test(ui): keep VRAM renderer dependency-light

tests/test_app_vram.py

@@ -1,20 +1,13 @@
-"""Deterministic contracts for the Gradio accelerator-memory display."""
+"""Deterministic contracts for the accelerator-memory display."""
 
 from __future__ import annotations
 
-import subprocess
-import sys
-
-
-def test_vram_html_covers_cpu_single_and_multi_accelerator_topologies():
-    """Exercise app state away from Gradio's import-time worker sockets."""
-    script = r'''
 from types import SimpleNamespace
 
-import app
+from obliteratus.ui_vram import render_vram_html
 
 
-def memory(used, reserved, total, name):
+def _memory(used, reserved, total, name):
     return SimpleNamespace(
         used_gb=used,
         reserved_gb=reserved,
@@ -23,65 +16,66 @@ def memory(used, reserved, total, name):
     )
 
 
-# Zero accelerators preserves the CPU-only message.
-app.dev.is_gpu_available = lambda: False
-html = app._get_vram_html()
-assert "CPU ONLY — NO GPU DETECTED" in html
-assert "data-device-index" not in html
+def test_vram_html_covers_cpu_single_and_multi_accelerator_topologies():
+    device = SimpleNamespace(is_gpu_available=lambda: False)
+    html = render_vram_html(device)
+    assert "CPU ONLY — NO GPU DETECTED" in html
+    assert "data-device-index" not in html
 
-# A single non-CUDA accelerator preserves one unified-memory row.
-app.dev.is_gpu_available = lambda: True
-app.dev.is_cuda = lambda: False
-app.dev.get_memory_info = lambda _index=0: memory(4, 0, 16, "Apple M3 (MPS)")
-html = app._get_vram_html()
-assert html.count("data-device-index=") == 1
-assert 'data-device-index="single"' in html
-assert "Apple M3 (MPS)" in html
-assert "4.0 / 16.0 GB (25%)" in html
-assert "Automatic sharding" not in html
-
-# Homogeneous CUDA devices each receive an indexed row and query.
-memories = [
-    memory(4, 5, 80, "NVIDIA A100"),
-    memory(16, 20, 80, "NVIDIA A100"),
-    memory(72, 74, 80, "NVIDIA A100"),
-]
-queried = []
-app.dev.is_cuda = lambda: True
-app.dev.device_count = lambda: len(memories)
-
-def memory_info(index):
-    queried.append(index)
-    return memories[index]
-
-app.dev.get_memory_info = memory_info
-html = app._get_vram_html()
-assert queried == [0, 1, 2]
-assert html.count("data-device-index=") == 3
-assert "GPU 0 · NVIDIA A100" in html
-assert "GPU 1 · NVIDIA A100" in html
-assert "GPU 2 · NVIDIA A100" in html
-assert "Automatic sharding uses additional GPUs" in html
-
-# Heterogeneous device names stay aligned with their CUDA indices.
-memories = [
-    memory(2, 3, 24, "NVIDIA RTX 4090"),
-    memory(8, 9, 80, "NVIDIA A100"),
-]
-app.dev.device_count = lambda: len(memories)
-app.dev.get_memory_info = memories.__getitem__
-html = app._get_vram_html()
-assert "GPU 0 · NVIDIA RTX 4090" in html
-assert "GPU 1 · NVIDIA A100" in html
-assert html.index("GPU 0 · NVIDIA RTX 4090") < html.index("GPU 1 · NVIDIA A100")
-'''
-
-    result = subprocess.run(
-        [sys.executable, "-c", script],
-        capture_output=True,
-        text=True,
-        timeout=120,
-        check=False,
+    device = SimpleNamespace(
+        is_gpu_available=lambda: True,
+        is_cuda=lambda: False,
+        get_memory_info=lambda _index=0: _memory(4, 0, 16, "Apple M3 (MPS)"),
     )
+    html = render_vram_html(device)
+    assert html.count("data-device-index=") == 1
+    assert 'data-device-index="single"' in html
+    assert "Apple M3 (MPS)" in html
+    assert "4.0 / 16.0 GB (25%)" in html
+    assert "Automatic sharding" not in html
 
-    assert result.returncode == 0, result.stdout + result.stderr
+    memories = [
+        _memory(4, 5, 80, "NVIDIA A100"),
+        _memory(16, 20, 80, "NVIDIA A100"),
+        _memory(72, 74, 80, "NVIDIA A100"),
+    ]
+    queried = []
+
+    def memory_info(index):
+        queried.append(index)
+        return memories[index]
+
+    device = SimpleNamespace(
+        is_gpu_available=lambda: True,
+        is_cuda=lambda: True,
+        device_count=lambda: len(memories),
+        get_memory_info=memory_info,
+    )
+    html = render_vram_html(device)
+    assert queried == [0, 1, 2]
+    assert html.count("data-device-index=") == 3
+    assert "GPU 0 · NVIDIA A100" in html
+    assert "GPU 1 · NVIDIA A100" in html
+    assert "GPU 2 · NVIDIA A100" in html
+    assert "Automatic sharding uses additional GPUs" in html
+
+    memories = [
+        _memory(2, 3, 24, "NVIDIA RTX 4090"),
+        _memory(8, 9, 80, "NVIDIA A100"),
+    ]
+    device.device_count = lambda: len(memories)
+    device.get_memory_info = memories.__getitem__
+    html = render_vram_html(device)
+    assert "GPU 0 · NVIDIA RTX 4090" in html
+    assert "GPU 1 · NVIDIA A100" in html
+    assert html.index("GPU 0 · NVIDIA RTX 4090") < html.index("GPU 1 · NVIDIA A100")
+
+
+def test_vram_html_handles_memory_errors():
+    device = SimpleNamespace(
+        is_gpu_available=lambda: True,
+        is_cuda=lambda: True,
+        device_count=lambda: 1,
+        get_memory_info=lambda _index: (_ for _ in ()).throw(RuntimeError("unavailable")),
+    )
+    assert "Memory: unavailable" in render_vram_html(device)