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