Commit Graph

11 Commits

Author SHA1 Message Date
Mircea Trofin 36bb1fb1fe [MLInliner] Factor out logging
Factored out the logging facility, to allow its reuse outside the
inliner.

Differential Revision: https://reviews.llvm.org/D88770
2020-10-05 18:09:17 -07:00
Mircea Trofin 7cfcecece0 [MLInliner] Simplify TFUTILS_SUPPORTED_TYPES
We only need the C++ type and the corresponding TF Enum. The other
parameter was used for the output spec json file, but we can just
standardize on the C++ type name there.

Differential Revision: https://reviews.llvm.org/D86549
2020-08-25 14:19:39 -07:00
Mircea Trofin ca7973cf18 [NFC]{MLInliner] Point out the tests' model dependencies 2020-08-06 09:57:26 -07:00
Mircea Trofin b18c41c66f [TFUtils] Expose untyped accessor to evaluation result tensors
These were implementation detail, but become necessary for generic data
copying.

Also added const variations to them, and move assignment, since we had a
move ctor (and the move assignment helps in a subsequent patch).

Differential Revision: https://reviews.llvm.org/D85262
2020-08-05 10:22:45 -07:00
Mircea Trofin 90b9c49ca6 [llvm] Expose type and element count-related APIs on TensorSpec
Added a mechanism to check the element type, get the total element
count, and the size of an element.

Differential Revision: https://reviews.llvm.org/D85250
2020-08-04 17:32:16 -07:00
Mircea Trofin 4b1b109c51 [llvm] Add a parser from JSON to TensorSpec
A JSON->TensorSpec utility we will use subsequently to specify
additional outputs needed for certain training scenarios.

Differential Revision: https://reviews.llvm.org/D84976
2020-08-03 09:49:31 -07:00
Mircea Trofin 71059257bd [llvm][NFC] TensorSpec abstraction for ML evaluator
Further abstracting the specification of a tensor, to more easily
support different types and shapes of tensor, and also to perform
initialization up-front, at TFModelEvaluator construction time.

Differential Revision: https://reviews.llvm.org/D84685
2020-07-29 16:29:21 -07:00
Mircea Trofin 4f763b2172 [llvm][NFC] Hide the tensorflow dependency from headers.
Summary:
This change avoids exposing tensorflow types when including TFUtils.h.
They are just an implementation detail, and don't need to be used
directly when implementing an analysis requiring ML model evaluation.

The TFUtils APIs, while generically typed, are still not exposed unless
the tensorflow C library is present, as they currently have no use
otherwise.

Reviewers: mehdi_amini, davidxl

Subscribers: hiraditya, llvm-commits

Tags: #llvm

Differential Revision: https://reviews.llvm.org/D83843
2020-07-14 21:14:11 -07:00
Mircea Trofin caf395ee8c Reapply "[llvm] Native size estimator for training -Oz inliner"
This reverts commit 9908a3b9f5.

The fix was to exclude the content of TFUtils.h (automatically
included in the LLVM_Analysis module, when LLVM_ENABLE_MODULES is enabled).

Differential Revision: https://reviews.llvm.org/D82817
2020-07-13 16:26:26 -07:00
Davide Italiano 9908a3b9f5 Revert "[llvm] Native size estimator for training -Oz inliner"
This reverts commit 83080a294a as
it breaks the macOS modules build.
2020-07-13 13:13:36 -07:00
Mircea Trofin 83080a294a [llvm] Native size estimator for training -Oz inliner
Summary:
This is an experimental ML-based native size estimator, necessary for
computing partial rewards during -Oz inliner policy training. Data
extraction for model training will be provided in a separate patch.

RFC: http://lists.llvm.org/pipermail/llvm-dev/2020-April/140763.html

Reviewers: davidxl, jdoerfert

Subscribers: mgorny, hiraditya, mgrang, arphaman, llvm-commits

Tags: #llvm

Differential Revision: https://reviews.llvm.org/D82817
2020-07-13 10:13:56 -07:00