Dim auto_generated flag (#950)

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

#634

Author: albertz

returnn/tf/layers/base.py

@@ -399,7 +399,7 @@ def _base_get_out_data_from_opts(cls, network, name,
             feature_dim_tag = out_dim
           else:
             dim = out_type.get("dim", None)
-            feature_dim_tag = FeatureDim("%s:feature-dense" % name, dim)
+            feature_dim_tag = FeatureDim("%s:feature-dense" % name, dim, auto_generated=True)
           if feature_dim_axis in (NotSpecified, None):
             if sources_data.feature_dim_axis is None:
               feature_dim_axis = len(dim_tags)

returnn/tf/layers/basic.py

@@ -1056,7 +1056,7 @@ def get_out_data_from_opts(
     if out_dim:
       assert out_dim.dimension == new_dim
     else:
-      out_dim = Dim(kind=dim_tag.kind, description="%s:slice" % name, dimension=new_dim)
+      out_dim = Dim(kind=dim_tag.kind, description="%s:slice" % name, dimension=new_dim, auto_generated=True)
     return input_data.copy_template_replace_dim_tag(axis=axis, new_dim_tag=out_dim, name="%s_output" % name)
 
 
@@ -1236,7 +1236,7 @@ def get_out_data_from_opts(cls, name, sources=(), start=None, size=None, axis="T
         out_spatial_dim = Dim(
           kind=Dim.Types.Spatial,
           description="sliced-time:%s" % name,
-          dimension=size)
+          dimension=size, auto_generated=True)
     gather_positions_data = gather_positions_data.copy_add_dim_by_tag(
       out_spatial_dim, unbroadcast=True, axis=start_data.batch_ndim)
     position = InternalLayer(
@@ -2544,7 +2544,9 @@ def get_out_data_from_opts(cls, name, shape, dtype="float32", **kwargs):
     :param str dtype:
     :rtype: Data
     """
-    dim_tags = [d if isinstance(d, Dim) else SpatialDim("%s:dim%i" % (name, i), d) for i, d in enumerate(shape)]
+    dim_tags = [
+      d if isinstance(d, Dim) else SpatialDim("%s:dim%i" % (name, i), d, auto_generated=True)
+      for i, d in enumerate(shape)]
     return Data(name="%s_output" % name, dim_tags=dim_tags, dtype=dtype)
 
 
@@ -2630,7 +2632,7 @@ def get_out_data_from_opts(cls, name, network, shape, maxval, minval=0, dtype="i
       elif isinstance(d, int):
         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("Layer %r: invalid type %s in shape %r" % (name, type(d), shape))
@@ -2696,12 +2698,12 @@ def get_out_data_from_opts(cls, name, limit, start=0, delta=1, dtype=None, spars
       else:
         dtype = "int32"
     dim = len(range(start, limit, delta))
-    tag = Dim(kind=Dim.Types.Spatial, dimension=dim, description="%s:range" % name)
+    tag = Dim(kind=Dim.Types.Spatial, dimension=dim, description="%s:range" % name, auto_generated=True)
     if out_spatial_dim:
       tag.declare_same_as(out_spatial_dim)
     sparse_dim = None
     if sparse:
-      sparse_dim = SpatialDim("%s:range-indices" % name)
+      sparse_dim = SpatialDim("%s:range-indices" % name, auto_generated=True)
     return Data(name="%s_output" % name, dim_tags=[tag], dtype=dtype, sparse_dim=sparse_dim)
 
 
@@ -2816,7 +2818,7 @@ def get_out_data_from_opts(cls, name, sources, dtype="int32", sparse=False, out_
       dim_tag = Dim.get_tag_from_size_tensor(source.placeholder)
     if not dim_tag:
       dim_tag = Dim(
-        kind=Dim.Types.Spatial, description="%s_input_len" % name,
+        kind=Dim.Types.Spatial, description="%s_input_len" % name, auto_generated=True,
         batch=source.batch, control_flow_ctx=source.control_flow_ctx,
         dyn_size_ext=source)
       if source.placeholder is not None:
@@ -2957,7 +2959,7 @@ def get_out_data_from_opts(cls, name, sources, n_out=NotSpecified, out_dim=None,
     if out_dim:
       assert out_dim.dimension == dim
     else:
-      out_dim = FeatureDim("%s:gating" % name, dimension=dim)
+      out_dim = FeatureDim("%s:gating" % name, dimension=dim, auto_generated=True)
     if n_out is not NotSpecified:
       assert n_out == dim
     return Data(
@@ -3096,15 +3098,15 @@ def get_out_data_from_opts(cls, name, network, sources, window_size=None, window
               filter_size=window_size, stride=stride, dilation_rate=1, padding=padding)
           out_spatial_dim = Dim(
             kind=Dim.Types.Spatial, description="%s:spatial" % name,
-            dimension=dim, derived_from_tag=in_spatial_dim,
+            dimension=dim, derived_from_tag=in_spatial_dim, auto_generated=True,
             batch=data.batch, control_flow_ctx=data.control_flow_ctx)
       data = data.copy_template_replace_dim_tag(axis=axis, new_dim_tag=out_spatial_dim)
       new_dim_axis = axis + 1  # add new axis right after
     if window_dim:
       assert window_dim.dimension == window_size
     else:
       window_dim = Dim(
-        kind=Dim.Types.Spatial, description="%s:window" % name, dimension=window_size)
+        kind=Dim.Types.Spatial, description="%s:window" % name, dimension=window_size, auto_generated=True)
     return data.copy_add_dim_by_tag(axis=new_dim_axis, dim_tag=window_dim, unbroadcast=True)
 
   # noinspection PyMethodOverriding
@@ -3602,9 +3604,11 @@ def _get_axis_size_splits_num_splits(cls, name, input_data, axis=None,
         err_prefix, out_dims, dim, input_data)
     if not out_dims:
       assert size_splits
-      out_dims = [Dim(
-        kind=input_data.dim_tags[axis].kind, description="%s_split%i" % (name, idx),
-        dimension=size_splits[idx]) for idx in range(len(size_splits))]
+      out_dims = [
+        Dim(
+          kind=input_data.dim_tags[axis].kind, description="%s_split%i" % (name, idx),
+          dimension=size_splits[idx], auto_generated=True)
+        for idx in range(len(size_splits))]
     return axis, out_dims
 
   def _make_split_layer(self, idx):
@@ -3884,6 +3888,7 @@ def get_out_data_from_opts(cls, name, axis, dims, pad_to_multiples=None, sources
             kind=axis_dim_tag.kind,
             description="%s_split_dims%i_rem" % (name, rem_dim_idx),
             dimension=resolved_shape_dims[rem_dim_idx],
+            auto_generated=True,
             derived_from_tag=axis_dim_tag,
             batch=axis_dim_tag.batch, control_flow_ctx=axis_dim_tag.control_flow_ctx)
           if rem_dim.dimension is None and axis_dim_tag.dyn_size_ext is not None:
@@ -3900,7 +3905,7 @@ def get_out_data_from_opts(cls, name, axis, dims, pad_to_multiples=None, sources
           Dim(
             kind=axis_dim_tag.kind if not axis_dim_tag.is_batch_dim() else Dim.Types.Spatial,
             description="%s_split_dims%i" % (name, i),
-            dimension=shape_dim)
+            dimension=shape_dim, auto_generated=True)
           if rem_dim is None or i != rem_dim_idx else rem_dim
           for i, shape_dim in enumerate(resolved_shape_dims))
     out_batch = data.batch
@@ -4175,7 +4180,7 @@ def get_out_data_from_opts(cls, name, sources, num_axes, in_dim="T", out_dims=No
       assert not declare_same_sizes_as
     else:
       out_dims = [
-        SpatialDim("%s:unflatten-nd:%i" % (name, i))
+        SpatialDim("%s:unflatten-nd:%i" % (name, i), auto_generated=True)
         for i in range(num_axes)]
       if declare_same_sizes_as:
         for i, other in declare_same_sizes_as.items():
@@ -4255,7 +4260,7 @@ def get_out_data_from_opts(cls, name, axis, dim=1, sources=(), **kwargs):
     else:
       new_dim = Dim(
         kind=Dim.Types.Feature if init_axis.lower() == "f" else Dim.Types.Spatial,
-        description="%s_expand_dims" % name,
+        description="%s_expand_dims" % name, auto_generated=True,
         dimension=dim)
     data = data.copy_template(name="%s_output" % name)
     data = data.copy_add_dim_by_tag(new_dim, unbroadcast=True, axis=axis)
@@ -4411,7 +4416,7 @@ def get_out_data_from_opts(cls, name, sources, axis, repetitions, out_dim=None,
       if isinstance(repetitions, int):
         out_dim = tag * repetitions
       else:
-        out_dim = Dim(description="repeated:%s" % name, kind=tag.kind, derived_from_tag=tag)
+        out_dim = Dim(description="repeated:%s" % name, kind=tag.kind, derived_from_tag=tag, auto_generated=True)
     return data.copy_template_replace_dim_tag(axis=data.get_batch_axis(0), new_dim_tag=out_dim)
 
 
@@ -4821,12 +4826,12 @@ def map_axis_name(s):
         pass
       else:
         out.sparse_dim = Dim(
-          kind=Dim.Types.Feature, dimension=set_sparse_dim, description="%s:set-sparse-dim" % name)
+          kind=Dim.Types.Feature, dimension=set_sparse_dim, description="%s:set-sparse-dim" % name, auto_generated=True)
     if increase_sparse_dim:
       assert out.sparse
       out.sparse_dim = Dim(
         kind=Dim.Types.Feature, dimension=out.sparse_dim.dimension + 1,
-        description="%s:inc-sparse-dim" % name)
+        description="%s:inc-sparse-dim" % name, auto_generated=True)
     if batch_dim_base:
       out.batch = batch_dim_base.output.batch
     return out
@@ -5103,7 +5108,7 @@ def transform_input(cls, input_data, network, in_dim=None, in_spatial_dims=None,
         cls._check_defined_in_spatial_dims(len(in_spatial_dims) == 1)
     if input_expand_dims:
       for i in range(input_expand_dims):
-        dim_tag = SpatialDim("input_expand_dims:%i" % i, dimension=1)
+        dim_tag = SpatialDim("input_expand_dims:%i" % i, dimension=1, auto_generated=True)
         input_data = input_data.copy_add_dim_by_tag(dim_tag, unbroadcast=True)
         in_spatial_dims.append(dim_tag)
     if input_split_feature_dim:
@@ -5280,10 +5285,10 @@ def get_out_data_from_opts(
             filter_size=filter_size[i], stride=strides[i], dilation_rate=dilation_rate[i], padding=padding)
         dim_tags.append(Dim(
           kind=Dim.Types.Spatial, description="%s:conv:s%i" % (name, i), dimension=new_dim,
-          derived_from_tag=old_tag, undefined=not old_tag))
+          derived_from_tag=old_tag, undefined=not old_tag, auto_generated=True))
     if not out_dim:
       assert n_out
-      out_dim = FeatureDim("%s:channel" % name, dimension=n_out)
+      out_dim = FeatureDim("%s:channel" % name, dimension=n_out, auto_generated=True)
     dim_tags.append(out_dim)
     feature_dim_axis = NotSpecified
     # Swap the dims if the input dim order doesn't fit the flag auto_use_channel_first.
@@ -5784,10 +5789,10 @@ def get_out_data_from_opts(cls, name, sources, network,
             padding=padding, output_padding=output_padding[i]) - remove_padding[i] * 2
         dim_tags.append(Dim(
           kind=Dim.Types.Spatial, description="%s:conv:s%i" % (name, i), dimension=new_dim,
-          derived_from_tag=old_tag, undefined=not old_tag))
+          derived_from_tag=old_tag, undefined=not old_tag, auto_generated=True))
     if not out_dim:
       assert n_out
-      out_dim = FeatureDim("%s:channel" % name, dimension=n_out)
+      out_dim = FeatureDim("%s:channel" % name, dimension=n_out, auto_generated=True)
     dim_tags.append(out_dim)
     return Data(
       name="%s_output" % name, dim_tags=dim_tags,
@@ -6000,7 +6005,8 @@ def get_out_data_from_opts(cls, name, sources, mode="", axes=None, axis=None, ke
     out_time_dim_axis = x.time_dim_axis
     if keep_dims:
       for i in axes:
-        y_dim_tags[i] = Dim(kind=y_dim_tags[i].kind, dimension=1, description="%s:keep-dim-%i" % (name, i))
+        y_dim_tags[i] = Dim(
+          kind=y_dim_tags[i].kind, dimension=1, description="%s:keep-dim-%i" % (name, i), auto_generated=True)
     else:
       if out_batch_dim_axis in axes:
         out_batch_dim_axis = None
@@ -6201,7 +6207,7 @@ def get_out_data_from_opts(cls, name, sources, axis=None, out_spatial_dim=None,
     out = common_source.copy_template(name="%s_output" % name)
     if not out_spatial_dim:
       out_spatial_dim = Dim(
-        kind=Dim.Types.Spatial, description="%s:stack" % name, dimension=len(sources))
+        kind=Dim.Types.Spatial, description="%s:stack" % name, dimension=len(sources), auto_generated=True)
     assert out_spatial_dim.dimension == len(sources)
     out = out.copy_add_dim_by_tag(axis=axis, dim_tag=out_spatial_dim, unbroadcast=True)
     return out
@@ -6333,7 +6339,8 @@ def get_out_data_from_opts(cls, name, sources, axes, padding=None, size=None, ke
       dim_tags = list(data.dim_tags)
       for i, a in enumerate(axes):
         dim_tags[a] = Dim(
-          kind=dim_tags[a].kind, description="%s:weighted-sum:%i" % (name, i), dimension=res_dims[i])
+          kind=dim_tags[a].kind, description="%s:weighted-sum:%i" % (name, i), dimension=res_dims[i],
+          auto_generated=True)
       data = data.copy_template_new_dim_tags(dim_tags, keep_special_axes=True)
     else:
       assert all([d == 1 for d in res_dims])
@@ -6484,7 +6491,8 @@ def get_out_data_from_opts(cls, name, sources, axis="T", out_dim=None, size_base
       assert not out_dim
       out_dim = size_base.output.get_time_dim_tag()
     if not out_dim:
-      out_dim = (repeat if isinstance(repeat, int) else SpatialDim("%s:repeat" % repeat.name)) + in_dim
+      out_dim = (
+        repeat if isinstance(repeat, int) else SpatialDim("%s:repeat" % repeat.name, auto_generated=True)) + in_dim
     assert out_dim.dimension == out_dim_int
     x = x.copy_template_replace_dim_tag(axis=axis_int, new_dim_tag=out_dim)
     if isinstance(repeat, LayerBase):
@@ -6647,7 +6655,7 @@ def get_out_data_from_opts(cls, name, sources, axis="T", out_dim=None, **kwargs)
     data = data.copy_move_axis(old_axis=axis, new_axis=0)
     data = data.copy_with_batch_dim_axis(1)
     if not out_dim:
-      out_dim = Dim(kind=in_dim.kind, description="%s:chunking" % name)
+      out_dim = Dim(kind=in_dim.kind, description="%s:chunking" % name, auto_generated=True)
     data = data.copy_template_replace_dim_tag(axis=0, new_dim_tag=out_dim)
     data.time_dim_axis = 0
     return data
@@ -7143,7 +7151,7 @@ def find_axis(a_axis, b_axis):
 
     if not b_var_dims and add_var2_if_empty:
       b_var_dims.append(
-        SpatialDim("%s:dot:dummy-var2" % name, dimension=1))
+        SpatialDim("%s:dot:dummy-var2" % name, dimension=1, auto_generated=True))
 
     dim_tags = list(a_rem_dims + a_var_dims + b_var_dims)
     return Data(
@@ -7206,9 +7214,9 @@ def __init__(self, axis, amount, pad=True, adjust_size_info=True, **kwargs):
         self.output.size_placeholder[axis_wob] + size_delta, 0, tf.shape(shifted)[axis])
       from ..util.data import Dim
       Dim(
-        kind=Dim.Types.Spatial, description="shift_axis",
+        kind=Dim.Types.Spatial, description="%s_shift_axis" % self.name,
         dyn_size=new_size, batch=self.output.batch,
-        src_data=self.output, src_axis=axis)
+        src_data=self.output, src_axis=axis, auto_generated=True)
       self.output.size_placeholder[axis_wob] = new_size
 
   @classmethod
@@ -7227,7 +7235,7 @@ def get_out_data_from_opts(cls, name, amount, axis, pad, sources=(), **kwargs):
     axis = out.get_axis_from_description(axis)
     tag = out.dim_tags[axis]
     dim = None if tag.dimension is None else max(0, tag.dimension - abs(amount))
-    tag = Dim(kind=tag.kind, description="%s_shift_axis" % name, dimension=dim)
+    tag = Dim(kind=tag.kind, description="%s_shift_axis" % name, dimension=dim, auto_generated=True)
     return out.copy_template_replace_dim_tag(axis=axis, new_dim_tag=tag)
 
 
@@ -7336,7 +7344,7 @@ def get_out_data_from_opts(cls, factor, axis, sources, name, out_dim=None, **kwa
     if out_dim:
       assert out_dim.dimension == dim
     else:
-      out_dim = Dim(kind=tag.kind, description="%s_resize" % name, dimension=dim)
+      out_dim = Dim(kind=tag.kind, description="%s_resize" % name, dimension=dim, auto_generated=True)
     return out.copy_template_replace_dim_tag(axis=axis, new_dim_tag=out_dim)
 
 
@@ -7427,7 +7435,8 @@ def get_out_data_from_opts(cls, name, sources, axis="T", out_dim=None, **kwargs)
     axis = out.get_axis_from_description(axis, allow_int=False)
     in_dim = out.dim_tags[axis]
     if not out_dim:
-      out_dim = Dim(kind=in_dim.kind, description="%s_removed_items", dimension=None, derived_from_tag=in_dim)
+      out_dim = Dim(
+        kind=in_dim.kind, description="%s_removed_items", dimension=None, derived_from_tag=in_dim, auto_generated=True)
     return out.copy_template_replace_dim_tag(axis=axis, new_dim_tag=out_dim)
 
 
@@ -8599,18 +8608,17 @@ def get_out_data_from_opts(cls, name, network,
       elif isinstance(d, int):
         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("Layer %r: invalid type %s in shape %r" % (name, type(d), shape))
       dim_tags.append(d)
     if add_time_axis:
       dim_tags.insert(
-        0, Dim(kind=Dim.Types.Time, description="%s:dummy-time" % name, dimension=1))
+        0, Dim(kind=Dim.Types.Time, description="%s:dummy-time" % name, dimension=1, auto_generated=True))
     if add_batch_axis:
       dim_tags.insert(
-        0, Dim(
-          kind=Dim.Types.Batch, description="batch", batch=network.get_global_batch_info()))
+        0, Dim(kind=Dim.Types.Batch, description="batch", batch=network.get_global_batch_info()))
     return Data(
       name="%s_output" % name, dim_tags=dim_tags, dtype=dtype,
       batch=network.get_global_batch_info() if add_batch_axis else None)