows.rows()[2])
# compare height # compare height
self.assertEqual(10, selcted_rows.height()) self.assertEqual(10, selected_rows.height())
# compare tensor # compare tensor
self.assertAlmostEqual(2.0, self.assertAlmostEqual(2.0,
selcted_rows.get_tensor().get_float_element(0)) selected_rows.get_tensor().get_float_element(0))
self.assertAlmostEqual(1.0, self.assertAlmostEqual(1.0,
selcted_rows.get_tensor().get_float_element(1)) selected_rows.get_tensor().get_float_element(1))
self.assertAlmostEqual( self.assertAlmostEqual(
4.0, selcted_rows.get_tensor().get_float_element(2 * row_numel + 8)) 4.0,
selected_rows.get_tensor().get_float_element(2 * row_numel + 8))
if __name__ == "__main__": if __name__ == "__main__":
......
import unittest import unittest
import numpy as np import numpy as np
import paddle.v2.framework.core as core
from paddle.v2.framework.op import Operator
from op_test import OpTest from op_test import OpTest
...@@ -17,5 +19,63 @@ class TestSGDOp(OpTest): ...@@ -17,5 +19,63 @@ class TestSGDOp(OpTest):
self.check_output() self.check_output()
class TestSparseSGDOp(unittest.TestCase):
def test_sparse_sgd(self):
scope = core.Scope()
# create and initialize Grad Variable
place = core.CPUPlace()
height = 10
rows = [0, 4, 7]
row_numel = 12
grad_selected_rows = scope.var('Grad').get_selected_rows()
grad_selected_rows.set_height(height)
grad_selected_rows.set_rows(rows)
np_array = np.ones((len(rows), row_numel)).astype("float32")
np_array[0, 0] = 2.0
np_array[2, 8] = 4.0
grad_tensor = grad_selected_rows.get_tensor()
grad_tensor.set(np_array, place)
# create and initialize Param Variable
param = scope.var('Param').get_tensor()
param_array = np.full((height, row_numel), 5.0).astype("float32")
param.set(param_array, place)
# create and initialize LeraningRate Variable
lr = scope.var('LearningRate').get_tensor()
lr_array = np.full((1), 2.0).astype("float32")
lr.set(lr_array, place)
# create and run sgd operator
sgd_op = Operator(
"sgd",
Param='Param',
Grad='Grad',
ParamOut='Param',
LearningRate='LearningRate')
ctx = core.DeviceContext.create(place)
sgd_op.run(scope, ctx)
# get and compare result
result_array = np.array(param)
# rows[0] = 0, 5.0 - 2.0 * 2.0
self.assertAlmostEqual(1.0, result_array[rows[0], 0])
# rows[0] = 0, 5.0 - 2.0 * 1.0
self.assertAlmostEqual(3.0, result_array[rows[0], 2])
# 5.0 - 2.0 * 0.0
self.assertAlmostEqual(5.0, result_array[1, 0])
# rows[1] = 4, 5.0 - 2.0 * 1.0
self.assertAlmostEqual(3.0, result_array[rows[1], 10])
# 5.0 - 2.0 * 0.0
self.assertAlmostEqual(5.0, result_array[5, 8])
# rows[2] = 7, 5.0 - 2.0 * 1.0
self.assertAlmostEqual(3.0, result_array[rows[2], 1])
# rows[2] = 7, 5.0 - 2.0 * 4.0
self.assertAlmostEqual(-3.0, result_array[rows[2], 8])
if __name__ == "__main__": if __name__ == "__main__":
unittest.main() unittest.main()
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