lightning/tests/utilities/test_memory.py

56 lines
1.8 KiB
Python

# Copyright The PyTorch Lightning team.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import math
import torch
import torch.nn as nn
from pytorch_lightning.utilities.memory import get_model_size_mb, recursive_detach
from tests.helpers import BoringModel
def test_recursive_detach():
device = "cuda" if torch.cuda.is_available() else "cpu"
x = {"foo": torch.tensor(0, device=device), "bar": {"baz": torch.tensor(1.0, device=device, requires_grad=True)}}
y = recursive_detach(x, to_cpu=True)
assert x["foo"].device.type == device
assert x["bar"]["baz"].device.type == device
assert x["bar"]["baz"].requires_grad
assert y["foo"].device.type == "cpu"
assert y["bar"]["baz"].device.type == "cpu"
assert not y["bar"]["baz"].requires_grad
def test_get_model_size_mb():
model = BoringModel()
size_bytes = get_model_size_mb(model)
# Size will be python version dependent.
assert math.isclose(size_bytes, 0.001319, rel_tol=0.1)
def test_get_sparse_model_size_mb():
class BoringSparseModel(BoringModel):
def __init__(self):
super().__init__()
self.layer = nn.Parameter(torch.ones(32).to_sparse())
model = BoringSparseModel()
size_bytes = get_model_size_mb(model)
assert math.isclose(size_bytes, 0.001511, rel_tol=0.1)