From 521f3bbbba9f04f48e81d78033c6e1c29a08e515 Mon Sep 17 00:00:00 2001
From: Gustaf Rydholm <gustaf.rydholm@gmail.com>
Date: Mon, 20 Jun 2022 00:09:20 +0200
Subject: Update eff net config

---
 text_recognizer/networks/efficientnet/efficientnet.py   | 17 ++---------------
 text_recognizer/networks/efficientnet/utils.py          | 10 +++++-----
 .../conf/experiment/conv_transformer_paragraphs.yaml    | 13 ++++++-------
 training/conf/network/conv_transformer.yaml             |  4 ++--
 4 files changed, 15 insertions(+), 29 deletions(-)

diff --git a/text_recognizer/networks/efficientnet/efficientnet.py b/text_recognizer/networks/efficientnet/efficientnet.py
index de08457..2a712d8 100644
--- a/text_recognizer/networks/efficientnet/efficientnet.py
+++ b/text_recognizer/networks/efficientnet/efficientnet.py
@@ -61,14 +61,14 @@ class EfficientNet(nn.Module):
         """Builds the efficientnet backbone."""
         _block_args = block_args()[: self.depth]
         in_channels = 1  # BW
-        out_channels = round_filters(32, self.params)
+        out_channels = round_filters(16, self.params)
         self._conv_stem = nn.Sequential(
             nn.ZeroPad2d((0, 1, 0, 1)),
             nn.Conv2d(
                 in_channels=in_channels,
                 out_channels=out_channels,
                 kernel_size=3,
-                stride=self.stride,
+                stride=2,
                 bias=False,
             ),
             nn.BatchNorm2d(
@@ -98,19 +98,6 @@ class EfficientNet(nn.Module):
             nn.Conv2d(
                 in_channels,
                 self.out_channels,
-                kernel_size=2,
-                stride=self.stride,
-                bias=False,
-            ),
-            nn.BatchNorm2d(
-                num_features=self.out_channels,
-                momentum=self.bn_momentum,
-                eps=self.bn_eps,
-            ),
-            nn.Mish(inplace=True),
-            nn.Conv2d(
-                self.out_channels,
-                self.out_channels,
                 kernel_size=1,
                 stride=1,
                 bias=False,
diff --git a/text_recognizer/networks/efficientnet/utils.py b/text_recognizer/networks/efficientnet/utils.py
index 5234324..770f85b 100644
--- a/text_recognizer/networks/efficientnet/utils.py
+++ b/text_recognizer/networks/efficientnet/utils.py
@@ -72,13 +72,13 @@ def block_args() -> List[DictConfig]:
         "se_ratio",
     ]
     args = [
-        [1, 3, (1, 1), 1, 32, 16, 0.25],
+        [1, 3, (1, 1), 1, 16, 16, 0.25],
         [2, 3, (2, 2), 6, 16, 24, 0.25],
         [2, 5, (2, 2), 6, 24, 40, 0.25],
-        [3, 3, (2, 2), 6, 40, 80, 0.25],
-        [3, 5, (1, 1), 6, 80, 112, 0.25],
-        [4, 5, (2, 2), 6, 112, 192, 0.25],
-        [1, 3, (1, 1), 6, 192, 320, 0.25],
+        [3, 3, (2, 1), 6, 40, 80, 0.25],
+        [3, 5, (2, 1), 6, 80, 112, 0.25],
+        [4, 5, (2, 1), 6, 112, 192, 0.25],
+        [1, 3, (2, 1), 6, 192, 320, 0.25],
     ]
     block_args_ = []
     for row in args:
diff --git a/training/conf/experiment/conv_transformer_paragraphs.yaml b/training/conf/experiment/conv_transformer_paragraphs.yaml
index 7c6e231..c8db485 100644
--- a/training/conf/experiment/conv_transformer_paragraphs.yaml
+++ b/training/conf/experiment/conv_transformer_paragraphs.yaml
@@ -34,15 +34,14 @@ optimizer:
   betas: [0.9, 0.999]
   weight_decay: 0
   eps: 1.0e-8
-  parameters: network
 
 lr_scheduler:
   _target_: torch.optim.lr_scheduler.OneCycleLR
   max_lr: 3.0e-4
   total_steps: null
   epochs: *epochs
-  steps_per_epoch: 3201
-  pct_start: 0.3
+  steps_per_epoch: 5037
+  pct_start: 0.15
   anneal_strategy: cos
   cycle_momentum: true
   base_momentum: 0.85
@@ -56,7 +55,7 @@ lr_scheduler:
   monitor: val/cer
 
 datamodule:
-  batch_size: 6
+  batch_size: 4
   train_fraction: 0.95
 
 network:
@@ -66,9 +65,9 @@ network:
   encoder:
     depth: 5
   decoder:
-    depth: 6
+    depth: 4
   pixel_embedding:
-    shape: [18, 78]
+    shape: [17, 79]
 
 model:
   max_output_len: *max_output_len
@@ -76,4 +75,4 @@ model:
 trainer:
   gradient_clip_val: 0.5
   max_epochs: *epochs
-  accumulate_grad_batches: 1
+  accumulate_grad_batches: 2
diff --git a/training/conf/network/conv_transformer.yaml b/training/conf/network/conv_transformer.yaml
index ccdf960..90c2cb8 100644
--- a/training/conf/network/conv_transformer.yaml
+++ b/training/conf/network/conv_transformer.yaml
@@ -9,7 +9,7 @@ encoder:
   stochastic_dropout_rate: 0.2
   bn_momentum: 0.99
   bn_eps: 1.0e-3
-  depth: 3
+  depth: 5
   out_channels: *hidden_dim
   stride: [2, 1]
 decoder:
@@ -47,4 +47,4 @@ decoder:
 pixel_embedding:
   _target_: text_recognizer.networks.transformer.AxialPositionalEmbedding
   dim: *hidden_dim
-  shape: [17, 78]
+  shape: [18, 78]
-- 
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