skip mnist download if not linux for speed

.github/workflows/test_pr.yml

@@ -55,12 +55,6 @@ jobs:
         run: |
           python -m pip install -U pip
           pip install -r prereq.txt
-      - name: Pre-test setup
-        run: |
-          curl -o ./train-images-idx3-ubyte.gz https://ossci-datasets.s3.amazonaws.com/mnist/train-images-idx3-ubyte.gz
-          curl -o ./train-labels-idx1-ubyte.gz https://ossci-datasets.s3.amazonaws.com/mnist/train-labels-idx1-ubyte.gz
-          curl -o ./t10k-images-idx3-ubyte.gz https://ossci-datasets.s3.amazonaws.com/mnist/t10k-images-idx3-ubyte.gz
-          curl -o ./t10k-labels-idx1-ubyte.gz https://ossci-datasets.s3.amazonaws.com/mnist/t10k-labels-idx1-ubyte.gz
       - name: Test Core
         run: |
           pip install .[testing]

tests/metrics/test_detection.py

@@ -1,4 +1,5 @@
 # stdlib
+import sys
 from typing import Type
 
 # third party
@@ -154,13 +155,11 @@ def test_detect_synth_timeseries(test_plugin: Plugin, evaluator_t: Type) -> None
     assert evaluator.direction() == "minimize"
 
 
+@pytest.mark.skipif(sys.platform == "linux", reason="Linux only for faster results")
 @pytest.mark.slow_1
 @pytest.mark.slow
 def test_image_support_detection() -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     X1 = ImageDataLoader(dataset).sample(100)
     X2 = ImageDataLoader(dataset).sample(100)

tests/metrics/test_performance.py

@@ -477,13 +477,11 @@ def test_evaluate_performance_time_series_survival(
     assert def_score == good_score["syn_id.c_index"] - good_score["syn_id.brier_score"]
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 @pytest.mark.slow_1
 @pytest.mark.slow
 def test_image_support_perf() -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     X1 = ImageDataLoader(dataset).sample(100)
     X2 = ImageDataLoader(dataset).sample(100)

tests/metrics/test_privacy.py

@@ -1,4 +1,5 @@
 # stdlib
+import sys
 from typing import Type
 
 # third party
@@ -80,11 +81,9 @@ def test_evaluator(evaluator_t: Type, test_plugin: Plugin) -> None:
     assert isinstance(def_score, (float, int))
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_image_support() -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     X1 = ImageDataLoader(dataset).sample(100)
     X2 = ImageDataLoader(dataset).sample(100)

tests/metrics/test_sanity.py

@@ -1,4 +1,5 @@
 # stdlib
+import sys
 from typing import Callable, Tuple
 
 # third party
@@ -194,11 +195,9 @@ def test_evaluate_distant_values(test_plugin: Plugin) -> None:
     assert isinstance(def_score, float)
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_image_support() -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     X1 = ImageDataLoader(dataset).sample(100)
     X2 = ImageDataLoader(dataset).sample(100)

tests/metrics/test_statistical.py

@@ -1,4 +1,5 @@
 # stdlib
+import sys
 from typing import Any, Tuple, Type
 
 # third party
@@ -283,11 +284,9 @@ def test_evaluate_survival_km_distance(test_plugin: Plugin) -> None:
     assert SurvivalKMDistance.direction() == "minimize"
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_image_support() -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     X1 = ImageDataLoader(dataset).sample(100)
     X2 = ImageDataLoader(dataset).sample(100)

tests/plugins/core/test_dataloader.py

@@ -1,4 +1,5 @@
 # stdlib
+import sys
 from datetime import datetime
 from typing import Any
 
@@ -635,13 +636,11 @@ def test_time_series_survival_pack_unpack_padding(as_numpy: bool) -> None:
         assert len(unp_observation_times[idx]) == max_window_len
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 @pytest.mark.parametrize("height", [55, 64])
 @pytest.mark.parametrize("width", [32, 22])
 def test_image_dataloader_sanity(height: int, width: int) -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     loader = ImageDataLoader(
         data=dataset,
@@ -680,11 +679,9 @@ def test_image_dataloader_sanity(height: int, width: int) -> None:
     assert loader.unpack().labels().shape == (len(loader),)
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_image_dataloader_create_from_info() -> None:
-    try:
-        dataset = datasets.MNIST(".", download=False)
-    except RuntimeError:
-        dataset = datasets.MNIST(".", download=True)
+    dataset = datasets.MNIST(".", download=True)
 
     loader = ImageDataLoader(
         data=dataset,

tests/plugins/images/test_image_adsgan.py

@@ -1,3 +1,6 @@
+# stdlib
+import sys
+
 # third party
 import numpy as np
 import pytest
@@ -11,11 +14,6 @@
 
 plugin_name = "image_adsgan"
 
-try:
-    dataset = datasets.MNIST(".", download=False)
-except RuntimeError:
-    dataset = datasets.MNIST(".", download=True)
-
 
 @pytest.mark.parametrize("test_plugin", generate_fixtures(plugin_name, plugin))
 def test_plugin_sanity(test_plugin: Plugin) -> None:
@@ -37,15 +35,19 @@ def test_plugin_hyperparams(test_plugin: Plugin) -> None:
     assert len(test_plugin.hyperparameter_space()) == 6
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_plugin_fit() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=5)
 
     X = ImageDataLoader(dataset).sample(100)
 
     test_plugin.fit(X)
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_plugin_generate() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=10, n_units_latent=13)
 
     X = ImageDataLoader(dataset).sample(100)
@@ -60,9 +62,11 @@ def test_plugin_generate() -> None:
     assert len(X_gen) == 50
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 @pytest.mark.slow_2
 @pytest.mark.slow
 def test_plugin_generate_with_conditional() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=10, n_units_latent=13)
 
     X = ImageDataLoader(dataset).sample(100)
@@ -75,9 +79,11 @@ def test_plugin_generate_with_conditional() -> None:
     assert len(X_gen) == 50
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 @pytest.mark.slow_2
 @pytest.mark.slow
 def test_plugin_generate_with_stop_conditional() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=10, n_units_latent=13, n_iter_print=2)
 
     X = ImageDataLoader(dataset).sample(100)

tests/plugins/images/test_image_cgan.py

@@ -1,3 +1,6 @@
+# stdlib
+import sys
+
 # third party
 import numpy as np
 import pytest
@@ -11,11 +14,6 @@
 
 plugin_name = "image_cgan"
 
-try:
-    dataset = datasets.MNIST(".", download=False)
-except RuntimeError:
-    dataset = datasets.MNIST(".", download=True)
-
 
 @pytest.mark.parametrize("test_plugin", generate_fixtures(plugin_name, plugin))
 def test_plugin_sanity(test_plugin: Plugin) -> None:
@@ -37,18 +35,22 @@ def test_plugin_hyperparams(test_plugin: Plugin) -> None:
     assert len(test_plugin.hyperparameter_space()) == 6
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 @pytest.mark.parametrize("height", [32, 64, 128])
 @pytest.mark.slow_2
 @pytest.mark.slow
 def test_plugin_fit(height: int) -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=5)
 
     X = ImageDataLoader(dataset, height=height).sample(100)
 
     test_plugin.fit(X)
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_plugin_generate() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=10, n_units_latent=13)
 
     X = ImageDataLoader(dataset).sample(100)
@@ -63,7 +65,9 @@ def test_plugin_generate() -> None:
     assert len(X_gen) == 50
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 def test_plugin_generate_with_conditional() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=10, n_units_latent=13)
 
     X = ImageDataLoader(dataset).sample(100)
@@ -76,9 +80,11 @@ def test_plugin_generate_with_conditional() -> None:
     assert len(X_gen) == 50
 
 
+@pytest.mark.skipif(sys.platform != "linux", reason="Linux only for faster results")
 @pytest.mark.slow_2
 @pytest.mark.slow
 def test_plugin_generate_with_stop_conditional() -> None:
+    dataset = datasets.MNIST(".", download=True)
     test_plugin = plugin(n_iter=10, n_units_latent=13, n_iter_print=2)
 
     X = ImageDataLoader(dataset).sample(100)