Delete interpretability.py

interpretability.py

@@ -1,67 +0,0 @@
-from rdkit import Chem
-from rdkit.Chem import Draw
-from rdkit.Chem.Draw import SimilarityMaps
-from IPython.display import SVG
-import io
-from PIL import Image
-import numpy as np
-import rdkit
-
-from transformers import AutoModelForSequenceClassification, AutoTokenizer
-from transformers_interpret import SequenceClassificationExplainer
-from transformers import pipeline
-
-model_name = "FartLabs/FART_Augmented"
-model = AutoModelForSequenceClassification.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-cls_explainer = SequenceClassificationExplainer(model, tokenizer)
-
-def save_high_quality_png(smiles, title, bw=True, padding=0.05):
-    """
-    Generates a high-quality PNG of atom-wise gradients or importance scores for a molecule.
-
-    Parameters:
-    - smiles (str): The SMILES string of the molecule to visualize.
-    - token_importance (list): List of importance scores for each atom.
-    - bw (bool): If True, renders the molecule in black and white.
-    - padding (float): Padding for molecule drawing.
-    - output_file (str): Path to save the high-quality PNG file.
-
-    Returns:
-    - None
-    """
-    
-    # Convert SMILES string to RDKit molecule object
-    molecule = Chem.MolFromSmiles(smiles)
-    Chem.rdDepictor.Compute2DCoords(molecule)
-    
-    # Get token importance scores and map to atoms
-    token_importance = cls_explainer(smiles)
-    atom_importance = [c[1] for c in token_importance if c[0].isalpha()]
-    num_atoms = molecule.GetNumAtoms()
-    atom_importance = atom_importance[:num_atoms]
-    
-    # Set a large canvas size for high resolution
-    d = Draw.MolDraw2DCairo(1500, 1500)
-
-    dopts = d.drawOptions()
-    dopts.padding = padding    
-    dopts.maxFontSize = 2000
-    dopts.bondLineWidth = 5
-
-    # Optionally set black and white palette
-    if bw:
-        d.drawOptions().useBWAtomPalette()
-    
-    # Generate and display a similarity map based on atom importance scores
-    SimilarityMaps.GetSimilarityMapFromWeights(molecule, atom_importance, draw2d=d)
-
-    # Draw molecule with color highlights
-    d.FinishDrawing()
-    
-    # Save to PNG file with high quality
-    with open(f"{title}.png", "wb") as png_file:
-        png_file.write(d.GetDrawingText())
-    
-    return None