turn on a new effective technique from x-transformers

meshgpt_pytorch/meshgpt_pytorch.py

@@ -457,15 +457,15 @@ def __init__(
             quantize_dropout = True,
             quantize_dropout_cutoff_index = 1,
             quantize_dropout_multiple_of = 1,
-            experimental_softplus_entropy_loss=True,
         ),
         rvq_kwargs: dict = dict(
             kmeans_init = True,
             threshold_ema_dead_code = 2,
         ),
         rlfq_kwargs: dict = dict(
             frac_per_sample_entropy = 1.,
-            soft_clamp_input_value = 10.
+            soft_clamp_input_value = 10.,
+            experimental_softplus_entropy_loss = True,
         ),
         rvq_stochastic_sample_codes = True,
         sageconv_kwargs: dict = dict(
@@ -1103,7 +1103,9 @@ def __init__(
         attn_heads = 16,
         attn_kwargs: dict = dict(
             ff_glu = True,
-            attn_num_mem_kv = 4
+            attn_num_mem_kv = 4,
+            add_value_residual = True,
+            learned_value_residual_mix = True
         ),
         cross_attn_num_mem_kv = 4, # needed for preventing nan when dropping out text condition
         dropout = 0.,

meshgpt_pytorch/version.py

@@ -1 +1 @@
-__version__ = '1.7.0'
+__version__ = '1.7.1'

setup.py

@@ -40,7 +40,7 @@
     'torch_geometric',
     'tqdm',
     'vector-quantize-pytorch>=1.18.1',
-    'x-transformers>=1.30.19,<1.31',
+    'x-transformers>=1.42.23',
   ],
   setup_requires=[
     'pytest-runner',