From: François Fleuret Date: Mon, 17 Jun 2024 13:53:17 +0000 (+0200) Subject: Update. X-Git-Url: https://fleuret.org/cgi-bin/gitweb/gitweb.cgi?a=commitdiff_plain;h=HEAD;hp=d95b9b72b0f098b5c955395905a0aff710f553a7;p=picoclvr.git Update. --- diff --git a/main.py b/main.py index 37515b5..3ff64b7 100755 --- a/main.py +++ b/main.py @@ -844,7 +844,7 @@ for n_epoch in range(nb_epochs_finished, args.nb_epochs): input = input.to(device) bs = model(mygpt.BracketedSequence(input)) - output_ar = bs.x + output = bs.x loss = F.cross_entropy(output.transpose(1, 2), input) diff --git a/turing.py b/turing.py new file mode 100755 index 0000000..2bcdeeb --- /dev/null +++ b/turing.py @@ -0,0 +1,46 @@ +#!/usr/bin/env python + +import torch + + +def generate_turing_sequences(N, nb_iter=5, nb_states=3, nb_symbols=4, tape_size=5): + next_state = torch.randint(nb_states, (N, nb_states, nb_symbols)) + next_symbol = torch.randint(nb_symbols, (N, nb_states, nb_symbols)) + next_move = torch.randint(3, (N, nb_states, nb_symbols)) + + all_n = torch.arange(N) + + tape = torch.randint(nb_symbols, (N, tape_size)) + # position = torch.randint(tape_size, (N,)) + # state = torch.randint(nb_states, (N,)) + position = torch.zeros(N, dtype=torch.int64) + state = torch.zeros(N, dtype=torch.int64) + + result = [] + + for _ in range(nb_iter): + result.append(tape.clone()) + current_symbol = tape[all_n, position] + tape[all_n, position] = next_symbol[all_n, state, current_symbol] + position = (position + next_move[all_n, state, current_symbol] - 1) % tape_size + state = next_state[all_n, state, current_symbol] + + result = torch.cat([x[:, None, :] for x in result], dim=1) + + return result + + +###################################################################### + +if __name__ == "__main__": + print("Basic check.") + + tapes = generate_turing_sequences(1, nb_iter=10) + + for i in range(tapes.size(1)): + # print(f"- {i:03d} ------------------------") + # for s, h, r in zip(state, position, tape): + # print("".join([f"{x}" for x in r])) + # print(" " * h + f"^[{s}]") + for r in tapes: + print("".join([f"{x}" for x in r[i]]))