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Hello,according to the py3_requirements.txt, I set up the pytorch-1.9.1 environment. But when I tried to run train.py, it returned TypeError. The details are as follows. If you can give me some suggestions, I would be very grateful.
name:
args Namespace(batch_size=2, epochs=200, gpus=None, lr=0.0001, name='', path=None, train_data='../dataset/lpd_5_prcem_mix_v8_10000.npz')
num of encoder classes: [ 18 3 18 129 18 6 20 102 4865] [1 1 1]
D_MODEL 512 N_LAYER 12 N_HEAD 8 DECODER ATTN causal-linear
: [ 18 3 18 129 18 6 20 102 4865]
DEVICE COUNT: 2
VISIBLE: 0,1
n_parameters: 39,005,620
train_data: dataset
batch_size: 2
num_batch: 1519
train_x: (3039, 9999, 9)
train_y: (3039, 9999, 9)
train_mask: (3039, 9999)
lr_init: 0.0001
DECAY_EPOCH: []
DECAY_RATIO: 0.1
Traceback (most recent call last):
File "train.py", line 219, in
train_dp()
File "train.py", line 162, in train_dp
losses = net(is_train=True, x=batch_x, target=batch_y, loss_mask=batch_mask, init_token=batch_init)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 168, in forward
outputs = self.parallel_apply(replicas, inputs, kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/parallel/data_parallel.py", line 178, in parallel_apply
return parallel_apply(replicas, inputs, kwargs, self.device_ids[:len(replicas)])
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 86, in parallel_apply
output.reraise()
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/_utils.py", line 425, in reraise
raise self.exc_type(msg)
TypeError: Caught TypeError in replica 0 on device 0.
Original Traceback (most recent call last):
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/parallel/parallel_apply.py", line 61, in _worker
output = module(*input, **kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/bing/CODE/video-bgm-generation/src/model.py", line 482, in forward
return self.train_forward(**kwargs)
File "/home/bing/CODE/video-bgm-generation/src/model.py", line 450, in train_forward
h, y_type = self.forward_hidden(x, memory=None, is_training=True, init_token=init_token)
File "/home/bing/CODE/video-bgm-generation/src/model.py", line 221, in forward_hidden
encoder_hidden = self.transformer_encoder(encoder_pos_emb, attn_mask)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/fast_transformers/transformers.py", line 138, in forward
x = layer(x, attn_mask=attn_mask, length_mask=length_mask)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/fast_transformers/transformers.py", line 81, in forward
key_lengths=length_mask
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/fast_transformers/attention/attention_layer.py", line 109, in forward
key_lengths
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/torch/nn/modules/module.py", line 1051, in _call_impl
return forward_call(*input, **kwargs)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/fast_transformers/attention/causal_linear_attention.py", line 101, in forward
values
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/fast_transformers/attention/causal_linear_attention.py", line 23, in causal_linear
V_new = causal_dot_product(Q, K, V)
File "/home/bing/anaconda3/envs/torch-1.9/lib/python3.7/site-packages/fast_transformers/causal_product/init.py", line 48, in forward
product
TypeError: 'NoneType' object is not callable
Looking forward to your reply!
The text was updated successfully, but these errors were encountered:
Hello,according to the py3_requirements.txt, I set up the pytorch-1.9.1 environment. But when I tried to run train.py, it returned TypeError. The details are as follows. If you can give me some suggestions, I would be very grateful.
name:
args Namespace(batch_size=2, epochs=200, gpus=None, lr=0.0001, name='', path=None, train_data='../dataset/lpd_5_prcem_mix_v8_10000.npz')
num of encoder classes: [ 18 3 18 129 18 6 20 102 4865] [1 1 1]
D_MODEL 512 N_LAYER 12 N_HEAD 8 DECODER ATTN causal-linear
Looking forward to your reply!
The text was updated successfully, but these errors were encountered: