update generated layers

Author: albertz

nn/_generated_layers.py

@@ -1,6 +1,6 @@
 """
 This file is auto-generated by _generate_layers.py.
-RETURNN: 1.20220211.120126+git.a10e882
+RETURNN: 1.20220214.111744+git.c52d07b
 
 These are the RETURNN layers directly wrapped.
 Note that we intentionally exclude some layers or options for more consistency.
@@ -2199,6 +2199,7 @@ def choice(
            beam_size: int,
            keep_beams: bool = NotSpecified,
            search: Union[NotSpecified, bool] = NotSpecified,
+           add_to_beam_scores: Union[NotSpecified, bool] = NotSpecified,
            input_type: str = NotSpecified,
            prob_scale: float = NotSpecified,
            base_beam_score_scale: float = NotSpecified,
@@ -2240,6 +2241,11 @@ def choice(
     i.e. we just expand, i.e. we just search on the dim. beam_size must be a multiple of beam_in.
   :param NotSpecified|bool search: whether to perform search, or use the ground truth (`target` option).
     If not specified, it will depend on `network.search_flag`.
+  :param NotSpecified|bool add_to_beam_scores: whether to add the scores to the beam scores.
+    This will be done with search obviously (not supported to not do it).
+    Without search, we can still add the scores of the ground-truth labels to the beam.
+    By default, this is derived from `search or network.search_flag`.
+    So with enabled net search flag, even when `search` is disabled here, it will add the scores.
   :param str input_type: "prob" or "log_prob", whether the input is in probability space, log-space, etc.
     or "regression", if it is a prediction of the data as-is. If there are several inputs, same format
     for all is assumed.
@@ -2264,6 +2270,7 @@ def choice(
     'beam_size': beam_size,
     'keep_beams': keep_beams,
     'search': search,
+    'add_to_beam_scores': add_to_beam_scores,
     'input_type': input_type,
     'prob_scale': prob_scale,
     'base_beam_score_scale': base_beam_score_scale,
@@ -2289,6 +2296,7 @@ def decide(
            *,
            length_normalization: bool = NotSpecified,
            search: Union[NotSpecified, bool] = NotSpecified,
+           add_to_beam_scores: Union[NotSpecified, bool] = NotSpecified,
            name: Optional[Union[str, nn.NameCtx]] = None) -> nn.Tensor:
   """
   This is kind of the counter-part to the choice layer.
@@ -2303,12 +2311,18 @@ def decide(
   :param bool length_normalization: performed on the beam scores
   :param NotSpecified|bool search: whether to perform search, or use the ground truth (`target` option).
     If not specified, it will depend on `network.search_flag`.
+  :param NotSpecified|bool add_to_beam_scores: whether to add the scores to the beam scores.
+    This will be done with search obviously (not supported to not do it).
+    Without search, we can still add the scores of the ground-truth labels to the beam.
+    By default, this is derived from `search or network.search_flag`.
+    So with enabled net search flag, even when `search` is disabled here, it will add the scores.
   :param str|nn.NameCtx|None name:
   :return: layer
   """
   args = {
     'length_normalization': length_normalization,
     'search': search,
+    'add_to_beam_scores': add_to_beam_scores,
     }
   args = {key: value for (key, value) in args.items() if value is not NotSpecified}
   return nn.make_layer({
@@ -2366,6 +2380,7 @@ def split_batch_beam(
                      *,
                      beam_dim: Optional[nn.Dim] = NotSpecified,
                      search: Union[NotSpecified, bool] = NotSpecified,
+                     add_to_beam_scores: Union[NotSpecified, bool] = NotSpecified,
                      name: Optional[Union[str, nn.NameCtx]] = None) -> Tuple[nn.Tensor, nn.Dim]:
   """
   Splits the batch dimension of the input, which includes a beam, into (batch,beam).
@@ -2376,6 +2391,11 @@ def split_batch_beam(
   :param nn.Dim|None beam_dim:
   :param NotSpecified|bool search: whether to perform search, or use the ground truth (`target` option).
     If not specified, it will depend on `network.search_flag`.
+  :param NotSpecified|bool add_to_beam_scores: whether to add the scores to the beam scores.
+    This will be done with search obviously (not supported to not do it).
+    Without search, we can still add the scores of the ground-truth labels to the beam.
+    By default, this is derived from `search or network.search_flag`.
+    So with enabled net search flag, even when `search` is disabled here, it will add the scores.
   :param str|nn.NameCtx|None name:
   :return: layer, beam_dim
   """
@@ -2384,6 +2404,7 @@ def split_batch_beam(
   args = {
     'beam_dim': beam_dim,
     'search': search,
+    'add_to_beam_scores': add_to_beam_scores,
     }
   args = {key: value for (key, value) in args.items() if value is not NotSpecified}
   layer = nn.make_layer({