From fe43389ad26559cc09f2fd00441c02556ff674c3 Mon Sep 17 00:00:00 2001 From: Gustaf Rydholm Date: Sun, 21 Nov 2021 21:35:50 +0100 Subject: Format files --- text_recognizer/models/base.py | 1 + text_recognizer/models/transformer.py | 4 ++-- text_recognizer/networks/transformer/attention.py | 2 -- text_recognizer/networks/transformer/norm.py | 4 ++++ 4 files changed, 7 insertions(+), 4 deletions(-) diff --git a/text_recognizer/models/base.py b/text_recognizer/models/base.py index cc54de4..821cb69 100644 --- a/text_recognizer/models/base.py +++ b/text_recognizer/models/base.py @@ -46,6 +46,7 @@ class BaseLitModel(LightningModule): optimizer: Type[torch.optim.Optimizer], optimizer_idx: int, ) -> None: + """Optimal way to set grads to zero.""" optimizer.zero_grad(set_to_none=True) def _configure_optimizer(self) -> List[Type[torch.optim.Optimizer]]: diff --git a/text_recognizer/models/transformer.py b/text_recognizer/models/transformer.py index d8cb665..369361b 100644 --- a/text_recognizer/models/transformer.py +++ b/text_recognizer/models/transformer.py @@ -60,8 +60,8 @@ class TransformerLitModel(BaseLitModel): # pred = self(data) # self.val_cer(pred, targets) # self.log("val/cer", self.val_cer, on_step=False, on_epoch=True, prog_bar=True) - # self.test_acc(pred, targets) - # self.log("val/acc", self.test_acc, on_step=False, on_epoch=True) + # self.val_acc(pred, targets) + # self.log("val/acc", self.val_acc, on_step=False, on_epoch=True) def test_step(self, batch: Tuple[Tensor, Tensor], batch_idx: int) -> None: """Test step.""" diff --git a/text_recognizer/networks/transformer/attention.py b/text_recognizer/networks/transformer/attention.py index b86636e..87792a9 100644 --- a/text_recognizer/networks/transformer/attention.py +++ b/text_recognizer/networks/transformer/attention.py @@ -20,7 +20,6 @@ class Attention(nn.Module): """Standard attention.""" def __attrs_pre_init__(self) -> None: - """Pre init constructor.""" super().__init__() dim: int = attr.ib() @@ -34,7 +33,6 @@ class Attention(nn.Module): fc: nn.Linear = attr.ib(init=False) def __attrs_post_init__(self) -> None: - """Post init configuration.""" self.scale = self.dim ** -0.5 inner_dim = self.num_heads * self.dim_head diff --git a/text_recognizer/networks/transformer/norm.py b/text_recognizer/networks/transformer/norm.py index c59744a..98f4d7f 100644 --- a/text_recognizer/networks/transformer/norm.py +++ b/text_recognizer/networks/transformer/norm.py @@ -12,6 +12,8 @@ from torch import Tensor class ScaleNorm(nn.Module): + """Scaled normalization.""" + def __init__(self, normalized_shape: int, eps: float = 1.0e-5) -> None: super().__init__() self.scale = normalized_shape ** -0.5 @@ -25,6 +27,8 @@ class ScaleNorm(nn.Module): class PreNorm(nn.Module): + """Applies layer normalization then function.""" + def __init__(self, normalized_shape: int, fn: Type[nn.Module]) -> None: super().__init__() self.norm = nn.LayerNorm(normalized_shape) -- cgit v1.2.3-70-g09d2