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Results 1 - 3 of 3 for ApplyRemat (0.37 sec)
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tensorflow/compiler/mlir/lite/experimental/remat/rematerializer_test.cc
ASSERT_THAT(remat.GetMemProfile(), ElementsAreArray({1, 3, 7, 15, 23, 19, 9, 4})); EXPECT_CALL(remat, ApplyRemat(FieldsAre(/*begin=*/2, /*end=*/3, /*insert=*/5))); EXPECT_CALL(remat, ApplyRemat(FieldsAre(/*begin=*/0, /*end=*/1, /*insert=*/8)));
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 14 20:57:44 UTC 2023 - 19.1K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/remat/rematerializer.h
// operations will be re-inserted. For each rematerialization found, // ApplyRemat is invoked (which can be used to apply the rematerialization to // the higher- level representation, e.g., MLIR, flatbuffer, ...) void RunGreedyAlgorithm(int max_cost, int max_block_length, SizeT min_savings); virtual void ApplyRemat(const RematSpec& remat) {} protected:
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 14 20:57:44 UTC 2023 - 12K bytes - Viewed (0) -
tensorflow/compiler/mlir/lite/experimental/remat/rematerializer.cc
Registered: Sun Jun 16 05:45:23 UTC 2024 - Last Modified: Tue Mar 14 20:57:44 UTC 2023 - 13.7K bytes - Viewed (0)