I have a case where I'd like to use the GatherLayer on the batch axis. This works, but the size placeholder is not gathered. Does anything speak against gathering on the batch axis or was this just not considered before and we should fix the size placeholder? Not gathering the size placeholder leads to an error later in my model and it also doesn't make sense to keep the same size placeholder in general. Here is a test case to demonstrate the issue: def test_GatherLayer_batch_dim(): with make_scope() as session: import numpy as np net = TFNetwork(extern_data=ExternData()) batch_dim, time_dim, feature_dim = 3, 4, 2 # [B, T, F] random = np.random.RandomState(42) values_seqs = random.rand(batch_dim, time_dim, feature_dim).astype('float32') values_size = np.array([4, 2, 3]) values_placeholder = tf.constant(values_seqs, dtype=tf.float32) values_size_placeholder = {0: tf.constant(values_size, dtype=tf.int32)} values = InternalLayer( name="values", network=net, output=Data( name="values", batch_dim_axis=0, time_dim_axis=1, feature_dim_axis=2, shape=[None, feature_dim], placeholder=values_placeholder, size_placeholder=values_size_placeholder, )) position_np = np.array([0, 2]) position = InternalLayer( name="position", network=net, output=Data( name="position", placeholder=tf.constant(position_np, dtype=tf.int64), batch_dim_axis=0, shape=[], dtype="int64", )) values.output.sanity_check() position.output.sanity_check() # should become [B', T, F] layer = GatherLayer( name="gather", network=net, sources=[values], position=position, axis="B", output=GatherLayer.get_out_data_from_opts( name="gather", sources=[values], position=position, axis="B")) layer.output.sanity_check() out_seqs, out_size = session.run([layer.output.placeholder, layer.output.size_placeholder.as_dict()]) assert isinstance(out_seqs, numpy.ndarray) np.testing.assert_equal(values_seqs[position_np, :], out_seqs) np.testing.assert_equal(values_size[position_np], out_size[0]) — Reply to this email directly, view it on GitHub <#1087>, or unsubscribe <https://github.com/notifications/unsubscribe-auth/AAAON7FN5OKOVE5WNI2SCPLVW7VX5ANCNFSM55IAJR6Q> . You are receiving this because you are subscribed to this thread.Message ID: ***@***.***>