- 12 8月, 2019 9 次提交
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262864322
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由 Taehee Jeong 提交于
PiperOrigin-RevId: 262861510
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由 A. Unique TensorFlower 提交于
failures. PiperOrigin-RevId: 262857756
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由 Feng Liu 提交于
PiperOrigin-RevId: 262855058
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由 Dero Gharibian 提交于
This is a part of a larger migration effort for tensorflow::tstring. See: https://github.com/tensorflow/community/pull/91 PiperOrigin-RevId: 262850088
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由 River Riddle 提交于
The pattern list is not modified by any of these APIs and should thus be passed with const. PiperOrigin-RevId: 262844002
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由 A. Unique TensorFlower 提交于
1/8/16 bit attrs. NFC PiperOrigin-RevId: 262843016
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由 Yanan Cao 提交于
Add tf_device dialect that models TensorFlow's actions of launching computations on accelerator devices. PiperOrigin-RevId: 262833506
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由 Feng Liu 提交于
PiperOrigin-RevId: 262828591
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- 11 8月, 2019 17 次提交
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262789479
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262787528
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262787524
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由 Gunhan Gulsoy 提交于
The function is very specific, and has limited use. PiperOrigin-RevId: 262782380
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由 Feng Liu 提交于
The existing implementation only works when the FullyConnected has none bias. This CL is to fuse the Add to the FullyConnected when there is a bias operand. PiperOrigin-RevId: 262779181
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由 Dero Gharibian 提交于
PiperOrigin-RevId: 262757814
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由 Feng Liu 提交于
The two patterns are actually to fold a sequence of Conv2D, BiasAdd/AddV2 and Mul. Technically, this sequence should be captured by a single pattern, but the current TableGen tool couldn't infer the output type of the Conv2D op, since its "depth" is 1. For this reason, a predicate to enable this pattern only if the input is defined by a Conv2D. PiperOrigin-RevId: 262757621
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由 River Riddle 提交于
The current implementation only returns one element for the splat case, which often comes as a surprise; leading to subtle/confusing bugs. The new behavior will include an iterate over the full range of elements, as defined by the shaped type, by providing the splat value for each iterator index. PiperOrigin-RevId: 262756780
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由 Andy Ly 提交于
Replace const ref of vectors with llvm::ArrayRef and pointers of TF executor ops with values in arguments of functions. Switch from passing around an OpBuilder to creating one locally when creating IslandOps and YieldOps. PiperOrigin-RevId: 262756302
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由 Dero Gharibian 提交于
Updated char* tstring::data() to conform to C++11. This is a part of a larger migration effort for tensorflow::tstring. See: https://github.com/tensorflow/community/pull/91 PiperOrigin-RevId: 262752692
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由 Mehdi Amini 提交于
This aligns with the namespace already used for the dialect. PiperOrigin-RevId: 262751499
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由 Ashwin Murthy 提交于
PiperOrigin-RevId: 262751066
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262747813
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由 Renjie Liu 提交于
PiperOrigin-RevId: 262742602
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由 Xiao Yu 提交于
Ensure we can propagate error properly when setting "TF_ENABLE_EAGER_CLIENT_STREAMING_ENQUEUE=false". PiperOrigin-RevId: 262737847
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由 Dero Gharibian 提交于
This is a part of a larger migration effort for tensorflow::tstring. See: https://github.com/tensorflow/community/pull/91 PiperOrigin-RevId: 262737181
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由 A. Unique TensorFlower 提交于
Move annotation's thread_local storage to .cc file and clean up dependencies to avoid a duplicate symbol error. PiperOrigin-RevId: 262733487
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- 10 8月, 2019 14 次提交
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由 Blake Hechtman 提交于
PiperOrigin-RevId: 262726250
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262704925
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262704920
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 262700718
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由 Ashwin Murthy 提交于
PiperOrigin-RevId: 262696484
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由 Tian Lin 提交于
PiperOrigin-RevId: 262682685
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由 River Riddle 提交于
There are currently several different terms used to refer to a parent IR unit in 'get' methods: getParent/getEnclosing/getContaining. This cl standardizes all of these methods to use 'getParent*'. PiperOrigin-RevId: 262680287
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262676072
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由 Juhyun Lee 提交于
About 15x speedup. PiperOrigin-RevId: 262675867
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由 Lei Zhang 提交于
In declarative rewrite rules, a symbol can be bound to op arguments or results in the source pattern, and it can be bound to op results in the result pattern. This means given a symbol in the pattern, it can stands for different things: op operand, op attribute, single op result, op result pack. We need a better way to model this complexity so that we can handle according to the specific kind a symbol corresponds to. Created SymbolInfo class for maintaining the information regarding a symbol. Also created a companion SymbolInfoMap class for a map of such symbols, providing insertion and querying depending on use cases. PiperOrigin-RevId: 262675515
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由 Anna R 提交于
PiperOrigin-RevId: 262675086
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由 Xiao Yu 提交于
PiperOrigin-RevId: 262671025
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 262668255
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由 Ashwin Murthy 提交于
By default, all functions are exported including main. This flag will be used to support new use cases like conversion of speech models to tflite where we want to run specific inference graphs through the converter and export specific functions (e.g. Joint, Encoder etc.) to a separate flatbuffer. PiperOrigin-RevId: 262667934
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