这是indexloc提供的服务，不要输入任何密码
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small changes to address deprecation warnings #22

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Jul 25, 2018
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small changes to address deprecation warnings #22

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4 changes: 2 additions & 2 deletions reco_encoder/model/model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -57,7 +57,7 @@ def __init__(self, layer_sizes, nl_type='selu', is_constrained=True, dp_drop_pro
self.encode_w = nn.ParameterList(
[nn.Parameter(torch.rand(layer_sizes[i + 1], layer_sizes[i])) for i in range(len(layer_sizes) - 1)])
for ind, w in enumerate(self.encode_w):
weight_init.xavier_uniform(w)
weight_init.xavier_uniform_(w)

self.encode_b = nn.ParameterList(
[nn.Parameter(torch.zeros(layer_sizes[i + 1])) for i in range(len(layer_sizes) - 1)])
Expand All @@ -69,7 +69,7 @@ def __init__(self, layer_sizes, nl_type='selu', is_constrained=True, dp_drop_pro
self.decode_w = nn.ParameterList(
[nn.Parameter(torch.rand(reversed_enc_layers[i + 1], reversed_enc_layers[i])) for i in range(len(reversed_enc_layers) - 1)])
for ind, w in enumerate(self.decode_w):
weight_init.xavier_uniform(w)
weight_init.xavier_uniform_(w)
self.decode_b = nn.ParameterList(
[nn.Parameter(torch.zeros(reversed_enc_layers[i + 1])) for i in range(len(reversed_enc_layers) - 1)])

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8 changes: 4 additions & 4 deletions run.py
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Expand Up @@ -71,8 +71,8 @@ def do_eval(encoder, evaluation_data_layer):
targets = Variable(eval.cuda().to_dense() if use_gpu else eval.to_dense())
outputs = encoder(inputs)
loss, num_ratings = model.MSEloss(outputs, targets)
total_epoch_loss += loss.data[0]
denom += num_ratings.data[0]
total_epoch_loss += loss.item()
denom += num_ratings.item()
return sqrt(total_epoch_loss / denom)

def log_var_and_grad_summaries(logger, layers, global_step, prefix, log_histograms=False):
Expand Down Expand Up @@ -195,7 +195,7 @@ def main():
loss.backward()
optimizer.step()
global_step += 1
t_loss += loss.data[0]
t_loss += loss.item()
t_loss_denom += 1

if i % args.summary_frequency == 0:
Expand All @@ -209,7 +209,7 @@ def main():
log_var_and_grad_summaries(logger, rencoder.decode_w, global_step, "Decode_W")
log_var_and_grad_summaries(logger, rencoder.decode_b, global_step, "Decode_b")

total_epoch_loss += loss.data[0]
total_epoch_loss += loss.item()
denom += 1

#if args.aug_step > 0 and i % args.aug_step == 0 and i > 0:
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8 changes: 4 additions & 4 deletions test/test_model.py
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Expand Up @@ -31,7 +31,7 @@ def test_CPU(self):
loss = loss / num_ratings
loss.backward()
optimizer.step()
print('[%d, %5d] loss: %.7f' % (epoch, i, loss.data[0]))
print('[%d, %5d] loss: %.7f' % (epoch, i, loss.item()))

def test_GPU(self):
print("iRecAutoEncoderTest Test on GPU started")
Expand All @@ -56,7 +56,7 @@ def test_GPU(self):
loss = loss / num_ratings
loss.backward()
optimizer.step()
total_epoch_loss += loss.data[0]
total_epoch_loss += loss.item()
denom += 1
print("Total epoch {} loss: {}".format(epoch, total_epoch_loss/denom))

Expand All @@ -81,7 +81,7 @@ def test_CPU(self):
loss = loss / num_ratings
loss.backward()
optimizer.step()
print('[%d, %5d] loss: %.7f' % (epoch, i, loss.data[0]))
print('[%d, %5d] loss: %.7f' % (epoch, i, loss.item()))
if i == 5: # too much compute for CPU
break

Expand All @@ -108,7 +108,7 @@ def test_GPU(self):
loss = loss / num_ratings
loss.backward()
optimizer.step()
total_epoch_loss += loss.data[0]
total_epoch_loss += loss.item()
denom += 1
print("Total epoch {} loss: {}".format(epoch, total_epoch_loss / denom))

Expand Down