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Adding L2 Regularization to Recognize digits MLP example #5186

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Oct 28, 2017
Merged

Adding L2 Regularization to Recognize digits MLP example #5186

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77fccf7
Adding L2 Regularization to Recognize digits MLP example
Oct 28, 2017
11e011d
Merge remote-tracking branch 'origin/develop' into recog_digits_reg
Oct 28, 2017
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10 changes: 6 additions & 4 deletions python/paddle/v2/framework/layer_helper.py
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Original file line number Diff line number Diff line change
Expand Up @@ -131,12 +131,14 @@ def input_dtype(self, input_param_name='input'):
return dtype

def create_parameter(self, attr, shape, dtype, suffix='w'):
if attr['name'] is None:
attr['name'] = unique_name(".".join([self.name, suffix]))
# Deepcopy the attr so that parameters can be shared in program
attr_copy = copy.deepcopy(attr)
if attr_copy['name'] is None:
attr_copy['name'] = unique_name(".".join([self.name, suffix]))
self.init_program.global_block().create_parameter(
dtype=dtype, shape=shape, **attr)
dtype=dtype, shape=shape, **attr_copy)
return self.program.global_block().create_parameter(
name=attr['name'], dtype=dtype, shape=shape)
name=attr_copy['name'], dtype=dtype, shape=shape)

def create_tmp_variable(self, dtype):
return self.program.current_block().create_var(
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23 changes: 18 additions & 5 deletions python/paddle/v2/framework/tests/test_recognize_digits_mlp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -5,9 +5,11 @@

from paddle.v2.framework.framework import Program, g_program
from paddle.v2.framework.executor import Executor
from paddle.v2.framework.regularizer import L2DecayRegularizer

import numpy as np

BATCH_SIZE = 128
init_program = Program()
program = Program()
image = layers.data(
Expand All @@ -17,22 +19,35 @@
program=program,
init_program=init_program)

param_attr = {
'name': None,
'init_attr': {
'type': 'uniform_random',
'min': -1.0,
'max': 1.0
},
'regularization': L2DecayRegularizer(0.0005 * BATCH_SIZE)
}

hidden1 = layers.fc(input=image,
size=128,
act='relu',
program=program,
init_program=init_program)
init_program=init_program,
param_attr=param_attr)
hidden2 = layers.fc(input=hidden1,
size=64,
act='relu',
program=program,
init_program=init_program)
init_program=init_program,
param_attr=param_attr)

predict = layers.fc(input=hidden2,
size=10,
act='softmax',
program=program,
init_program=init_program)
init_program=init_program,
param_attr=param_attr)

label = layers.data(
name='y',
Expand All @@ -48,8 +63,6 @@
sgd_optimizer = optimizer.SGDOptimizer(learning_rate=0.001)
opts = sgd_optimizer.minimize(avg_cost)

BATCH_SIZE = 128

train_reader = paddle.batch(
paddle.reader.shuffle(
paddle.dataset.mnist.train(), buf_size=8192),
Expand Down