Adjust embedding outputs and unwrap ONNX scalar - #237
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Use squeezed embedding outputs and add shape comments for BST and DIEN so embedding(...) returns flattened [B, context_dim] where appropriate (pass squeeze_dim=True) and avoid redundant .flatten() calls when building MLP inputs. DIEN: also embed negative history features and document tensor shapes through the interest extraction/evolving logic. Add 'neg_history_features' to extract_feature_info. Update ONNX wrapper to unwrap models that return (output, scalar_loss) by returning only the primary output, preventing a 0-dim tensor from being emitted.
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What does this PR do? / 这个PR做了什么？
Use squeezed embedding outputs and add shape comments for BST and DIEN so embedding(...) returns flattened [B, context_dim] where appropriate (pass squeeze_dim=True) and avoid redundant .flatten() calls when building MLP inputs. DIEN: also embed negative history features and document tensor shapes through the interest extraction/evolving logic. Add 'neg_history_features' to extract_feature_info. Update ONNX wrapper to unwrap models that return (output, scalar_loss) by returning only the primary output, preventing a 0-dim tensor from being emitted.
Type of Change / 变更类型
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python config/format_code.py) / 代码遵循项目风格（运行了格式化脚本）