2025.03.18.post5

2025.03.18.post5 MAJOR

app_main_hf.py

@@ -1,18 +1,22 @@
+import os
+import sys
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 from streamlit_extras.bottom_container import bottom
 from streamlit_extras.app_logo import add_logo
 from streamlit_extras.add_vertical_space import add_vertical_space
 from streamlit_extras.stylable_container import stylable_container
-
+import torch
 from imports import *
 import streamlit as st
 from streamlit_option_menu import option_menu
-import os
 import asyncio
-import sys
 import shutil
 import gc
 from transformers.utils.hub import TRANSFORMERS_CACHE
 
+# torch.classes.__path__ = []
+
 
 try:
     asyncio.get_running_loop()
@@ -32,7 +36,7 @@ import joblib
 import importlib
 import importlib.util
 
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+# sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
 
 
 from emotion_analysis import show_emotion_analysis

dashboard.py

@@ -1,10 +1,13 @@
+import os
+import sys
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 import streamlit as st
 from transformers.utils.hub import TRANSFORMERS_CACHE
 import shutil
 import torch
 import psutil
 import gc
-import os
 
 def free_memory():
     #  """Free up CPU & GPU memory before loading a new model."""

imports.py

@@ -1,6 +1,11 @@
+import os
+import sys
+
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModel, DebertaV2Tokenizer, DebertaV2ForSequenceClassification
-import torch
+# import torch
 import numpy as np
 import matplotlib.pyplot as plt
 import plotly.express as px
@@ -14,7 +19,4 @@ import importlib.util
 import asyncio
 import sys
 import pytorch_lightning as pl
-from transformers.utils.hub import TRANSFORMERS_CACHE
-
-
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+from transformers.utils.hub import TRANSFORMERS_CACHE

pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "tachygraphy-microtext-analysis-and-normalization"
-version = "2025.03.18.post3"
+version = "2025.03.18.post5"
 description = ""
 authors = [
     { name = "Archisman Karmakar", email = "92569441+ArchismanKarmakar@users.noreply.github.com" },

pyprojectOLD.toml

@@ -1,6 +1,8 @@
 [project]
 name = "tachygraphy-microtext-analysis-and-normalization"
-version = "2025.03.18.post2"
+version = "2025.03.18.post4_3"
+# version = "2025.03.18.post3"
+# version = "2025.03.18.post2"
 # version = "2025.03.18.post1"
 # version = "2025.03.17.post1"
 # version = "2025.03.16.post3"

requirements.txt

@@ -155,8 +155,8 @@ pyproject-hooks==1.2.0 ; python_version >= "3.12"
 python-dateutil==2.9.0.post0 ; python_version >= "3.12"
 pytorch-lightning==2.5.0.post0 ; python_version >= "3.12"
 pytz==2025.1 ; python_version >= "3.12"
-pywin32-ctypes==0.2.3 ; python_version >= "3.12"
-pywin32==309 ; python_version >= "3.12"
+pywin32-ctypes==0.2.3 ; python_version >= "3.12" and sys_platform == "win32"
+pywin32==309 ; python_version >= "3.12" and sys_platform == "win32"
 pyyaml==6.0.2 ; python_version >= "3.12"
 pyzmq==26.3.0 ; python_version >= "3.12"
 rapidfuzz==3.12.2 ; python_version >= "3.12"

sentiment_analysis/hmv_cfg_base_stage1/imports.py

@@ -1,6 +1,11 @@
+import os
+import sys
+
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 import streamlit as st
 from transformers import AutoTokenizer, AutoModelForSequenceClassification, AutoModel, DebertaV2Tokenizer, DebertaV2ForSequenceClassification, DebertaV2Model
-import torch
+# import torch
 import numpy as np
 import matplotlib.pyplot as plt
 import plotly.express as px
@@ -8,12 +13,10 @@ import pandas as pd
 import json
 import gc
 import psutil
-import os
 import importlib
 import importlib.util
 import asyncio
-import sys
-import pytorch_lightning as pl
+# import pytorch_lightning as pl
 
 import safetensors
 from safetensors import load_file, save_file

sentiment_analysis/hmv_cfg_base_stage1/model1.py

@@ -1,10 +1,18 @@
+import os
+import sys
+
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
+BASE_DIR = os.path.dirname(os.path.abspath(__file__))
+CONFIG_STAGE1 = os.path.join(BASE_DIR, "..", "config", "stage1_models.json")
+
+import torch
 import torch.nn as nn
 from imports import *
 import torch.nn.functional as F
 
 
-BASE_DIR = os.path.dirname(os.path.abspath(__file__))
-CONFIG_STAGE1 = os.path.join(BASE_DIR, "..", "config", "stage1_models.json")
+
 
 MODEL_OPTIONS = {
 "1": {

sentiment_analysis/hmv_cfg_base_stage1/model2.py

@@ -1,3 +1,7 @@
+import os
+import sys
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 from imports import *
 
 import importlib.util
@@ -15,8 +19,6 @@ import json
 from huggingface_hub import hf_hub_download
 from safetensors.torch import save_file, safe_open
 
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
-
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 CONFIG_STAGE1 = os.path.join(BASE_DIR, "..", "config", "stage1_models.json")
 

sentiment_analysis/hmv_cfg_base_stage1/model3.py

@@ -1,3 +1,8 @@
+import os
+import sys
+
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 from imports import *
 
 import importlib.util
@@ -15,7 +20,6 @@ import json
 from huggingface_hub import hf_hub_download
 from safetensors.torch import save_file, safe_open
 
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
 
 BASE_DIR = os.path.dirname(os.path.abspath(__file__))
 CONFIG_STAGE1 = os.path.join(BASE_DIR, "..", "config", "stage1_models.json")

sentiment_analysis/sentiment_analysis_main.py

@@ -1,15 +1,20 @@
+import os
+import sys
+
+sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
+
 from imports import *
 import importlib.util
 import os
 import sys
 import joblib
 import time
+import torch
 # from transformers.utils import move_cache_to_trash 
 # from huggingface_hub import delete_cache
 from transformers.utils.hub import TRANSFORMERS_CACHE
 import shutil
 
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), )))
 
 # from hmv_cfg_base_stage1.model1 import load_model as load_model1
 # from hmv_cfg_base_stage1.model1 import predict as predict1