Support QDQ transformations with com.microsoft.Quantize/Dequantize ops #17127
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…nsformerTests.QDQPropagation_Forward/Backward
edgchen1
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onnxruntime/test/testdata/transform/qdq_with_multi_consumer_dq_nodes.fixed.qdq_contrib.onnx
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@yufenglee The work is being broken down into separate/smaller PRs. This specific PR focuses on making sure contrib QDQ ops can be optimized in the same manner as ONNX ops (please refer to the PR description for details). The next PR (linked in the description) adds int16 support, but I'd like to get this one merged in before starting reviews on it. |
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microsoft#17127) ### Description - Enables int32 support for com.microsoft.DequantizeLinear (contrib op) - Makes the `zero_point` input optional for Quantize/Dequantize contrib ops - Enables QDQ transformations with the Quantize/Dequantize contrib ops - Update tests: EnsureUniqueDQForNodeUnitTests, QDQTransformerTests, TransposeOptimizerTests ### Testing List of tested graph transformations: - [x] QDQSelectorActionTransformer - qdq_transformer_test.cc - [x] QDQS8ToU8Transformer - qdq_transformer_test.cc - [x] DoubleQDQPairsRemover - qdq_transformer_test.cc - [x] IdenticalChildrenConsolidation - qdq_transformer_test.cc - [x] QDQPropagation - qdq_transformer_test.cc - [x] QDQFinalCleanup - qdq_transformer_test.cc - [x] CliQuantFusion - qdq_transformer_test.cc - [x] ReluQuantFusion - qdq_transformer_test.cc - [x] EnsureUniqueDQForNodeUnit - ensure_unique_dq_for_node_unit_test.cc - [x] TransposeOptimizer - transpose_optimizer_test.cc - [x] CommonSubexpressionElimination - graph_transform_test.cc - [x] ConstantFolding - graph_transform_test.cc ### Motivation and Context We need to [support mixed 16-bit/8-bit precision QDQ models](microsoft#17015). This PR is the first step in achieving this goal: we need to make QDQ contrib ops work with our optimizations/transformations. --------- Co-authored-by: Edward Chen <[email protected]> Co-authored-by: Scott McKay <[email protected]>
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Description
zero_pointinput optional for Quantize/Dequantize contrib opsTesting
List of tested graph transformations:
Motivation and Context
We need to support mixed 16-bit/8-bit precision QDQ models. This PR is the first step in achieving this goal: we need to make QDQ contrib ops work with our optimizations/transformations.