pass the attend kwargs for the block causal masking in tokenizer

dreamer4/dreamer4.py

@@ -1278,6 +1278,8 @@ class VideoTokenizer(Module):
 
         tokens, packed_latent_shape = pack((decoder_pos_emb, latent_tokens), 'b t * d')
 
+        space_seq_len = tokens.shape[-2]
+
         # pack time
 
         tokens, inverse_pack_time = pack_one(tokens, 'b * d')
@@ -1286,7 +1288,16 @@ class VideoTokenizer(Module):
 
         # decoder attend
 
-        decoder_attend_fn = get_attend_fn(use_flex, seq_len, seq_len, causal = True, num_special_tokens = self.num_latent_tokens, special_attend_only_itself = True)
+        decoder_attend_fn = get_attend_fn(
+            use_flex,
+            seq_len, seq_len,
+            causal = True,
+            causal_block_size = space_seq_len,
+            softclamp_value = self.attn_softclamp_value,
+            block_size_per_special = space_seq_len,
+            num_special_tokens = self.num_latent_tokens,
+            special_attend_only_itself = True # different than encoder
+        )
 
         # decoder attention
 
@@ -1373,14 +1384,6 @@ class VideoTokenizer(Module):
 
         # attend hyper parameters
 
-        attend_kwargs = dict(
-            causal = True,
-            causal_block_size = space_seq_len,
-            softclamp_value = self.attn_softclamp_value,
-            block_size_per_special = space_seq_len,
-            num_special_tokens = 1
-        )
-
         use_flex = tokens.is_cuda and exists(flex_attention)
 
         # encoder attend
@@ -1388,7 +1391,16 @@ class VideoTokenizer(Module):
         # modality can only attend to itself while latents can attend to everything
         # similar to agent token in dynamics model
 
-        encoder_attend_fn = get_attend_fn(use_flex, seq_len, seq_len, causal = True, num_special_tokens = self.num_latent_tokens, special_attend_only_itself = False)
+        encoder_attend_fn = get_attend_fn(
+            use_flex,
+            seq_len, seq_len,
+            causal = True,
+            causal_block_size = space_seq_len,
+            softclamp_value = self.attn_softclamp_value,
+            block_size_per_special = space_seq_len,
+            num_special_tokens = self.num_latent_tokens,
+            special_attend_only_itself = False # different than decoder
+        )
 
         # encoder
 

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "dreamer4"
-version = "0.0.22"
+version = "0.0.23"
 description = "Dreamer 4"
 authors = [
     { name = "Phil Wang", email = "lucidrains@gmail.com" }