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[ Dy2Static ] fix the outputs of net is x,x #44313

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Jul 14, 2022
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Original file line number Diff line number Diff line change
Expand Up @@ -441,18 +441,26 @@ def _prepare(self, inputs):
continue
input_vars.append(var)

# mapping from name(string) -> VarBase
out_varbase_map = {}

def create_out(var_id):
var = self._outputs[var_id]
assert isinstance(var, framework.Variable)
var_desc = var.desc
varbase = None

if var_desc.name() in out_varbase_map:
return out_varbase_map[var_desc.name()]

if not framework._in_eager_mode_:
var_base = core.VarBase(var_desc.dtype(), var_desc.shape(),
var_desc.name(), var_desc.type(), False)
else:
var_base = core.eager.Tensor(var_desc.dtype(), var_desc.shape(),
var_desc.name(), var_desc.type(),
False)
out_varbase_map[var_desc.name()] = var_base
return var_base

# Create VarBase to receive output data.
Expand Down
Original file line number Diff line number Diff line change
@@ -0,0 +1,65 @@
# 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 numpy as np
import unittest

import paddle

np.random.seed(1)

if paddle.fluid.is_compiled_with_cuda():
place = paddle.fluid.CUDAPlace(0)
else:
place = paddle.fluid.CPUPlace()


class SimpleNet(paddle.nn.Layer):

def __init__(self):
super().__init__()
self._linear = paddle.nn.Linear(1, 1)

def forward(self, x):
""" forward with duplicate outputs.
"""
x = self._linear(x)
return x, x


class TestDuplicateOutput(unittest.TestCase):
"""
TestCase for the transformation from control flow `if/else`
dependent on tensor in Dygraph into Static `fluid.layers.cond`.
"""

def setUp(self):
self.net = paddle.jit.to_static(SimpleNet())
self.x = paddle.to_tensor([1.0])

def _run_static(self):
loss0, loss1 = self.net(self.x)
loss0.backward()
param = self.net.parameters()
self.assertEqual(param[0].grad.numpy(), 1.0)

def test_ast_to_func(self):
self._run_static()


if __name__ == '__main__':
with paddle.fluid.framework._test_eager_guard():
unittest.main()