evaluting causing error for infer language pair on pretrained cnndm

[amiyamandal-dev]

fairseq-generate cnndm/processed --path /e/workspace/ProphetNet/a.pt --user-dir prophetnet --task translation_prophetnet --batch-size 32 --gen-subset test --beam 5 --num-workers 4 --min-len 45 --max-len-b 110  --no-repeat-ngram-size 3 --lenpen 1.2 2>&1 > cnndm/output-ck9-pelt1.2-test-beam5.txt

using the above command for Inference and Evaluation but causing an error on a pre-trained model for CNN/Daily Mail

Traceback (most recent call last):
  File "D:\windows_program\conda\envs\p\Scripts\fairseq-generate-script.py", line 33, in <module>
    sys.exit(load_entry_point('fairseq', 'console_scripts', 'fairseq-generate')())
  File "e:\fairseq\fairseq_cli\generate.py", line 270, in cli_main
    main(args)
  File "e:\fairseq\fairseq_cli\generate.py", line 36, in main
    return _main(args, sys.stdout)
  File "e:\fairseq\fairseq_cli\generate.py", line 57, in _main
    task = tasks.setup_task(args)
  File "e:\fairseq\fairseq\tasks\__init__.py", line 17, in setup_task
    return TASK_REGISTRY[args.task].setup_task(args, **kwargs)
  File "e:\fairseq\fairseq\tasks\translation.py", line 226, in setup_task
    raise Exception('Could not infer language pair, please provide it explicitly')
Exception: Could not infer language pair, please provide it explicitly

but in docs their no such arguments for fairseq-generate

fairseq 0.9.0
torch 1.5.1
model prophetnet_large_160G_cnndm_model.pt

[amiyamandal-dev]

the same issue is coming while training from scartch

sh-4.4$ sh run.sh
2020-06-30 14:00:05 | INFO | fairseq_cli.train | Namespace(activation_dropout=0.1, activation_fn='gelu', adam_betas='(0.9, 0.999)', adam_eps=1e-08, all_gather_list_size=16384, arch='ngram_transformer_prophet_large', attention_dropout=0.1, best_checkpoint_metric='loss', bf16=False, bpe=None, broadcast_buffers=False, bucket_cap_mb=25, checkpoint_suffix='', clip_norm=0.1, cpu=False, criterion='ngram_language_loss', curriculum=0, data='cnndm/processed', data_buffer_size=10, dataset_impl=None, ddp_backend='no_c10d', decoder_attention_heads=16, decoder_embed_dim=1024, decoder_ffn_embed_dim=4096, decoder_layers=12, device_id=0, disable_ngram_loss=False, disable_validation=False, distributed_backend='nccl', distributed_init_method=None, distributed_no_spawn=False, distributed_port=-1, distributed_rank=0, distributed_world_size=1, distributed_wrapper='DDP', dropout=0.1, empty_cache_freq=0, encoder_attention_heads=16, encoder_embed_dim=1024, encoder_ffn_embed_dim=4096, encoder_layers=12, eval_bleu=False, eval_bleu_args=None, eval_bleu_detok='space', eval_bleu_detok_args=None, eval_bleu_print_samples=False, eval_bleu_remove_bpe=None, eval_tokenized_bleu=False, fast_stat_sync=False, find_unused_parameters=False, fix_batches_to_gpus=False, fixed_validation_seed=None, fp16=True, fp16_init_scale=128, fp16_no_flatten_grads=False, fp16_scale_tolerance=0.0, fp16_scale_window=None, keep_best_checkpoints=-1, keep_interval_updates=-1, keep_last_epochs=10, label_smoothing=0.1, left_pad_source='True', left_pad_target='False', load_alignments=False, load_from_pretrained_model='../prophetnet_large_pretrained_160G_14epoch_model.pt', load_sep=True, localsgd_frequency=3, log_format=None, log_interval=100, lr=[0.0001], lr_scheduler='inverse_sqrt', max_epoch=10, max_sentences=2, max_sentences_valid=2, max_source_positions=512, max_target_positions=512, max_tokens=None, max_tokens_valid=None, max_update=0, maximize_best_checkpoint_metric=False, memory_efficient_bf16=False, memory_efficient_fp16=False, min_loss_scale=0.0001, min_lr=-1, model_parallel_size=1, ngram=2, no_epoch_checkpoints=False, no_last_checkpoints=False, no_progress_bar=False, no_save=False, no_save_optimizer_state=False, nprocs_per_node=1, num_batch_buckets=0, num_buckets=32, num_workers=4, optimizer='adam', optimizer_overrides='{}', patience=-1, profile=False, quantization_config_path=None, relative_max_distance=128, required_batch_size_multiple=8, reset_dataloader=False, reset_lr_scheduler=False, reset_meters=False, reset_optimizer=False, restore_file='checkpoint_last.pt', save_dir='cnndm/finetune_cnndm_checkpoints', save_interval=1, save_interval_updates=0, seed=1, sentence_avg=False, share_all_embeddings=True, share_decoder_input_output_embed=True, skip_invalid_size_inputs_valid_test=True, slowmo_algorithm='LocalSGD', slowmo_momentum=None, source_lang=None, target_lang=None, task='translation_prophetnet', tensorboard_logdir='cnndm/finetune_cnndm_tensorboard', threshold_loss_scale=None, tokenizer=None, tpu=False, train_subset='train', truncate_source=False, update_freq=[32], upsample_primary=1, use_bmuf=False, use_old_adam=False, user_dir='./prophetnet', valid_subset='valid', validate_interval=1, warmup_init_lr=1e-07, warmup_updates=1000, weight_decay=0.01)
Traceback (most recent call last):
  File "D:\windows_program\conda\envs\p\Scripts\fairseq-train-script.py", line 33, in <module>
    sys.exit(load_entry_point('fairseq', 'console_scripts', 'fairseq-train')())
  File "e:\fairseq\fairseq_cli\train.py", line 347, in cli_main
    cli_main_helper(args)
  File "e:\fairseq\fairseq_cli\train.py", line 385, in cli_main_helper
    main(args)
  File "e:\fairseq\fairseq_cli\train.py", line 64, in main
    task = tasks.setup_task(args)
  File "e:\fairseq\fairseq\tasks\__init__.py", line 17, in setup_task
    return TASK_REGISTRY[args.task].setup_task(args, **kwargs)
  File "e:\fairseq\fairseq\tasks\translation.py", line 226, in setup_task
    raise Exception('Could not infer language pair, please provide it explicitly')
Exception: Could not infer language pair, please provide it explicitly