Dim auto_generated flag

Allows for better Dim is_equal
which does not rely on the description.

#634

Author: albertz

returnn/tf/util/data.py

@@ -214,6 +214,7 @@ def copy(self, same_as_self=True, description=None, kind=None, match_priority=No
       assert description is not None, "%s copy with not same_as_self should have a new description" % self
     tag = Dim(
       kind=kind or self.kind, description=description or self.description,
+      auto_generated=self.auto_generated,
       match_priority=match_priority if match_priority is not None else self.match_priority,
       dimension=self.dimension, dyn_size_ext=self.dyn_size_ext,
       batch=self.batch,
@@ -380,6 +381,7 @@ def get_for_batch_ctx(self, batch, ctx, allow_none=False):
       return None
     dim_tag = Dim(
       kind=self.kind, description=self.description, dimension=self.dimension,
+      auto_generated=self.auto_generated,
       batch=batch, control_flow_ctx=dyn_size_ext.control_flow_ctx if dyn_size_ext else ctx,
       dyn_size_ext=dyn_size_ext)
     dim_tag.same_as = same_base
@@ -2743,7 +2745,7 @@ def template_from_constant(cls, x, name, dtype=None, shape=None, with_batch_dim=
           assert d == d_
         d = Dim(
           kind=Dim.Types.Spatial if i < len(shape) - 1 else Dim.Types.Feature,
-          description="%s:static:%i" % (name, i),
+          description="%s:static:%i" % (name, i), auto_generated=True,
           dimension=d)
       else:
         raise TypeError("%r shape[%i] invalid type %r in shape %r" % (name, i, type(d), shape))
@@ -3409,7 +3411,8 @@ def copy_add_dim_by_tag(self, dim_tag, unbroadcast=False, axis=None):
       dim_tag = dim_tag.copy(same_as_self=True, kind=Dim.Types.Spatial)
     if not unbroadcast and dim_tag.dimension != 1:
       dim_tag = Dim(
-        kind=dim_tag.kind, description="%s_dummy_dim1" % (dim_tag.description or "unnamed"), dimension=1)
+        kind=dim_tag.kind, description="%s_dummy_dim1" % (dim_tag.description or "unnamed"), dimension=1,
+        auto_generated=True)
     data_opts["dim_tags"] = self.dim_tags[:axis] + (dim_tag,) + self.dim_tags[axis:]
     other_special_axes = self.get_special_axes_dict(counted_with_batch_dim=True, only_available=True)
     for k, a in other_special_axes.items():
@@ -3444,11 +3447,11 @@ def copy_split_feature_dim(self, new_feature_dim):
     new_feature_dim_axis = self.feature_dim_axis + 1
     data_opts = self.get_kwargs(include_special_axes=False)
     dim_tag_split_rem = Dim(
-      kind=Dim.Types.Spatial, description="feature_split_rem_%i" % feature_dim_rem,
+      kind=Dim.Types.Spatial, description="feature_split_rem_%i" % feature_dim_rem, auto_generated=True,
       dimension=feature_dim_rem)
     dim_tag_new = Dim(
       kind=self.dim_tags[self.feature_dim_axis].kind,
-      description="feature_split_new_%i" % new_feature_dim,
+      description="feature_split_new_%i" % new_feature_dim, auto_generated=True,
       dimension=new_feature_dim)
     dim_tags = (
       self.dim_tags[:self.feature_dim_axis] +
@@ -3614,7 +3617,7 @@ def copy_time_flattened(self):
       data_opts["placeholder"] = self.get_placeholder_time_flattened()
     dim_tag = self.dim_tags[self.time_dim_axis]
     dim_tag = Dim(
-      kind=Dim.Types.Spatial, description="%s_flattened" % (dim_tag.description or "unnamed"))
+      kind=Dim.Types.Spatial, description="%s_flattened" % (dim_tag.description or "unnamed"), auto_generated=True)
     data_opts["dim_tags"] = (
       (dim_tag,) +
       tuple(tag for (i, tag) in enumerate(self.dim_tags) if i not in (self.batch_dim_axis, self.time_dim_axis)))
@@ -3818,7 +3821,7 @@ def copy_template_adding_time_dim(self, name=None, time_dim_axis=0):
       assert time_dim_axis >= 0
     assert 0 <= time_dim_axis <= self.batch_ndim
     kwargs = self.get_kwargs(include_special_axes=False)
-    dim_tag = Dim(kind=Dim.Types.Time, description="unknown_time", dimension=None)
+    dim_tag = Dim(kind=Dim.Types.Time, description="unknown_time", dimension=None, auto_generated=True)
     dim_tags = self.dim_tags[:time_dim_axis] + (dim_tag,) + self.dim_tags[time_dim_axis:]
     kwargs["dim_tags"] = dim_tags
     other_special_axes = self.get_special_axes_dict(counted_with_batch_dim=True, only_available=True)
@@ -3872,6 +3875,7 @@ def copy_template_replace_dim(self, axis, new_dim, new_size=None):
       return self.copy_template()  # nothing to do
     dim_tag = Dim(
       kind=dim_tag.kind, description="%s_replaced" % (dim_tag.description or "unnamed"),
+      auto_generated=True,
       dimension=new_dim, dyn_size=new_size)
     return self.copy_template_replace_dim_tag(axis=axis, new_dim_tag=dim_tag)
 
@@ -5572,7 +5576,7 @@ def _infer_dim_tags_tuple_from_shape(
     if axis == feature_dim_axis and dyn_size is None and axis != time_dim_axis:
       tag = Dim(
         kind=Dim.Types.Feature, dimension=dim, description="feature:%s" % name,
-        undefined=dim is None)
+        undefined=dim is None, auto_generated=True)
     else:
       assert axis in spatial_axes
       description = "time" if axis == time_dim_axis else "spatial%i" % spatial_axes.index(axis)
@@ -5587,7 +5591,7 @@ def _infer_dim_tags_tuple_from_shape(
       description += ":%s" % name
       tag = Dim(
         kind=Dim.Types.Spatial, description=description, dimension=dim, dyn_size=dyn_size,
-        undefined=dim is None and dyn_size is None)
+        undefined=dim is None and dyn_size is None, auto_generated=True)
     dim_tags[axis] = tag
   assert sorted(dim_tags.keys()) == list(range(len(batch_shape)))
   return tuple(dim_tags[axis] for axis in range(len(batch_shape)))