#2 fixed

nicolay-r · May 6, 2024 · a9b4ab3 · a9b4ab3
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diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 ## THOR: Three-hop Reasoning for Emotion Cause Analysis in Context • [![twitter](https://img.shields.io/twitter/url/https/shields.io.svg?style=social)](https://twitter.com/nicolayr_/status/1777005686611751415)
 
-![](https://img.shields.io/badge/Python-3.8-lightgreen.svg)
+![](https://img.shields.io/badge/Python-3.10-lightgreen.svg)
 [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/nicolay-r/THOR-ECAC/blob/master/THoR_Finetuning_SemEval2023_t3_1_public.ipynb)
 [![arXiv](https://img.shields.io/badge/arXiv-2404.03361-b31b1b.svg)](https://arxiv.org/abs/2404.03361)
 
@@ -11,9 +11,9 @@ enhanced
 and adapted for SemEval-2024 paper 
 [nicolay-r at SemEval-2024 Task 3: Using Flan-T5 for Reasoning Emotion Cause in Conversations with Chain-of-Thought on Emotion States](https://arxiv.org/abs/2404.03361)**
 
-> **Update 05 March 2024**: The quick [arXiv paper](https://arxiv.org/abs/2404.03361) breakdowns 🔨 are @ [Twitter/X post](https://twitter.com/nicolayr_/status/1777005686611751415)
+> **Update 06 March 2024**: 🔓 `attrdict` represents the main limitation for code launching in `Python 3.10` and hence been switched to `addict` (see [Issue#2](https://github.com/nicolay-r/THOR-ECAC/issues/2)).
 
-> **Update 03 March 2024**: `attrdict` represents the main limitation for code launching in `Python > 3.8`.
+> **Update 05 March 2024**: The quick [arXiv paper](https://arxiv.org/abs/2404.03361) breakdowns 🔨 are @ [Twitter/X post](https://twitter.com/nicolayr_/status/1777005686611751415)
 
 > **Update 17 February 2024**: We support `--bf16` mode for launching Flan-T5 with `torch.bfloat16` type; 
 > this feature allows launching `xl`-sized model training with just a single NVidia-A100 (40GB)
@@ -67,9 +67,9 @@ To form the Codalab Submission, please [follow this section](#submitting-results
 ## Usage<a name="code" />
 
 ### Requirement<a name="requirement" />
-![](https://img.shields.io/badge/Python-3.8-lightgreen.svg)
+![](https://img.shields.io/badge/Python-3.10-lightgreen.svg)
 
-This project has been tested under **Python-3.8**. 
+This project has been tested under **Python-3.8** and [adapted](https://github.com/nicolay-r/THOR-ECAC/issues/2) for the **Python-3.10**. 
 
 Using `pip`, you can install the necessary dependencies as follows:
 ``` bash 

diff --git a/download_data.py b/download_data.py
@@ -4,7 +4,7 @@
 from os.path import dirname, join, realpath
 
 import yaml
-from attrdict import AttrDict
+from addict import Dict
 
 from src.service import CsvService, THoRFrameworkService, download
 
@@ -66,7 +66,7 @@ def se24_states(src, target):
     args = parser.parse_args()
 
     # Reading configuration.
-    config = AttrDict(yaml.load(open(args.config, 'r', encoding='utf-8'), Loader=yaml.FullLoader))
+    config = Dict(yaml.load(open(args.config, 'r', encoding='utf-8'), Loader=yaml.FullLoader))
     names = []
     for k, v in vars(args).items():
         setattr(config, k, v)

diff --git a/main.py b/main.py
@@ -2,7 +2,7 @@
 
 import yaml
 import torch
-from attrdict import AttrDict
+from addict import Dict
 import pandas as pd
 from transformers import GenerationConfig
 
@@ -19,7 +19,7 @@
 
 class Template:
     def __init__(self, args):
-        config = AttrDict(yaml.load(open(args.config, 'r', encoding='utf-8'), Loader=yaml.FullLoader))
+        config = Dict(yaml.load(open(args.config, 'r', encoding='utf-8'), Loader=yaml.FullLoader))
         names = []
         for k, v in vars(args).items():
             setattr(config, k, v)

diff --git a/requirements.txt b/requirements.txt
@@ -1,4 +1,4 @@
-attrdict==2.0.1
+addict
 PyYAML==6.0
 transformers==4.38.0
 numpy