for i in range(EPOCH_NUM):
reader.start()
while True:
try:
executor.run(feed=None)
except fluid.core.EOFException:
reader.reset()
break
Executor.run(feed=...)
import paddle
import paddle.fluid as fluid
import numpy as np
EPOCH_NUM = 3
ITER_NUM = 5
BATCH_SIZE = 10
def network(image, label):
# softmax
predict = fluid.layers.fc(input=image, size=10, act='softmax')
return fluid.layers.cross_entropy(input=predict, label=label)
def reader_creator_random_image(height, width):
def reader():
for i in range(ITER_NUM):
fake_image = np.random.uniform(low=0, high=255, size=[height, width]),
fake_label = np.ones([1])
yield fake_image, fake_label
return reader
image = fluid.layers.data(name='image', shape=[784, 784], dtype='float32')
label = fluid.layers.data(name='label', shape=[1], dtype='int64')
reader = fluid.io.PyReader(feed_list=[image, label], capacity=4, iterable=True, ret
urn_list=False)
user_defined_reader = reader_creator_random_image(784, 784)
reader.decorate_sample_list_generator(
paddle.batch(user_defined_reader, batch_size=BATCH_SIZE),
fluid.core.CPUPlace())