mlx

-module(quick_test).
-export([run/0]).

run() ->
    io:format("=== Quick MLX Test ===~n"),
    
    % Test basic functionality
    try
        io:format("Testing basic array creation...~n"),
        case catch test_basic_arrays() of
            ok -> 
                io:format("✓ Basic arrays: PASS~n");
            Error1 -> 
                io:format("✗ Basic arrays: FAIL - ~p~n", [Error1])
        end,
        
        io:format("Testing neural network operations...~n"),
        case catch test_nn_ops() of
            ok -> 
                io:format("✓ Neural network ops: PASS~n");
            Error2 -> 
                io:format("✗ Neural network ops: FAIL - ~p~n", [Error2])
        end,
        
        io:format("Testing random generation...~n"),
        case catch test_random_ops() of
            ok -> 
                io:format("✓ Random operations: PASS~n");
            Error3 -> 
                io:format("✗ Random operations: FAIL - ~p~n", [Error3])
        end,
        
        io:format("~n=== Test Complete ===~n")
        
    catch
        Class:Reason:Stacktrace ->
            io:format("Test crashed: ~p:~p~n~p~n", [Class, Reason, Stacktrace])
    end.

test_basic_arrays() ->
    % Test if we can create basic arrays
    {ok, A} = mlx:zeros([3, 3]),
    {ok, B} = mlx:ones([3, 3]),
    {ok, C} = mlx:add(A, B),
    {ok, [3, 3]} = mlx:shape(C),
    ok.

test_nn_ops() ->
    % Test neural network operations
    {ok, X} = mlx:random([10, 5]),
    {ok, Y} = mlx_nn:relu(X),
    {ok, Z} = mlx_nn:softmax(Y),
    {ok, [10, 5]} = mlx:shape(Z),
    ok.

test_random_ops() ->
    % Test random operations
    {ok, R1} = mlx_random:normal([100]),
    {ok, R2} = mlx_random:uniform([50, 2]),
    {ok, [100]} = mlx:shape(R1),
    {ok, [50, 2]} = mlx:shape(R2),
    ok.