Stabilize first-run cudagraph timing and colorize terminal output

- _cudagraph_plugin: warm up autotune/JIT explicitly before graph capture
  (internal 5-iter warmup is too short), tag fallback markers with the
  failing phase; first-run latency no longer jitters run-to-run.
- _device_guard_plugin (new): set GEMS_VENDOR via torch probe before
  importing flag_gems, avoiding its timeout-less nvidia-smi subprocess
  probe that can hang import in fork-broken environments.
- _pretty_report_plugin (new) + _term_style (new): fold inputs identical
  across all result rows into a legend line, color status/plugin
  tags/markers on the live terminal; run.log is ANSI-stripped and keeps
  upstream SUCCESS/column wording for grep compatibility.
- run_pytest.sh: make USE_FLAGTUNE overridable, group all knobs into a
  config section with Chinese comments, add start/end banners.
- README: document the warmup semantics, new plugins/env vars, and the
  A/B rule that both sides must use the same USE_FLAGTUNE.

_shape_inject_plugin.py

@@ -26,7 +26,9 @@ def _load_yaml(path: str) -> dict:
         with open(path, "r") as f:
             return _yaml.safe_load(f) or {}
     except Exception as exc:
-        print(f"[shape-inject-plugin] failed to load {path}: {exc}", file=sys.stderr)
+        from _term_style import tag
+        print(f"{tag('[shape-inject-plugin]')} failed to load {path}: {exc}",
+              file=sys.stderr)
         return {}
 
 
@@ -76,8 +78,9 @@ def _patch_init_user_config():
             cur_homogeneous = len(cur_arities) == 1
             yaml_homogeneous = len(yaml_arities) == 1
             if cur_homogeneous and yaml_homogeneous and cur_arities != yaml_arities:
+                from _term_style import tag
                 print(
-                    f"[shape-inject-plugin] skip override for op_name={self.op_name!r}: "
+                    f"{tag('[shape-inject-plugin]')} skip override for op_name={self.op_name!r}: "
                     f"subclass produced homogeneous arity {next(iter(cur_arities))}, "
                     f"yaml has homogeneous arity {next(iter(yaml_arities))} "
                     f"— subclass normalization preserved",
@@ -93,7 +96,8 @@ def _patch_init_user_config():
 
 
 def pytest_configure(config):
+    from _term_style import tag
     _patch_init_user_config()
-    print("[shape-inject-plugin] Benchmark.init_user_config patched: "
+    print(f"{tag('[shape-inject-plugin]')} Benchmark.init_user_config patched: "
           "yaml shapes now win over hardcoded subclass set_shapes()",
           file=sys.stderr, flush=True)