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authorGustaf Rydholm <gustaf.rydholm@gmail.com>2021-04-07 22:12:10 +0200
committerGustaf Rydholm <gustaf.rydholm@gmail.com>2021-04-07 22:12:10 +0200
commit8afa8e1c6e9623b0dea86236da04b2b4173e9443 (patch)
tree4c9462507b3b3076aa26f08ab629f64b90aed2cb /text_recognizer/networks
parent33190bc9c0c377edab280efe4b0bd0e53bb6cb00 (diff)
Fixed typing and typos, train script load config, reformatted
Diffstat (limited to 'text_recognizer/networks')
-rw-r--r--text_recognizer/networks/__init__.py1
-rw-r--r--text_recognizer/networks/image_transformer.py6
-rw-r--r--text_recognizer/networks/residual_network.py6
-rw-r--r--text_recognizer/networks/transducer/transducer.py7
-rw-r--r--text_recognizer/networks/vqvae/decoder.py18
-rw-r--r--text_recognizer/networks/vqvae/encoder.py12
6 files changed, 10 insertions, 40 deletions
diff --git a/text_recognizer/networks/__init__.py b/text_recognizer/networks/__init__.py
index 4dcaf2e..979149f 100644
--- a/text_recognizer/networks/__init__.py
+++ b/text_recognizer/networks/__init__.py
@@ -1,3 +1,2 @@
"""Network modules"""
from .image_transformer import ImageTransformer
-
diff --git a/text_recognizer/networks/image_transformer.py b/text_recognizer/networks/image_transformer.py
index edebca9..9ed67a4 100644
--- a/text_recognizer/networks/image_transformer.py
+++ b/text_recognizer/networks/image_transformer.py
@@ -13,7 +13,7 @@ import math
from typing import Dict, List, Union, Sequence, Tuple, Type
from einops import rearrange
-from omegaconf import OmegaConf
+from omegaconf import DictConfig, OmegaConf
import torch
from torch import nn
from torch import Tensor
@@ -34,7 +34,7 @@ class ImageTransformer(nn.Module):
self,
input_shape: Sequence[int],
output_shape: Sequence[int],
- encoder: Union[OmegaConf, Dict],
+ encoder: Union[DictConfig, Dict],
mapping: str,
num_decoder_layers: int = 4,
hidden_dim: int = 256,
@@ -101,7 +101,7 @@ class ImageTransformer(nn.Module):
nn.init.normal_(self.feature_map_encoding.bias, -bound, bound)
@staticmethod
- def _configure_encoder(encoder: Union[OmegaConf, NamedTuple]) -> Type[nn.Module]:
+ def _configure_encoder(encoder: Union[DictConfig, Dict]) -> Type[nn.Module]:
encoder = OmegaConf.create(encoder)
network_module = importlib.import_module("text_recognizer.networks")
encoder_class = getattr(network_module, encoder.type)
diff --git a/text_recognizer/networks/residual_network.py b/text_recognizer/networks/residual_network.py
index da7553d..c33f419 100644
--- a/text_recognizer/networks/residual_network.py
+++ b/text_recognizer/networks/residual_network.py
@@ -20,11 +20,7 @@ class Conv2dAuto(nn.Conv2d):
def conv_bn(in_channels: int, out_channels: int, *args, **kwargs) -> nn.Sequential:
"""3x3 convolution with batch norm."""
- conv3x3 = partial(
- Conv2dAuto,
- kernel_size=3,
- bias=False,
- )
+ conv3x3 = partial(Conv2dAuto, kernel_size=3, bias=False,)
return nn.Sequential(
conv3x3(in_channels, out_channels, *args, **kwargs),
nn.BatchNorm2d(out_channels),
diff --git a/text_recognizer/networks/transducer/transducer.py b/text_recognizer/networks/transducer/transducer.py
index b10f93a..d7e3d08 100644
--- a/text_recognizer/networks/transducer/transducer.py
+++ b/text_recognizer/networks/transducer/transducer.py
@@ -392,12 +392,7 @@ def load_transducer_loss(
transitions = gtn.load(str(processed_path / transitions))
preprocessor = Preprocessor(
- data_dir,
- num_features,
- tokens_path,
- lexicon_path,
- use_words,
- prepend_wordsep,
+ data_dir, num_features, tokens_path, lexicon_path, use_words, prepend_wordsep,
)
num_tokens = preprocessor.num_tokens
diff --git a/text_recognizer/networks/vqvae/decoder.py b/text_recognizer/networks/vqvae/decoder.py
index 67ed0d9..8847aba 100644
--- a/text_recognizer/networks/vqvae/decoder.py
+++ b/text_recognizer/networks/vqvae/decoder.py
@@ -44,12 +44,7 @@ class Decoder(nn.Module):
# Configure encoder.
self.decoder = self._build_decoder(
- channels,
- kernel_sizes,
- strides,
- num_residual_layers,
- activation,
- dropout,
+ channels, kernel_sizes, strides, num_residual_layers, activation, dropout,
)
def _build_decompression_block(
@@ -78,9 +73,7 @@ class Decoder(nn.Module):
)
if i < len(self.upsampling):
- modules.append(
- nn.Upsample(size=self.upsampling[i]),
- )
+ modules.append(nn.Upsample(size=self.upsampling[i]),)
if dropout is not None:
modules.append(dropout)
@@ -109,12 +102,7 @@ class Decoder(nn.Module):
) -> nn.Sequential:
self.res_block.append(
- nn.Conv2d(
- self.embedding_dim,
- channels[0],
- kernel_size=1,
- stride=1,
- )
+ nn.Conv2d(self.embedding_dim, channels[0], kernel_size=1, stride=1,)
)
# Bottleneck module.
diff --git a/text_recognizer/networks/vqvae/encoder.py b/text_recognizer/networks/vqvae/encoder.py
index ede5c31..d3adac5 100644
--- a/text_recognizer/networks/vqvae/encoder.py
+++ b/text_recognizer/networks/vqvae/encoder.py
@@ -11,10 +11,7 @@ from text_recognizer.networks.vqvae.vector_quantizer import VectorQuantizer
class _ResidualBlock(nn.Module):
def __init__(
- self,
- in_channels: int,
- out_channels: int,
- dropout: Optional[Type[nn.Module]],
+ self, in_channels: int, out_channels: int, dropout: Optional[Type[nn.Module]],
) -> None:
super().__init__()
self.block = [
@@ -138,12 +135,7 @@ class Encoder(nn.Module):
)
encoder.append(
- nn.Conv2d(
- channels[-1],
- self.embedding_dim,
- kernel_size=1,
- stride=1,
- )
+ nn.Conv2d(channels[-1], self.embedding_dim, kernel_size=1, stride=1,)
)
return nn.Sequential(*encoder)