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https://github.com/MLSysBook/TinyTorch.git
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77150be3a6
✅ COMPLETED: - Instructor solution executes perfectly - NBDev export works (fixed import directives) - Package functionality verified - Student assignment generation works - CLI integration complete - Systematic testing framework established ⚠️ CRITICAL DISCOVERY: - NBGrader requires cell metadata architecture changes - Current generator creates content correctly but wrong cell types - Would require major rework of assignment generation pipeline 📊 STATUS: - Core TinyTorch functionality: ✅ READY FOR STUDENTS - NBGrader integration: Requires Phase 2 rework - Ready to continue systematic testing of modules 01-06 🔧 FIXES APPLIED: - Added #| export directive to imports in enhanced modules - Fixed generator logic for student scaffolding - Updated testing framework and documentation
82 lines
2.7 KiB
Python
82 lines
2.7 KiB
Python
# NBGrader Configuration for TinyTorch ML Systems Course
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c = get_config()
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# Course Information
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c.CourseDirectory.course_id = "tinytorch-ml-systems"
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c.CourseDirectory.assignment_id = "" # Will be set per assignment
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# Directory Structure
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c.CourseDirectory.root = "."
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c.CourseDirectory.source_directory = "assignments/source"
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c.CourseDirectory.release_directory = "assignments/release"
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c.CourseDirectory.submitted_directory = "assignments/submitted"
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c.CourseDirectory.autograded_directory = "assignments/autograded"
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c.CourseDirectory.feedback_directory = "assignments/feedback"
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# Student Configuration
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c.CourseDirectory.student_id = "*" # All students
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c.CourseDirectory.student_id_exclude = ""
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# Database Configuration
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c.CourseDirectory.db_assignments = []
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c.CourseDirectory.db_students = []
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# Auto-grading Configuration
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c.Execute.timeout = 300 # 5 minutes per cell
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c.Execute.allow_errors = True
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c.Execute.error_on_timeout = True
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c.Execute.interrupt_on_timeout = True
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# Solution Removal Configuration
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c.ClearSolutions.code_stub = {
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"python": "# YOUR CODE HERE\nraise NotImplementedError()",
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"javascript": "// YOUR CODE HERE\nthrow new Error();",
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"R": "# YOUR CODE HERE\nstop('No Answer Given!')",
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"matlab": "% YOUR CODE HERE\nerror('No Answer Given!')",
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"octave": "% YOUR CODE HERE\nerror('No Answer Given!')",
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"sage": "# YOUR CODE HERE\nraise NotImplementedError()",
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"scala": "// YOUR CODE HERE\n???"
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}
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# Text Stub for written responses
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c.ClearSolutions.text_stub = "YOUR ANSWER HERE"
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# Preprocessor Configuration
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c.ClearSolutions.begin_solution_delimeter = "BEGIN SOLUTION"
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c.ClearSolutions.end_solution_delimeter = "END SOLUTION"
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c.ClearSolutions.begin_hidden_tests_delimeter = "BEGIN HIDDEN TESTS"
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c.ClearSolutions.end_hidden_tests_delimeter = "END HIDDEN TESTS"
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# Enforce Metadata (require proper cell metadata)
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c.ClearSolutions.enforce_metadata = True
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# Grade Calculation
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c.TotalPoints.total_points = 100 # Each module is worth 100 points
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# Validation Configuration
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c.Validate.ignore_checksums = False
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# Feedback Configuration
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c.GenerateFeedback.force = False
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c.GenerateFeedback.max_dir_size = 1000000 # 1MB max feedback size
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# Exchange Configuration (for distributing assignments)
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c.Exchange.course_id = "tinytorch-ml-systems"
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c.Exchange.timezone = "UTC"
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# Notebook Configuration
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c.NbGraderConfig.logfile = "nbgrader.log"
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c.NbGraderConfig.log_level = "INFO"
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# Custom TinyTorch Configuration (stored as comments for reference)
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# Each module is worth 100 points:
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# - setup: 100 points (easy, 1-2 hours)
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# - tensor: 100 points (medium, 2-3 hours)
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# - activations: 100 points (medium, 2-3 hours)
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# - layers: 100 points (hard, 3-4 hours)
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#
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# Grading policy:
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# - Partial credit enabled
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# - Late penalty: 10% per day
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# - Max attempts: 3 |