inference.py

from vllm import LLM, SamplingParams
from transformers import AutoTokenizer

MODEL_DIR = "path/to/CodeV-SVA/"

def get_nl2sva_prompt(testbench: str, problem: str, reset_signal=None) -> str:
    prompt =  ""
    prompt += "Here is the testbench to perform your translation:\n"
    prompt += testbench
    prompt += "\nQuestion: Create a SVA assertion that checks: "
    prompt += problem + "\n"

    if reset_signal is not None:
        prompt += f"You should use `{reset_signal}` as the disable condition signal. "
        example = f'''asrt: assert property (@(posedge clk) disable iff ({reset_signal})
    (a && b) != 1'b1
);'''
    else:
        example = '''asrt: assert property (@(posedge clk) 
    (a && b) != 1'b1
);'''
    prompt += f"""Do not add code to output an error message string.
Enclose your SVA code with ```systemverilog and ```. Only output the code snippet and do NOT output anything else.

For example,
```systemverilog
{example}
```
Answer:"""
    return prompt

if __name__ == "__main__":
    system_prompt = "You are an AI assistant tasked with formal verification of register transfer level (RTL) designs.\nYour job is to translate a description of an assertion to concrete SystemVerilog Assertion (SVA) implementation.\n"
    testbench = "module fifo_1r1w_tb (\n     clk,\n     reset_,\n     wr_vld,\n     wr_data,\n     wr_ready,\n     rd_vld,\n     rd_data,\n     rd_ready\n   );\n  \n    parameter   FIFO_DEPTH                              = 4;\n    parameter   DATA_WIDTH                              = 1;\n\nlocalparam FIFO_DEPTH_log2 = $clog2(FIFO_DEPTH); \nlocalparam DATA_WIDTH_log2 = $clog2(DATA_WIDTH); \n\n    input                   clk;\n    input                   reset_;\n    input                   wr_vld;\n    input  [DATA_WIDTH-1:0] wr_data;\n    input                   wr_ready;\n    input                   rd_vld;\n    input  [DATA_WIDTH-1:0] rd_data;\n    input                   rd_ready;\n\nwire wr_push;\nwire rd_pop;\n\nwire tb_reset;\nassign tb_reset = (reset_ == 1'b0);\n\nwire fifo_full;\nassign wr_push = wr_vld && wr_ready;\nassign rd_pop = rd_vld && rd_ready; \n\nreg [DATA_WIDTH-1:0]             fifo_array [FIFO_DEPTH-1:0]; //fifo array - shift register\nreg [FIFO_DEPTH_log2-1:0]        fifo_rd_ptr;                 //fifo array - rd_ptr\nwire                             actual_fifo_pop;             // actual pop == pop\nreg                              fifo_empty;                  // fifo empty\nwire [DATA_WIDTH-1:0]            fifo_out_data;               // dout\n\n// ---- shift register code start ----\nalways @(posedge clk) begin\n    if (!reset_) fifo_array[0] <= 'd0;\n    else if (wr_push) begin\n        fifo_array[0] <= wr_data;\n    end else fifo_array[0] <= fifo_array[0];\nend\nfor (genvar i = 1; i < FIFO_DEPTH; i++ ) begin : loop_id\n    always @(posedge clk) begin\n        if (!reset_) fifo_array[i] <= 'd0;\n        else if (wr_push) begin\n            fifo_array[i] <= fifo_array[i-1];\n        end else fifo_array[i] <= fifo_array[i];\n    end\nend\n\n// ---- read pointer/fifo empty code start ----\nalways @(posedge clk) begin\n    if (!reset_) begin\n        fifo_rd_ptr <= 'd0;\n    end else if (wr_push && fifo_empty)  begin\n        fifo_rd_ptr <= 'd0;\n    end else if (rd_pop && !fifo_empty && (fifo_rd_ptr == 'd0)) begin\n        fifo_rd_ptr <= 'd0;\n    end else begin\n        fifo_rd_ptr <= fifo_rd_ptr + wr_push - rd_pop;\n    end\n    if (!reset_) begin\n        fifo_empty <= 'd1;\n    end else if (rd_pop && !fifo_empty && (fifo_rd_ptr == 'd0) && !wr_push) begin\n        fifo_empty <= 'd1;\n    end else if ((fifo_rd_ptr != 'd0) || wr_push && !rd_pop) begin\n        fifo_empty <= 'd0;\n    end\nend\n// ---- fifo full and dout code start ----\nassign fifo_full = (fifo_rd_ptr == (FIFO_DEPTH - 1)) && !fifo_empty;\nassign fifo_out_data = fifo_array[fifo_rd_ptr];\n\nendmodule"
    problem = "When there is a write push to the FIFO, data is eventually popped. Use the signals 'rd_pop' and 'wr_push'."
    reset_signal = "tb_reset"
    user_prompt = get_nl2sva_prompt(testbench, problem, reset_signal)

    dialog = [
        {"role": "system", "content": system_prompt},
        {"role": "user", "content": user_prompt}
    ] 

    tokenizer = AutoTokenizer.from_pretrained(MODEL_DIR)
    prompt = tokenizer.apply_chat_template(dialog, tokenize=False, add_generation_prompt=True)
    print(f"### Prompt:\n{prompt}")

    model = LLM(
        MODEL_DIR, 
        tensor_parallel_size=4
    )

    sampling_params = SamplingParams(
        temperature=0.8,
        top_p=0.95,
        max_tokens=32768,
        n=1
    )

    responses = model.generate(prompt, sampling_params)
    formal_statements = []
    for i, output in enumerate(responses[0].outputs):
        response_text = output.text
        print(f"### Response:\n{response_text}")