[Flax] Fixes typo in Bart based Flax Models (#13565)

src/transformers/models/bart/modeling_flax_bart.py

@@ -406,7 +406,7 @@ class FlaxBartEncoderLayer(nn.Module):
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
         self.fc1 = nn.Dense(
             self.config.encoder_ffn_dim,
             dtype=self.dtype,
@@ -433,7 +433,7 @@ class FlaxBartEncoderLayer(nn.Module):
 
         residual = hidden_states
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states
@@ -515,7 +515,7 @@ class FlaxBartDecoderLayer(nn.Module):
         )
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
 
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.encoder_attn = FlaxBartAttention(
@@ -572,7 +572,7 @@ class FlaxBartDecoderLayer(nn.Module):
         # Fully Connected
         residual = hidden_states
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states

src/transformers/models/marian/modeling_flax_marian.py

@@ -411,7 +411,7 @@ class FlaxMarianEncoderLayer(nn.Module):
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
         self.fc1 = nn.Dense(
             self.config.encoder_ffn_dim,
             dtype=self.dtype,
@@ -438,7 +438,7 @@ class FlaxMarianEncoderLayer(nn.Module):
 
         residual = hidden_states
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states
@@ -523,7 +523,7 @@ class FlaxMarianDecoderLayer(nn.Module):
         )
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
 
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.encoder_attn = FlaxMarianAttention(
@@ -580,7 +580,7 @@ class FlaxMarianDecoderLayer(nn.Module):
         # Fully Connected
         residual = hidden_states
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states

src/transformers/models/mbart/modeling_flax_mbart.py

@@ -417,7 +417,7 @@ class FlaxMBartEncoderLayer(nn.Module):
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
         self.fc1 = nn.Dense(
             self.config.encoder_ffn_dim,
             dtype=self.dtype,
@@ -444,7 +444,7 @@ class FlaxMBartEncoderLayer(nn.Module):
         residual = hidden_states
         hidden_states = self.final_layer_norm(hidden_states)
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states
@@ -527,7 +527,7 @@ class FlaxMBartDecoderLayer(nn.Module):
         )
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
 
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.encoder_attn = FlaxMBartAttention(
@@ -585,7 +585,7 @@ class FlaxMBartDecoderLayer(nn.Module):
         residual = hidden_states
         hidden_states = self.final_layer_norm(hidden_states)
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states

src/transformers/models/pegasus/modeling_flax_pegasus.py

@@ -411,7 +411,7 @@ class FlaxPegasusEncoderLayer(nn.Module):
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
         self.fc1 = nn.Dense(
             self.config.encoder_ffn_dim,
             dtype=self.dtype,
@@ -438,7 +438,7 @@ class FlaxPegasusEncoderLayer(nn.Module):
         residual = hidden_states
         hidden_states = self.final_layer_norm(hidden_states)
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states
@@ -522,7 +522,7 @@ class FlaxPegasusDecoderLayer(nn.Module):
         )
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
 
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.encoder_attn = FlaxPegasusAttention(
@@ -580,7 +580,7 @@ class FlaxPegasusDecoderLayer(nn.Module):
         residual = hidden_states
         hidden_states = self.final_layer_norm(hidden_states)
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states

templates/adding_a_new_model/cookiecutter-template-{{cookiecutter.modelname}}/modeling_flax_{{cookiecutter.lowercase_modelname}}.py

@@ -1432,7 +1432,7 @@ class Flax{{cookiecutter.camelcase_modelname}}EncoderLayer(nn.Module):
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
         self.fc1 = nn.Dense(
             self.config.encoder_ffn_dim,
             dtype=self.dtype,
@@ -1459,7 +1459,7 @@ class Flax{{cookiecutter.camelcase_modelname}}EncoderLayer(nn.Module):
 
         residual = hidden_states
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states
@@ -1541,7 +1541,7 @@ class Flax{{cookiecutter.camelcase_modelname}}DecoderLayer(nn.Module):
         )
         self.dropout_layer = nn.Dropout(rate=self.config.dropout)
         self.activation_fn = ACT2FN[self.config.activation_function]
-        self.acticvation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
+        self.activation_dropout_layer = nn.Dropout(rate=self.config.activation_dropout)
 
         self.self_attn_layer_norm = nn.LayerNorm(dtype=self.dtype)
         self.encoder_attn = Flax{{cookiecutter.camelcase_modelname}}Attention(
@@ -1598,7 +1598,7 @@ class Flax{{cookiecutter.camelcase_modelname}}DecoderLayer(nn.Module):
         # Fully Connected
         residual = hidden_states
         hidden_states = self.activation_fn(self.fc1(hidden_states))
-        hidden_states = self.acticvation_dropout_layer(hidden_states, deterministic=deterministic)
+        hidden_states = self.activation_dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = self.fc2(hidden_states)
         hidden_states = self.dropout_layer(hidden_states, deterministic=deterministic)
         hidden_states = residual + hidden_states