From 6679f473475690d158c49765593f81eb94110a6b Mon Sep 17 00:00:00 2001
From: manonBlanco <blanco@teklia.com>
Date: Mon, 17 Jul 2023 09:29:44 +0200
Subject: [PATCH] Never use lstm
---
dan/decoder.py | 18 +-----------------
dan/ocr/document/train.py | 1 -
docs/get_started/training.md | 1 -
docs/usage/train/parameters.md | 1 -
tests/conftest.py | 1 -
tests/data/prediction/parameters.yml | 1 -
6 files changed, 1 insertion(+), 22 deletions(-)
diff --git a/dan/decoder.py b/dan/decoder.py
index 84518ab5..af5c28cb 100644
--- a/dan/decoder.py
+++ b/dan/decoder.py
@@ -2,16 +2,7 @@
import torch
from torch import relu, softmax
-from torch.nn import (
- LSTM,
- Conv1d,
- Dropout,
- Embedding,
- LayerNorm,
- Linear,
- Module,
- ModuleList,
-)
+from torch.nn import Conv1d, Dropout, Embedding, LayerNorm, Linear, Module, ModuleList
from torch.nn.init import xavier_uniform_
@@ -336,7 +327,6 @@ class GlobalHTADecoder(Module):
params["attention_win"] if params["attention_win"] is not None else 1
)
self.use_1d_pe = "use_1d_pe" not in params or params["use_1d_pe"]
- self.use_lstm = params["use_lstm"]
self.features_updater = FeaturesUpdater(params)
self.att_decoder = GlobalAttDecoder(params)
@@ -348,9 +338,6 @@ class GlobalHTADecoder(Module):
params["enc_dim"], params["l_max"], params["device"]
)
- if self.use_lstm:
- self.lstm_predict = LSTM(params["enc_dim"], params["enc_dim"])
-
vocab_size = params["vocab_size"] + 1
self.end_conv = Conv1d(params["enc_dim"], vocab_size, kernel_size=1)
@@ -426,9 +413,6 @@ class GlobalHTADecoder(Module):
keep_all_weights=keep_all_weights,
)
- if self.use_lstm:
- output, hidden_predict = self.lstm_predict(output, hidden_predict)
-
dp_output = self.dropout(relu(output))
preds = self.end_conv(dp_output.permute(1, 2, 0))
diff --git a/dan/ocr/document/train.py b/dan/ocr/document/train.py
index 63b5080a..6f5e17b3 100644
--- a/dan/ocr/document/train.py
+++ b/dan/ocr/document/train.py
@@ -153,7 +153,6 @@ def get_config():
"dec_dim_feedforward": 256, # number of dimension for feedforward layer in transformer decoder layers
"use_2d_pe": True, # use 2D positional embedding
"use_1d_pe": True, # use 1D positional embedding
- "use_lstm": False,
"attention_win": 100, # length of attention window
# Curriculum dropout
"dropout_scheduler": {
diff --git a/docs/get_started/training.md b/docs/get_started/training.md
index 5438363e..bc0764c3 100644
--- a/docs/get_started/training.md
+++ b/docs/get_started/training.md
@@ -59,7 +59,6 @@ parameters:
dec_pred_dropout: float
attention_win: int
use_1d_pe: bool
- use_lstm: bool
vocab_size: int
h_max: int
w_max: int
diff --git a/docs/usage/train/parameters.md b/docs/usage/train/parameters.md
index 0e6a2b47..bc346d86 100644
--- a/docs/usage/train/parameters.md
+++ b/docs/usage/train/parameters.md
@@ -138,7 +138,6 @@ For a detailed description of all augmentation transforms, see the [dedicated pa
| `model_params.dec_dim_feedforward` | Number of dimensions for feedforward layer in transformer decoder layers. | `int` | `256` |
| `model_params.use_2d_pe` | Whether to use 2D positional embedding. | `bool` | `True` |
| `model_params.use_1d_pe` | Whether to use 1D positional embedding. | `bool` | `True` |
-| `model_params.use_lstm` | Whether to use a LSTM layer in the decoder. | `bool` | `False` |
| `model_params.attention_win` | Length of attention window. | `int` | `100` |
| `model_params.dropout_scheduler.function` | Curriculum dropout scheduler. | custom class | `exponential_dropout_scheduler` |
| `model_params.dropout_scheduler.T` | Exponential factor. | `float` | `5e4` |
diff --git a/tests/conftest.py b/tests/conftest.py
index e398d9df..136cead1 100644
--- a/tests/conftest.py
+++ b/tests/conftest.py
@@ -101,7 +101,6 @@ def training_config():
"dec_dim_feedforward": 256, # number of dimension for feedforward layer in transformer decoder layers
"use_2d_pe": True, # use 2D positional embedding
"use_1d_pe": True, # use 1D positional embedding
- "use_lstm": False,
"attention_win": 100, # length of attention window
# Curriculum dropout
"dropout_scheduler": {
diff --git a/tests/data/prediction/parameters.yml b/tests/data/prediction/parameters.yml
index bc56c1f6..469afc8d 100644
--- a/tests/data/prediction/parameters.yml
+++ b/tests/data/prediction/parameters.yml
@@ -11,7 +11,6 @@ parameters:
dec_pred_dropout: 0.1
attention_win: 100
use_1d_pe: True
- use_lstm: False
vocab_size: 96
h_max: 500
w_max: 1000
--
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