diff --git a/deepspeech/exps/u2/model.py b/deepspeech/exps/u2/model.py
index af84d9cfddec4467975158735102ab02ecefe6fe..df233cdc2ba6814d9e999da9a6b71097ee2f84b4 100644
--- a/deepspeech/exps/u2/model.py
+++ b/deepspeech/exps/u2/model.py
@@ -24,6 +24,7 @@ import numpy as np
 import paddle
 from paddle import distributed as dist
 from paddle.io import DataLoader
+from paddle.io import DistributedBatchSampler
 from yacs.config import CfgNode
 
 from deepspeech.io.collator import SpeechCollator
@@ -162,8 +163,10 @@ class U2Trainer(Trainer):
             self.save(tag='init')
 
         self.lr_scheduler.step(self.iteration)
-        if self.parallel:
-            self.train_loader.batch_sampler.set_epoch(self.epoch)
+        if hasattr(self.train_loader, "batch_sampler"):
+            batch_sampler = self.train_loader.batch_sampler
+            if isinstance(batch_sampler, DistributedBatchSampler):
+                batch_sampler.set_epoch(self.epoch)
 
         logger.info(f"Train Total Examples: {len(self.train_loader.dataset)}")
         while self.epoch < self.config.training.n_epoch:
@@ -476,13 +479,6 @@ class U2Tester(U2Trainer):
             })
             f.write(data + '\n')
 
-    # def run_test(self):
-    #     self.resume_or_scratch()
-    #     try:
-    #         self.test()
-    #     except KeyboardInterrupt:
-    #         sys.exit(-1)
-
     def load_inferspec(self):
         """infer model and input spec.
 
@@ -491,7 +487,7 @@ class U2Tester(U2Trainer):
             List[paddle.static.InputSpec]: input spec.
         """
         from deepspeech.models.u2 import U2InferModel
-        infer_model = U2InferModel.from_pretrained(self.test_loader.dataset,
+        infer_model = U2InferModel.from_pretrained(self.test_loader,
                                                    self.config.model.clone(),
                                                    self.args.checkpoint_path)
         feat_dim = self.test_loader.dataset.feature_size
@@ -511,37 +507,3 @@ class U2Tester(U2Trainer):
         static_model = paddle.jit.to_static(infer_model, input_spec=input_spec)
         logger.info(f"Export code: {static_model.forward.code}")
         paddle.jit.save(static_model, self.args.export_path)
-
-    # def run_export(self):
-    #     try:
-    #         self.export()
-    #     except KeyboardInterrupt:
-    #         sys.exit(-1)
-
-    # def setup(self):
-    #     """Setup the experiment.
-    #     """
-    #     paddle.set_device(self.args.device)
-
-    #     self.setup_output_dir()
-    #     self.setup_checkpointer()
-
-    #     self.setup_dataloader()
-    #     self.setup_model()
-
-    #     self.iteration = 0
-    #     self.epoch = 0
-
-    # def setup_output_dir(self):
-    #     """Create a directory used for output.
-    #     """
-    #     # output dir
-    #     if self.args.output:
-    #         output_dir = Path(self.args.output).expanduser()
-    #         output_dir.mkdir(parents=True, exist_ok=True)
-    #     else:
-    #         output_dir = Path(
-    #             self.args.checkpoint_path).expanduser().parent.parent
-    #         output_dir.mkdir(parents=True, exist_ok=True)
-
-    #     self.output_dir = output_dir
diff --git a/deepspeech/frontend/augmentor/spec_augment.py b/deepspeech/frontend/augmentor/spec_augment.py
index 1c2e09fc76e4f17fe7097352772c5c54fd08d6fd..956975c6b1375e28f0a184c391d52ae22e064fa8 100644
--- a/deepspeech/frontend/augmentor/spec_augment.py
+++ b/deepspeech/frontend/augmentor/spec_augment.py
@@ -25,10 +25,10 @@ class SpecAugmentor(AugmentorBase):
 
     SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition
         https://arxiv.org/abs/1904.08779
-        
+
     SpecAugment on Large Scale Datasets
         https://arxiv.org/abs/1912.05533
-    
+
     """
 
     def __init__(self,
@@ -41,7 +41,8 @@ class SpecAugmentor(AugmentorBase):
                  W=40,
                  adaptive_number_ratio=0,
                  adaptive_size_ratio=0,
-                 max_n_time_masks=20):
+                 max_n_time_masks=20,
+                 **kwargs):
         """SpecAugment class.
         Args:
             rng (random.Random): random generator object.
@@ -121,7 +122,7 @@ class SpecAugmentor(AugmentorBase):
     def time_mask(self):
         return self._time_mask
 
-    def time_warp(xs, W=40):
+    def time_warp(self, xs, W=40):
         raise NotImplementedError
 
     def mask_freq(self, xs, replace_with_zero=False):
diff --git a/deepspeech/frontend/featurizer/text_featurizer.py b/deepspeech/frontend/featurizer/text_featurizer.py
index 6c481f91fc0942d72c8c3631bf3381638565f303..47c1e6b0e16eadaafb2a210ae807ed891961604a 100644
--- a/deepspeech/frontend/featurizer/text_featurizer.py
+++ b/deepspeech/frontend/featurizer/text_featurizer.py
@@ -13,6 +13,7 @@
 # limitations under the License.
 """Contains the text featurizer class."""
 import sentencepiece as spm
+from pprint import pformat
 
 from ..utility import EOS
 from ..utility import SPACE
@@ -206,7 +207,7 @@ class TextFeaturizer():
         """Load vocabulary from file."""
         vocab_list = load_dict(vocab_filepath, maskctc)
         assert vocab_list is not None
-        logger.info(f"Vocab: {vocab_list}")
+        logger.info(f"Vocab: {pformat(vocab_list)}")
 
         id2token = dict(
             [(idx, token) for (idx, token) in enumerate(vocab_list)])
@@ -220,10 +221,10 @@ class TextFeaturizer():
         sos_id = vocab_list.index(SOS) if SOS in vocab_list else -1
         space_id = vocab_list.index(SPACE) if SPACE in vocab_list else -1
 
+        logger.info(f"BLANK id: {blank_id}")
         logger.info(f"UNK id: {unk_id}")
         logger.info(f"EOS id: {eos_id}")
         logger.info(f"SOS id: {sos_id}")
         logger.info(f"SPACE id: {space_id}")
-        logger.info(f"BLANK id: {blank_id}")
         logger.info(f"MASKCTC id: {maskctc_id}")
         return token2id, id2token, vocab_list, unk_id, eos_id
diff --git a/deepspeech/models/u2/u2.py b/deepspeech/models/u2/u2.py
index e6cd7b5c8fce9ac75330e8ab0e5ad8cb64c69fb9..579961c1602449c903b7a5b727b077b43adde957 100644
--- a/deepspeech/models/u2/u2.py
+++ b/deepspeech/models/u2/u2.py
@@ -911,8 +911,10 @@ class U2Model(U2BaseModel):
             DeepSpeech2Model: The model built from pretrained result.
         """
         with UpdateConfig(config):
-            config.input_dim = dataloader.collate_fn.feature_size
-            config.output_dim = dataloader.collate_fn.vocab_size
+            #config.input_dim = dataloader.collate_fn.feature_size
+            #config.output_dim = dataloader.collate_fn.vocab_size
+            config.input_dim = dataloader.dataset.feature_size
+            config.output_dim = dataloader.dataset.vocab_size
 
         model = cls.from_config(config)
 
diff --git a/deepspeech/training/trainer.py b/deepspeech/training/trainer.py
index 70d7ec1faec363ede313d5ae3835e5221cf93b9f..c0b628abe0974d60354081b2d0c0c14cc03e56e2 100644
--- a/deepspeech/training/trainer.py
+++ b/deepspeech/training/trainer.py
@@ -17,6 +17,7 @@ from pathlib import Path
 
 import paddle
 from paddle import distributed as dist
+from paddle.io import DistributedBatchSampler
 from tensorboardX import SummaryWriter
 
 from deepspeech.utils import mp_tools
@@ -179,8 +180,10 @@ class Trainer():
         """Reset the train loader seed and increment `epoch`.
         """
         self.epoch += 1
-        if self.parallel:
-            self.train_loader.batch_sampler.set_epoch(self.epoch)
+        if hasattr(self.train_loader, "batch_sampler"):
+            batch_sampler = self.train_loader.batch_sampler
+            if isinstance(batch_sampler, DistributedBatchSampler):
+                batch_sampler.set_epoch(self.epoch)
 
     def train(self):
         """The training process control by epoch."""
@@ -190,8 +193,10 @@ class Trainer():
             self.save(tag='init')
 
         self.lr_scheduler.step(self.iteration)
-        if self.parallel:
-            self.train_loader.batch_sampler.set_epoch(self.epoch)
+        if hasattr(self.train_loader, "batch_sampler"):
+            batch_sampler = self.train_loader.batch_sampler
+            if isinstance(batch_sampler, DistributedBatchSampler):
+                batch_sampler.set_epoch(self.epoch)
 
         logger.info(f"Train Total Examples: {len(self.train_loader.dataset)}")
         while self.epoch < self.config.training.n_epoch:
diff --git a/examples/tiny/s0/conf/augmentation.json b/examples/tiny/s0/conf/augmentation.json
index a1a759e67f3a118b6754a60aead069742ede6ecc..4480307b98e3e7c5492e5e419be529617cc2bb24 100644
--- a/examples/tiny/s0/conf/augmentation.json
+++ b/examples/tiny/s0/conf/augmentation.json
@@ -1,4 +1,13 @@
 [
+  {
+    "type": "speed",
+    "params": {
+      "min_speed_rate": 0.9,
+      "max_speed_rate": 1.1,
+      "num_rates": 3
+    },
+    "prob": 0.0
+  },
   {
     "type": "shift",
     "params": {
@@ -6,5 +15,22 @@
       "max_shift_ms": 5
     },
     "prob": 1.0
+  },
+  {
+    "type": "specaug",
+    "params": {
+      "W": 5,
+      "warp_mode": "PIL",
+      "F": 30,
+      "n_freq_masks": 2,
+      "T": 40,
+      "n_time_masks": 2,
+      "p": 1.0,
+      "adaptive_number_ratio": 0,
+      "adaptive_size_ratio": 0,
+      "max_n_time_masks": 20,
+      "replace_with_zero": true
+    },
+    "prob": 1.0
   }
 ]
diff --git a/examples/tiny/s0/local/data.sh b/examples/tiny/s0/local/data.sh
index e2bfffc7e3e7351aeed64c54f62241f169bc45c2..fabf2e4048c4a08425a9e2295a36e0a53bed96d7 100755
--- a/examples/tiny/s0/local/data.sh
+++ b/examples/tiny/s0/local/data.sh
@@ -1,4 +1,4 @@
-#! /usr/bin/env bash
+#!/bin/bash
 
 stage=-1
 stop_stage=100
diff --git a/examples/tiny/s1/path.sh b/examples/tiny/s1/path.sh
index 30adb6ca029e9accc094f19e1764069ce54d8538..29841bc10130a012d5d5eb92855a0394e9acff93 100644
--- a/examples/tiny/s1/path.sh
+++ b/examples/tiny/s1/path.sh
@@ -1,4 +1,4 @@
-export MAIN_ROOT=${PWD}/../../../
+export MAIN_ROOT=`realpath ${PWD}/../../../`
 
 export PATH=${MAIN_ROOT}:${MAIN_ROOT}/utils:${PATH}
 export LC_ALL=C
diff --git a/examples/tiny/s1/test.profile b/examples/tiny/s1/test.profile
deleted file mode 100644
index c64affa2343aae4b5f32f60a642cc47761e73123..0000000000000000000000000000000000000000
Binary files a/examples/tiny/s1/test.profile and /dev/null differ