update doc
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@@ -296,7 +296,9 @@ composed of the types that are supported by TVM FFI. The example below shows how
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Limitations
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-----------
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The Fake Tensor flow is ONLY compatible with TVM FFI because TVM FFI support more flexible constraints on Tensor arguments.
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The Fake Tensor flow supports more flexible constraints on Tensor arguments than the `from_dlpack` flow.
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TVM FFI backend is recommended when fake tensor is used as TVM FFI support flexible constraints on Tensor arguments.
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For instance, fake tensor can specify per-mode static shape or constraints on shape and strides which is not supported by
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existing `from_dlpack` flow. It's expected that JIT function compiled with fake tensor may have different ABI with
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tensor converted by `from_dlpack`.
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