CoreML: ML Program DepthToSpace #21426
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We need to manually handle CRD format by decomposing the steps. Luckily we can work around CoreML's 5D limit as the data movement is not affected by merging the batch dimension with the channel dimension.
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edgchen1
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Jul 22, 2024
onnxruntime/core/providers/coreml/builders/impl/builder_utils.h
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edgchen1
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Jul 22, 2024
onnxruntime/core/providers/coreml/builders/impl/depthtospace_op_builder.cc
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skottmckay
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Jul 24, 2024
- Add Concat (#21423) - Add DepthToSpace (#21426) - Add LeakyRelu (#21453) - Add test scripts (#21427) - Add ability to set coreml flags from python (#21434) Also updated partitioning utils to support dropping constant initializers from a ComputeCapability's inputs. We copy these to a CoreML model so don't need the originals. If they remain as inputs ORT can't free them as they appear to be in use. Misc changes - Fix SkipLayerNormFusion incorrectly setting `modified` - causes unnecessary loops of the L2 transformers
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skottmckay
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Jul 25, 2024
…#21472) ### Description <!-- Describe your changes. --> Add these changes to one PR to simplify checkin - Add Concat (#21423) - Add DepthToSpace (#21426) - Add LeakyRelu (#21453) - Add test scripts (#21427) - Add ability to set coreml flags from python (#21434) Other changes - updated partitioning utils to support dropping constant initializers from a ComputeCapability's inputs. - noticed that the list of inputs to the coreml model was unexpectedly long due to this - we copy constant initializers to a CoreML model so don't need the originals, and if they remain as inputs ORT can't free them as they appear to be in use. ### Motivation and Context <!-- - Why is this change required? What problem does it solve? - If it fixes an open issue, please link to the issue here. -->
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Description
Add DepthToSpace ML Program support.
We need to manually handle CRD format by decomposing the steps.
Luckily we can work around CoreML's 5D limit as the data movement is not affected by merging the batch dimension with the channel dimension.
Motivation and Context
Improve CoreML coverage for high priority models.