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336 lines
11 KiB
336 lines
11 KiB
# Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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import unittest
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import numpy as np
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import paddle
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import paddle.fluid as fluid
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from paddle.fluid.dygraph import to_variable
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from paddle.fluid.framework import ParamBase
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from paddle.jit import ProgramTranslator
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class L1(fluid.Layer):
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def __init__(self):
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super(L1, self).__init__()
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self._param_attr = fluid.ParamAttr(
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initializer=fluid.initializer.Constant(value=0.1))
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self.w1 = self.create_parameter(
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attr=self._param_attr, shape=[2, 2], dtype='float32', is_bias=False)
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self.w2 = self.create_parameter(
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attr=self._param_attr, shape=[2, 2], dtype='float32', is_bias=False)
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def forward(self):
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return self.w1 + self.w2
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class L2(fluid.Layer):
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def __init__(self):
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super(L2, self).__init__()
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self.layer1 = L1()
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self.layer2 = L1()
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def forward(self):
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return self.layer1() + self.layer2()
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class L3(fluid.Layer):
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def __init__(self):
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super(L3, self).__init__()
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self.layer1 = L2()
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self.layer2 = L2()
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def forward(self):
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return self.layer1() + self.layer2()
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class TestBaseLayer(unittest.TestCase):
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def test_one_level(self):
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with fluid.dygraph.guard():
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l = L1()
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ret = l()
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expected_names = ['l1.w1', 'l1.w2']
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idx = 0
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for name, _ in l.named_parameters(prefix='l1'):
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self.assertEqual(name, expected_names[idx])
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idx += 1
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self.assertTrue(np.allclose(ret.numpy(), 0.2 * np.ones([2, 2])))
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def test_three_level(self):
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with fluid.dygraph.guard():
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l = L3()
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expected_names = [
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'l3.layer1.layer1.w1',
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'l3.layer1.layer1.w2',
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'l3.layer1.layer2.w1',
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'l3.layer1.layer2.w2',
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'l3.layer2.layer1.w1',
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'l3.layer2.layer1.w2',
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'l3.layer2.layer2.w1',
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'l3.layer2.layer2.w2',
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]
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idx = 0
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for name, _ in l.named_parameters(prefix='l3'):
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self.assertEqual(name, expected_names[idx])
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idx += 1
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ret = l()
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self.assertTrue(np.allclose(ret.numpy(), 0.8 * np.ones([2, 2])))
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def test_add_parameter_with_error(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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param = net.create_parameter(shape=[1])
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with self.assertRaises(TypeError):
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net.add_parameter(10, param)
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with self.assertRaises(KeyError):
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net.add_parameter("param.name", param)
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with self.assertRaises(KeyError):
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net.add_parameter("", param)
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with self.assertRaises(KeyError):
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net.test_param = 10
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net.add_parameter("test_param", param)
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with self.assertRaises(TypeError):
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net.add_parameter("no_param", 10)
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load_param = net.create_parameter(shape=[1])
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net._loaddict_holder[load_param.name] = load_param
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net.add_parameter("load_param", load_param)
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class BufferLayer(fluid.Layer):
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def __init__(self):
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super(BufferLayer, self).__init__()
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buffer_var = to_variable(np.zeros([2, 4]).astype('int32'))
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self.register_buffer("layer_buffer", buffer_var)
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def forward(self):
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pass
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class BufferNet(fluid.Layer):
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def __init__(self):
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super(BufferNet, self).__init__()
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self.buffer_layer = BufferLayer()
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self.w1 = self.create_parameter(
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shape=[2, 2], dtype='float32', is_bias=False)
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buffer_var = to_variable(np.ones([2, 4]).astype('int32'))
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self.register_buffer("net_buffer", buffer_var)
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self.new_buffer = to_variable(np.ones([4, 2]).astype('int32'))
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def forward(self):
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pass
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class TestBuffer(unittest.TestCase):
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def test_buffers_and_named_buffers(self):
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def names(named_buffers):
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return [name for name, _ in named_buffers]
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with fluid.dygraph.guard():
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layer = BufferLayer()
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net = BufferNet()
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self.assertEqual(len(layer.buffers()), 1)
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self.assertEqual(names(layer.named_buffers()), ['layer_buffer'])
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self.assertEqual(len(net.buffers()), 3)
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self.assertEqual(
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names(net.named_buffers()),
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['net_buffer', 'new_buffer', 'buffer_layer.layer_buffer'])
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self.assertEqual(len(net.buffers(include_sublayers=False)), 2)
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self.assertEqual(
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names(net.named_buffers(include_sublayers=False)),
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['net_buffer', 'new_buffer'])
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def test_register_buffer_with_error(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var = to_variable(np.zeros([1]))
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with self.assertRaisesRegexp(TypeError,
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"name of buffer should be a string"):
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net.register_buffer(12, var)
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with self.assertRaisesRegexp(TypeError,
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"buffer should be a core.VarBase"):
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net.register_buffer("buffer_name", ParamBase([2, 2], 'float32'))
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with self.assertRaisesRegexp(KeyError,
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"name of buffer can not contain"):
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net.register_buffer("buffer.name", var)
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with self.assertRaisesRegexp(KeyError,
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"name of buffer can not be empty"):
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net.register_buffer("", var)
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net.attr_name = 10
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with self.assertRaisesRegexp(KeyError, "already exists"):
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net.register_buffer("attr_name", var)
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del net.attr_name
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net.attr_name = ParamBase([2, 2], 'float32')
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with self.assertRaisesRegexp(KeyError, "already exists"):
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net.register_buffer("attr_name", var)
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def test_register_buffer_same_name(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([1]))
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var2 = to_variable(np.zeros([2]))
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var3 = to_variable(np.zeros([3]))
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net.register_buffer("buffer_name", var1)
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self.assert_var_base_equal(net.buffer_name, var1)
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net.register_buffer("buffer_name", var2)
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self.assert_var_base_equal(net.buffer_name, var2)
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net.register_buffer("buffer_name", var3)
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self.assert_var_base_equal(net.buffer_name, var3)
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def test_buffer_not_persistable(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([1]))
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net.register_buffer("buffer_name", var1, persistable=False)
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self.assertEqual(len(net.buffers()), 1)
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self.assertEqual(len(net.state_dict()), 0)
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def test_buffer_not_persistable_del(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([1]))
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net.register_buffer("buffer_name", var1, persistable=False)
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del net.buffer_name
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self.assertEqual(len(net.buffers()), 0)
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def test_buffer_not_persistable_overwrite(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([1]))
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var2 = to_variable(np.zeros([2]))
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net.register_buffer("buffer_name", var1, persistable=False)
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net.register_buffer("buffer_name", var2)
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# Allow to overwrite a non-persistable buffer with a persistable var.
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self.assertEqual(len(net.buffers()), 1)
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self.assertEqual(len(net.state_dict()), 1)
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net.register_buffer("buffer_name", var1, persistable=False)
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self.assertEqual(len(net.buffers()), 1)
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self.assertEqual(len(net.state_dict()), 0)
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def test_buffer_not_persistable_assign(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([1]))
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net.register_buffer("buffer_name", var1, persistable=False)
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# Assigning Nones will remove the buffer, but allow to re-assign
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# to remark it as buffer.
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net.buffer_name = None
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self.assertEqual(len(net.buffers()), 0)
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self.assertEqual(len(net.state_dict()), 0)
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net.buffer_name = var1
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self.assertEqual(len(net.buffers()), 1)
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self.assertEqual(len(net.state_dict()), 0)
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# Re-assign a ParamBase will remove the buffer.
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net.buffer_name = ParamBase([2, 2], 'float32')
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self.assertEqual(len(net.buffers()), 0)
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self.assertEqual(len(net.state_dict()), 1)
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def test_buffer_not_persistable_load(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([1]))
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net.register_buffer("buffer_name", var1, persistable=False)
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net.load_dict({})
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def test_buffer_state_dict(self):
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with fluid.dygraph.guard():
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net = fluid.Layer()
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var1 = to_variable(np.zeros([2, 3]))
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var2 = to_variable(np.zeros([3, 2]))
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net.register_buffer("buffer_var1", var1)
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net.register_buffer("buffer_var2", var2, persistable=False)
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self.assertEqual(len(net.state_dict()), 1)
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self.assertEqual([name for name, _ in net.state_dict().items()],
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["buffer_var1"])
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# load state_dict
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net_load = fluid.Layer()
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var = to_variable(np.ones([2, 3]))
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net_load.register_buffer("buffer_var1", var)
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net_load.load_dict(net.state_dict())
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self.assert_var_base_equal(net_load.buffer_var1, var1)
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def assert_var_base_equal(self, var1, var2):
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self.assertTrue(np.array_equal(var1.numpy(), var2.numpy()))
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class BufferNetWithModification(paddle.nn.Layer):
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def __init__(self, shape):
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super(BufferNetWithModification, self).__init__()
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self.buffer1 = paddle.zeros(shape, 'int32')
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self.buffer2 = paddle.zeros(shape, 'int32')
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@paddle.jit.to_static
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def forward(self, x):
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self.buffer1 += x
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self.buffer2 = self.buffer1 + x
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out = self.buffer1 + self.buffer2
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return out
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class TestModifiedBuffer(unittest.TestCase):
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def setUp(self):
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paddle.disable_static()
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self.prog_trans = ProgramTranslator()
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self.shape = [10, 16]
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def _run(self, to_static=False):
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self.prog_trans.enable(to_static)
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x = paddle.ones([1], 'int32')
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net = BufferNetWithModification(self.shape)
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out = net(x)
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return out, net.buffer1, net.buffer2
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def test_modified(self):
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dy_outs = self._run(False)
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st_outs = self._run(True)
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for i in range(len(dy_outs)):
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self.assertTrue(
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np.array_equal(dy_outs[i].numpy(), st_outs[i].numpy()))
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if __name__ == '__main__':
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unittest.main()
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