Change dtype functions interface to take ints tuple for each tensor #1865
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The original design for the dtype functions outlined in llvm#1462 was unable to properly handle ops that take optional tensors as an input when the optional tensor has a value of None. By the time the op gets imported into torch-mlir, if an optional value is None, all information about the original type is lost from the op type signature, preventing torch-mlir from knowing if a value of None was from an optional tensor or not, which was crucial in the original design since each tensor argument must be turned into two separate arguments for the dtype function. This commit changes the interface to dtype functions such that each tensor turns into a tuple of two ints, the first representing the rank of the tensor and the second the dtype of the tensor. Since now there is a one-to-one correspondence between the operands of an op and the operands of its dtype function, there is no ambiguity about which operand of the op corresponds with which operand of the dtype function. To test the implementation, this commit defines dtype functions for the convolution ops, all of which take one optional tensor as an argument.
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commit bafe339 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon May 8 21:26:56 2023 +0000 Add dtype functions for aten.atan and prims.squeeze commit bebf695 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon May 8 21:26:10 2023 +0000 Remove duplicate code from merge with main commit 0d11895 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Fri May 5 21:39:02 2023 +0000 Update LLVM tag commit 73d5c07 Merge: 899d8bc eaaaeb6 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Fri May 5 21:30:09 2023 +0000 Merge remote-tracking branch 'upstream/main' into merge-main commit 899d8bc Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Mar 13 21:39:14 2023 +0000 Add dtype functions for `aten.ge.Tensor` and `aten.le.Tensor` commit f58f9c2 Merge: ce7abf4 4912c39 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Mar 13 21:32:00 2023 +0000 Merge branch 'main' into merge-main commit ce7abf4 Author: Jiahao Li <liplus17@163.com> Date: Wed Feb 22 06:54:41 2023 +0800 Add dtype functions for ops that take dtype from 2nd operand (llvm#1891) commit 63945a2 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Feb 13 17:56:09 2023 -0800 Change dtype functions interface to take ints tuple for each tensor (llvm#1865) The original design for the dtype functions outlined in llvm#1462 was unable to properly handle ops that take optional tensors as an input when the optional tensor has a value of None. By the time the op gets imported into torch-mlir, if an optional value is None, all information about the original type is lost from the op type signature, preventing torch-mlir from knowing if a value of None was from an optional tensor or not, which was crucial in the original design since each tensor argument must be turned into two separate arguments for the dtype function. This commit changes the interface to dtype functions such that each tensor turns into a tuple of two ints, the first representing the rank of the tensor and the second the dtype of the tensor. Since now there is a one-to-one correspondence between the operands of an op and the operands of its dtype function, there is no ambiguity about which operand of the op corresponds with which operand of the dtype function. To test the implementation, this commit defines dtype functions for the convolution ops, all of which take one optional tensor as an argument. commit 981ac88 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Wed Feb 1 22:30:27 2023 +0000 Add dtype functions for two tensor promotion ops (llvm#1831) This commit adds dtype functions for ops in RefineTypes under the category of "Promote the two dtypes". The only ops not added here are convolution ops, since they take an optional tensor argument, and the dtype pipeline currently does not correctly handle that case. I will add a follow up patch fixing this. This commit also adds two helper functions that perform a very thorough testing of dtype functions. The helper function `_check_two_tensor_op` is able to independently test invalid input dtypes and invalid output dtypes. Lastly, this commit also XFAILs "MobilenetV3Module_basic". commit 83d4e89 Author: Jiahao Li <liplus17@163.com> Date: Sat Jan 21 02:39:41 2023 +0800 Add dtype functions for floating point ops (llvm#1813) commit 8cae5ba Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Jan 16 14:32:23 2023 -0800 Add dtype functions for comparison ops (llvm#1806) This commit adds dtype functions for comparison ops that always return a tensor of dtype `i1`. commit 5b77c15 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Jan 16 20:27:49 2023 +0000 Add CI to `dtype-functions-staging` branch commit ac94ba2 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Thu Jan 12 22:41:04 2023 +0000 Move dtype functions into their own section in lib gen file In order to easily keep track of the dtype functions that have been moved to `abstract_interp_lib_gen.py` and make it easier to add new ones, this commit groups all the dtype functions together, rather than having them interspersed between the shape functions.
ramiro050
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May 9, 2023
commit bafe339 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon May 8 21:26:56 2023 +0000 Add dtype functions for aten.atan and prims.squeeze commit bebf695 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon May 8 21:26:10 2023 +0000 Remove duplicate code from merge with main commit 0d11895 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Fri May 5 21:39:02 2023 +0000 Update LLVM tag commit 73d5c07 Merge: 899d8bc eaaaeb6 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Fri May 5 21:30:09 2023 +0000 Merge remote-tracking branch 'upstream/main' into merge-main commit 899d8bc Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Mar 13 21:39:14 2023 +0000 Add dtype functions for `aten.ge.Tensor` and `aten.le.Tensor` commit f58f9c2 Merge: ce7abf4 4912c39 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Mar 13 21:32:00 2023 +0000 Merge branch 'main' into merge-main commit ce7abf4 Author: Jiahao Li <liplus17@163.com> Date: Wed Feb 22 06:54:41 2023 +0800 Add dtype functions for ops that take dtype from 2nd operand (llvm#1891) commit 63945a2 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Feb 13 17:56:09 2023 -0800 Change dtype functions interface to take ints tuple for each tensor (llvm#1865) The original design for the dtype functions outlined in llvm#1462 was unable to properly handle ops that take optional tensors as an input when the optional tensor has a value of None. By the time the op gets imported into torch-mlir, if an optional value is None, all information about the original type is lost from the op type signature, preventing torch-mlir from knowing if a value of None was from an optional tensor or not, which was crucial in the original design since each tensor argument must be turned into two separate arguments for the dtype function. This commit changes the interface to dtype functions such that each tensor turns into a tuple of two ints, the first representing the rank of the tensor and the second the dtype of the tensor. Since now there is a one-to-one correspondence between the operands of an op and the operands of its dtype function, there is no ambiguity about which operand of the op corresponds with which operand of the dtype function. To test the implementation, this commit defines dtype functions for the convolution ops, all of which take one optional tensor as an argument. commit 981ac88 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Wed Feb 1 22:30:27 2023 +0000 Add dtype functions for two tensor promotion ops (llvm#1831) This commit adds dtype functions for ops in RefineTypes under the category of "Promote the two dtypes". The only ops not added here are convolution ops, since they take an optional tensor argument, and the dtype pipeline currently does not correctly handle that case. I will add a follow up patch fixing this. This commit also adds two helper functions that perform a very thorough testing of dtype functions. The helper function `_check_two_tensor_op` is able to independently test invalid input dtypes and invalid output dtypes. Lastly, this commit also XFAILs "MobilenetV3Module_basic". commit 83d4e89 Author: Jiahao Li <liplus17@163.com> Date: Sat Jan 21 02:39:41 2023 +0800 Add dtype functions for floating point ops (llvm#1813) commit 8cae5ba Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Jan 16 14:32:23 2023 -0800 Add dtype functions for comparison ops (llvm#1806) This commit adds dtype functions for comparison ops that always return a tensor of dtype `i1`. commit 5b77c15 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Mon Jan 16 20:27:49 2023 +0000 Add CI to `dtype-functions-staging` branch commit ac94ba2 Author: Ramiro Leal-Cavazos <ramiroleal050@gmail.com> Date: Thu Jan 12 22:41:04 2023 +0000 Move dtype functions into their own section in lib gen file In order to easily keep track of the dtype functions that have been moved to `abstract_interp_lib_gen.py` and make it easier to add new ones, this commit groups all the dtype functions together, rather than having them interspersed between the shape functions.
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The original design for the dtype functions outlined in #1462 was unable to properly handle ops that take optional tensors as an input when the optional tensor has a value of None. By the time the op gets imported into torch-mlir, if an optional value is None, all information about the original type is lost from the op type signature, preventing torch-mlir from knowing if a value of None was from an optional tensor or not, which was crucial in the original design since each tensor argument must be turned into two separate arguments for the dtype function.
This commit changes the interface to dtype functions such that each tensor turns into a tuple of two ints, the first representing the rank of the tensor and the second the dtype of the tensor. Since now there is a one-to-one correspondence between the operands of an op and the operands of its dtype function, there is no ambiguity about which operand of the op corresponds with which operand of the dtype function.
To test the implementation, this commit defines dtype functions for the convolution ops, all of which take one optional tensor as an argument.