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Functions986 in github.com/Amazing-J/structural-transformer

⨍ Functions 986◇ Types & classes 128
↓ 1 callersFunctionmain
()
opennmt-cnn/preprocess.py:534
↓ 1 callersFunctionmain
(opt)
opennmt-avg/train.py:11
↓ 1 callersFunctionmain
(opt, device_id)
opennmt-avg/train_single.py:64
↓ 1 callersFunctionmain
(opt)
opennmt-avg/translate.py:13
↓ 1 callersFunctionmain
()
opennmt-avg/preprocess.py:534
↓ 1 callersFunctionmain
(opt)
opennmt-baseline/train.py:11
↓ 1 callersFunctionmain
(opt, device_id)
opennmt-baseline/train_single.py:64
↓ 1 callersFunctionmain
(opt)
opennmt-baseline/translate.py:13
↓ 1 callersFunctionmain
()
opennmt-baseline/preprocess.py:249
↓ 1 callersFunctionmain
(opt)
opennmt-self/train.py:11
↓ 1 callersFunctionmain
(opt, device_id)
opennmt-self/train_single.py:64
↓ 1 callersFunctionmain
(opt)
opennmt-self/translate.py:13
↓ 1 callersFunctionmain
()
opennmt-self/preprocess.py:534
↓ 1 callersMethodmake_nested_examples
(text_iter, truncate, side)
opennmt-feature/inputters/dataset.py:376
↓ 1 callersMethodmaybe_save
Main entry point for model saver It wraps the `_save` method with checks and apply `keep_checkpoint` related logic
opennmt-feature/train_single.py:155
↓ 1 callersMethodmaybe_save
Main entry point for model saver It wraps the `_save` method with checks and apply `keep_checkpoint` related logic
opennmt-cnn/train_single.py:155
↓ 1 callersMethodmaybe_save
Main entry point for model saver It wraps the `_save` method with checks and apply `keep_checkpoint` related logic
opennmt-avg/train_single.py:155
↓ 1 callersMethodmaybe_save
Main entry point for model saver It wraps the `_save` method with checks and apply `keep_checkpoint` related logic
opennmt-baseline/train_single.py:156
↓ 1 callersMethodmaybe_save
Main entry point for model saver It wraps the `_save` method with checks and apply `keep_checkpoint` related logic
opennmt-self/train_single.py:155
↓ 1 callersFunctionmerge_vocabs
(vocabs, vocab_size=None, min_frequency=1)
opennmt-feature/preprocess.py:40
↓ 1 callersFunctionmerge_vocabs
(vocabs, vocab_size=None, min_frequency=1)
opennmt-baseline/preprocess.py:35
↓ 1 callersMethodmonolithic_compute_loss
Compute the forward loss for the batch. Args: batch (batch): batch of labeled examples output (:obj:`FloatTensor
opennmt-feature/utils/loss.py:103
↓ 1 callersMethodmonolithic_compute_loss
Compute the forward loss for the batch. Args: batch (batch): batch of labeled examples output (:obj:`FloatTensor
opennmt-cnn/utils/loss.py:103
↓ 1 callersMethodmonolithic_compute_loss
Compute the forward loss for the batch. Args: batch (batch): batch of labeled examples output (:obj:`FloatTensor
opennmt-avg/utils/loss.py:103
↓ 1 callersMethodmonolithic_compute_loss
Compute the forward loss for the batch. Args: batch (batch): batch of labeled examples output (:obj:`FloatTensor
opennmt-baseline/utils/loss.py:103
↓ 1 callersMethodmonolithic_compute_loss
Compute the forward loss for the batch. Args: batch (batch): batch of labeled examples output (:obj:`FloatTensor
opennmt-self/utils/loss.py:103
↓ 1 callersMethodoutput
Write out statistics to stdout. Args: step (int): current step n_batch (int): total batches start (int): start time of step.
opennmt-feature/utils/statistics.py:103
↓ 1 callersMethodoutput
Write out statistics to stdout. Args: step (int): current step n_batch (int): total batches start (int): start time of step.
opennmt-cnn/utils/statistics.py:103
↓ 1 callersMethodoutput
Write out statistics to stdout. Args: step (int): current step n_batch (int): total batches start (int): start time of step.
opennmt-avg/utils/statistics.py:103
↓ 1 callersMethodoutput
Write out statistics to stdout. Args: step (int): current step n_batch (int): total batches start (int): start time of step.
opennmt-baseline/utils/statistics.py:103
↓ 1 callersMethodoutput
Write out statistics to stdout. Args: step (int): current step n_batch (int): total batches start (int): start time of step.
opennmt-self/utils/statistics.py:103
↓ 1 callersFunctionparse_args
()
opennmt-feature/preprocess.py:114
↓ 1 callersFunctionparse_args
()
opennmt-cnn/preprocess.py:195
↓ 1 callersFunctionparse_args
()
opennmt-avg/preprocess.py:195
↓ 1 callersFunctionparse_args
()
opennmt-baseline/preprocess.py:95
↓ 1 callersFunctionparse_args
()
opennmt-self/preprocess.py:195
↓ 1 callersMethodreport_step
Report stats of a step Args: train_stats(Statistics): training stats valid_stats(Statistics): validation sta
opennmt-feature/utils/report_manager.py:88
↓ 1 callersMethodreport_step
Report stats of a step Args: train_stats(Statistics): training stats valid_stats(Statistics): validation sta
opennmt-cnn/utils/report_manager.py:88
↓ 1 callersMethodreport_step
Report stats of a step Args: train_stats(Statistics): training stats valid_stats(Statistics): validation sta
opennmt-avg/utils/report_manager.py:88
↓ 1 callersMethodreport_step
Report stats of a step Args: train_stats(Statistics): training stats valid_stats(Statistics): validation sta
opennmt-baseline/utils/report_manager.py:88
↓ 1 callersMethodreport_step
Report stats of a step Args: train_stats(Statistics): training stats valid_stats(Statistics): validation sta
opennmt-self/utils/report_manager.py:88
↓ 1 callersMethodreport_training
This is the user-defined batch-level traing progress report function. Args: step(int): current step count.
opennmt-feature/utils/report_manager.py:55
↓ 1 callersMethodreport_training
This is the user-defined batch-level traing progress report function. Args: step(int): current step count.
opennmt-cnn/utils/report_manager.py:55
↓ 1 callersMethodreport_training
This is the user-defined batch-level traing progress report function. Args: step(int): current step count.
opennmt-avg/utils/report_manager.py:55
↓ 1 callersMethodreport_training
This is the user-defined batch-level traing progress report function. Args: step(int): current step count.
opennmt-baseline/utils/report_manager.py:55
↓ 1 callersMethodreport_training
This is the user-defined batch-level traing progress report function. Args: step(int): current step count.
opennmt-self/utils/report_manager.py:55
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-feature/preprocess.py:17
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-feature/inputters/dataset.py:46
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-cnn/preprocess.py:17
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-cnn/inputters/dataset.py:46
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-avg/preprocess.py:17
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-avg/inputters/dataset.py:46
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-baseline/preprocess.py:17
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-baseline/inputters/dataset.py:47
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-self/preprocess.py:17
↓ 1 callersFunctionsave_fields_to_vocab
Save Vocab objects in Field objects to `vocab.pt` file.
opennmt-self/inputters/dataset.py:46
↓ 1 callersMethodset_parameters
?
opennmt-feature/utils/optimizers.py:172
↓ 1 callersMethodset_parameters
?
opennmt-cnn/utils/optimizers.py:172
↓ 1 callersMethodset_parameters
?
opennmt-avg/utils/optimizers.py:172
↓ 1 callersMethodset_parameters
?
opennmt-baseline/utils/optimizers.py:172
↓ 1 callersMethodset_parameters
?
opennmt-self/utils/optimizers.py:172
↓ 1 callersMethodsharded_compute_loss
Compute the forward loss and backpropagate. Computation is done with shards and optionally truncation for memory efficiency. Also su
opennmt-feature/utils/loss.py:123
↓ 1 callersMethodsharded_compute_loss
Compute the forward loss and backpropagate. Computation is done with shards and optionally truncation for memory efficiency. Also su
opennmt-cnn/utils/loss.py:123
↓ 1 callersMethodsharded_compute_loss
Compute the forward loss and backpropagate. Computation is done with shards and optionally truncation for memory efficiency. Also su
opennmt-avg/utils/loss.py:123
↓ 1 callersMethodsharded_compute_loss
Compute the forward loss and backpropagate. Computation is done with shards and optionally truncation for memory efficiency. Also su
opennmt-baseline/utils/loss.py:123
↓ 1 callersMethodsharded_compute_loss
Compute the forward loss and backpropagate. Computation is done with shards and optionally truncation for memory efficiency. Also su
opennmt-self/utils/loss.py:123
↓ 1 callersFunctionshards
Args: state: A dictionary which corresponds to the output of *LossCompute._make_shard_state(). The values for
opennmt-feature/utils/loss.py:256
↓ 1 callersFunctionshards
Args: state: A dictionary which corresponds to the output of *LossCompute._make_shard_state(). The values for
opennmt-cnn/utils/loss.py:256
↓ 1 callersFunctionshards
Args: state: A dictionary which corresponds to the output of *LossCompute._make_shard_state(). The values for
opennmt-avg/utils/loss.py:256
↓ 1 callersFunctionshards
Args: state: A dictionary which corresponds to the output of *LossCompute._make_shard_state(). The values for
opennmt-baseline/utils/loss.py:256
↓ 1 callersFunctionshards
Args: state: A dictionary which corresponds to the output of *LossCompute._make_shard_state(). The values for
opennmt-self/utils/loss.py:256
↓ 1 callersFunctiontile
Tiles x on dimension dim count times.
opennmt-feature/utils/misc.py:28
↓ 1 callersFunctiontile
Tiles x on dimension dim count times.
opennmt-cnn/utils/misc.py:28
↓ 1 callersFunctiontile
Tiles x on dimension dim count times.
opennmt-avg/utils/misc.py:28
↓ 1 callersFunctiontile
Tiles x on dimension dim count times.
opennmt-baseline/utils/misc.py:28
↓ 1 callersFunctiontile
Tiles x on dimension dim count times.
opennmt-self/utils/misc.py:28
↓ 1 callersFunctiontraining_opt_postprocessing
(opt, device_id)
opennmt-feature/train_single.py:39
↓ 1 callersFunctiontraining_opt_postprocessing
(opt, device_id)
opennmt-cnn/train_single.py:39
↓ 1 callersFunctiontraining_opt_postprocessing
(opt, device_id)
opennmt-avg/train_single.py:39
↓ 1 callersFunctiontraining_opt_postprocessing
(opt, device_id)
opennmt-baseline/train_single.py:40
↓ 1 callersFunctiontraining_opt_postprocessing
(opt, device_id)
opennmt-self/train_single.py:39
↓ 1 callersMethodtranslate
(self, src_data_iter, tgt_data_iter, structure_iter, batch_size, out_file=None)
opennmt-feature/onmt/translator.py:59
↓ 1 callersMethodtranslate
(self, src_data_iter, tgt_data_iter, structure_iter1,
opennmt-cnn/onmt/translator.py:59
↓ 1 callersMethodtranslate
(self, src_data_iter, tgt_data_iter, structure_iter1,
opennmt-avg/onmt/translator.py:59
↓ 1 callersMethodtranslate
(self, src_data_iter, tgt_data_iter, batch_size, out_file=None)
opennmt-baseline/onmt/translator.py:56
↓ 1 callersMethodtranslate
(self, src_data_iter, tgt_data_iter, structure_iter1,
opennmt-self/onmt/translator.py:59
↓ 1 callersMethodtranslate_batch
(self, batch)
opennmt-feature/onmt/translator.py:120
↓ 1 callersMethodtranslate_batch
(self, batch)
opennmt-cnn/onmt/translator.py:137
↓ 1 callersMethodtranslate_batch
(self, batch)
opennmt-avg/onmt/translator.py:137
↓ 1 callersMethodtranslate_batch
(self, batch)
opennmt-baseline/onmt/translator.py:104
↓ 1 callersMethodtranslate_batch
(self, batch)
opennmt-self/onmt/translator.py:137
↓ 1 callersFunctionvalid_iter_fct
()
opennmt-feature/train_single.py:110
↓ 1 callersFunctionvalid_iter_fct
()
opennmt-cnn/train_single.py:110
↓ 1 callersFunctionvalid_iter_fct
()
opennmt-avg/train_single.py:110
↓ 1 callersFunctionvalid_iter_fct
()
opennmt-baseline/train_single.py:110
↓ 1 callersFunctionvalid_iter_fct
()
opennmt-self/train_single.py:110
↓ 1 callersMethodvalidate
Validate model. valid_iter: validate data iterator Returns: :obj:`nmt.Statistics`: validation loss statistics
opennmt-feature/trainer.py:209
↓ 1 callersMethodvalidate
Validate model. valid_iter: validate data iterator Returns: :obj:`nmt.Statistics`: validation loss statistics
opennmt-cnn/trainer.py:208
↓ 1 callersMethodvalidate
Validate model. valid_iter: validate data iterator Returns: :obj:`nmt.Statistics`: validation loss statistics
opennmt-avg/trainer.py:208
↓ 1 callersMethodvalidate
Validate model. valid_iter: validate data iterator Returns: :obj:`nmt.Statistics`: validation loss statistics
opennmt-baseline/trainer.py:209
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