fix io; add test

.bashrc

+# Locales
+
+export LC_ALL=en_US.UTF-8
+export LANG=en_US.UTF-8
+export LANGUAGE=en_US.UTF-8
+
+# Aliases
+alias nvs="nvidia-smi"
+alias rsync="rsync --progress -raz"
+alias his="history"

deepspeech/io/batchfy.py

@@ -347,7 +347,7 @@ def make_batchset(
     Note that if any utts doesn't have "category",
     perform as same as batchfy_by_{count}
 
-    :param Dict[str, Dict[str, Any]] data: dictionary loaded from data.json
+    :param List[Dict[str, Any]] data: dictionary loaded from data.json
     :param int batch_size: maximum number of sequences in a minibatch.
     :param int batch_bins: maximum number of bins (frames x dim) in a minibatch.
     :param int batch_frames_in:  maximum number of input frames in a minibatch.
@@ -374,7 +374,6 @@ def make_batchset(
         reserved for future research, -1 means all axis.)
     :return: List[List[Tuple[str, dict]]] list of batches
     """
-
     # check args
     if count not in BATCH_COUNT_CHOICES:
         raise ValueError(
@@ -386,7 +385,6 @@ def make_batchset(
     ikey = "input"
     okey = "output"
     batch_sort_axis = 0  # index of list 
-
     if count == "auto":
         if batch_size != 0:
             count = "seq"
@@ -405,7 +403,8 @@ def make_batchset(
             "batch_sort_key=shuffle is only available if batch_count=seq")
 
     category2data = {}  # Dict[str, dict]
-    for k, v in data.items():
+    for v in data:
+        k = v['utt']
         category2data.setdefault(v.get("category"), {})[k] = v
 
     batches_list = []  # List[List[List[Tuple[str, dict]]]]
@@ -422,6 +421,7 @@ def make_batchset(
             key=lambda data: int(data[1][batch_sort_key][batch_sort_axis]["shape"][0]),
             reverse=not shortest_first, )
         logger.info("# utts: " + str(len(sorted_data)))
+        
         if count == "seq":
             batches = batchfy_by_seq(
                 sorted_data,

deepspeech/io/dataset.py

@@ -16,7 +16,7 @@ from typing import Optional
 from paddle.io import Dataset
 from yacs.config import CfgNode
 
-from deepspeech.frontend.utility import read_manifest
+
 from deepspeech.utils.log import Log
 
 __all__ = ["ManifestDataset", "TripletManifestDataset", "TransformDataset"]