- 19 12月, 2019 40 次提交
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由 Andy Ly 提交于
ConvertMaxPoolOp, ConvertRangeOp, and ConvertSigmoidOp were added to the patterns list twice. PiperOrigin-RevId: 286300831 Change-Id: I9106e8fa3c275b9ed78f5176715d0a803463f1e4
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由 Jacques Pienaar 提交于
Ran into case where failed constant folds resulted in non-deterministic test behavior (e.g., failed to fold unrelated op). Need to dig into this a bit more. PiperOrigin-RevId: 286299132 Change-Id: I290dade5fba0fd5b08dae4d696878b9196fc516d
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由 Lucy Fox 提交于
In the training case, the TF op lowers to HLO op BatchNormTraining. Otherwise, it lowers to HLO op BatchNormInference. PiperOrigin-RevId: 286297657 Change-Id: If8e14edcc8f43016f273ce29ef503ea83d639a25
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由 Amit Patankar 提交于
This version fixed a segment fault issue in GRPC. See https://github.com/grpc/grpc/pull/19531. PiperOrigin-RevId: 286294784 Change-Id: I11c585833f952fac224990e4d3e2b350a3ba1416
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由 Nupur Garg 提交于
PiperOrigin-RevId: 286290570 Change-Id: Ia30be150c3a25c81fc17a458fc3f4b85cc3da11f
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由 Dong Lin 提交于
This version fixed a segment fault issue in GRPC. See https://github.com/grpc/grpc/pull/19531. PiperOrigin-RevId: 286289959 Change-Id: I7c107f8102b3a98b493b1992bec39a4794ad23c4
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由 Zhenyu Tan 提交于
PiperOrigin-RevId: 286288622 Change-Id: I2625c877389c5a627d96ed82025d3a623c9bbb6f
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由 Francois Chollet 提交于
PiperOrigin-RevId: 286287077 Change-Id: Iea055499b8900fdb4903b7a22ca6a091e548bffe
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由 Yunlu Li 提交于
PiperOrigin-RevId: 286286868 Change-Id: I92bb40fb8eff9a16e5b382fec19befd39c93aeaa
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 286283327 Change-Id: I8fd9102c04ffe56af92fa19b01bcece139c45bae
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由 Frank Chen 提交于
PiperOrigin-RevId: 286281695 Change-Id: I021eec024331e65b2d6243e14bb477957ce0e2f6
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由 Frank Chen 提交于
PiperOrigin-RevId: 286281590 Change-Id: I2c87462702d3ec9b6e92a23968f5b02745adb777
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 286279090 Change-Id: I5f817cd51b8516ff581093413992b199674d5bdd
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由 Nick Kreeger 提交于
This version varies slightly from the current reference implementation in TFLite (original): 1.) All references to tensor_utils:: namespace are dropped due to the build incompatibility and size the include brings in (just like the rest of this port for float/hybrid-quant). 2.) Scratch tensors are re-worked into variable tensors. This is a temporary workaround until memory planning lands . 3.) An additional Tensor is required to provide pre-calculated scale values. These calculations are very expensive on low power device. PiperOrigin-RevId: 286278125 Change-Id: Ibbadb2f38a6c25b5550b4fced5b32c7a5b9420df
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 286277617 Change-Id: Ief36745883c36d48a0aad4f49aee806573502cc1
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由 Jose Baiocchi 提交于
PiperOrigin-RevId: 286276718 Change-Id: Ide2445cc395c1a28c4faf176034c2f34f41cc50a
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由 Jose Baiocchi 提交于
PiperOrigin-RevId: 286276313 Change-Id: I0010b5cceb096b639f8a8cde82debfcbae177d51
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由 Amit Patankar 提交于
PiperOrigin-RevId: 286275744 Change-Id: Ie82e11c606bb65a0853c1432d1336cca290b636c
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由 Yifei Feng 提交于
Looks like https://launchpad.net/~jonathonf is getting slowly removed. Fix "The repository 'http://ppa.launchpad.net/jonathonf/python-3.6/ubuntu xenial Release' does not have a Release file." PiperOrigin-RevId: 286273233 Change-Id: I5fd9b896f03f748fea440d5ab4077d996ebe2afd
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由 Yash Katariya 提交于
PiperOrigin-RevId: 286271783 Change-Id: I6acc71de279834957bd22271990609f79e1e2517
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 286257478 Change-Id: I56574945f4f0aba418e2bfb8dbe3a510713a65f4
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由 Peng Wang 提交于
PiperOrigin-RevId: 286257170 Change-Id: I656383638ba145405ed00ebb5279ebd900787fca
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由 Rohan Jain 提交于
PiperOrigin-RevId: 286256630 Change-Id: I91d97553a64656c575ae5a5771a9145978065910
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 286256158 Change-Id: I172217925eacb8e6c49a8182fb699ad9d7111a98
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由 Gunhan Gulsoy 提交于
PiperOrigin-RevId: 286256041 Change-Id: Ie61edb82e440deda698d21b7655ecde550c97ca2
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 286253056 Change-Id: I9928d21effe92bed1a9f131a47d9e172cd970330
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由 Daniel Situnayake 提交于
PiperOrigin-RevId: 286252818 Change-Id: Id74db3b9ed867c59b2d32cfe70079445f60ca96c
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由 Feng Liu 提交于
The optimization pass might introduce constant in the tf dialect due to the constant folding for fully connected op. These constants should be converted to standard / tfl constant instead so the quantization can work. PiperOrigin-RevId: 286251602 Change-Id: Icc6c8512f7709b719cbe0409bfe14afcb90cd571
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由 Prakalp Srivastava 提交于
'outfeed_config' is imported as a default valued string attribute. Custom support during export is required because of the shape argument required by the XlaBuilder API to set outfeed_shape field of HLO instruction. PiperOrigin-RevId: 286245978 Change-Id: I15040903f41c00c9080e090033a06580ade47fdc
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由 Sean Silva 提交于
This makes it easier to narrow down on ops that are preventing inlining. PiperOrigin-RevId: 286243868 Change-Id: I7184463b74ff89fff65db1c0610d5295fda3cb16
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 286242467 Change-Id: I9b023f6e979a18978d3cc10cca2706134bb8611e
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由 T.J. Alumbaugh 提交于
PiperOrigin-RevId: 286241942 Change-Id: Ie1320c17f6a50468a03dad2664a1c8645e09f3ce
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由 A. Unique TensorFlower 提交于
https://gitlab.com/libeigen/eigen/commit/7252163335f56f23fcc7381c1efdea47161005fa PiperOrigin-RevId: 286240066 Change-Id: I55b71da4cb6148bf2f6ec3f8daffd4cabe34a522
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由 Andy Ly 提交于
This is based on the current lowering/evaluation at https://github.com/tensorflow/tensorflow/blob/f4d29bb3635d2a7a9bb1f557d486de7fdaa3b101/tensorflow/compiler/tf2xla/kernels/concat_op.cc#L121 where for constant concat_dim and shape input tensors, an exclusive cumulative sum is performed over the concat_dim dimension of all shape input tensors. All values in other dimensions are zero'd out. PiperOrigin-RevId: 286237744 Change-Id: I49adf851d0dc5f2e6d52cac946b08b120f5e1302
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 286237503 Change-Id: Ib77a42b8f22f142d15ef6f42135852a3c8188d53
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由 Mark Daoust 提交于
Converted it to a notebook. Expanded content. PiperOrigin-RevId: 286235401 Change-Id: I7419a59b34ee7ad56b2a29732c99204ae8cb5f64
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由 River Riddle 提交于
Move the specializations of VectorTransferRewriter::matchAndRewrite back into the anonymous namespace. This appeases the GCC bug related to specializations in a different namespace. PiperOrigin-RevId: 286234667 Change-Id: I2f56a3f0e8bf7116c4721da11bc3a7b2ef756349
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由 Marcel Koester 提交于
Added test cases for the newly added LLVM operations and lowering features. Closes #300 COPYBARA_INTEGRATE_REVIEW=https://github.com/tensorflow/mlir/pull/300 from dfki-jugr:std_to_llvm da6168bbc1a369ae2e99ad3881fdddd82f075dd4 PiperOrigin-RevId: 286231169 Change-Id: I364bda2adad4054052a3a53b4cb1c3de1102864f
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由 Aart Bik 提交于
Examples: vector.print %f : f32 vector.print %x : vector<4xf32> vector.print %y : vector<3x4xf32> vector.print %z : vector<2x3x4xf32> LLVM lowering replaces these with fully unrolled calls into a small runtime support library that provides some basic printing operations (single value, opening closing bracket, comma, newline). PiperOrigin-RevId: 286230325 Change-Id: I4aec72975a3cb9612ab0aa44984c44aa014aae95
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由 Andy Ly 提交于
ConvertMaxPoolOp, ConvertRangeOp and ConvertSigmoidOp were inserted twice to the patterns list. PiperOrigin-RevId: 286228460 Change-Id: I5ddaaa22d97ddc2414e2858d20d47402429bffa0
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