[s2t] DataLoader with BatchSampler or DistributeBatchSampler (#1242)

* batchsampler or distributebatchsampler

* format

paddlespeech/s2t/exps/u2_st/model.py

@@ -292,7 +292,8 @@ class U2STTrainer(Trainer):
                 n_iter_processes=config.collator.num_workers,
                 subsampling_factor=1,
                 load_aux_output=load_transcript,
-                num_encs=1)
+                num_encs=1,
+                dist_sampler=True)
 
             self.valid_loader = BatchDataLoader(
                 json_file=config.data.dev_manifest,
@@ -313,7 +314,8 @@ class U2STTrainer(Trainer):
                 n_iter_processes=config.collator.num_workers,
                 subsampling_factor=1,
                 load_aux_output=load_transcript,
-                num_encs=1)
+                num_encs=1,
+                dist_sampler=True)
             logger.info("Setup train/valid Dataloader!")
         else:
             # test dataset, return raw text
@@ -335,7 +337,8 @@ class U2STTrainer(Trainer):
                 augmentation_config,  # aug will be off when train_mode=False
                 n_iter_processes=config.collator.num_workers,
                 subsampling_factor=1,
-                num_encs=1)
+                num_encs=1,
+                dist_sampler=False)
 
             logger.info("Setup test Dataloader!")
 
@@ -542,7 +545,8 @@ class U2STTester(U2STTrainer):
                 len_refs += metrics['len_refs']
                 num_ins += metrics['num_ins']
                 rtf = num_time / (num_frames * stride_ms)
-                logger.info("RTF: %f, instance (%d), batch BELU   = %f" % (rtf, num_ins, bleu))
+                logger.info("RTF: %f, instance (%d), batch BELU   = %f" %
+                            (rtf, num_ins, bleu))
 
         rtf = num_time / (num_frames * stride_ms)
         msg = "Test: "

paddlespeech/s2t/io/converter.py

@@ -65,7 +65,8 @@ class CustomConverter():
                 # text data (output): (text_len, )
                 ys_data.append(ud)
 
-        assert xs_data[0][0] is not None, "please check Reader and Augmentation impl."
+        assert xs_data[0][
+            0] is not None, "please check Reader and Augmentation impl."
 
         xs_pad, ilens = [], []
         for xs in xs_data:
@@ -88,12 +89,16 @@ class CustomConverter():
         ys_pad, olens = [], []
 
         for ys in ys_data:
-            ys_pad.append(pad_list(
-                [np.array(y[0][:]) if isinstance(y, tuple) else y for y in ys],
-                self.ignore_id))
-
-            olens.append(np.array(
-                [y[0].shape[0] if isinstance(y, tuple) else y.shape[0] for y in ys]))
+            ys_pad.append(
+                pad_list([
+                    np.array(y[0][:]) if isinstance(y, tuple) else y for y in ys
+                ], self.ignore_id))
+
+            olens.append(
+                np.array([
+                    y[0].shape[0] if isinstance(y, tuple) else y.shape[0]
+                    for y in ys
+                ]))
 
             if not self.load_aux_output:
                 ys_pad, olens = ys_pad[0], olens[0]

paddlespeech/s2t/io/dataloader.py

@@ -18,6 +18,7 @@ from typing import Text
 
 import jsonlines
 import numpy as np
+from paddle.io import BatchSampler
 from paddle.io import DataLoader
 from paddle.io import DistributedBatchSampler
 
@@ -76,7 +77,8 @@ class BatchDataLoader():
                  subsampling_factor: int=1,
                  load_aux_input: bool=False,
                  load_aux_output: bool=False,
-                 num_encs: int=1):
+                 num_encs: int=1,
+                 dist_sampler: bool=False):
         self.json_file = json_file
         self.train_mode = train_mode
         self.use_sortagrad = sortagrad == -1 or sortagrad > 0
@@ -94,6 +96,7 @@ class BatchDataLoader():
         self.n_iter_processes = n_iter_processes
         self.load_aux_input = load_aux_input
         self.load_aux_output = load_aux_output
+        self.dist_sampler = dist_sampler
 
         # read json data
         with jsonlines.open(json_file, 'r') as reader:
@@ -145,11 +148,18 @@ class BatchDataLoader():
         self.dataset = TransformDataset(self.minibaches, self.converter,
                                         self.reader)
 
-        self.sampler = DistributedBatchSampler(
-            dataset=self.dataset,
-            batch_size=1,
-            shuffle=not self.use_sortagrad if self.train_mode else False,
-            )
+        if self.dist_sampler:
+            self.sampler = DistributedBatchSampler(
+                dataset=self.dataset,
+                batch_size=1,
+                shuffle=not self.use_sortagrad if self.train_mode else False,
+                drop_last=False, )
+        else:
+            self.sampler = BatchSampler(
+                dataset=self.dataset,
+                batch_size=1,
+                shuffle=not self.use_sortagrad if self.train_mode else False,
+                drop_last=False, )
 
         self.dataloader = DataLoader(
             dataset=self.dataset,
@@ -181,5 +191,8 @@ class BatchDataLoader():
         echo += f"subsampling_factor: {self.subsampling_factor}, "
         echo += f"num_encs: {self.num_encs}, "
         echo += f"num_workers: {self.n_iter_processes}, "
+        echo += f"load_aux_input: {self.load_aux_input}, "
+        echo += f"load_aux_output: {self.load_aux_output}, "
+        echo += f"dist_sampler: {self.dist_sampler}, "
         echo += f"file: {self.json_file}"
         return echo

paddlespeech/t2s/exps/synthesize_e2e.py

@@ -203,12 +203,15 @@ def evaluate(args):
             get_tone_ids = True
         if args.lang == 'zh':
             input_ids = frontend.get_input_ids(
-                sentence, merge_sentences=merge_sentences, get_tone_ids=get_tone_ids)
+                sentence,
+                merge_sentences=merge_sentences,
+                get_tone_ids=get_tone_ids)
             phone_ids = input_ids["phone_ids"]
             if get_tone_ids:
                 tone_ids = input_ids["tone_ids"]
         elif args.lang == 'en':
-            input_ids = frontend.get_input_ids(sentence, merge_sentences=merge_sentences)
+            input_ids = frontend.get_input_ids(
+                sentence, merge_sentences=merge_sentences)
             phone_ids = input_ids["phone_ids"]
         else:
             print("lang should in {'zh', 'en'}!")