import { GPT2Tokenizer, GraniteForCausalLM } from "../../../src/transformers.js";

import { MAX_MODEL_LOAD_TIME, MAX_TEST_EXECUTION_TIME, MAX_MODEL_DISPOSE_TIME, DEFAULT_MODEL_OPTIONS } from "../../init.js";

export default () => {
  describe("GraniteForCausalLM", () => {
    const model_id = "hf-internal-testing/tiny-random-GraniteForCausalLM";
    /** @type {GraniteForCausalLM} */
    let model;
    /** @type {GPT2Tokenizer} */
    let tokenizer;
    beforeAll(async () => {
      model = await GraniteForCausalLM.from_pretrained(model_id, DEFAULT_MODEL_OPTIONS);
      tokenizer = await GPT2Tokenizer.from_pretrained(model_id);
    }, MAX_MODEL_LOAD_TIME);

    it(
      "batch_size=1",
      async () => {
        const inputs = tokenizer("hello");
        const outputs = await model.generate({
          ...inputs,
          max_length: 10,
        });
        expect(outputs.tolist()).toEqual([[7656n, 39727n, 33077n, 9643n, 30539n, 47869n, 48739n, 15085n, 9203n, 14020n]]);
      },
      MAX_TEST_EXECUTION_TIME,
    );

    it(
      "batch_size>1",
      async () => {
        const inputs = tokenizer(["hello", "hello world"], { padding: true });
        const outputs = await model.generate({
          ...inputs,
          max_length: 10,
        });
        expect(outputs.tolist()).toEqual([
          [0n, 7656n, 39727n, 33077n, 9643n, 30539n, 47869n, 48739n, 15085n, 9203n],
          [7656n, 5788n, 17835n, 13234n, 7592n, 21471n, 30537n, 23023n, 43450n, 4824n],
        ]);
      },
      MAX_TEST_EXECUTION_TIME,
    );

    afterAll(async () => {
      await model?.dispose();
    }, MAX_MODEL_DISPOSE_TIME);
  });
};