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8185 - Refactor test #8231

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075ec11
Eliminates code repetition
garciadias Nov 20, 2024
e8d3e19
Replace relative import with absolute
garciadias Nov 20, 2024
d4b01e6
Directly tests export_ckpt function instead of using command_line_tests
garciadias Nov 21, 2024
bfc68a4
Style fix
garciadias Nov 21, 2024
10eb2af
Merge branch 'dev' into 8185-tests-refactor
garciadias Nov 21, 2024
55fcd22
Revert "Style fix"
garciadias Nov 23, 2024
ba16743
Revert "Replace relative import with absolute"
garciadias Nov 23, 2024
1667eb7
Revert "Directly tests export_ckpt function instead of using command_…
garciadias Nov 23, 2024
702e740
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Nov 24, 2024
9a2c2f4
moves tests to their corresponding folder
garciadias Nov 28, 2024
f2cf158
replace relative imports with absolute import
garciadias Nov 28, 2024
b3fd8e9
Change locating integrations
garciadias Nov 28, 2024
114fc72
Corrects the download path for integration tests
garciadias Nov 28, 2024
626e050
Move array/* and dictionary/* files to parent directory
garciadias Dec 2, 2024
4c6b59c
Move single files on their parent folders
garciadias Dec 2, 2024
050e71b
Merge remote-tracking branch 'upstream/dev' into dev
garciadias Dec 2, 2024
7d68938
Merge branch 'dev' into 8185-tests-refactor
garciadias Dec 2, 2024
3508211
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Dec 2, 2024
2d55074
Recovers deleted file
garciadias Dec 3, 2024
6e9c66e
Merge remote-tracking branch 'upstream/dev' into 8185-tests-refactor
garciadias Dec 3, 2024
fa5c75c
Merge remote-tracking branch 'upstream/dev' into dev
garciadias Dec 4, 2024
dda65c4
Merge branch 'dev' into 8185-tests-refactor
garciadias Dec 4, 2024
bf82225
Start fixing path issues after moving files
garciadias Dec 6, 2024
56c2a48
Keep fixing data paths
garciadias Dec 9, 2024
98d3ab2
rerouting paths
garciadias Dec 11, 2024
6d1af88
Merge remote-tracking branch 'origin/8185-tests-refactor' into 8185-t…
garciadias Dec 11, 2024
a0d2395
Solve many more issues
garciadias Dec 11, 2024
9977e98
Merge remote-tracking branch 'origin/8185-tests-refactor' into 8185-t…
garciadias Dec 11, 2024
8831dc0
reorder imports
garciadias Dec 11, 2024
58c461c
[pre-commit.ci] auto fixes from pre-commit.com hooks
pre-commit-ci[bot] Dec 11, 2024
bb85f53
Fix path issues
garciadias Dec 11, 2024
865dc22
Move utils inside utils to avoid coflict
garciadias Dec 12, 2024
cf1025a
Keep cleaning tests but reverting utils.utils change
Dec 16, 2024
d2e7a2e
Merge remote-tracking branch 'origin/8185-tests-refactor' into 8185-t…
garciadias Jan 8, 2025
5632fdf
Merge remote-tracking branch 'upstream/dev' into 8185-tests-refactor
garciadias Jan 20, 2025
4af739c
rename utils to distinguish from utils folder
garciadias Jan 20, 2025
19b2fdf
Restore deleted testing_data files
garciadias Jan 23, 2025
7a34f01
Corrects testing_data paths on tests
garciadias Jan 23, 2025
0730b56
Merge remote-tracking branch 'upstream/dev' into 8185-tests-refactor
garciadias Jan 23, 2025
069b07c
autofix
garciadias Jan 23, 2025
67c0521
correct reference to util
garciadias Jan 23, 2025
a4a0baa
Fixes more of the util problems
garciadias Jan 23, 2025
34627e8
revert changes unrelated to test restructuring
garciadias Jan 23, 2025
08cd2ac
Correct utils in the reverted files
garciadias Jan 23, 2025
d348aa6
Merge remote-tracking branch 'upstream/dev' into 8185-tests-refactor
garciadias Jan 25, 2025
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1 change: 1 addition & 0 deletions .gitignore
Original file line number Diff line number Diff line change
Expand Up @@ -130,6 +130,7 @@ temp/
.DS_Store

# temporary testing data MedNIST
tests/integration/testing_data/MedNIST*
tests/testing_data/MedNIST*
tests/testing_data/*Hippocampus*
tests/testing_data/*.tiff
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2 changes: 1 addition & 1 deletion runtests.sh
Original file line number Diff line number Diff line change
Expand Up @@ -740,7 +740,7 @@ if [ $doNetTests = true ]
then
set +e # disable exit on failure so that diagnostics can be given on failure
echo "${separator}${blue}integration${noColor}"
for i in tests/*integration_*.py
for i in tests/integration/*.py
do
echo "$i"
${cmdPrefix}${cmd} "$i"
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108 changes: 108 additions & 0 deletions tests/bundle/test_bundle_ckpt_export.py
Original file line number Diff line number Diff line change
@@ -0,0 +1,108 @@
# Copyright (c) MONAI Consortium
# 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.

from __future__ import annotations

import json
import os
import tempfile
import unittest

from parameterized import parameterized

from monai.bundle import ConfigParser
from monai.data import load_net_with_metadata
from monai.networks import save_state
from tests.utils import command_line_tests, skip_if_windows

TEST_CASE_1 = [True, "", ""]

TEST_CASE_2 = [True, "model", ""]

TEST_CASE_3 = [True, "model", "True"]

TEST_CASE_4 = [False, "", ""]

TEST_CASE_5 = [False, "model", ""]

TEST_CASE_6 = [False, "model", "True"]


@skip_if_windows
class TestCKPTExport(unittest.TestCase):
def setUp(self):
self.device = os.environ.get("CUDA_VISIBLE_DEVICES")
if not self.device:
os.environ["CUDA_VISIBLE_DEVICES"] = "0" # default
self.meta_file = os.path.join(os.path.dirname(__file__), "testing_data", "metadata.json")
self.config_file = os.path.join(os.path.dirname(__file__), "testing_data", "inference.json")
self.tempdir_obj = tempfile.TemporaryDirectory()
tempdir = self.tempdir_obj.name
self.def_args = {"meta_file": "will be replaced by `meta_file` arg"}
self.def_args_file = os.path.join(tempdir, "def_args.yaml")

self.ckpt_file = os.path.join(tempdir, "model.pt")
self.ts_file = os.path.join(tempdir, "model.ts")

self.parser = ConfigParser()
self.parser.export_config_file(config=self.def_args, filepath=self.def_args_file)
self.parser.read_config(self.config_file)
self.net = self.parser.get_parsed_content("network_def")
self.cmd = ["coverage", "run", "-m", "monai.bundle", "ckpt_export", "network_def", "--filepath", self.ts_file]
self.cmd += [
"--meta_file",
self.meta_file,
"--config_file",
f"['{self.config_file}','{self.def_args_file}']",
"--ckpt_file",
]

def tearDown(self):
if self.device is not None:
os.environ["CUDA_VISIBLE_DEVICES"] = self.device
else:
del os.environ["CUDA_VISIBLE_DEVICES"] # previously unset
self.tempdir_obj.cleanup()

@parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3])
def test_export(self, key_in_ckpt, use_trace):
save_state(src=self.net if key_in_ckpt == "" else {key_in_ckpt: self.net}, path=self.ckpt_file)
full_cmd = self.cmd + [self.ckpt_file, "--key_in_ckpt", key_in_ckpt, "--args_file", self.def_args_file]
if use_trace == "True":
full_cmd += ["--use_trace", use_trace, "--input_shape", "[1, 1, 96, 96, 96]"]
command_line_tests(full_cmd)
self.assertTrue(os.path.exists(self.ts_file))

_, metadata, extra_files = load_net_with_metadata(
self.ts_file, more_extra_files=["inference.json", "def_args.json"]
)
self.assertIn("schema", metadata)
self.assertIn("meta_file", json.loads(extra_files["def_args.json"]))
self.assertIn("network_def", json.loads(extra_files["inference.json"]))

@parameterized.expand([TEST_CASE_1, TEST_CASE_2, TEST_CASE_3])
def test_default_value(self, key_in_ckpt, use_trace):
ckpt_file = os.path.join(self.tempdir_obj.name, "models/model.pt")
ts_file = os.path.join(self.tempdir_obj.name, "models/model.ts")

save_state(src=self.net if key_in_ckpt == "" else {key_in_ckpt: self.net}, path=ckpt_file)

# check with default value
cmd = ["coverage", "run", "-m", "monai.bundle", "ckpt_export", "--key_in_ckpt", key_in_ckpt]
cmd += ["--config_file", self.config_file, "--bundle_root", self.tempdir_obj.name]
if use_trace == "True":
cmd += ["--use_trace", use_trace, "--input_shape", "[1, 1, 96, 96, 96]"]
command_line_tests(cmd)
self.assertTrue(os.path.exists(ts_file))


if __name__ == "__main__":
unittest.main()
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Expand Up @@ -64,7 +64,7 @@ def test_train(self):
data = ExchangeObject(weights=get_state_dict(network))
# test train
for i in range(2):
print(f"Testing round {i+1} of {2}...")
print(f"Testing round {i + 1} of {2}...")
# test evaluate
metric_eo = algo.evaluate(data=data, extra={})
self.assertIsInstance(metric_eo, ExchangeObject)
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Original file line number Diff line number Diff line change
Expand Up @@ -99,7 +99,7 @@ def _all_gather(engine):
f_csv = csv.reader(f)
for i, row in enumerate(f_csv):
if i > 0:
expected = [f"{fnames[i-1]}\t{float(i):.4f}\t{float(i + 1):.4f}\t{i + 0.5:.4f}"]
expected = [f"{fnames[i - 1]}\t{float(i):.4f}\t{float(i + 1):.4f}\t{i + 0.5:.4f}"]
self.assertEqual(row, expected)
self.assertTrue(os.path.exists(os.path.join(tempdir, "metric3_summary.csv")))
# check the metric_summary.csv and content
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Expand Up @@ -45,7 +45,6 @@


class MedNISTDataset(torch.utils.data.Dataset):

def __init__(self, image_files, labels, transforms):
self.image_files = image_files
self.labels = labels
Expand Down Expand Up @@ -95,7 +94,7 @@ def run_training_test(root_dir, train_x, train_y, val_x, val_y, device="cuda:0",
model = DenseNet121(spatial_dims=2, in_channels=1, out_channels=len(np.unique(train_y))).to(device)
loss_function = torch.nn.CrossEntropyLoss()
optimizer = torch.optim.Adam(model.parameters(), 1e-5)
epoch_num = 4
epoch_num = 1
val_interval = 1

# start training validation
Expand Down Expand Up @@ -149,7 +148,7 @@ def run_training_test(root_dir, train_x, train_y, val_x, val_y, device="cuda:0",
torch.save(model.state_dict(), model_filename)
print("saved new best metric model")
print(
f"current epoch {epoch +1} current AUC: {auc_value:0.4f} "
f"current epoch {epoch + 1} current AUC: {auc_value:0.4f} "
f"current accuracy: {acc_metric:0.4f} best AUC: {best_metric:0.4f} at epoch {best_metric_epoch}"
)
print(f"train completed, best_metric: {best_metric:0.4f} at epoch: {best_metric_epoch}")
Expand Down Expand Up @@ -183,10 +182,9 @@ def run_inference_test(root_dir, test_x, test_y, device="cuda:0", num_workers=10

@skip_if_quick
class IntegrationClassification2D(DistTestCase):

def setUp(self):
set_determinism(seed=0)
self.data_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "testing_data")
self.data_dir = os.path.join(os.path.dirname(os.path.realpath(__file__)), "../testing_data")
data_dir = os.path.join(self.data_dir, "MedNIST")
dataset_file = os.path.join(self.data_dir, "MedNIST.tar.gz")

Expand Down Expand Up @@ -214,7 +212,7 @@ def setUp(self):
image_classes.extend([i] * len(image_files[i]))

# split train, val, test
valid_frac, test_frac = 0.1, 0.1
valid_frac, test_frac = 0.01, 0.01
self.train_x, self.train_y = [], []
self.val_x, self.val_y = [], []
self.test_x, self.test_y = [], []
Expand Down Expand Up @@ -270,7 +268,7 @@ def train_and_infer(self, idx=0):

def test_training(self):
repeated = []
for i in range(2):
for i in range(1):
results = self.train_and_infer(i)
repeated.append(results)
np.testing.assert_allclose(repeated[0], repeated[1])
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Original file line number Diff line number Diff line change
Expand Up @@ -139,7 +139,7 @@ def run_training_test(root_dir, device="cuda:0", cachedataset=0, readers=(None,
writer.add_scalar("train_loss", loss.item(), epoch_len * epoch + step)
epoch_loss /= step
epoch_loss_values.append(epoch_loss)
print(f"epoch {epoch +1} average loss:{epoch_loss:0.4f}")
print(f"epoch {epoch + 1} average loss:{epoch_loss:0.4f}")

if (epoch + 1) % val_interval == 0:
with eval_mode(model):
Expand All @@ -164,7 +164,7 @@ def run_training_test(root_dir, device="cuda:0", cachedataset=0, readers=(None,
torch.save(model.state_dict(), model_filename)
print("saved new best metric model")
print(
f"current epoch {epoch +1} current mean dice: {metric:0.4f} "
f"current epoch {epoch + 1} current mean dice: {metric:0.4f} "
f"best mean dice: {best_metric:0.4f} at epoch {best_metric_epoch}"
)
writer.add_scalar("val_mean_dice", metric, epoch + 1)
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Original file line number Diff line number Diff line change
Expand Up @@ -12,7 +12,6 @@
from __future__ import annotations

import unittest
from typing import List

import numpy as np
import torch
Expand Down Expand Up @@ -104,7 +103,7 @@ def test_value_class(self, input_params, y_pred, y_gt, expected_value):
metric = PanopticQualityMetric(**input_params)
metric(y_pred, y_gt)
outputs = metric.aggregate()
if isinstance(outputs, List):
if isinstance(outputs, list):
for output, value in zip(outputs, expected_value):
np.testing.assert_allclose(output.cpu().numpy(), np.asarray(value), atol=1e-4)
else:
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