# CODE_VAL=val + 2 * nb_stacks
-def generate(nb, nb_steps, nb_stacks, nb_values):
+def generate_sequences(nb, nb_steps, nb_stacks, nb_values, device=torch.device("cpu")):
stack = torch.empty(nb, nb_stacks, nb_steps, dtype=torch.int64)
- stack_pointers = torch.zeros(nb, nb_stacks, dtype=torch.int64)
+ stack_counts = torch.zeros(nb, nb_stacks, dtype=torch.int64)
k = torch.arange(nb)
result = torch.empty(nb, 2 * nb_steps, dtype=torch.int64)
- depth_counts = torch.zeros(nb, 2 * nb_steps, dtype=torch.int64)
+ recorded_stack_counts = torch.zeros(nb, 2 * nb_steps, dtype=torch.int64)
for t in range(nb_steps):
op = torch.randint(2, (nb,))
st = torch.randint(nb_stacks, (nb,))
- op = op * (stack_pointers[k, st] > 0)
+ op = op * (stack_counts[k, st] > 0)
val_push = torch.randint(nb_values, (nb,))
val_pop = stack[
k,
st,
- (stack_pointers[k, st] - 1).clamp(min=0),
+ (stack_counts[k, st] - 1).clamp(min=0),
]
- stack[k, st, stack_pointers[k, st]] = val_push
- depth_counts[:, 2 * t + 1] = stack_pointers[k, st]
- stack_pointers[k[op == 0], st[op == 0]] += 1
- stack_pointers[k[op == 1], st[op == 1]] -= 1
+ stack[k, st, stack_counts[k, st]] = val_push
+ recorded_stack_counts[:, 2 * t + 1] = stack_counts[k, st]
+ stack_counts[k[op == 0], st[op == 0]] += 1
+ stack_counts[k[op == 1], st[op == 1]] -= 1
result[:, 2 * t] = st * 2 + op
result[:, 2 * t + 1] = (op * val_pop + (1 - op) * val_push) + 2 * nb_stacks
- return result, depth_counts
+ return result.to(device), recorded_stack_counts.to(device)
-def seq_to_str(seq, depth_counts=None):
+def remove_poped_values(seq, nb_stacks):
+ m = torch.logical_and(seq % 2 == 1, seq < 2 * nb_stacks).long()
+ seq[:, 1:] = -m[:, :-1] + (1 - m[:, :-1]) * seq[:, 1:]
+
+
+def seq_to_str(seq, show_stack_nb=True,recorded_stack_counts=None):
assert seq.size(0) % 2 == 0
s = ""
for t in range(seq.size(0) // 2):
- op = seq[2 * t]
- op = f"POP_{op//2}" if op % 2 == 1 else f"PUSH_{op//2}"
- val = seq[2 * t + 1] - 2 * nb_stacks
+ n_op = seq[2 * t]
+ op = f"POP" if n_op % 2 == 1 else f"PSH"
+ if show_stack_nb: op+=f"_{n_op//2}"
+ if seq[2 * t + 1] == -1:
+ val = "?"
+ else:
+ val = seq[2 * t + 1] - 2 * nb_stacks
if t > 0:
s += " "
- if depth_counts is not None:
- s += f"[{depth_counts[2*t+1]}] "
+ if recorded_stack_counts is not None:
+ s += f"[{recorded_stack_counts[2*t+1]}] "
s += f"{op} {val}"
return s
if __name__ == "__main__":
nb, nb_steps, nb_stacks, nb_values = 150000, 10, 1, 5
- seq, depth_counts = generate(
+ seq, recorded_stack_counts = generate_sequences(
nb=nb, nb_steps=nb_steps, nb_stacks=nb_stacks, nb_values=nb_values
)
+ print("-- TRAIN -----------------------------")
+
+ for n in range(min(10, seq.size(0))):
+ # print(seq_to_str(seq[n], recorded_stack_counts[n]))
+ print(seq_to_str(seq[n],show_stack_nb=nb_stacks>1))
+
+ print("-- TEST ------------------------------")
+
+ remove_poped_values(seq, nb_stacks)
+
for n in range(min(10, seq.size(0))):
- print(seq_to_str(seq[n], depth_counts[n]))
+ print(seq_to_str(seq[n],show_stack_nb=nb_stacks>1))