Training working, multiple bug fixes

1 files changed, 11 insertions, 16 deletions

diff --git a/text_recognizer/networks/transformer/layers.py b/text_recognizer/networks/transformer/layers.py
index ce443e5..70a0ac7 100644
--- a/text_recognizer/networks/transformer/layers.py
+++ b/text_recognizer/networks/transformer/layers.py
@@ -1,5 +1,4 @@
 """Transformer attention layer."""
-from functools import partial
 from typing import Any, Dict, Optional, Tuple
 
 import attr
@@ -27,25 +26,17 @@ class AttentionLayers(nn.Module):
     norm_fn: str = attr.ib()
     ff_fn: str = attr.ib()
     ff_kwargs: Dict = attr.ib()
+    rotary_emb: Optional[RotaryEmbedding] = attr.ib()
     causal: bool = attr.ib(default=False)
     cross_attend: bool = attr.ib(default=False)
     pre_norm: bool = attr.ib(default=True)
-    rotary_emb: Optional[RotaryEmbedding] = attr.ib(default=None)
     layer_types: Tuple[str, ...] = attr.ib(init=False)
     layers: nn.ModuleList = attr.ib(init=False)
-    attn: partial = attr.ib(init=False)
-    norm: partial = attr.ib(init=False)
-    ff: partial = attr.ib(init=False)
 
     def __attrs_post_init__(self) -> None:
         """Post init configuration."""
         self.layer_types = self._get_layer_types() * self.depth
-        attn = load_partial_fn(
-            self.attn_fn, dim=self.dim, num_heads=self.num_heads, **self.attn_kwargs
-        )
-        norm = load_partial_fn(self.norm_fn, normalized_shape=self.dim)
-        ff = load_partial_fn(self.ff_fn, dim=self.dim, **self.ff_kwargs)
-        self.layers = self._build_network(attn, norm, ff)
+        self.layers = self._build_network()
 
     def _get_layer_types(self) -> Tuple:
         """Get layer specification."""
@@ -53,10 +44,13 @@ class AttentionLayers(nn.Module):
             return "a", "c", "f"
         return "a", "f"
 
-    def _build_network(
-        self, attn: partial, norm: partial, ff: partial,
-    ) -> nn.ModuleList:
+    def _build_network(self) -> nn.ModuleList:
         """Configures transformer network."""
+        attn = load_partial_fn(
+            self.attn_fn, dim=self.dim, num_heads=self.num_heads, **self.attn_kwargs
+        )
+        norm = load_partial_fn(self.norm_fn, normalized_shape=self.dim)
+        ff = load_partial_fn(self.ff_fn, dim=self.dim, **self.ff_kwargs)
         layers = nn.ModuleList([])
         for layer_type in self.layer_types:
             if layer_type == "a":
@@ -106,6 +100,7 @@ class Encoder(AttentionLayers):
     causal: bool = attr.ib(default=False, init=False)
 
 
-@attr.s(auto_attribs=True, eq=False)
 class Decoder(AttentionLayers):
-    causal: bool = attr.ib(default=True, init=False)
+    def __init__(self, **kwargs: Any) -> None:
+        assert "causal" not in kwargs, "Cannot set causality on decoder"
+        super().__init__(causal=True, **kwargs)