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This repository has been archived by the owner on Dec 11, 2023. It is now read-only.
Hi,
The --embed_prefix option is introduced in the nmt.py file as follows:
The pre training word vector file format is as follows:
World 0.342344...(vector size=300)
One 1.341233...
But,An error occurred while I was running the command
python -m nmt.nmt
--src=vi --tgt=en
--num_units=300
--embed_prefix=nmt/nmt_data/vector
But ,error:
FailedPreconditionError (see above for traceback): HashTable has different value for same key. Key ᠤ has 23 and trying to add value 1518
[[Node: string_to_index/hash_table/table_init = InitializeTableFromTextFileV2[delimiter="\t", key_index=-2, value_index=-1, vocab_size=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](string_to_index/hash_table, string_to_index/hash_table/table_init/asset_filepath)]]
Looking forward to your advice or answers.
Best regards,
Thank you very much!
The text was updated successfully, but these errors were encountered:
yapingzhao
changed the title
the pretrained word representations (word2vec)
--embed_prefix for translation model training
Sep 3, 2018
Hi,
The --embed_prefix option is introduced in the nmt.py file as follows:
The pre training word vector file format is as follows:
World 0.342344...(vector size=300)
One 1.341233...
But,An error occurred while I was running the command
python -m nmt.nmt
--src=vi --tgt=en
--num_units=300
--embed_prefix=nmt/nmt_data/vector
But ,error:
FailedPreconditionError (see above for traceback): HashTable has different value for same key. Key ᠤ has 23 and trying to add value 1518
[[Node: string_to_index/hash_table/table_init = InitializeTableFromTextFileV2[delimiter="\t", key_index=-2, value_index=-1, vocab_size=-1, _device="/job:localhost/replica:0/task:0/device:CPU:0"](string_to_index/hash_table, string_to_index/hash_table/table_init/asset_filepath)]]
Looking forward to your advice or answers.
Best regards,
Thank you very much!
The text was updated successfully, but these errors were encountered: