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IBM / transition-amr-parser

SoTA Abstract Meaning Representation (AMR) parsing with word-node alignments in Pytorch. Includes checkpoints and other tools such as statistical significance Smatch.
Apache License 2.0
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"Unable to infer Criterion arguments, please implement LabelSmoothedCrossEntropyPointerCriterion.build_criterion" when running minimal_test.sh #28

Closed aianta closed 2 years ago

aianta commented 2 years ago

I'm trying to get going on wsl2, and have been running into some trouble getting set up.

At first the scripts were searching for fairseq_ext on the wrong path: specifically I was getting FileNotFound errors on the path /ibm-amr/fairseq_ext. This made sense because fairseq_ext was of course located in /ibm-amr/transition-amr-parser/fairseq_ext.

So I went ahead and did a global find & replace changing ../fairseq_ext to ./fairseq_ext, which got me a little further. Unfortunately, the problem then was:

ImportError: Failed to import --user-dir=/home/aianta/ibm-amr/transition-amr-parser/fairseq_ext because the corresponding module name (fairseq_ext) is not globally unique. Please rename the directory to something unique and try again.

Renaming the folder did not help, but I reasoned, if the issue is a duplicate module, that might suggest that fairseq_ext was in fact already loaded. So I went ahead and commented out all instances of utils.import_user_module(usr_args) and sure enough, the minimal test proceeded further.

I'm now stuck on:

[Configuration file:]
configs/wiki25.sh
[Building oracle actions:]
[Configuration file:]
configs/wiki25.sh
Directory to aligner: DATA/wiki25/aligned/cofill/ already exists --- do nothing.
[normalize rules] months
[normalize rules] units
[normalize rules] cardinals
[normalize rules] ordinals
Reading DATA/wiki25/aligned/cofill//train.txt
25 sentences
216/293 node types/tokens
35/285 edge types/tokens
241/383 word types/tokens
Oracle: 25it [00:00, 431.06it/s]
Base actions:
Counter({'PRED': 63, 'RA': 20, 'LA': 19, 'ENTITY': 15, 'REDUCE': 1, 'SHIFT': 1, 'COPY_LEMMA': 1, 'COPY_SENSE01': 1, 'MERGE': 1})
Most frequent actions:
[('SHIFT', 198), ('REDUCE', 184), ('COPY_LEMMA', 62), ('MERGE', 26), ('LA(root)', 22), ('COPY_SENSE01', 20), ('LA(:ARG1)', 18), ('RA(:ARG1)', 13), ('LA(:ARG0)', 12), ('PRED(person)', 12)]
80 singleton actions
Counter({'PRED': 59, 'ENTITY': 9, 'RA': 8, 'LA': 4})
Reading DATA/wiki25/aligned/cofill//dev.txt
25 sentences
216/293 node types/tokens
35/285 edge types/tokens
241/383 word types/tokens
Oracle: 25it [00:00, 445.79it/s]
Base actions:
Counter({'PRED': 63, 'RA': 20, 'LA': 19, 'ENTITY': 15, 'REDUCE': 1, 'SHIFT': 1, 'COPY_LEMMA': 1, 'COPY_SENSE01': 1, 'MERGE': 1})
Most frequent actions:
[('SHIFT', 198), ('REDUCE', 184), ('COPY_LEMMA', 62), ('MERGE', 26), ('LA(root)', 22), ('COPY_SENSE01', 20), ('LA(:ARG1)', 18), ('RA(:ARG1)', 13), ('LA(:ARG0)', 12), ('PRED(person)', 12)]
80 singleton actions
Counter({'PRED': 59, 'ENTITY': 9, 'RA': 8, 'LA': 4})
Reading DATA/wiki25/aligned/cofill//test.txt
25 sentences
216/293 node types/tokens
35/285 edge types/tokens
241/383 word types/tokens
Oracle: 25it [00:00, 427.50it/s]
Base actions:
Counter({'PRED': 63, 'RA': 20, 'LA': 19, 'ENTITY': 15, 'REDUCE': 1, 'SHIFT': 1, 'COPY_LEMMA': 1, 'COPY_SENSE01': 1, 'MERGE': 1})
Most frequent actions:
[('SHIFT', 198), ('REDUCE', 184), ('COPY_LEMMA', 62), ('MERGE', 26), ('LA(root)', 22), ('COPY_SENSE01', 20), ('LA(:ARG1)', 18), ('RA(:ARG1)', 13), ('LA(:ARG0)', 12), ('PRED(person)', 12)]
80 singleton actions
Counter({'PRED': 59, 'ENTITY': 9, 'RA': 8, 'LA': 4})
[Preprocessing data:]
[Configuration file:]
configs/wiki25.sh
Cleaning up partially completed DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//
Namespace(user_dir='./fairseq_ext')
Namespace(alignfile=None, batch_normalize_reward=False, bert_layers=[1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24], bpe=None, cpu=False, criterion='cross_entropy', dataset_impl='mmap', destdir='DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//', embdir='DATA/wiki25/embeddings/RoBERTa-large-top24', fp16=False, fp16_init_scale=128, fp16_scale_tolerance=0.0, fp16_scale_window=None, gold_annotations=None, gold_episode_ratio=None, joined_dictionary=False, log_format=None, log_interval=1000, lr_scheduler='fixed', machine_rules=None, machine_type=None, memory_efficient_fp16=False, min_loss_scale=0.0001, no_progress_bar=False, nwordssrc=-1, nwordstgt=-1, only_source=False, optimizer=None, padding_factor=8, pretrained_embed='roberta.large', scoring='bleu', seed=1, source_lang='en', srcdict=None, target_lang='actions', task='amr_action_pointer_graphmp', tbmf_wrapper=False, tensorboard_logdir='', testpref='DATA/wiki25/oracles/cofill_o8.3_act-states//test', tgtdict=None, threshold_loss_scale=None, thresholdsrc=0, thresholdtgt=0, tokenizer=None, trainpref='DATA/wiki25/oracles/cofill_o8.3_act-states//train', user_dir='./fairseq_ext', validpref='DATA/wiki25/oracles/cofill_o8.3_act-states//dev', workers=1)
| [en] Dictionary: 247 types
| [en] DATA/wiki25/oracles/cofill_o8.3_act-states//train.en: 25 sents, 408 tokens, 0.0% replaced by <unk>
| [en] Dictionary: 247 types
| [en] DATA/wiki25/oracles/cofill_o8.3_act-states//dev.en: 25 sents, 408 tokens, 0.0% replaced by <unk>
| [en] Dictionary: 247 types
| [en] DATA/wiki25/oracles/cofill_o8.3_act-states//test.en: 25 sents, 408 tokens, 0.0% replaced by <unk>
----------------------------------------------------------------------------------------------------
Generate and process action states information (number of workers: 1):
[English sentence file: DATA/wiki25/oracles/cofill_o8.3_act-states//train.en]
[AMR actions file: DATA/wiki25/oracles/cofill_o8.3_act-states//train.actions]
processing ...
finished !
Processed data saved to path with prefix: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//train.en-actions.actions
Total time elapsed: 0s
----------------------------------------------------------------------------------------------------
| [actions] DATA/wiki25/oracles/cofill_o8.3_act-states//train.actions_nopos: 25 sents, 796 tokens, 0.0% replaced by <unk>
----------------------------------------------------------------------------------------------------
Generate and process action states information (number of workers: 1):
[English sentence file: DATA/wiki25/oracles/cofill_o8.3_act-states//dev.en]
[AMR actions file: DATA/wiki25/oracles/cofill_o8.3_act-states//dev.actions]
processing ...
finished !
Processed data saved to path with prefix: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions
Total time elapsed: 0s
----------------------------------------------------------------------------------------------------
| [actions] DATA/wiki25/oracles/cofill_o8.3_act-states//dev.actions_nopos: 25 sents, 796 tokens, 0.0% replaced by <unk>
----------------------------------------------------------------------------------------------------
Generate and process action states information (number of workers: 1):
[English sentence file: DATA/wiki25/oracles/cofill_o8.3_act-states//test.en]
[AMR actions file: DATA/wiki25/oracles/cofill_o8.3_act-states//test.actions]
processing ...
finished !
Processed data saved to path with prefix: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//test.en-actions.actions
Total time elapsed: 0s
----------------------------------------------------------------------------------------------------
| [actions] DATA/wiki25/oracles/cofill_o8.3_act-states//test.actions_nopos: 25 sents, 796 tokens, 0.0% replaced by <unk>
Using cache found in /home/aianta/.cache/torch/hub/pytorch_fairseq_main
Using roberta.large extraction in GPU

Using cache found in /home/aianta/.cache/torch/hub/pytorch_fairseq_main
Using roberta.large extraction in GPU

Using cache found in /home/aianta/.cache/torch/hub/pytorch_fairseq_main
Using roberta.large extraction in GPU

| Wrote preprocessed oracle data to DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//
| Wrote preprocessed embedding data to DATA/wiki25/embeddings/RoBERTa-large-top24
[Training:]
[Configuration file:]
configs/wiki25.sh
Namespace(activation_dropout=0.0, activation_fn='relu', adam_betas='(0.9,0.98)', adam_eps=1e-08, adaptive_input=False, adaptive_softmax_cutoff=None, adaptive_softmax_dropout=0, all_gather_list_size=16384, append_eos_to_target=0, apply_tgt_actnode_masks=0, apply_tgt_input_src=0, apply_tgt_src_align=1, apply_tgt_vocab_masks=1, arch='transformer_tgt_pointer_graphmp', attention_dropout=0.0, batch_size=None, batch_size_valid=None, bert_backprop=False, best_checkpoint_metric='loss', bf16=False, bpe=None, broadcast_buffers=False, bucket_cap_mb=25, checkpoint_shard_count=1, checkpoint_suffix='', clip_norm=0.0, collate_tgt_states=1, cpu=False, criterion='label_smoothed_cross_entropy_pointer', curriculum=0, data='DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//', data_buffer_size=10, dataset_impl=None, ddp_backend='c10d', decoder_attention_heads=4, decoder_embed_dim=256, decoder_embed_path=None, decoder_ffn_embed_dim=512, decoder_input_dim=256, decoder_layers=6, decoder_learned_pos=False, decoder_normalize_before=False, decoder_output_dim=256, device_id=0, disable_validation=False, distributed_backend='nccl', distributed_init_method=None, distributed_no_spawn=False, distributed_num_procs=1, distributed_port=-1, distributed_rank=0, distributed_world_size=1, distributed_wrapper='DDP', dropout=0.3, emb_dir='DATA/wiki25/embeddings/RoBERTa-large-top24', empty_cache_freq=0, encode_state_machine=None, encoder_attention_heads=4, encoder_embed_dim=256, encoder_embed_path=None, encoder_ffn_embed_dim=512, encoder_layers=6, encoder_learned_pos=False, encoder_normalize_before=False, fast_stat_sync=False, find_unused_parameters=False, finetune_from_model=None, fix_batches_to_gpus=False, fixed_validation_seed=None, fp16=False, fp16_init_scale=128, fp16_no_flatten_grads=False, fp16_scale_tolerance=0.0, fp16_scale_window=None, gen_subset='test', keep_best_checkpoints=-1, keep_interval_updates=-1, keep_last_epochs=6, label_smoothing=0.01, lazy_load=False, left_pad_source='True', left_pad_target='False', localsgd_frequency=3, log_format='json', log_interval=100, loss_coef=1.0, lr=[0.0005], lr_scheduler='inverse_sqrt', max_epoch=10, max_source_positions=1024, max_target_positions=1024, max_tokens=3584, max_tokens_valid=3584, max_update=0, maximize_best_checkpoint_metric=False, memory_efficient_bf16=False, memory_efficient_fp16=False, min_loss_scale=0.0001, min_lr=1e-09, model_parallel_size=1, no_bert_precompute=False, no_epoch_checkpoints=False, no_last_checkpoints=False, no_progress_bar=False, no_save=False, no_save_optimizer_state=False, no_seed_provided=False, no_token_positional_embeddings=False, nprocs_per_node=1, num_shards=1, num_workers=1, optimizer='adam', optimizer_overrides='{}', patience=-1, pipeline_balance=None, pipeline_checkpoint='never', pipeline_chunks=0, pipeline_decoder_balance=None, pipeline_decoder_devices=None, pipeline_devices=None, pipeline_encoder_balance=None, pipeline_encoder_devices=None, pipeline_model_parallel=False, pointer_dist_decoder_selfattn_avg=0, pointer_dist_decoder_selfattn_heads=1, pointer_dist_decoder_selfattn_infer=5, pointer_dist_decoder_selfattn_layers=[5], pretrained_embed_dim=1024, profile=False, quantization_config_path=None, raw_text=False, required_batch_size_multiple=8, required_seq_len_multiple=1, reset_dataloader=False, reset_lr_scheduler=False, reset_meters=False, reset_optimizer=False, restore_file='checkpoint_last.pt', save_dir='DATA/wiki25/models/exp_cofill_o8.3_act-states_RoBERTa-large-top24/_act-pos-grh_vmask1_shiftpos1_ptr-lay6-h1_grh-lay123-h2-allprev_1in1out_cam-layall-h2-abuf/ep10-seed42', save_interval=1, save_interval_updates=0, scoring='bleu', seed=42, sentence_avg=False, shard_id=0, share_all_embeddings=False, share_decoder_input_output_embed=0, shift_pointer_value=1, skip_invalid_size_inputs_valid_test=False, slowmo_algorithm='LocalSGD', slowmo_momentum=None, source_lang=None, stop_time_hours=0, target_lang=None, task='amr_action_pointer_graphmp', tensorboard_logdir='DATA/wiki25/models/exp_cofill_o8.3_act-states_RoBERTa-large-top24/_act-pos-grh_vmask1_shiftpos1_ptr-lay6-h1_grh-lay123-h2-allprev_1in1out_cam-layall-h2-abuf/ep10-seed42', tgt_factored_emb_out=0, tgt_graph_heads=2, tgt_graph_layers=[0, 1, 2], tgt_graph_mask='allprev_1in1out', tgt_input_src_backprop=1, tgt_input_src_combine='add', tgt_input_src_emb='top', tgt_src_align_focus=['p0c1n0', 'p0c0n*'], tgt_src_align_heads=2, tgt_src_align_layers=[0, 1, 2, 3, 4, 5], threshold_loss_scale=None, tokenizer=None, tpu=False, train_subset='train', update_freq=[1], upsample_primary=1, use_bmuf=False, use_old_adam=False, user_dir='./fairseq_ext', valid_subset='valid', validate_after_updates=0, validate_interval=1, validate_interval_updates=0, warmup_init_lr=1e-07, warmup_updates=4000, weight_decay=0.0, zero_sharding='none')
| [en] dictionary: 248 types
| [actions_nopos] dictionary: 128 types
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.en
| loaded 25 examples from: DATA/wiki25/embeddings/RoBERTa-large-top24/valid.en-actions.en.bert
| loaded 25 examples from: DATA/wiki25/embeddings/RoBERTa-large-top24/valid.en-actions.en.wordpieces
| loaded 25 examples from: DATA/wiki25/embeddings/RoBERTa-large-top24/valid.en-actions.en.wp2w
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.nopos_in
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.nopos_out
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.pos
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.vocab_masks
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.src_cursors
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actnode_masks
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_masks
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_1stnode_masks
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_indexes
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_cur_node_indexes
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_cur_1stnode_indexes
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_pre_node_indexes
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_directions
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_allpre_indexes
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_allpre_pre_node_indexes
| loaded 25 examples from: DATA/wiki25/features/cofill_o8.3_act-states_RoBERTa-large-top24//valid.en-actions.actions.actedge_allpre_directions
Traceback (most recent call last):
  File "fairseq_ext/train.py", line 338, in <module>
    cli_main()
  File "fairseq_ext/train.py", line 334, in cli_main
    main(args)
  File "fairseq_ext/train.py", line 73, in main
    criterion = task.build_criterion(args)
  File "/home/aianta/anaconda3/envs/amr-2/lib/python3.7/site-packages/fairseq/tasks/fairseq_task.py", line 289, in build_criterion
    return criterions.build_criterion(args, self)
  File "/home/aianta/anaconda3/envs/amr-2/lib/python3.7/site-packages/fairseq/criterions/__init__.py", line 31, in build_criterion
    return build_criterion_(criterion_cfg, task)
  File "/home/aianta/anaconda3/envs/amr-2/lib/python3.7/site-packages/fairseq/registry.py", line 54, in build_x
    return builder(args, *extra_args, **extra_kwargs)
  File "/home/aianta/anaconda3/envs/amr-2/lib/python3.7/site-packages/fairseq/criterions/fairseq_criterion.py", line 57, in build_criterion
    "{}.build_criterion".format(cls.__name__)
NotImplementedError: Unable to infer Criterion arguments, please implement LabelSmoothedCrossEntropyPointerCriterion.build_criterion

This is my conda list:

# packages in environment at /home/aianta/anaconda3/envs/amr-2:
#
# Name                    Version                   Build  Channel
_libgcc_mutex             0.1                        main
_openmp_mutex             5.1                       1_gnu
antlr-python-runtime      4.8                pyhd8ed1ab_3    conda-forge
astunparse                1.6.3                      py_0
attrs                     21.4.0             pyhd3eb1b0_0
blas                      1.0                         mkl
brotlipy                  0.7.0           py37h27cfd23_1003
bzip2                     1.0.8                h7b6447c_0
c-ares                    1.18.1               h7f8727e_0
ca-certificates           2022.4.26            h06a4308_0
catalogue                 1.0.0                    py37_1
certifi                   2022.6.15        py37h06a4308_0
cffi                      1.15.0           py37hd667e15_1
charset-normalizer        2.0.4              pyhd3eb1b0_0
cmake                     3.22.1               h1fce559_0
colorama                  0.4.5              pyhd8ed1ab_0    conda-forge
cryptography              37.0.1           py37h9ce1e76_0
cudatoolkit               11.3.1               h2bc3f7f_2
cymem                     2.0.6            py37h295c915_0
cython                    0.29.30          py37hd23a5d3_0    conda-forge
cython-blis               0.7.7            py37hce1f21e_0
dataclasses               0.8                pyh6d0b6a4_7
en-core-web-sm            2.3.1                    pypi_0    pypi
expat                     2.4.4                h295c915_0
fairseq                   0.10.2           py37hdc94413_0    conda-forge
ffmpeg                    4.3                  hf484d3e_0    pytorch
freetype                  2.10.4               h0708190_1    conda-forge
future                    0.18.2                   py37_1
gmp                       6.2.1                h58526e2_0    conda-forge
gnutls                    3.6.13               h85f3911_1    conda-forge
hydra-core                1.1.1              pyhd8ed1ab_0    conda-forge
idna                      3.3                pyhd3eb1b0_0
importlib-metadata        4.11.3           py37h06a4308_0
importlib_metadata        4.11.3               hd3eb1b0_0
importlib_resources       5.8.0              pyhd8ed1ab_0    conda-forge
intel-openmp              2021.4.0          h06a4308_3561
jpeg                      9e                   h166bdaf_1    conda-forge
jsonschema                3.0.2                    py37_0
krb5                      1.19.2               hac12032_0
lame                      3.100             h7f98852_1001    conda-forge
lcms2                     2.12                 hddcbb42_0    conda-forge
ld_impl_linux-64          2.38                 h1181459_1
libcurl                   7.82.0               h0b77cf5_0
libedit                   3.1.20210910         h7f8727e_0
libev                     4.33                 h7f8727e_1
libffi                    3.3                  he6710b0_2
libgcc-ng                 11.2.0               h1234567_1
libgomp                   11.2.0               h1234567_1
libiconv                  1.17                 h166bdaf_0    conda-forge
libnghttp2                1.46.0               hce63b2e_0
libpng                    1.6.37               h21135ba_2    conda-forge
libssh2                   1.10.0               h8f2d780_0
libstdcxx-ng              11.2.0               h1234567_1
libtiff                   4.2.0                h2818925_1
libuv                     1.40.0               h7b6447c_0
libwebp-base              1.2.2                h7f98852_1    conda-forge
lz4-c                     1.9.3                h295c915_1
mkl                       2021.4.0           h06a4308_640
mkl-include               2022.0.1           h06a4308_117
mkl-service               2.4.0            py37h7f8727e_0
mkl_fft                   1.3.1            py37hd3c417c_0
mkl_random                1.2.2            py37h51133e4_0
murmurhash                1.0.7            py37h295c915_0
ncurses                   6.3                  h7f8727e_2
nettle                    3.6                  he412f7d_0    conda-forge
ninja                     1.10.2               h06a4308_5
ninja-base                1.10.2               hd09550d_5
numpy                     1.21.5           py37h6c91a56_3
numpy-base                1.21.5           py37ha15fc14_3
olefile                   0.46               pyh9f0ad1d_1    conda-forge
omegaconf                 2.1.1            py37h89c1867_1    conda-forge
openh264                  2.1.1                h780b84a_0    conda-forge
openssl                   1.1.1o               h7f8727e_0
packaging                 21.3               pyhd3eb1b0_0
pillow                    7.2.0            py37h718be6c_2    conda-forge
pip                       21.2.2           py37h06a4308_0
plac                      1.1.0                    py37_1
portalocker               2.4.0            py37h89c1867_0    conda-forge
preshed                   3.0.6            py37h295c915_0
pycparser                 2.21               pyhd3eb1b0_0
pyopenssl                 22.0.0             pyhd3eb1b0_0
pyparsing                 3.0.4              pyhd3eb1b0_0
pyrsistent                0.18.0           py37heee7806_0
pysocks                   1.7.1                    py37_1
python                    3.7.13               h12debd9_0
python_abi                3.7                     2_cp37m    conda-forge
pytorch                   1.10.1          py3.7_cuda11.3_cudnn8.2.0_0    pytorch
pytorch-mutex             1.0                        cuda    pytorch
pyyaml                    6.0              py37h7f8727e_1
readline                  8.1.2                h7f8727e_1
regex                     2022.4.24        py37h540881e_0    conda-forge
requests                  2.27.1             pyhd3eb1b0_0
rhash                     1.4.1                h3c74f83_1
sacrebleu                 2.1.0              pyhd8ed1ab_0    conda-forge
setuptools                61.2.0           py37h06a4308_0
six                       1.16.0             pyhd3eb1b0_1
spacy                     2.3.5            py37hff7bd54_0
sqlite                    3.38.5               hc218d9a_0
srsly                     1.0.5            py37h2531618_0
tabulate                  0.8.10             pyhd8ed1ab_0    conda-forge
thinc                     7.4.5            py37h9a67853_0
tk                        8.6.12               h1ccaba5_0
torch                     1.13.0a0+git4300f64          pypi_0    pypi
torchaudio                0.10.1               py37_cu113    pytorch
torchvision               0.11.2               py37_cu113    pytorch
tqdm                      4.64.0           py37h06a4308_0
typing                    3.10.0.0           pyhd8ed1ab_0    conda-forge
typing_extensions         4.1.1              pyh06a4308_0
urllib3                   1.26.9           py37h06a4308_0
wasabi                    0.9.1            py37h06a4308_0
wheel                     0.37.1             pyhd3eb1b0_0
xz                        5.2.5                h7f8727e_1
yaml                      0.2.5                h7b6447c_0
zipp                      3.8.0            py37h06a4308_0
zlib                      1.2.12               h7f8727e_2
zstd                      1.5.2                ha4553b6_0

The correctly_installed.sh script returns:

pytorch 1.10.1
cuda 11.3
Apex not installed
Pytorch binaries were compiled with Cuda 11.3 but binary /usr/local/cuda/bin/nvcc is 11.4,
fairseq 0.10.2
spacy 2.3.5
[OK] correctly installed

Are the pytorch libraries the issue here?

ramon-astudillo commented 2 years ago

You should not need to move fairseq_ext that should be at the heart of the problem, if I have to guess.

Try a new install and ensure you use the --editable flag as in

pip install --editable .
aianta commented 2 years ago

Tried again with a completely fresh instance of Ubuntu 20.04 on WSL2 and everything worked like a charm. Thanks! Not quite sure what was wrong with the earlier setup.