remove laser attention

README.md

@@ -515,15 +515,6 @@ docker run -v .:/data --gpus all -it af3
 }
 ```
 
-```bibtex
-@inproceedings{Duvvuri2024LASERAW,
-    title   = {LASER: Attention with Exponential Transformation},
-    author  = {Sai Surya Duvvuri and Inderjit S. Dhillon},
-    year    = {2024},
-    url     = {https://api.semanticscholar.org/CorpusID:273849947}
-}
-```
-
 ```bibtex
 @article{Zhu2024HyperConnections,
     title   = {Hyper-Connections},

alphafold3_pytorch/attention.py

@@ -184,8 +184,6 @@ def __init__(
         query_bias = True,
         window_size = None,
         num_memory_kv: int = 0,
-        laser = False,
-        laser_softclamp_value = 15.,
         enable_attn_softclamp = False,
         attn_softclamp_value = 50.,
         softmax_full_precision = False,
@@ -211,8 +209,6 @@ def __init__(
             dropout = dropout,
             window_size = window_size,
             enable_attn_softclamp = enable_attn_softclamp,
-            laser = laser,
-            laser_softclamp_value = laser_softclamp_value,
             attn_softclamp_value = attn_softclamp_value,
             softmax_full_precision = softmax_full_precision
         )
@@ -322,8 +318,6 @@ class Attend(Module):
     def __init__(
         self,
         dropout = 0.,
-        laser = False,
-        laser_softclamp_value = 15.,
         window_size = None,
         scale: float | None = None,
         enable_attn_softclamp = False,
@@ -352,11 +346,6 @@ def __init__(
 
         self.attn_dropout = nn.Dropout(dropout)
 
-        # laser attention
-
-        self.laser = laser
-        self.laser_softclamp_value = laser_softclamp_value
-
         # softclamp attention logits
         # being adopted by a number of recent llms (gemma, grok)
 
@@ -477,20 +466,10 @@ def local_attn(
 
         attn = sim.softmax(dim = -1)
 
-        # maybe laser
-
-        if self.laser:
-            v = softclamp(v, self.laser_softclamp_value)
-
         # aggregate
 
         out = einsum(attn, v, "... i j, ... j d -> ... i d")
 
-        # maybe laser
-
-        if self.laser:
-            out = log(out)
-
         # un-window the output
 
         out = rearrange(out, "b h n w d -> b h (n w) d")
@@ -586,19 +565,8 @@ def forward(
 
         attn = self.attn_dropout(attn)
 
-        # maybe laser
-
-        if self.laser:
-            v_max = v.amax(dim = -2, keepdim = True)
-            v = (v - v_max).exp()
-
         # aggregate values
 
         out = einsum(attn, v, "b h i j, b h j d -> b h i d")
 
-        # maybe laser
-
-        if self.laser:
-            out = log(out) + v_max
-
         return out

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "alphafold3-pytorch"
-version = "0.7.4"
+version = "0.7.5"
 description = "Alphafold 3 - Pytorch"
 authors = [
     { name = "Phil Wang", email = "[email protected]" },