dcslin commented on pull request #724:
URL: https://github.com/apache/singa/pull/724#issuecomment-647273232
Hi @joddiy , thank you for the code. testing this for lstm model, but it
seems that the `model.compile` could not pass.
``` python
#!/usr/bin/env python
# coding: utf-8
# In[2]:
import sys
build_path = r'/root/singa-imdb/build/python'
sys.path.append(build_path)
from singa import autograd
from singa import layer
from singa import model
from singa import tensor
from singa import device
from singa import opt
import numpy as np
bs = 32
seq_limit = 50
embed_size = 300
hid = 64
max_epoch=20
vocab_size=100
# In[3]:
class IMDB(model.Model):
def __init__(self, hidden_size, seq_length):
super().__init__()
batch_first = True
self.em = layer.Embedding(vocab_size, embed_size)
self.l1 = layer.Linear(64)
self.l2 = layer.Linear(2)
def forward(self, x):
y = self.em(x)
y = autograd.reshape(y, (y.shape[0], -1))
y = self.l1(y)
y = autograd.relu(y)
y = self.l2(y)
return y
def train_one_batch(self, x, y):
out = self.forward(x)
loss = autograd.softmax_cross_entropy(out, y)
self.optimizer(loss)
return out, loss
def set_opt(self, optimizer):
self.optimizer = optimizer
# In[ ]:
dev = device.create_cuda_gpu_on(7)
x = np.random.randint(0, vocab_size, (bs, seq_limit))
tx = tensor.from_numpy(x)
tx.to_device(dev)
ty = tensor.Tensor((bs, 2), dev, tensor.float32)
ty.gaussian(0,1)
m = IMDB(hid, seq_limit)
m.set_opt(opt.SGD())
m.compile([tx], is_train=True, use_graph=False, sequential=False)
# In[1]:
"""
WARNING: Logging before InitGoogleLogging() is written to STDERR
F0622 04:00:20.654505 388 common.cc:34] Check failed: initialized_ Must
initialize data before reading it
*** Check failure stack trace: ***
"""
# In[3]:
# out, loss = m(tx, ty)
```
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