defmodule Bumblebee.Text.GemmaTest do
  use ExUnit.Case, async: true

  import Bumblebee.TestHelpers

  @moduletag model_test_tags()

  test ":base" do
    assert {:ok, %{model: model, params: params, spec: spec}} =
             Bumblebee.load_model({:hf, "bumblebee-testing/tiny-random-GemmaModel"})

    assert %Bumblebee.Text.Gemma{architecture: :base} = spec

    inputs = %{
      "input_ids" => Nx.tensor([[10, 20, 30, 40, 50, 60, 70, 80, 0, 0]]),
      "attention_mask" => Nx.tensor([[1, 1, 1, 1, 1, 1, 1, 1, 0, 0]])
    }

    outputs = Axon.predict(model, params, inputs)

    assert Nx.shape(outputs.hidden_state) == {1, 10, 32}

    assert_all_close(
      outputs.hidden_state[[.., 1..3, 1..3]],
      Nx.tensor([
        [[-2.0724, -1.1056, -0.4123], [0.7144, -1.5150, -1.8728], [0.7222, 0.7930, 0.3218]]
      ])
    )
  end

  test ":for_sequence_classification" do
    assert {:ok, %{model: model, params: params, spec: spec}} =
             Bumblebee.load_model(
               {:hf, "bumblebee-testing/tiny-random-GemmaForSequenceClassification"}
             )

    assert %Bumblebee.Text.Gemma{architecture: :for_sequence_classification} = spec

    inputs = %{
      "input_ids" => Nx.tensor([[10, 20, 30, 40, 50, 60, 70, 80, 0, 0]]),
      "attention_mask" => Nx.tensor([[1, 1, 1, 1, 1, 1, 1, 1, 0, 0]])
    }

    outputs = Axon.predict(model, params, inputs)

    assert Nx.shape(outputs.logits) == {1, 2}

    assert_all_close(
      outputs.logits,
      Nx.tensor([[-0.1422, 0.0613]])
    )
  end

  test ":for_causal_language_modeling" do
    assert {:ok, %{model: model, params: params, spec: spec}} =
             Bumblebee.load_model({:hf, "bumblebee-testing/tiny-random-GemmaForCausalLM"})

    assert %Bumblebee.Text.Gemma{architecture: :for_causal_language_modeling} = spec

    inputs = %{
      "input_ids" => Nx.tensor([[10, 20, 30, 40, 50, 60, 70, 80, 0, 0]]),
      "attention_mask" => Nx.tensor([[1, 1, 1, 1, 1, 1, 1, 1, 0, 0]])
    }

    outputs = Axon.predict(model, params, inputs)

    assert Nx.shape(outputs.logits) == {1, 10, 1024}

    assert_all_close(
      outputs.logits[[.., 1..3, 1..3]],
      Nx.tensor([
        [[0.0924, 0.1602, -0.0448], [-0.0934, -0.0543, -0.1045], [-0.1467, 0.0339, -0.1926]]
      ])
    )
  end
end
