Source code for protomotions.agents.utils.step_tracker

# SPDX-FileCopyrightText: Copyright (c) 2025-2026 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
# SPDX-License-Identifier: Apache-2.0

import torch
from torch import Tensor, nn


[docs] class StepTracker(nn.Module): steps: Tensor
[docs] def __init__( self, num_envs: int, min_steps: int, max_steps: int, device: torch.device ): super().__init__() self.register_buffer( "steps", torch.zeros(num_envs, dtype=torch.long), persistent=False ) self.register_buffer( "cur_max_steps", torch.zeros(num_envs, dtype=torch.long), persistent=False ) self.num_envs = num_envs self.min_steps = min_steps self.max_steps = max_steps self.to(device)
[docs] def advance(self): self.steps += 1
[docs] def done_indices(self): return torch.nonzero( torch.greater_equal(self.steps, self.cur_max_steps), as_tuple=False ).squeeze(-1)
[docs] def reset_steps(self, env_ids: Tensor = None): if env_ids is None: env_ids = torch.arange( 0, self.num_envs, device=self.device, dtype=torch.long ) n = len(env_ids) self.steps[env_ids] = 0 self.cur_max_steps[env_ids] = torch.randint( self.min_steps, self.max_steps, size=[n], dtype=torch.long, device=self.device, )
[docs] def shift_counter(self, env_ids: Tensor, shift: Tensor): self.steps[env_ids] -= shift self.cur_max_steps[env_ids] -= shift
@property def device(self) -> torch.device: """Get device from registered buffers.""" return self.steps.device