Created by: shaoshenchen

paddle版本：1.7.1 在训练时没报错但是输出不正常 我在想应该是数据的某一环节出了问题，看了好久都没思路......

import paddle.fluid as fluid
import numpy as np

def train_reader():
    train_data = [i for i in range(100)]
    test_data = [i for i in range(0, 200, 2)]
    samples = [sample for sample in zip(train_data, test_data)]
    for sample in samples:
        yield sample

buf_size = 100
batch_size = 5

reader = fluid.io.batch(
    fluid.io.shuffle(train_reader, buf_size=buf_size), 
    batch_size=batch_size
    )    # 分批送入网络

print("试一下效果：")

for i, sample in enumerate(reader()):
    print("epoch:{0}  batch_size:{1}  sample:{2}" .format(i, len(sample), sample))
x = fluid.data(name='x', shape=[-1, 1])
y = fluid.data(name='y', shape=[-1, 1])
fc = fluid.layers.fc(x, 10)    # 偷偷加一层全连接
fc = fluid.layers.fc(fc, 1)

loss = fluid.layers.square_error_cost(fc, y)
loss_mean = fluid.layers.mean(loss)
lm = fluid.layers.Print(loss_mean)
optimizer = fluid.optimizer.SGDOptimizer(learning_rate=1e-3)
optimizer.minimize(loss_mean)

use_gpu = False
place = fluid.CUDAPlace(0) if use_gpu else fluid.CPUPlace()
exe = fluid.Executor(place)
exe.run(fluid.default_startup_program())

feeder = fluid.DataFeeder(place=place, feed_list=[x, y])

for epoch in range(1000):
    for samples in reader():
        y_predict, loss  = exe.run(
            feed=feeder.feed(samples),
            fetch_list=[fc, loss_mean]
            )
    if (epoch+1) % 100 == 0:
        print("当前训练第 %d 次" % (epoch+1))
        print("Predict: {0}\tLoss: {1}".format(y_predict[0], loss))

# 当前训练第 100 次
# Predict: [nan]	Loss: [nan]
# 当前训练第 200 次
# Predict: [nan]	Loss: [nan]
# ...

# 保存模型
save_path = 'linear_regression'
fluid.io.save_inference_model(save_path, ['x'], [fc], exe)