You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
93 lines
3.5 KiB
93 lines
3.5 KiB
# 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.
|
|
|
|
from __future__ import print_function
|
|
|
|
import unittest
|
|
import paddle.fluid as fluid
|
|
import paddle.fluid.core as core
|
|
from paddle.fluid.dygraph.nn import Embedding
|
|
import paddle.fluid.framework as framework
|
|
from paddle.fluid.optimizer import SGDOptimizer
|
|
from paddle.fluid.dygraph.base import to_variable
|
|
from test_imperative_base import new_program_scope
|
|
import numpy as np
|
|
import six
|
|
|
|
|
|
class RecurrentTest(fluid.Layer):
|
|
def __init__(self, name_scope):
|
|
super(RecurrentTest, self).__init__(name_scope)
|
|
|
|
def forward(self, in1, in2):
|
|
out = fluid.layers.mul(in1, in2)
|
|
sum_out = fluid.layers.reduce_sum(out)
|
|
return sum_out, out
|
|
|
|
|
|
class TestRecurrentFeed(unittest.TestCase):
|
|
def test_recurrent_feed(self):
|
|
|
|
seed = 90
|
|
original_np1 = np.arange(1, 5).reshape(2, 2).astype("float32")
|
|
original_np2 = np.arange(5, 9).reshape(2, 2).astype("float32")
|
|
with fluid.dygraph.guard():
|
|
fluid.default_startup_program().random_seed = seed
|
|
fluid.default_main_program().random_seed = seed
|
|
original_in1 = to_variable(original_np1)
|
|
original_in2 = to_variable(original_np2)
|
|
rt = RecurrentTest("RecurrentTest")
|
|
|
|
for i in range(3):
|
|
sum_out, out = rt(original_in1, original_in2)
|
|
original_in1 = out
|
|
sum_out_value = sum_out.numpy()
|
|
sum_out.backward()
|
|
dyout = out.gradient()
|
|
rt.clear_gradients()
|
|
|
|
with new_program_scope():
|
|
fluid.default_startup_program().random_seed = seed
|
|
fluid.default_main_program().random_seed = seed
|
|
in1 = fluid.layers.data(
|
|
name="inp1", shape=[2, 2], append_batch_size=False)
|
|
in2 = fluid.layers.data(
|
|
name="inp2", shape=[2, 2], append_batch_size=False)
|
|
rt1 = RecurrentTest("RecurrentTest")
|
|
static_sum_out, static_out = rt1(in1, in2)
|
|
fluid.backward.append_backward(static_sum_out)
|
|
exe = fluid.Executor(fluid.CPUPlace(
|
|
) if not core.is_compiled_with_cuda() else fluid.CUDAPlace(0))
|
|
|
|
static_dout = fluid.default_main_program().block(
|
|
0)._find_var_recursive(static_out.name + "@GRAD")
|
|
fetch_list = [static_sum_out, static_out, static_dout]
|
|
for i in range(3):
|
|
out = exe.run(
|
|
fluid.default_main_program(),
|
|
feed={"inp1": original_np1,
|
|
"inp2": original_np2},
|
|
fetch_list=fetch_list)
|
|
static_out_value = out[1]
|
|
static_sum_out = out[0]
|
|
static_dout = out[2]
|
|
original_np1 = static_out_value
|
|
|
|
self.assertTrue(np.array_equal(static_sum_out, sum_out_value))
|
|
self.assertTrue(np.array_equal(static_dout, dyout))
|
|
|
|
|
|
if __name__ == '__main__':
|
|
unittest.main()
|