77 lines
2.3 KiB
Python
77 lines
2.3 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 os
|
|
import platform
|
|
|
|
import pytest
|
|
import torch
|
|
|
|
from pytorch_lightning import Trainer
|
|
from tests.helpers import BoringModel
|
|
|
|
|
|
def test_model_torch_save(tmpdir):
|
|
"""Test to ensure torch save does not fail for model and trainer."""
|
|
model = BoringModel()
|
|
num_epochs = 1
|
|
trainer = Trainer(
|
|
default_root_dir=tmpdir,
|
|
max_epochs=num_epochs,
|
|
)
|
|
temp_path = os.path.join(tmpdir, 'temp.pt')
|
|
trainer.fit(model)
|
|
|
|
# Ensure these do not fail
|
|
torch.save(trainer.model, temp_path)
|
|
torch.save(trainer, temp_path)
|
|
trainer = torch.load(temp_path)
|
|
|
|
|
|
@pytest.mark.skipif(platform.system() == "Windows", reason="Distributed training is not supported on Windows")
|
|
def test_model_torch_save_ddp_cpu(tmpdir):
|
|
"""Test to ensure torch save does not fail for model and trainer using cpu ddp."""
|
|
model = BoringModel()
|
|
num_epochs = 1
|
|
trainer = Trainer(
|
|
default_root_dir=tmpdir,
|
|
max_epochs=num_epochs,
|
|
accelerator="ddp_cpu",
|
|
num_processes=2,
|
|
)
|
|
temp_path = os.path.join(tmpdir, 'temp.pt')
|
|
trainer.fit(model)
|
|
|
|
# Ensure these do not fail
|
|
torch.save(trainer.model, temp_path)
|
|
torch.save(trainer, temp_path)
|
|
|
|
|
|
@pytest.mark.skipif(torch.cuda.device_count() < 2, reason="test requires multi-GPU machine")
|
|
def test_model_torch_save_ddp_cuda(tmpdir):
|
|
"""Test to ensure torch save does not fail for model and trainer using gpu ddp."""
|
|
model = BoringModel()
|
|
num_epochs = 1
|
|
trainer = Trainer(
|
|
default_root_dir=tmpdir,
|
|
max_epochs=num_epochs,
|
|
accelerator="ddp_spawn",
|
|
gpus=2,
|
|
)
|
|
temp_path = os.path.join(tmpdir, 'temp.pt')
|
|
trainer.fit(model)
|
|
|
|
# Ensure these do not fail
|
|
torch.save(trainer.model, temp_path)
|
|
torch.save(trainer, temp_path)
|