33 lines
1.0 KiB
Python
33 lines
1.0 KiB
Python
import torch
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from torch import nn
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def populate_queues(queues, batch):
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for key in batch:
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if len(queues[key]) != queues[key].maxlen:
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# initialize by copying the first observation several times until the queue is full
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while len(queues[key]) != queues[key].maxlen:
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queues[key].append(batch[key])
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else:
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# add latest observation to the queue
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queues[key].append(batch[key])
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return queues
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def get_device_from_parameters(module: nn.Module) -> torch.device:
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"""Get a module's device by checking one of its parameters.
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Note: assumes that all parameters have the same device
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TODO(now): Add test.
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"""
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return next(iter(module.parameters())).device
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def get_dtype_from_parameters(module: nn.Module) -> torch.dtype:
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"""Get a module's parameter dtype by checking one of its parameters.
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Note: assumes that all parameters have the same dtype.
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TODO(now): Add test.
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"""
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return next(iter(module.parameters())).dtype
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