Release v4.0.0 (#2294)
This commit is contained in:
Kihiro Bando
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# SPDX-FileCopyrightText: Copyright (c) 2025 NVIDIA CORPORATION & AFFILIATES. All rights reserved.
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# SPDX-License-Identifier: LicenseRef-NvidiaProprietary
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#
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# Use of this software is governed by the terms and conditions of the
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# NVIDIA End User License Agreement (EULA), available at:
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# https://docs.nvidia.com/cutlass/media/docs/pythonDSL/license.html
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#
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# Any use, reproduction, disclosure, or distribution of this software
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# and related documentation outside the scope permitted by the EULA
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# is strictly prohibited.
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import os
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from typing import Any, Dict, Iterable, Optional, Union
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"""
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This module provides a Exception classes DSL class for any Dialect.
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"""
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# Add color codes at the top of the file after imports
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class Colors:
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"""ANSI color codes for error messages"""
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RED = "\033[91m"
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YELLOW = "\033[93m"
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BLUE = "\033[94m"
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GREEN = "\033[92m"
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BOLD = "\033[1m"
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RESET = "\033[0m"
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# =============================================================================
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# DSL Exceptions
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# =============================================================================
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class DSLBaseError(Exception):
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"""
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Base exception for DSL-related errors.
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Provides optional contextual metadata to aid in debugging.
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"""
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def __init__(
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self,
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message: str,
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line: Optional[int] = None,
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snippet: Optional[str] = None,
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filename: Optional[str] = None,
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error_code: Optional[Union[str, int]] = None,
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context: Optional[Union[Dict[str, Any], str]] = None,
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suggestion: Optional[str] = None,
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cause: Optional[BaseException] = None,
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) -> None:
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self.message = message
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self.line = line
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self.filename = filename
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self.snippet = snippet
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self.error_code = error_code
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self.context = context
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self.suggestion = suggestion
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self.cause = cause
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super().__init__(self._format_message())
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def _format_message(self):
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"""
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Formats the complete error message with available metadata.
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Override this in subclasses if you want to change formatting logic.
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"""
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parts = [f"{self.__class__.__name__}: {self.message}"]
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if self.error_code is not None:
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parts.append(f"{Colors.BOLD}Error Code:{Colors.RESET} {self.error_code}\n")
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if self.line is not None:
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parts.append(f" Line: {self.line}")
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if self.filename is not None:
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parts.append(f" File: {self.filename}")
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if self.snippet:
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# Optionally truncate long snippets for readability
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parts.append(f" Snippet: \n {self.snippet}")
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if self.cause:
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parts.append(f" Caused exception: {self.cause}")
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if self.context:
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if isinstance(self.context, dict):
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parts.append(f"{Colors.BLUE}🔍 Additional Context:{Colors.RESET}\n")
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for key, value in self.context.items():
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parts.append(f" {key}: {value}")
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else:
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parts.append(
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f"{Colors.BLUE}🔍 Additional Context:{Colors.RESET} {self.context}"
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)
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if self.suggestion:
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parts.append(f"{Colors.GREEN}💡 Suggestions:{Colors.RESET}")
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if isinstance(self.suggestion, (list, tuple)):
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for suggestion in self.suggestion:
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parts.append(f" {Colors.GREEN}{suggestion}{Colors.RESET}")
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else:
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parts.append(f" {self.suggestion}")
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return "\n".join(parts)
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class DSLRuntimeError(DSLBaseError):
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"""
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Raised when an error occurs during JIT-time code generation in the DSL.
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"""
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# Inherits all logic from DSLBaseError; override methods if you need
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# specialized behavior or formatting for runtime errors.
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pass
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def _get_friendly_cuda_error_message(error_code, error_name):
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# Avoid circular dependency
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from .runtime.cuda import get_device_info
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"""Get a user-friendly error message for common CUDA errors."""
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# Strip the byte string markers if present
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if isinstance(error_name, bytes):
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error_name = error_name.decode("utf-8")
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elif (
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isinstance(error_name, str)
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and error_name.startswith("b'")
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and error_name.endswith("'")
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):
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error_name = error_name[2:-1]
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# Add target architecture info
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target_arch = os.getenv("CUTE_DSL_ARCH", "unknown")
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error_messages = {
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"CUDA_ERROR_INVALID_SOURCE": (
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f"{Colors.RED}❌ Failed to load CUDA kernel - likely architecture mismatch.{Colors.RESET}\n\n"
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),
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"CUDA_ERROR_NO_BINARY_FOR_GPU": (
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f"{Colors.RED}❌ CUDA kernel not compatible with your GPU.{Colors.RESET}\n\n"
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),
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"CUDA_ERROR_OUT_OF_MEMORY": (
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f"{Colors.RED}💾 CUDA out of memory error.{Colors.RESET}\n\n"
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),
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"CUDA_ERROR_INVALID_DEVICE": (
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f"{Colors.RED}❌ Invalid CUDA device.{Colors.RESET}\n\n"
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),
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"CUDA_ERROR_NOT_INITIALIZED": (
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f"{Colors.RED}❌ CUDA context not initialized.{Colors.RESET}\n\n"
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),
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"CUDA_ERROR_INVALID_VALUE": (
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f"{Colors.RED}⚠️ Invalid parameter passed to CUDA operation.{Colors.RESET}\n\n"
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f"{Colors.YELLOW}This is likely a bug - please report it with:{Colors.RESET}"
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),
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}
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error_suggestions = {
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"CUDA_ERROR_INVALID_SOURCE": (
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f"1. Ensure env CUTE_DSL_ARCH matches your GPU architecture",
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f"2. Clear the compilation cache and regenerate the kernel",
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f"3. Check CUDA toolkit installation",
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),
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"CUDA_ERROR_NO_BINARY_FOR_GPU": (
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f"Set env CUTE_DSL_ARCH to match your GPU architecture",
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),
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"CUDA_ERROR_OUT_OF_MEMORY": (
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f"1. Reduce batch size",
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f"2. Reduce model size",
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f"3. Free unused GPU memory",
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),
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"CUDA_ERROR_INVALID_DEVICE": (
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f"1. Check if CUDA device is properly initialized",
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f"2. Verify GPU is detected: nvidia-smi",
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f"3. Check CUDA_VISIBLE_DEVICES environment variable",
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),
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"CUDA_ERROR_NOT_INITIALIZED": (
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f"1. Check CUDA driver installation",
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f"2. call `cuda.cuInit(0)` before any other CUDA operation",
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f"3. Run nvidia-smi to confirm GPU status",
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),
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"CUDA_ERROR_INVALID_VALUE": (
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f"1. Your GPU model",
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f"2. SM ARCH setting",
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f"3. Steps to reproduce",
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),
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}
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message = error_messages.get(
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error_name, f"{Colors.RED}Unknown CUDA error{Colors.RESET}"
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)
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# Add debug information
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debug_info = f"\n- {Colors.BOLD}Error name: {error_name}\n"
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debug_info += f"- CUDA_TOOLKIT_PATH: {os.getenv('CUDA_TOOLKIT_PATH', 'not set')}\n"
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debug_info += (
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f"- Target SM ARCH: {os.getenv('CUTE_DSL_ARCH', 'not set')}{Colors.RESET}\n"
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)
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try:
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# Get GPU information using CUDA Python API
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debug_info += f"\n{Colors.BLUE}📊 GPU Information:{Colors.RESET}\n"
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gpu_info = get_device_info()
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debug_info += gpu_info.pretty_str()
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if target_arch and gpu_info.compatible_archs:
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debug_info += f"\n{Colors.BOLD}Compatibility Check:{Colors.RESET}\n"
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if target_arch not in gpu_info.compatible_archs:
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debug_info += (
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f"{Colors.RED}❌ Error: Target SM ARCH {target_arch} is not compatible\n"
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f"💡 Please use one of SM ARCHs: "
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f"{Colors.GREEN}{', '.join(gpu_info.compatible_archs or [])}{Colors.RESET}\n"
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)
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elif target_arch != gpu_info.sm_arch:
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debug_info += (
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f"{Colors.YELLOW}⚠️ Warning: Using compatible but non-optimal architecture\n"
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f"• Current: {target_arch}\n"
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f"• Recommended: {Colors.GREEN}{gpu_info.sm_arch}{Colors.RESET} (native)\n"
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)
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else:
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debug_info += f"{Colors.GREEN}✓ Using optimal architecture: {gpu_info.sm_arch}{Colors.RESET}\n"
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except Exception as e:
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debug_info += (
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f"\n{Colors.YELLOW}ℹ️ Could not retrieve GPU info: {str(e)}{Colors.RESET}"
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)
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return message, debug_info, error_suggestions.get(error_name, "")
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class DSLCudaRuntimeError(DSLBaseError):
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"""
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Raised when an error occurs during CUDA runtime code generation in the DSL.
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"""
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# Inherits all logic from DSLRuntimeError; override methods if you need
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# specialized behavior or formatting for runtime errors.
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def __init__(self, error_code, error_name) -> None:
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self._error_code = error_code
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self._error_name = error_name
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message, debug_info, suggestion = _get_friendly_cuda_error_message(
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error_code, error_name
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)
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super().__init__(
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message, error_code=error_code, context=debug_info, suggestion=suggestion
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)
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class DSLAstPreprocessorError(DSLBaseError):
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"""
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Raised when an error occurs during AST preprocessing or visiting in the DSL.
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"""
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# Same approach: You could override _format_message if you want
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# to emphasize AST node details or anything specific to preprocessing.
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pass
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class DSLNotImplemented(DSLBaseError):
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"""
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Raised when a feature of the DSL is not implemented yet.
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"""
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# Useful for stubs in your DSL that you plan to implement in the future.
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pass
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