Add a supports_fp64 function.

[comfyanonymous]

No description provided.

[coderabbitai]

📝 Walkthrough

Walkthrough

A new supports_fp64() helper function was added to comfy/model_management.py to determine floating-point precision support across different device backends. The rope() function in comfy/ldm/flux/math.py was refactored to use this new helper instead of directly checking for specific device types (MPS, Intel XPU, DirectML). The helper returns False for unsupported backends and True otherwise, replacing the prior hardcoded device checks. The underlying RoPE computation logic and outputs remain unchanged.

🚥 Pre-merge checks | ✅ 1 | ❌ 2

❌ Failed checks (1 warning, 1 inconclusive)

Check name	Status	Explanation	Resolution
Docstring Coverage	⚠️ Warning	Docstring coverage is 0.00% which is insufficient. The required threshold is 80.00%.	Write docstrings for the functions missing them to satisfy the coverage threshold.
Description check	❓ Inconclusive	No description was provided by the author, making it impossible to assess relevance to the changeset.	Add a pull request description explaining the purpose of the supports_fp64 function and why it's needed for the RoPE computation changes.

✅ Passed checks (1 passed)

Check name	Status	Explanation
Title check	✅ Passed	The title accurately describes the main change: adding a new supports_fp64 function to the codebase.

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[coderabbitai]

Actionable comments posted: 1

🤖 Prompt for all review comments with AI agents

Verify each finding against the current code and only fix it if needed.

Inline comments:
In `@comfy/model_management.py`:
- Around line 1735-1748: supports_fp64 currently accepts device=None but never
resolves None to the active device, causing MPS to be misdetected; update
supports_fp64 to resolve a None device to the current/active device before
calling is_device_mps (e.g., obtain torch.cuda.current_device()/torch.device or
use the existing project helper that returns the active device), then run the
existing checks (is_device_mps, is_intel_xpu, is_directml_enabled, is_ixuca)
against that resolved device so MPS is detected correctly and FP64 support is
reported accurately.

🪄 Autofix (Beta)

Fix all unresolved CodeRabbit comments on this PR:

• Push a commit to this branch (recommended)
• Create a new PR with the fixes

---

ℹ️ Review info

⚙️ Run configuration

Configuration used: Path: .coderabbit.yaml

Review profile: CHILL

Plan: Pro

Run ID: 104a9aad-a218-4140-b887-3d8e550656aa

📥 Commits

Reviewing files that changed from the base of the PR and between a2840e7 and 4748d5d.

📒 Files selected for processing (2)

• comfy/ldm/flux/math.py
• comfy/model_management.py

[coderabbitai]

⚠️ Potential issue | 🟠 Major

device=None currently reports FP64 support incorrectly on MPS.

Line 1735 introduces device=None, but the function never resolves None to the active device. In MPS mode, supports_fp64() returns True, which can route FP64 ops to an unsupported backend.

Proposed fix

 def supports_fp64(device=None):
+    if device is None:
+        device = get_torch_device()
+
     if is_device_mps(device):
         return False
 
     if is_intel_xpu():
         return False

📝 Committable suggestion

‼️ IMPORTANT
Carefully review the code before committing. Ensure that it accurately replaces the highlighted code, contains no missing lines, and has no issues with indentation. Thoroughly test & benchmark the code to ensure it meets the requirements.

Suggested change

	def supports_fp64(device=None):
	if is_device_mps(device):
	return False
	if is_intel_xpu():
	return False
	if is_directml_enabled():
	return False
	if is_ixuca():
	return False
	return True
	def supports_fp64(device=None):
	if device is None:
	device = get_torch_device()
	if is_device_mps(device):
	return False
	if is_intel_xpu():
	return False
	if is_directml_enabled():
	return False
	if is_ixuca():
	return False
	return True

🤖 Prompt for AI Agents

Verify each finding against the current code and only fix it if needed.

In `@comfy/model_management.py` around lines 1735 - 1748, supports_fp64 currently
accepts device=None but never resolves None to the active device, causing MPS to
be misdetected; update supports_fp64 to resolve a None device to the
current/active device before calling is_device_mps (e.g., obtain
torch.cuda.current_device()/torch.device or use the existing project helper that
returns the active device), then run the existing checks (is_device_mps,
is_intel_xpu, is_directml_enabled, is_ixuca) against that resolved device so MPS
is detected correctly and FP64 support is reported accurately.