mirror of
https://github.com/MLSysBook/TinyTorch.git
synced 2026-06-05 06:25:50 -05:00
d892a10492
- Remove unnecessary module_paths.txt file for cleaner architecture - Update export command to discover modules dynamically from modules/source/ - Simplify nbdev command to support --all and module-specific exports - Use single source of truth: nbdev settings.ini for module paths - Clean up import structure in setup module for proper nbdev export - Maintain clean separation between module discovery and export logic This implements a proper software engineering approach with: - Single source of truth (settings.ini) - Dynamic discovery (no hardcoded paths) - Clean CLI interface (tito package nbdev --export [--all|module]) - Robust error handling with helpful feedback
84 lines
2.8 KiB
Python
84 lines
2.8 KiB
Python
"""
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Configuration management for TinyTorch CLI.
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"""
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import os
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import sys
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from pathlib import Path
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from typing import Dict, Any, Optional
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from dataclasses import dataclass
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@dataclass
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class CLIConfig:
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"""Configuration for TinyTorch CLI."""
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# Project paths
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project_root: Path
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assignments_dir: Path
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tinytorch_dir: Path
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bin_dir: Path
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# Environment settings
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python_min_version: tuple = (3, 8)
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required_packages: list = None # type: ignore
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# CLI settings
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verbose: bool = False
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no_color: bool = False
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def __post_init__(self):
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"""Initialize default values."""
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if self.required_packages is None:
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self.required_packages = ['numpy', 'pytest', 'rich']
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@classmethod
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def from_project_root(cls, project_root: Optional[Path] = None) -> 'CLIConfig':
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"""Create config from project root directory."""
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if project_root is None:
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# Auto-detect project root
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current = Path.cwd()
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while current != current.parent:
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if (current / 'pyproject.toml').exists():
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project_root = current
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break
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current = current.parent
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else:
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project_root = Path.cwd()
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return cls(
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project_root=project_root,
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assignments_dir=project_root / 'modules' / 'source',
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tinytorch_dir=project_root / 'tinytorch',
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bin_dir=project_root / 'bin'
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)
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def validate(self) -> list[str]:
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"""Validate the configuration and return any issues."""
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issues = []
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# Check Python version
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if sys.version_info < self.python_min_version:
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issues.append(f"Python {'.'.join(map(str, self.python_min_version))}+ required, "
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f"found {sys.version_info.major}.{sys.version_info.minor}")
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# Check virtual environment
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in_venv = (hasattr(sys, 'real_prefix') or
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(hasattr(sys, 'base_prefix') and sys.base_prefix != sys.prefix))
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if not in_venv:
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issues.append("Virtual environment not activated. Run: source .venv/bin/activate")
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# Check required directories
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if not self.assignments_dir.exists():
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issues.append(f"Assignments directory not found: {self.assignments_dir}")
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if not self.tinytorch_dir.exists():
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issues.append(f"TinyTorch package not found: {self.tinytorch_dir}")
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# Check required packages
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for package in self.required_packages:
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try:
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__import__(package)
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except ImportError:
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issues.append(f"Missing dependency: {package}. Run: pip install -r requirements.txt")
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return issues |