diff --git a/returnn/tf/engine.py b/returnn/tf/engine.py
index e302d9d25..addb6a248 100644
--- a/returnn/tf/engine.py
+++ b/returnn/tf/engine.py
@@ -1293,6 +1293,8 @@ def _init_network(self, net_desc, epoch=None):
     use_dataset_pipeline = False
     if self.config.is_true("dataset_pipeline"):
       use_dataset_pipeline = True
+    from returnn.tf.util.data import batch_dim
+    batch_dim.batch = None  # make sure it is reset
     extern_data = ExternData()
     extern_data.init_from_config(config=self.config, auto_create_placeholders=not use_dataset_pipeline)
     if use_dataset_pipeline:
diff --git a/returnn/tf/util/data.py b/returnn/tf/util/data.py
index 0e67a23bc..1a8e610fc 100644
--- a/returnn/tf/util/data.py
+++ b/returnn/tf/util/data.py
@@ -2823,11 +2823,6 @@ def __init__(self, name,
       if time_dim_axis is NotSpecified:
         time_dim_axis = _default_time_dim_axis_dim_tags(dim_tags)
       dim_tags = tuple(dim_tags)
-      if auto_create_placeholders:
-        _auto_create_size_placeholders_on_dim_tags(name=name, dim_tags=dim_tags)
-      if batch_dim_axis_ is not None:
-        if dim_tags[batch_dim_axis_].batch and not self._batch:
-          self._batch = dim_tags[batch_dim_axis_].batch
       del shape_
       del batch_dim_axis_
     else:
@@ -2846,7 +2841,7 @@ def __init__(self, name,
       dim_tags = _infer_dim_tags_tuple_from_shape(
         shape, batch_dim_axis=batch_dim_axis, time_dim_axis=time_dim_axis, feature_dim_axis=feature_dim_axis,
         size_placeholder=size_placeholder, name=name,
-        auto_create_placeholders=auto_create_placeholders,
+        extern_data=auto_create_placeholders,
         dim_tags=dim_tags, sparse=sparse)
       del batch_dim_axis
       del shape
@@ -2893,8 +2888,10 @@ def __init__(self, name,
         base_tag = self._dim_tags[_axis]
         if base_tag != _dim_tag:
           base_tag.declare_same_as(_dim_tag)
-          if _dim_tag.dyn_size is not None:
-            self.set_dynamic_size(_axis, _dim_tag.dyn_size)
+        self._dim_tags = self._dim_tags[:_axis] + (_dim_tag,) + self._dim_tags[_axis + 1:]
+    if auto_create_placeholders:
+      # Do that after same_dim_tags_as handling.
+      _auto_create_size_placeholders_on_dim_tags(name=name, dim_tags=self._dim_tags)
     self._adapt_batch_consistent_dim_tags()
     self.sanity_check(assume_complete=False)
 
@@ -5780,7 +5777,7 @@ def _infer_dim_tags_tuple_from_shape(
   size_placeholder,
   dim_tags,
   name,
-  auto_create_placeholders
+  extern_data
 ):
   """
   :param tuple[int|None]|list[int|None] shape: this is without batch-dim-axis
@@ -5790,7 +5787,7 @@ def _infer_dim_tags_tuple_from_shape(
   :param bool sparse:
   :param dict[int,tf.Tensor]|None size_placeholder: key is axis without batch-dim
   :param dict[int,Dim]|None dim_tags: some existing explicitly specified dim tags. key is axis with batch-dim
-  :param bool auto_create_placeholders:
+  :param bool extern_data:
   :param str name:
   :return: dim tags tuple
   :rtype: tuple[Dim]
@@ -5808,8 +5805,6 @@ def _infer_dim_tags_tuple_from_shape(
   dim_tags = dim_tags.copy() if dim_tags else {}
   if batch_dim_axis is not None and batch_dim_axis not in dim_tags:
     dim_tags[batch_dim_axis] = Dim(kind=Dim.Types.Batch, description="batch:%s" % name)
-  # noinspection PyShadowingNames
-  batch_dim = dim_tags[batch_dim_axis] if batch_dim_axis is not None else None
   # Note: Consistent to Data.get_dim_tag,
   # prefer interpretation as spatial axis if there is a dynamic size or this is marked as time axis.
   if size_placeholder:
@@ -5833,7 +5828,7 @@ def _infer_dim_tags_tuple_from_shape(
     axis_wo_b = _get_axis_wo_b(axis, batch_dim_axis=batch_dim_axis)
     dyn_size = size_placeholder.get(axis_wo_b) if (size_placeholder and axis_wo_b is not None) else None
     dim = batch_shape[axis]
-    if auto_create_placeholders and dim is None and dyn_size is None and axis != batch_dim_axis:
+    if extern_data and dim is None and dyn_size is None and axis != batch_dim_axis:
       if not tag:
         if axis == time_dim_axis:
           tag_name = "time"
@@ -5845,7 +5840,6 @@ def _infer_dim_tags_tuple_from_shape(
           # This is such that Dim.is_equal behaves as before, e.g. in Data.get_common_data.
           kind=Dim.Types.Spatial)
         dim_tags[axis] = tag
-      _create_size_placeholder(name=name, axis_wo_b=axis_wo_b, tag=tag, batch_dim=batch_dim)
       dyn_size = tag.dyn_size
     if tag:
       # Just some sanity checks.
diff --git a/tests/test_TFNetworkLayer.py b/tests/test_TFNetworkLayer.py
index 3e7e515e2..61dd1fcf7 100644
--- a/tests/test_TFNetworkLayer.py
+++ b/tests/test_TFNetworkLayer.py
@@ -2223,12 +2223,13 @@ def test_SplitDimsLayer_dim_tags():
     feat_dim = FeatureDim("feat", 3)
     config = Config({
       "extern_data": {"data": {"dim_tags": [batch_dim, time_dim, feat_dim]}}})
-    net = TFNetwork(config=config)
-    net.construct_from_dict({
-      "output": {
-        'class': 'split_dims', 'from': 'data', 'axis': time_dim, 'dims': [rem_dim, window_dim],
-        'out_shape': {batch_dim, rem_dim, window_dim, feat_dim}}
-    })
+    with make_scope():
+      net = TFNetwork(config=config)
+      net.construct_from_dict({
+        "output": {
+          'class': 'split_dims', 'from': 'data', 'axis': time_dim, 'dims': [rem_dim, window_dim],
+          'out_shape': {batch_dim, rem_dim, window_dim, feat_dim}}
+      })
 
 
 def test_SplitDimsLayer_dim_tags_expand():
@@ -2238,12 +2239,13 @@ def test_SplitDimsLayer_dim_tags_expand():
   expand_dim = SpatialDim("expand_dim", 1)
   config = Config({
     "extern_data": {"data": {"dim_tags": [batch_dim, time_dim, feat_dim]}}})
-  net = TFNetwork(config=config)
-  net.construct_from_dict({
-    "output": {
-      'class': 'split_dims', 'from': 'data', 'axis': feat_dim, 'dims': [feat_dim, expand_dim],
-      'out_shape': {batch_dim, time_dim, feat_dim, expand_dim}}
-  })
+  with make_scope():
+    net = TFNetwork(config=config)
+    net.construct_from_dict({
+      "output": {
+        'class': 'split_dims', 'from': 'data', 'axis': feat_dim, 'dims': [feat_dim, expand_dim],
+        'out_shape': {batch_dim, time_dim, feat_dim, expand_dim}}
+    })
 
 
 def test_SplitDimsLayer_dim_tags_split_batch_simple():
diff --git a/tests/test_TFUtil.py b/tests/test_TFUtil.py
index 9a8eac7de..bb0b9c989 100644
--- a/tests/test_TFUtil.py
+++ b/tests/test_TFUtil.py
@@ -1243,6 +1243,22 @@ def test_Data_verify_out_shape_optional_implicit_dim():
   x.verify_out_shape({time_dim, feat_dim}, allow_missing_implicit_dims=True)
 
 
+def test_Data_auto_create_placeholders_same_dim_tags_as_existing():
+  # Came up via: https://github.com/rwth-i6/returnn/pull/1143
+  n_out = 3
+  time_tag = SpatialDim("time")
+  with tf.Graph().as_default() as graph, tf_compat.v1.Session(graph=graph) as session:
+    assert isinstance(graph, tf.Graph)
+    data = Data("data", dim=n_out, same_dim_tags_as={"t": time_tag}, auto_create_placeholders=True)
+    classes = Data("classes", dim=n_out, sparse=True, same_dim_tags_as={"t": time_tag}, auto_create_placeholders=True)
+    assert time_tag.dyn_size is not None  # this is not so relevant and might change
+    seq_len = time_tag.dyn_size
+    assert seq_len is data.get_sequence_lengths() is classes.get_sequence_lengths()
+    assert seq_len.op.type == "Placeholder"
+    placeholder_ops = [op for op in graph.get_operations() if op.type == "Placeholder"]
+    assert_equal(set(placeholder_ops), {data.placeholder.op, classes.placeholder.op, time_tag.dyn_size.op})
+
+
 def test_Dim_copy():
   # https://github.com/rwth-i6/returnn/issues/860
   import copy