Remove test_generation.py

test_generation.py

@@ -1,51 +0,0 @@
-import torch
-from transformers import AutoTokenizer, AutoModelForCausalLM
-
-device = 'cuda' if torch.cuda.is_available() else 'cpu'
-print(f"Using device: {device}\n")
-
-print("Loading RL-optimized PlasmidGPT-GRPO model...")
-model = AutoModelForCausalLM.from_pretrained(
-    ".",
-    trust_remote_code=True
-).to(device)
-model.eval()
-
-tokenizer = AutoTokenizer.from_pretrained(
-    ".",
-    trust_remote_code=True
-)
-
-print("Generating optimized plasmid sequences...\n")
-
-start_sequence = 'ATGGCTAGCGAATTCGGCGCGCCT'
-print(f"Start sequence: {start_sequence}\n")
-
-input_ids = tokenizer.encode(start_sequence, return_tensors='pt').to(device)
-
-outputs = model.generate(
-    input_ids,
-    max_length=400,
-    num_return_sequences=3,
-    temperature=0.8,
-    do_sample=True,
-    top_k=50,
-    top_p=0.95,
-    pad_token_id=tokenizer.pad_token_id,
-    eos_token_id=tokenizer.eos_token_id
-)
-
-print("=" * 80)
-for i, output in enumerate(outputs, 1):
-    sequence = tokenizer.decode(output, skip_special_tokens=True)
-    print(f"\nPlasmid {i}:")
-    print(f"  Length: {len(sequence)} bp")
-    print(f"  First 100 bp: {sequence[:100]}")
-    print(f"  Last 100 bp: {sequence[-100:]}")
-print("\n" + "=" * 80)
-
-print("\nNote: These sequences are generated by an RL-optimized model trained to:")
-print("  ✓ Include proper genetic elements (ori, promoters, CDS, markers)")
-print("  ✓ Avoid repeat regions > 50 bp")
-print("  ✓ Generate compact, functional plasmids")
-print("  ✓ Organize genes in proper cassettes (promoter → CDS → terminator)")