fix xfe ops td alignment#679
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… types - Change OptionalAttr to DefaultValuedAttr for ceil_mode, count_include_pad (AveragePool), storage_order (MaxPool) to match ONNX defaults - Make kernel_shape required (I64ArrayAttr) in AveragePool/MaxPool - Make blocksize required (SI64Attr) in DepthToSpace/SpaceToDepth - Add missing stash_type attribute to XFEGroupNormalizationOp - Fix element type ordering to BF16-first matching ONNX convention - Remove I8/UI8 from ops where ONNX spec does not include them; keep only in MaxPool - Remove I32 from Conv/ConvTranspose bias to match ONNX - Add remapQuantTypeNchw2Nhwc for GroupNorm output and forward stash_type - Update XFEVerify.cpp and XFEShapeInference.cpp accessor patterns
…pool and GroupNorm ops - Add kernel_shape to unranked pool verifier tests (now required) - Add ceil_mode, count_include_pad to AveragePool CHECK patterns - Add ceil_mode, storage_order to MaxPool CHECK patterns - Add stash_type to GroupNormalization CHECK patterns
jorickert
reviewed
Apr 10, 2026
…ions - Fix attribute types: add default_value for ceil_mode, count_include_pad, storage_order; mark kernel_shape and blocksize as required - Add missing stash_type attribute to GroupNormalization (default 1) - Remove int8/uint8 from ops where ONNX spec excludes them (Conv, AveragePool, BatchNorm, InstanceNorm, GlobalAvgPool, GlobalMaxPool, GroupNorm); retain int8/uint8 for MaxPool per ONNX spec - Remove int32 from Conv/ConvTranspose bias type constraints - Reorder element types with bfloat16 first across all XFE ops - Fix gen_onnx_mlir.py UTF-8 encoding for Windows compatibility - Regenerate XFEOps.td from updated YAML schema
sambanerxilinxamd
approved these changes
Apr 15, 2026
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allign xfe ops definition to corresponding onnx ops