add GC stress scripts

tests/python/gc_stress/many_large_many_rows_recordings.py

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+"""
+Stress test for cross-recording garbage collection.
+
+Logs many large recordings that contain a lot of large rows.
+
+Usage:
+- Start a Rerun Viewer in release mode with 2GiB of memory limit:
+  `cargo r -p rerun-cli --release --no-default-features --features native_viewer -- --memory-limit 2GiB`
+- Open the memory panel to see what's going on.
+- Run this script.
+- You should see recordings coming in and going out in a ringbuffer-like rolling fashion.
+"""
+from __future__ import annotations
+
+import rerun as rr
+from numpy.random import default_rng
+
+rng = default_rng(12345)
+
+for i in range(0, 20000000):
+    rr.init("rerun_example_recording_gc", recording_id=f"image-rec-{i}", spawn=True)
+    for j in range(0, 10000):
+        positions = rng.uniform(-5, 5, size=[10000000, 3])
+        colors = rng.uniform(0, 255, size=[10000000, 3])
+        radii = rng.uniform(0, 1, size=[10000000])
+        rr.log("points", rr.Points3D(positions, colors=colors, radii=radii))

tests/python/gc_stress/many_large_single_row_recordings.py

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+"""
+Stress test for cross-recording garbage collection.
+
+Logs many large recordings that contain a single large row.
+
+Usage:
+- Start a Rerun Viewer in release mode with 2GiB of memory limit:
+  `cargo r -p rerun-cli --release --no-default-features --features native_viewer -- --memory-limit 2GiB`
+- Open the memory panel to see what's going on.
+- Run this script.
+- You should see recordings coming in and going out in a ringbuffer-like rolling fashion.
+"""
+from __future__ import annotations
+
+import time
+
+import rerun as rr
+from numpy.random import default_rng
+
+rng = default_rng(12345)
+
+for i in range(0, 20000000):
+    rr.init("rerun_example_recording_gc", recording_id=f"recording-gc-rec-{i}", spawn=True)
+
+    positions = rng.uniform(-5, 5, size=[10000000, 3])
+    colors = rng.uniform(0, 255, size=[10000000, 3])
+    radii = rng.uniform(0, 1, size=[10000000])
+    rr.log("points", rr.Points3D(positions, colors=colors, radii=radii))
+
+    # Sleep because large rows will absolutely destroy the viewer.
+    # TODO(#4183): Investigate this.
+    time.sleep(1)

tests/python/gc_stress/many_medium_sized_many_rows_recordings.py

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+"""
+Stress test for cross-recording garbage collection.
+
+Logs many medium-sized recordings that contain a lot of small-ish rows.
+
+Usage:
+- Start a Rerun Viewer in release mode with 500MiB of memory limit:
+  `cargo r -p rerun-cli --release --no-default-features --features native_viewer -- --memory-limit 500MiB`
+- Open the memory panel to see what's going on.
+- Run this script.
+- You should see recordings coming in and going out in a ringbuffer-like rolling fashion.
+"""
+from __future__ import annotations
+
+import rerun as rr
+from numpy.random import default_rng
+
+rng = default_rng(12345)
+
+for i in range(0, 20000000):
+    rr.init("rerun_example_recording_gc", recording_id=f"image-rec-{i}", spawn=True)
+    for j in range(0, 10000):
+        rr.set_time_sequence("frame", j)
+        positions = rng.uniform(-5, 5, size=[1000, 3])
+        colors = rng.uniform(0, 255, size=[1000, 3])
+        radii = rng.uniform(0, 1, size=[1000])
+        rr.log("points", rr.Points3D(positions, colors=colors, radii=radii))

tests/python/gc_stress/many_medium_sized_single_row_recordings.py

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+"""
+Stress test for cross-recording garbage collection.
+
+Logs many medium-sized recordings that contain a single medium-sized row.
+
+Usage:
+- Start a Rerun Viewer in release mode with 200MiB of memory limit:
+  `cargo r -p rerun-cli --release --no-default-features --features native_viewer -- --memory-limit 200MiB`
+- Open the memory panel to see what's going on.
+- Run this script.
+- You should see recordings coming in and going out in a ringbuffer-like rolling fashion.
+"""
+from __future__ import annotations
+
+import time
+
+import rerun as rr
+from numpy.random import default_rng
+
+rng = default_rng(12345)
+
+for i in range(0, 20000000):
+    rr.init("rerun_example_recording_gc", recording_id=f"recording-gc-rec-{i}", spawn=True)
+
+    positions = rng.uniform(-5, 5, size=[10000, 3])
+    colors = rng.uniform(0, 255, size=[10000, 3])
+    radii = rng.uniform(0, 1, size=[10000])
+    rr.log("points", rr.Points3D(positions, colors=colors, radii=radii))
+
+    # Sleep so we don't run out of TCP sockets.
+    # Timings might need to be adjusted depending on your hardware.
+    time.sleep(0.05)