提交 3a8017d1 编写于 作者: F fengjiayi

Merge branch 'backward_dev' into dev_add_FillZerosLikeOp_test

......@@ -13,8 +13,6 @@ See the License for the specific language governing permissions and
limitations under the License. */
#include "paddle/operators/fill_zeros_like_op.h"
#include "paddle/framework/op_registry.h"
#include "paddle/framework/tensor.h"
namespace paddle {
namespace operators {
......
......@@ -13,9 +13,7 @@ See the License for the specific language governing permissions and
limitations under the License. */
#pragma once
#include "glog/logging.h"
#include "paddle/framework/eigen.h"
#include "paddle/framework/operator.h"
#include "paddle/operators/type_alias.h"
namespace paddle {
namespace operators {
......
cc_library(paddle_pybind SHARED SRCS pybind.cc DEPS pybind python
add_op fc_op sgd_op cross_entropy_op recurrent_network_op)
add_op fc_op sgd_op cross_entropy_op recurrent_network_op fill_zeros_like_op)
......@@ -37,6 +37,7 @@ USE_OP(sigmoid);
USE_OP(softmax);
USE_OP(rowwise_add);
USE_OP_WITHOUT_KERNEL(recurrent_op);
USE_OP(fill_zeros_like);
template <typename ClassType>
void ExposeOperator(ClassType& m) {
......
......@@ -13,4 +13,5 @@ add_python_test(test_framework
test_sigmoid_op.py
test_softmax_op.py
test_rowwise_add_op.py
test_fill_zeros_like_op.py
test_network.py)
import unittest
import paddle.v2.framework.create_op_creation_methods as creation
import paddle.v2.framework.core as core
from op_test_util import OpTestMeta
import numpy
class TestFillZerosLikeOp(unittest.TestCase):
def test_fill(self):
scope = core.Scope(None)
a = scope.create_var("input")
a_tensor = a.get_tensor()
a_tensor.set_dims([546, 291])
a_tensor.alloc_float()
a_tensor.set(numpy.random.random((546, 291)).astype("float32"))
op = creation.op_creations.fill_zeros_like(Src="input", Dst="output")
for out in op.outputs():
if scope.get_var(out) is None:
scope.create_var(out).get_tensor()
b_tensor = scope.get_var("output").get_tensor()
op.infer_shape(scope)
self.assertEqual([546, 291], b_tensor.shape())
ctx = core.DeviceContext.cpu_context()
op.run(scope, ctx)
b_tensor_array = numpy.array(b_tensor)
for r in range(0, 546):
for c in range(0, 291):
self.assertEqual(b_tensor_array[r][c], 0.0)
if __name__ == '__main__':
unittest.main()
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