Reduce install time and fix registry metadata
- Auto-install now only installs the matching TensorRT wheels instead of the multi-GB cuda-toolkit package from PyPI. - Use a single pip install -r call per requirements file for faster dependency resolution and better cache reuse. - Add install-success/failure markers to avoid repeating the install on every ComfyUI startup. - Fix pyproject.toml Repository and PublisherId to point to huchukato/ComfyUI-RIFE-TensorRT-Auto. Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
This commit is contained in:
huchukato
+90
-64
@@ -80,42 +80,58 @@ def detect_cloud_environment():
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# Auto-detect CUDA and install appropriate TensorRT packages
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def _auto_install_tensorrt():
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"""Auto-detect CUDA version and install appropriate TensorRT packages if needed"""
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# Check if auto-install is disabled
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"""Auto-detect CUDA version and install the matching TensorRT wheels.
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The NVIDIA CUDA Toolkit must already be installed on the system.
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This function installs only the TensorRT packages via pip.
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A marker file prevents repeated install attempts on every ComfyUI startup.
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"""
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disable_auto_install = os.environ.get("DISABLE_TENSORRT_AUTO_INSTALL", "false").lower() == "true"
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if disable_auto_install:
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print("[ComfyUI-RIFE-TensorRT] Auto-installation disabled via DISABLE_TENSORRT_AUTO_INSTALL")
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return True
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node_dir = Path(__file__).resolve().parent
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installed_marker = node_dir / ".tensorrt_auto_installed"
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failed_marker = node_dir / ".tensorrt_auto_install_failed"
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# Skip if we already installed successfully in a previous run.
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if installed_marker.exists():
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return True
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# Avoid retrying too often after a failure (do not block every startup).
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if failed_marker.exists():
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try:
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last_fail = failed_marker.stat().st_mtime
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if time.time() - last_fail < 3600:
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print("[ComfyUI-RIFE-TensorRT] Recent failed install attempt; skipping auto-install.")
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return False
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except Exception:
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pass
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try:
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# Check if TensorRT is already installed - with retry mechanism
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max_retries = 3
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for attempt in range(max_retries):
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try:
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import tensorrt
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print(f"✅ TensorRT already installed (version: {tensorrt.__version__})")
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return True
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except ImportError:
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if attempt < max_retries - 1:
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print(f"🔍 TensorRT not found (attempt {attempt + 1}/{max_retries}), waiting 2 seconds...")
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time.sleep(2) # Wait for potential concurrent installation
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else:
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print("🔍 TensorRT not found after retries, detecting CUDA version...")
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# Check if TensorRT is already installed.
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try:
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import tensorrt
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print(f"[ComfyUI-RIFE-TensorRT] TensorRT already installed (version: {tensorrt.__version__})")
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installed_marker.touch()
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return True
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except ImportError:
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print("[ComfyUI-RIFE-TensorRT] TensorRT not found, detecting CUDA version...")
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# Detect CUDA version
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cuda_version = None
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# Try PyTorch CUDA version first (most reliable on cloud platforms)
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try:
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import torch
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if hasattr(torch, 'version') and hasattr(torch.version, 'cuda'):
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pytorch_cuda = torch.version.cuda
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if pytorch_cuda:
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cuda_version = pytorch_cuda
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print(f"✅ Detected CUDA version from PyTorch: {cuda_version}")
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print(f"[ComfyUI-RIFE-TensorRT] Detected CUDA version from PyTorch: {cuda_version}")
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except Exception as e:
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print(f"⚠️ Could not detect CUDA from PyTorch: {e}")
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print(f"[ComfyUI-RIFE-TensorRT] Could not detect CUDA from PyTorch: {e}")
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# Try nvcc command as fallback
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if not cuda_version:
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try:
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@@ -124,81 +140,91 @@ def _auto_install_tensorrt():
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match = re.search(r"release (\d+\.\d+)", result.stdout)
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if match:
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cuda_version = match.group(1)
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print(f"✅ Detected CUDA version from nvcc: {cuda_version}")
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except:
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print(f"[ComfyUI-RIFE-TensorRT] Detected CUDA version from nvcc: {cuda_version}")
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except Exception:
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pass
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# Try CUDA_PATH
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if not cuda_version and os.environ.get("CUDA_PATH"):
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nvcc_path = os.path.join(os.environ["CUDA_PATH"], "bin", "nvcc")
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if os.path.exists(nvcc_path):
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try:
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result = subprocess.run(f"{nvcc_path} --version", shell=True, capture_output=True, text=True)
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result = subprocess.run(f'"{nvcc_path}" --version', shell=True, capture_output=True, text=True)
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if result.returncode == 0:
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match = re.search(r"release (\d+\.\d+)", result.stdout)
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if match:
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cuda_version = match.group(1)
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print(f"✅ Detected CUDA via CUDA_PATH: {cuda_version}")
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except:
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print(f"[ComfyUI-RIFE-TensorRT] Detected CUDA via CUDA_PATH: {cuda_version}")
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except Exception:
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pass
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# Try CUDA_HOME
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if not cuda_version and os.environ.get("CUDA_HOME"):
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nvcc_path = os.path.join(os.environ["CUDA_HOME"], "bin", "nvcc")
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if os.path.exists(nvcc_path):
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try:
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result = subprocess.run(f"{nvcc_path} --version", shell=True, capture_output=True, text=True)
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result = subprocess.run(f'"{nvcc_path}" --version', shell=True, capture_output=True, text=True)
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if result.returncode == 0:
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match = re.search(r"release (\d+\.\d+)", result.stdout)
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if match:
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cuda_version = match.group(1)
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print(f"✅ Detected CUDA via CUDA_HOME: {cuda_version}")
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except:
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print(f"[ComfyUI-RIFE-TensorRT] Detected CUDA via CUDA_HOME: {cuda_version}")
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except Exception:
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pass
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if not cuda_version:
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print("⚠️ Could not detect CUDA version automatically")
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print("Please run 'python install.py' manually to install TensorRT")
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print("[ComfyUI-RIFE-TensorRT] WARNING: Could not detect CUDA version automatically.")
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print("The NVIDIA CUDA Toolkit must be installed before TensorRT can work.")
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print("Please run 'python install.py' manually after installing CUDA.")
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failed_marker.touch()
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return False
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# Install appropriate TensorRT packages
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major_version = int(cuda_version.split('.')[0])
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if major_version == 13:
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print("🚀 Installing CUDA 13 TensorRT packages (RTX 50 series)")
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packages = [
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"tensorrt_cu13==10.15.1.29",
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"tensorrt_cu13_bindings==10.15.1.29",
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"tensorrt_cu13_libs==10.15.1.29",
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"cuda-toolkit>=13.0.0,<13.1.0"
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]
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print("[ComfyUI-RIFE-TensorRT] Installing CUDA 13 TensorRT packages (RTX 50 series)")
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req_file = "requirements_cu13.txt"
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elif major_version == 12:
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print("🔧 Installing CUDA 12 TensorRT packages (RTX 30/40 series)")
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packages = [
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"tensorrt-cu12==10.13.3.9",
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"tensorrt-cu12-libs==10.13.3.9",
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"tensorrt-cu12-bindings==10.13.3.9",
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"cuda-toolkit>=12.8.0,<13.0.0"
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]
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print("[ComfyUI-RIFE-TensorRT] Installing CUDA 12 TensorRT packages (RTX 30/40 series)")
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req_file = "requirements_cu12.txt"
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else:
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print(f"❌ Unsupported CUDA version: {cuda_version}")
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print(f"[ComfyUI-RIFE-TensorRT] Unsupported CUDA version: {cuda_version}")
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failed_marker.touch()
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return False
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# Install packages
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for package in packages:
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print(f"Installing {package}...")
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result = subprocess.run([sys.executable, "-m", "pip", "install", package], capture_output=True)
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req_path = node_dir / req_file
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if not req_path.exists():
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print(f"[ComfyUI-RIFE-TensorRT] Missing requirements file: {req_path}")
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failed_marker.touch()
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return False
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# Install base dependencies first, then the CUDA-specific TensorRT wheels.
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for req_name in ["requirements.txt", req_file]:
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req_file_path = node_dir / req_name
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if not req_file_path.exists():
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continue
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print(f"[ComfyUI-RIFE-TensorRT] Installing from {req_name}...")
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result = subprocess.run(
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[sys.executable, "-m", "pip", "install", "--prefer-binary", "-r", str(req_file_path)],
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capture_output=True
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)
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if result.returncode != 0:
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print(f"❌ Failed to install {package}")
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print(f"Error: {result.stderr.decode()}")
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print(f"[ComfyUI-RIFE-TensorRT] Failed to install {req_name}")
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print(result.stderr.decode(errors="replace"))
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failed_marker.touch()
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return False
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print("✅ TensorRT installation completed successfully!")
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installed_marker.touch()
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print("[ComfyUI-RIFE-TensorRT] TensorRT installation completed successfully!")
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return True
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except Exception as e:
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print(f"❌ Auto-installation failed: {e}")
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print(f"[ComfyUI-RIFE-TensorRT] Auto-installation failed: {e}")
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print("Please run 'python install.py' manually to install TensorRT")
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try:
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failed_marker.touch()
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except Exception:
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pass
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return False
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# Run auto-install on module import
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+22
-18
@@ -1,31 +1,33 @@
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@echo off
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REM Auto-install script for ComfyUI RIFE TensorRT (Windows)
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REM Detects CUDA version and installs appropriate requirements
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REM Auto-install script for ComfyUI RIFE TensorRT Auto (Windows)
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REM Detects CUDA version and installs only the matching TensorRT wheels.
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REM The NVIDIA CUDA Toolkit must already be installed on the system.
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setlocal EnableDelayedExpansion
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echo 🔍 Detecting CUDA version...
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echo Detecting CUDA version...
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REM Try to detect CUDA version
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set CUDA_VERSION=
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where nvcc >nul 2>nul
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if %ERRORLEVEL% EQU 0 (
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for /f "tokens=6 delims=, " %%i in ('nvcc --version ^| findstr "release"') do set CUDA_VERSION=%%i
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echo ✅ Found CUDA version: %CUDA_VERSION%
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echo Found CUDA version: %CUDA_VERSION%
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) else if defined CUDA_PATH (
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if exist "%CUDA_PATH%\bin\nvcc.exe" (
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for /f "tokens=6 delims=, " %%i in ('"%CUDA_PATH%\bin\nvcc.exe" --version ^| findstr "release"') do set CUDA_VERSION=%%i
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echo ✅ Found CUDA version via CUDA_PATH: %CUDA_VERSION%
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echo Found CUDA version via CUDA_PATH: %CUDA_VERSION%
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)
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) else if defined CUDA_HOME (
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if exist "%CUDA_HOME%\bin\nvcc.exe" (
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for /f "tokens=6 delims=, " %%i in ('"%CUDA_HOME%\bin\nvcc.exe" --version ^| findstr "release"') do set CUDA_VERSION=%%i
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echo ✅ Found CUDA version via CUDA_HOME: %CUDA_VERSION%
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echo Found CUDA version via CUDA_HOME: %CUDA_VERSION%
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)
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)
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if "%CUDA_VERSION%"=="" (
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echo ⚠️ Could not detect CUDA version automatically
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echo Please ensure CUDA is installed and nvcc is in your PATH
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echo Or set CUDA_PATH or CUDA_HOME environment variables
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echo Could not detect CUDA version automatically.
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echo Please ensure the NVIDIA CUDA Toolkit is installed and nvcc is in your PATH,
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echo or set CUDA_PATH / CUDA_HOME.
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pause
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exit /b 1
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)
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@@ -33,27 +35,29 @@ if "%CUDA_VERSION%"=="" (
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REM Extract major version
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for /f "tokens=1 delims=." %%i in ("%CUDA_VERSION%") do set CUDA_MAJOR=%%i
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echo 📦 Installing requirements for CUDA %CUDA_MAJOR%...
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echo Installing requirements for CUDA %CUDA_MAJOR%...
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REM Install appropriate requirements based on CUDA version
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if "%CUDA_MAJOR%"=="13" (
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echo 🚀 Using CUDA 13 requirements ^(RTX 50 series^)
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pip install -r requirements.txt
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echo Using CUDA 13 TensorRT packages ^(RTX 50 series^)
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python -m pip install --prefer-binary -r requirements.txt
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python -m pip install --prefer-binary -r requirements_cu13.txt
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) else if "%CUDA_MAJOR%"=="12" (
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echo 🔧 Using CUDA 12 requirements ^(RTX 30/40 series^)
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pip install -r requirements_cu12.txt
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echo Using CUDA 12 TensorRT packages ^(RTX 30/40 series^)
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python -m pip install --prefer-binary -r requirements.txt
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python -m pip install --prefer-binary -r requirements_cu12.txt
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) else (
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echo ❌ Unsupported CUDA version: %CUDA_VERSION%
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echo Unsupported CUDA version: %CUDA_VERSION%
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echo Supported versions: CUDA 12.x, CUDA 13.x
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pause
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exit /b 1
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)
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if %ERRORLEVEL% EQU 0 (
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echo ✅ Installation completed successfully!
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echo 🎯 You can now use the ComfyUI RIFE TensorRT node
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echo Installation completed successfully!
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echo You can now use the ComfyUI RIFE TensorRT Auto node.
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) else (
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echo ❌ Installation failed!
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echo Installation failed!
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pause
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exit /b 1
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)
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+57
-38
@@ -1,102 +1,121 @@
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#!/usr/bin/env python3
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"""
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Auto-install script for ComfyUI RIFE TensorRT
|
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Detects CUDA version and installs appropriate requirements
|
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Auto-install script for ComfyUI RIFE TensorRT Auto.
|
||||
Detects the local CUDA version and installs only the matching TensorRT wheels.
|
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The NVIDIA CUDA Toolkit must already be installed on the system.
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"""
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import subprocess
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import sys
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import os
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import re
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from pathlib import Path
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SCRIPT_DIR = Path(__file__).resolve().parent
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def run_command(cmd):
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"""Run command and return output"""
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"""Run a shell command and return stdout + return code."""
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try:
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result = subprocess.run(cmd, shell=True, capture_output=True, text=True)
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return result.stdout.strip(), result.returncode
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except Exception as e:
|
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return "", 1
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|
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|
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def detect_cuda_version():
|
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"""Detect CUDA version"""
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print("🔍 Detecting CUDA version...")
|
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|
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"""Detect CUDA version from nvcc, CUDA_PATH or CUDA_HOME."""
|
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print("Detecting CUDA version...")
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|
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# Try nvcc command
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stdout, returncode = run_command("nvcc --version")
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if returncode == 0:
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match = re.search(r"release (\d+\.\d+)", stdout)
|
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if match:
|
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version = match.group(1)
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print(f"✅ Found CUDA version: {version}")
|
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print(f"Found CUDA version: {version}")
|
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return version
|
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|
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|
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# Try CUDA_PATH
|
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cuda_path = os.environ.get("CUDA_PATH")
|
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if cuda_path:
|
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nvcc_path = os.path.join(cuda_path, "bin", "nvcc")
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if os.path.exists(nvcc_path):
|
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stdout, returncode = run_command(f"{nvcc_path} --version")
|
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stdout, returncode = run_command(f'"{nvcc_path}" --version')
|
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if returncode == 0:
|
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match = re.search(r"release (\d+\.\d+)", stdout)
|
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if match:
|
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version = match.group(1)
|
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print(f"✅ Found CUDA version via CUDA_PATH: {version}")
|
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print(f"Found CUDA version via CUDA_PATH: {version}")
|
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return version
|
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|
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|
||||
# Try CUDA_HOME
|
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cuda_home = os.environ.get("CUDA_HOME")
|
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if cuda_home:
|
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nvcc_path = os.path.join(cuda_home, "bin", "nvcc")
|
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if os.path.exists(nvcc_path):
|
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stdout, returncode = run_command(f"{nvcc_path} --version")
|
||||
stdout, returncode = run_command(f'"{nvcc_path}" --version')
|
||||
if returncode == 0:
|
||||
match = re.search(r"release (\d+\.\d+)", stdout)
|
||||
if match:
|
||||
version = match.group(1)
|
||||
print(f"✅ Found CUDA version via CUDA_HOME: {version}")
|
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print(f"Found CUDA version via CUDA_HOME: {version}")
|
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return version
|
||||
|
||||
print("⚠️ Could not detect CUDA version automatically")
|
||||
print("Please ensure CUDA is installed and nvcc is in your PATH")
|
||||
print("Or set CUDA_PATH or CUDA_HOME environment variables")
|
||||
|
||||
print("Could not detect CUDA version automatically.")
|
||||
print("Please ensure the NVIDIA CUDA Toolkit is installed and nvcc is in your PATH,")
|
||||
print("or set CUDA_PATH / CUDA_HOME.")
|
||||
return None
|
||||
|
||||
|
||||
def install_requirements(cuda_version):
|
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"""Install appropriate requirements based on CUDA version"""
|
||||
"""Install the correct TensorRT packages for the detected CUDA version."""
|
||||
major_version = int(cuda_version.split('.')[0])
|
||||
|
||||
print(f"📦 Installing requirements for CUDA {major_version}...")
|
||||
|
||||
print(f"Installing requirements for CUDA {major_version}...")
|
||||
|
||||
if major_version == 13:
|
||||
print("🚀 Using CUDA 13 requirements (RTX 50 series)")
|
||||
requirements_file = "requirements.txt"
|
||||
print("Using CUDA 13 TensorRT packages (RTX 50 series)")
|
||||
req_file = "requirements_cu13.txt"
|
||||
elif major_version == 12:
|
||||
print("🔧 Using CUDA 12 requirements (RTX 30/40 series)")
|
||||
requirements_file = "requirements_cu12.txt"
|
||||
print("Using CUDA 12 TensorRT packages (RTX 30/40 series)")
|
||||
req_file = "requirements_cu12.txt"
|
||||
else:
|
||||
print(f"❌ Unsupported CUDA version: {cuda_version}")
|
||||
print(f"Unsupported CUDA version: {cuda_version}")
|
||||
print("Supported versions: CUDA 12.x, CUDA 13.x")
|
||||
return False
|
||||
|
||||
# Install requirements
|
||||
returncode = subprocess.run([sys.executable, "-m", "pip", "install", "-r", requirements_file]).returncode
|
||||
|
||||
if returncode == 0:
|
||||
print("✅ Installation completed successfully!")
|
||||
print("🎯 You can now use the ComfyUI RIFE TensorRT node")
|
||||
return True
|
||||
else:
|
||||
print("❌ Installation failed!")
|
||||
|
||||
req_path = SCRIPT_DIR / req_file
|
||||
if not req_path.exists():
|
||||
print(f"Missing requirements file: {req_path}")
|
||||
return False
|
||||
|
||||
# Install base dependencies first, then the CUDA-specific TensorRT wheels.
|
||||
# Using a single pip call per file lets pip resolve and cache dependencies efficiently.
|
||||
for req_name in ["requirements.txt", req_file]:
|
||||
req_file_path = SCRIPT_DIR / req_name
|
||||
if not req_file_path.exists():
|
||||
continue
|
||||
print(f"Installing from {req_name}...")
|
||||
result = subprocess.run(
|
||||
[sys.executable, "-m", "pip", "install", "--prefer-binary", "-r", str(req_file_path)]
|
||||
)
|
||||
if result.returncode != 0:
|
||||
print(f"Failed to install {req_name}")
|
||||
return False
|
||||
|
||||
print("Installation completed successfully!")
|
||||
print("You can now use the ComfyUI RIFE TensorRT Auto node.")
|
||||
return True
|
||||
|
||||
|
||||
def main():
|
||||
"""Main installation function"""
|
||||
cuda_version = detect_cuda_version()
|
||||
if not cuda_version:
|
||||
sys.exit(1)
|
||||
|
||||
|
||||
success = install_requirements(cuda_version)
|
||||
sys.exit(0 if success else 1)
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
main()
|
||||
|
||||
+23
-20
@@ -1,9 +1,9 @@
|
||||
#!/bin/bash
|
||||
|
||||
# FALLBACK install script for ComfyUI RIFE TensorRT
|
||||
#
|
||||
# FALLBACK install script for ComfyUI RIFE TensorRT Auto (Linux/macOS)
|
||||
#
|
||||
# NOTE: This is a BACKUP script - auto-installation is recommended!
|
||||
#
|
||||
#
|
||||
# PRIMARY METHOD (Recommended):
|
||||
# 1. pip install -r requirements.txt
|
||||
# 2. Restart ComfyUI
|
||||
@@ -11,9 +11,12 @@
|
||||
#
|
||||
# Use this script ONLY if auto-installation fails!
|
||||
#
|
||||
# The NVIDIA CUDA Toolkit must already be installed on the system.
|
||||
# This script installs only the matching TensorRT wheels via pip.
|
||||
#
|
||||
|
||||
echo "⚠️ FALLBACK INSTALLATION - Use only if auto-installation fails!"
|
||||
echo "🔍 Detecting CUDA version..."
|
||||
echo "FALLBACK INSTALLATION - Use only if auto-installation fails!"
|
||||
echo "Detecting CUDA version..."
|
||||
|
||||
# Try to detect CUDA version
|
||||
CUDA_VERSION=""
|
||||
@@ -40,28 +43,28 @@ echo "📦 Installing requirements for CUDA $CUDA_MAJOR..."
|
||||
|
||||
# Install appropriate requirements based on CUDA version
|
||||
if [ "$CUDA_MAJOR" = "13" ]; then
|
||||
echo "🚀 Installing CUDA 13 requirements (RTX 50 series)"
|
||||
echo "📦 Installing base dependencies + CUDA 13 TensorRT..."
|
||||
pip install -r requirements.txt
|
||||
echo "📦 Installing CUDA 13 specific TensorRT packages..."
|
||||
pip install -r requirements_cu13.txt
|
||||
echo "Installing CUDA 13 requirements (RTX 50 series)"
|
||||
echo "Installing base dependencies + CUDA 13 TensorRT..."
|
||||
python3 -m pip install --prefer-binary -r requirements.txt
|
||||
echo "Installing CUDA 13 specific TensorRT packages..."
|
||||
python3 -m pip install --prefer-binary -r requirements_cu13.txt
|
||||
elif [ "$CUDA_MAJOR" = "12" ]; then
|
||||
echo "🔧 Installing CUDA 12 requirements (RTX 30/40 series)"
|
||||
echo "📦 Installing base dependencies + CUDA 12 TensorRT..."
|
||||
pip install -r requirements.txt
|
||||
echo "📦 Installing CUDA 12 specific TensorRT packages..."
|
||||
pip install -r requirements_cu12.txt
|
||||
echo "Installing CUDA 12 requirements (RTX 30/40 series)"
|
||||
echo "Installing base dependencies + CUDA 12 TensorRT..."
|
||||
python3 -m pip install --prefer-binary -r requirements.txt
|
||||
echo "Installing CUDA 12 specific TensorRT packages..."
|
||||
python3 -m pip install --prefer-binary -r requirements_cu12.txt
|
||||
else
|
||||
echo "❌ Unsupported CUDA version: $CUDA_VERSION"
|
||||
echo "Unsupported CUDA version: $CUDA_VERSION"
|
||||
echo "Supported versions: CUDA 12.x, CUDA 13.x"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
if [ $? -eq 0 ]; then
|
||||
echo "✅ Fallback installation completed!"
|
||||
echo "🎯 You can now use ComfyUI RIFE TensorRT node"
|
||||
echo "💡 In the future, try auto-installation by just installing requirements.txt"
|
||||
echo "Fallback installation completed!"
|
||||
echo "You can now use ComfyUI RIFE TensorRT Auto node"
|
||||
echo "In the future, try auto-installation by just installing requirements.txt"
|
||||
else
|
||||
echo "❌ Installation failed!"
|
||||
echo "Installation failed!"
|
||||
exit 1
|
||||
fi
|
||||
|
||||
+2
-2
@@ -5,10 +5,10 @@ version = "1.1.1"
|
||||
license = { file = "LICENSE" }
|
||||
|
||||
[project.urls]
|
||||
Repository = "https://github.com/silveroxides/ComfyUI_RIFE_TensorRT_Auto"
|
||||
Repository = "https://github.com/huchukato/ComfyUI-RIFE-TensorRT-Auto"
|
||||
# Used by Comfy Registry https://comfyregistry.org
|
||||
|
||||
[tool.comfy]
|
||||
PublisherId = "silveroxides"
|
||||
PublisherId = "huchukato"
|
||||
DisplayName = "ComfyUI_RIFE_TensorRT_Auto"
|
||||
Icon = ""
|
||||
|
||||
+3
-2
@@ -1,6 +1,7 @@
|
||||
# Base dependencies - TensorRT will be auto-installed based on CUDA detection
|
||||
# The node will automatically detect CUDA 12/13 and install appropriate TensorRT packages
|
||||
#
|
||||
# The node will automatically detect CUDA 12/13 and install appropriate TensorRT packages.
|
||||
# The NVIDIA CUDA Toolkit must already be installed on the system; it is NOT installed via pip.
|
||||
#
|
||||
# Installation happens automatically when the node loads for the first time
|
||||
# No manual TensorRT installation required!
|
||||
|
||||
|
||||
@@ -1,12 +1,9 @@
|
||||
# CUDA 12 specific packages (RTX 30/40 series, CUDA 12.x)
|
||||
#
|
||||
# NOTE: This file is for REFERENCE ONLY - manual installation
|
||||
# The recommended method is AUTO-INSTALLATION via the node:
|
||||
# - Just install requirements.txt and restart ComfyUI
|
||||
# - The node will auto-detect CUDA and install TensorRT automatically
|
||||
# CUDA 12 specific TensorRT packages (RTX 30/40 series, CUDA 12.x)
|
||||
#
|
||||
# Use this file ONLY if auto-installation fails or for manual setup
|
||||
# NOTE: cuda-toolkit is NOT installed via pip. Install the NVIDIA CUDA Toolkit separately if needed.
|
||||
# The node will auto-detect CUDA 12 and install these packages automatically.
|
||||
#
|
||||
# Use this file ONLY if auto-installation fails or for manual setup.
|
||||
# Installation order for MANUAL setup only:
|
||||
# 1. pip install -r requirements.txt (base dependencies)
|
||||
# 2. pip install -r requirements_cu12.txt (CUDA 12 specific TensorRT)
|
||||
@@ -14,4 +11,3 @@
|
||||
tensorrt-cu12==10.13.3.9
|
||||
tensorrt-cu12-libs==10.13.3.9
|
||||
tensorrt-cu12-bindings==10.13.3.9
|
||||
cuda-toolkit>=12.8.0,<13.0.0
|
||||
|
||||
@@ -1,12 +1,9 @@
|
||||
# CUDA 13 specific packages (RTX 50 series, CUDA 13.x)
|
||||
#
|
||||
# NOTE: This file is for REFERENCE ONLY - manual installation
|
||||
# The recommended method is AUTO-INSTALLATION via the node:
|
||||
# - Just install requirements.txt and restart ComfyUI
|
||||
# - The node will auto-detect CUDA and install TensorRT automatically
|
||||
# CUDA 13 specific TensorRT packages (RTX 50 series, CUDA 13.x)
|
||||
#
|
||||
# Use this file ONLY if auto-installation fails or for manual setup
|
||||
# NOTE: cuda-toolkit is NOT installed via pip. Install the NVIDIA CUDA Toolkit separately if needed.
|
||||
# The node will auto-detect CUDA 13 and install these packages automatically.
|
||||
#
|
||||
# Use this file ONLY if auto-installation fails or for manual setup.
|
||||
# Installation order for MANUAL setup only:
|
||||
# 1. pip install -r requirements.txt (base dependencies)
|
||||
# 2. pip install -r requirements_cu13.txt (CUDA 13 specific TensorRT)
|
||||
@@ -14,4 +11,3 @@
|
||||
tensorrt_cu13==10.15.1.29
|
||||
tensorrt_cu13_bindings==10.15.1.29
|
||||
tensorrt_cu13_libs==10.15.1.29
|
||||
cuda-toolkit>=13.0.0,<13.1.0
|
||||
|
||||
Reference in New Issue
Block a user