I get the following error when I try to train g2p-seq2seq using a dictionary I wrote for a language. However, it works fine when I use a french or english dictionary.
g2p-seq2seq --train '/home/yinx/Desktop/Thoth/Dict stuff/twiDict' --model '/home/yinx/Desktop/Thoth/Dict stuff/model'
Preparing G2P data
Loading vocabularies from /home/yinx/Desktop/Thoth/Dict stuff/model
Reading development and training data.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Creating model with parameters:
Learning rate: 0.5
LR decay factor: 0.99
Max gradient norm: 5.0
Batch size: 64
Size of layer: 64
Number of layers: 2
Steps per checkpoint: 200
Max steps: 0
Optimizer: sgd
Created model with fresh parameters.
global step 200 learning rate 0.5000 step-time 0.26 perplexity 4.92
eval: perplexity 2.51
global step 400 learning rate 0.5000 step-time 0.21 perplexity 1.81
eval: perplexity 2.78
No improvement over last 1 times. Training will stop after -1iterations if no improvement was seen.
Training done.
Traceback (most recent call last):
File "/usr/local/bin/g2p-seq2seq", line 11, in <module>
load_entry_point('g2p-seq2seq==5.0.0a0', 'console_scripts', 'g2p-seq2seq')()
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/app.py", line 80, in main
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 278, in train
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 72, in load_decode_model
RuntimeError: Model not found in /home/yinx/Desktop/Thoth/Dict stuff/model
g2p-seq2seq --train '/home/yinx/Desktop/Thoth/Dict stuff/twiDict' --model '/home/yinx/Desktop/Thoth/Dict stuff/model'
Preparing G2P data
Loading vocabularies from /home/yinx/Desktop/Thoth/Dict stuff/model
Reading development and training data.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Creating model with parameters:
Learning rate: 0.5
LR decay factor: 0.99
Max gradient norm: 5.0
Batch size: 64
Size of layer: 64
Number of layers: 2
Steps per checkpoint: 200
Max steps: 0
Optimizer: sgd
Created model with fresh parameters.
global step 200 learning rate 0.5000 step-time 0.26 perplexity 4.92
eval: perplexity 2.51
global step 400 learning rate 0.5000 step-time 0.21 perplexity 1.81
eval: perplexity 2.78
No improvement over last 1 times. Training will stop after -1iterations if no improvement was seen.
Training done.
Traceback (most recent call last):
File "/usr/local/bin/g2p-seq2seq", line 11, in <module>
load_entry_point('g2p-seq2seq==5.0.0a0', 'console_scripts', 'g2p-seq2seq')()
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/app.py", line 80, in main
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 278, in train
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 72, in load_decode_model
RuntimeError: Model not found in /home/yinx/Desktop/Thoth/Dict stuff/model
Last edit: Bryan Adaare 2018-02-03
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I get the following error when I try to train g2p-seq2seq using a dictionary I wrote for a language. However, it works fine when I use a french or english dictionary.
g2p-seq2seq --train '/home/yinx/Desktop/Thoth/Dict stuff/twiDict' --model '/home/yinx/Desktop/Thoth/Dict stuff/model'
Preparing G2P data
Loading vocabularies from /home/yinx/Desktop/Thoth/Dict stuff/model
Reading development and training data.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Creating model with parameters:
Learning rate: 0.5
LR decay factor: 0.99
Max gradient norm: 5.0
Batch size: 64
Size of layer: 64
Number of layers: 2
Steps per checkpoint: 200
Max steps: 0
Optimizer: sgd
Created model with fresh parameters.
global step 200 learning rate 0.5000 step-time 0.26 perplexity 4.92
eval: perplexity 2.51
global step 400 learning rate 0.5000 step-time 0.21 perplexity 1.81
eval: perplexity 2.78
No improvement over last 1 times. Training will stop after -1iterations if no improvement was seen.
Training done.
Traceback (most recent call last):
File "/usr/local/bin/g2p-seq2seq", line 11, in <module>
load_entry_point('g2p-seq2seq==5.0.0a0', 'console_scripts', 'g2p-seq2seq')()
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/app.py", line 80, in main
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 278, in train
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 72, in load_decode_model
RuntimeError: Model not found in /home/yinx/Desktop/Thoth/Dict stuff/model
g2p-seq2seq --train '/home/yinx/Desktop/Thoth/Dict stuff/twiDict' --model '/home/yinx/Desktop/Thoth/Dict stuff/model'
Preparing G2P data
Loading vocabularies from /home/yinx/Desktop/Thoth/Dict stuff/model
Reading development and training data.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE3 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.1 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use SSE4.2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use AVX2 instructions, but these are available on your machine and could speed up CPU computations.
W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
Creating model with parameters:
Learning rate: 0.5
LR decay factor: 0.99
Max gradient norm: 5.0
Batch size: 64
Size of layer: 64
Number of layers: 2
Steps per checkpoint: 200
Max steps: 0
Optimizer: sgd
Created model with fresh parameters.
global step 200 learning rate 0.5000 step-time 0.26 perplexity 4.92
eval: perplexity 2.51
global step 400 learning rate 0.5000 step-time 0.21 perplexity 1.81
eval: perplexity 2.78
No improvement over last 1 times. Training will stop after -1iterations if no improvement was seen.
Training done.
Traceback (most recent call last):
File "/usr/local/bin/g2p-seq2seq", line 11, in <module>
load_entry_point('g2p-seq2seq==5.0.0a0', 'console_scripts', 'g2p-seq2seq')()
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/app.py", line 80, in main
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 278, in train
File "build/bdist.linux-x86_64/egg/g2p_seq2seq/g2p.py", line 72, in load_decode_model
RuntimeError: Model not found in /home/yinx/Desktop/Thoth/Dict stuff/model
Last edit: Bryan Adaare 2018-02-03
Fixed the issue. Dictionary size was too small for the particular language
Are you working in ubontu?
Does g2p_seq2seq work in windows too?