Add FP32 cast in ConvNext LayerNorm to prevent rounding errors with FP16 input (#18746)

* Adding cast to fp32 in convnext layernorm to prevent rounding errors in the case of fp16 input

* Trigger CI

src/transformers/models/convnext/modeling_convnext.py

@@ -109,9 +109,12 @@ class ConvNextLayerNorm(nn.Module):
         if self.data_format == "channels_last":
             x = torch.nn.functional.layer_norm(x, self.normalized_shape, self.weight, self.bias, self.eps)
         elif self.data_format == "channels_first":
+            input_dtype = x.dtype
+            x = x.float()
             u = x.mean(1, keepdim=True)
             s = (x - u).pow(2).mean(1, keepdim=True)
             x = (x - u) / torch.sqrt(s + self.eps)
+            x = x.to(dtype=input_dtype)
             x = self.weight[:, None, None] * x + self.bias[:, None, None]
         return x