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Enhance model factory with comprehensive improvements (Issue #151) (#156)
* Enhance model factory with comprehensive improvements (Issue #151) ## Summary - Add comprehensive model factory infrastructure with validation, presets, and multi-format support - Fix datetime deprecation warning affecting all model creation - Add extensive testing and documentation improvements ## Features Added - JSON configuration file support alongside YAML - Auto-format detection for configuration files (.yaml/.yml/.json) - 5 predefined model presets for common configurations - Parameter validation with helpful error messages - Model introspection and utility functions ## API Enhancements - `create_selection_model_from_json()` - JSON file support - `create_selection_model_from_file()` - Auto-detect file format - `create_model_from_preset()` - Create from predefined configurations - `list_available_models()` - List all available model classes - `get_model_info()` - Model parameter introspection - `describe_model()` - Model architecture summary ## Bug Fixes - Fix datetime.utcnow() deprecation warning in netam/models.py - Enhanced error messages with suggestions and usage hints - Comprehensive parameter validation for transformer models ## Testing - 25 comprehensive tests covering all new functionality - Tests for error conditions, validation, and edge cases - All existing tests still pass (113 total) ## Documentation - Enhanced docstrings with examples and parameter details - 6 example configuration files (5 YAML + 1 JSON) - Clear usage examples for all new functions 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <[email protected]> * refactor: Remove JSON support and move presets to config files Based on PR feedback: - Remove JSON configuration support to maintain YAML-only approach - Move preset configurations from hardcoded dictionary to model_configs/ directory - Add list_available_presets() function for preset discovery - Update package configuration to include model_configs/*.yaml files This change improves consistency by using YAML throughout and separates configuration from code, making presets easier to maintain and extend. 🤖 Generated with [Claude Code](https://claude.ai/code) Co-Authored-By: Claude <[email protected]> * more robust configuration of MODEL_CONFIGS_DIR --------- Co-authored-by: Claude <[email protected]>
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‎examples/bidirectional_transformer.yaml‎

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model_class: BidirectionalTransformerBinarySelectionModel
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20
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nhead: 4
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d_model_per_head: 6
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dim_feedforward: 512
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layer_count: 2
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dropout_prob: 0.1

‎examples/parent_independent.yaml‎

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model_class: ParentIndependentBinarySelectionModel
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20

‎examples/single.yaml‎

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model_class: SingleValueBinarySelectionModel
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20

‎examples/transformer_large.yaml‎

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model_class: TransformerBinarySelectionModelWiggleAct
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20
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nhead: 8
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d_model_per_head: 8
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dim_feedforward: 2048
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layer_count: 6
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dropout_prob: 0.1

‎examples/transformer_sml.yaml‎

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model_class: TransformerBinarySelectionModelWiggleAct
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20
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nhead: 4
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d_model_per_head: 4
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dim_feedforward: 1024
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layer_count: 3
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dropout_prob: 0.1

‎netam/__init__.py‎

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"""netam: Neural networks for antibody affinity maturation."""
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from .model_factory import (
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create_selection_model_from_dict,
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create_selection_model_from_yaml,
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create_selection_model_from_file,
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create_model_from_preset,
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list_available_models,
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list_available_presets,
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get_model_info,
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describe_model,
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)
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__all__ = [
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"create_selection_model_from_dict",
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"create_selection_model_from_yaml",
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"create_selection_model_from_file",
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"create_model_from_preset",
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"list_available_models",
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"list_available_presets",
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"get_model_info",
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"describe_model",
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]

‎netam/model_configs/bidirectional_default.yaml‎

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model_class: BidirectionalTransformerBinarySelectionModel
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20
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nhead: 4
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d_model_per_head: 6
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dim_feedforward: 256
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layer_count: 2

‎netam/model_configs/parent_independent_default.yaml‎

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model_class: ParentIndependentBinarySelectionModel
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20

‎netam/model_configs/single_default.yaml‎

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model_class: SingleValueBinarySelectionModel
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20

‎netam/model_configs/transformer_large.yaml‎

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model_class: TransformerBinarySelectionModelWiggleAct
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hparams:
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model_type: dasm
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known_token_count: 21
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output_dim: 20
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nhead: 8
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d_model_per_head: 8
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dim_feedforward: 2048
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layer_count: 6
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dropout_prob: 0.1

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