Created by: Wahaha1314

• 版本、环境信息：    1）PaddlePaddle版本：1.6.1      2）GPU：预测若用GPU，CUDA 9.0，cudnn 7.6    3）系统环境：window 10 python3.6
• 训练信息    1）单机，单卡  
• 部分复现信息：（train_X, train_Y就是我自己的数据集，其维度的我有在下面打印出来） batch_size=60 #迭代次数 max_len=10 #input_dim不能超过该值 dropout_prob=0.2 seq_len=20 #时间序列长度 hidden_size=6 #隐藏层单元 num_layers=1 #叠加LSTM的层数 learning_rate=0.002 #学习率

data1= fluid.data(name='data1', shape=[-1,20,6], dtype='float64') label = fluid.data(name='label', shape=[-1,1], dtype='float64')

print(data1) init_h = fluid.layers.fill_constant( [num_layers, batch_size, hidden_size], 'float64', 0.0 ) init_c = fluid.layers.fill_constant( [num_layers, batch_size, hidden_size], 'float64', 0.0 )

rnn_out, last_h, last_c = fluid.layers.lstm(data1, init_h, init_c, max_len, hidden_size, num_layers, dropout_prob=dropout_prob) print(last_h) last_result=last_h[0,:,:] print(last_result) out = fluid.layers.fc(input=last_result, size=1, act=None)

获取损失函数

cost = fluid.layers.square_error_cost(input=out, label=label) avg_cost = fluid.layers.mean(cost)

获取预测程序

test_program = fluid.default_main_program().clone(for_test=True)

定义优化方法

optimizer = fluid.optimizer.AdagradOptimizer(learning_rate) opt = optimizer.minimize(avg_cost)

创建一个执行器，CPU训练速度比较慢

place = fluid.CPUPlace()

place = fluid.CUDAPlace(0) exe = fluid.Executor(place)

进行参数初始化

exe.run(fluid.default_startup_program())

def reader_createor(data, label): def reader(): for i in range(len(data)): yield data[i,:], label[i] return reader

train_reader = fluid.io.batch(fluid.io.shuffle(reader_createor(train_X, train_Y), 3000), batch_size=60,drop_last=True)

#加载测试数据 #train_reader = fluid.io.batch(fluid.io.shuffle(train_X, 3000), batch_size=60,drop_last=True)

feeder = fluid.DataFeeder(place=place, feed_list=[data1, label])

开始训练

for pass_id in range(1000): # 进行训练 train_cost = 0 for batch_id, data in enumerate(train_reader()): train_cost = exe.run(program=fluid.default_main_program(), feed=feeder.feed(data), fetch_list=[avg_cost])

    if batch_id % 20 == 0:
        print('Pass:%d, Batch:%d, Cost:%0.5f' % (pass_id, batch_id, train_cost[0]))

• 问题描述：请详细描述您的问题，同步贴出报错信息、日志、可复现的代码片段 前面是一点输出，后面是报错信息（我也试过换类型，换成了float32类型，但是就报PaddleCheckError: CUDNN_STATUS_BAD_PARAM at [D:\1.6.1\paddle\paddle\fluid\operators\cudnn_lstm_op.cu.cc:113]错误！！） train_x1的维度： (2980, 20) train_Y的维度： (2980, 1) train_XT的维度： (6, 2980, 20) train_X的维度： (2980, 20, 6) name: "data1" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP64 dims: -1 dims: 20 dims: 6 } lod_level: 0 } } persistable: false need_check_feed: true

name: "cudnn_lstm_0.tmp_1" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP64 dims: 1 dims: 60 dims: 6 } } } persistable: false

name: "cudnn_lstm_0.tmp_1_slice_0" type { type: LOD_TENSOR lod_tensor { tensor { data_type: FP64 dims: 60 dims: 6 } } }

C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\executor.py:774: UserWarning: The following exception is not an EOF exception. "The following exception is not an EOF exception.") Traceback (most recent call last): File "D:\eclipse-workspace\pd_pd\pd_lstm\pd_lstm3.py", line 181, in fetch_list=[avg_cost]) File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\executor.py", line 775, in run six.reraise(*sys.exc_info()) File "E:\Anaconda3\lib\site-packages\six.py", line 693, in reraise raise value File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\executor.py", line 770, in run use_program_cache=use_program_cache) File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\executor.py", line 817, in _run_impl use_program_cache=use_program_cache) File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\executor.py", line 894, in _run_program fetch_var_name) paddle.fluid.core_avx.EnforceNotMet:

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C++ Call Stacks (More useful to developers):

Windows not support stack backtrace yet.

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Python Call Stacks (More useful to users):

File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\framework.py", line 2459, in append_op attrs=kwargs.get("attrs", None)) File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\layer_helper.py", line 43, in append_op return self.main_program.current_block().append_op(*args, **kwargs) File "C:\Users\17720\AppData\Roaming\Python\Python36\site-packages\paddle\fluid\layers\nn.py", line 1018, in lstm 'seed': seed, File "D:\eclipse-workspace\pd_pd\pd_lstm\pd_lstm3.py", line 129, in rnn_out, last_h, last_c = fluid.layers.lstm(data1, init_h, init_c, max_len, hidden_size, num_layers, dropout_prob=dropout_prob)

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Error Message Summary:

PaddleCheckError: op cudnn_lstm does not have kernel for data_type[double]:data_layout[ANY_LAYOUT]:place[CUDAPlace(0)]:library_type[PLAIN] at [D:\1.6.1\paddle\paddle\fluid\framework\operator.cc:1007] [operator < cudnn_lstm > error] W1112 09:50:24.788756 14520 device_context.cc:235] Please NOTE: device: 0, CUDA Capability: 61, Driver API Version: 9.1, Runtime API Version: 9.0 W1112 09:50:24.795739 14520 device_context.cc:243] device: 0, cuDNN Version: 7.6.