[compiler] add interReturnType function for byteir.reshape and byteir.one_hot #451
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heromapwrd
commented
Sep 29, 2024
heromapwrd
commented
- [tf-frontend] convert tf.Reshpe, which has dynamic input shape and output shape, to byteir.reshape
- [compiler] add inferReturnType function for byteir.reshape op
- [compiler] add inferReturnType function for byteir.one_hot op
qingyunqu
reviewed
Oct 9, 2024
| @@ -69,6 +69,10 @@ constexpr llvm::StringRef getOneHotName() { | |||
| return CUSTOM_CALL_NAME_PREFIX "one_hot"; | |||
| } | |||
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| constexpr llvm::StringRef getReshapeName() { | |||
| return CUSTOM_CALL_NAME_PREFIX "reshape"; | |||
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Is it necessary to add byteir.reshape?
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There are four reasons for switching to byteir.reshape instead of retaining the original tf.Reshape form:
- If possible, convert regular op (such as reshape op) to custom_call@byteir., rather than custom_call@tf.
- custom_call@byteir.*** indicates that it cannot be converted to regular mhlo op, but we have identified this case. But the form custom_call@tf.*** does not convey this meaning
- when other front-end reshape op appears and cannot be converted into regular mhlo.reshape op and mhlo.dynamic_reshape op, it can also be converted into byteir.reshape, a unified representation
- getReshapeName function will be used in shape/bounded shape inference
qingyunqu
reviewed
Oct 9, 2024
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| func.func @reshape_case0(%arg0: tensor<?x24xf16>) -> tensor<?x24x1xf16> { | ||
| %cst = "tf.Const"() <{value = dense<[-1, 24, 1]> : tensor<3xi64>}> : () -> tensor<3xi64> | ||
| %0 = "tf.Reshape"(%arg0, %cst) : (tensor<?x24xf16>, tensor<3xi64>) -> tensor<?x24x1xf16> |
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=> compute_reshape_shape + mhlo.dynamic_reshape
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