- 12 7月, 2019 35 次提交
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由 Andy Ly 提交于
PiperOrigin-RevId: 257684824
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 257684378
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由 Reed Wanderman-Milne 提交于
I tried to fix this in 1ec90f6a, but it was rolled back in e737182e because it broke cases where one layer tried accessed another layer's variables when AutoCastVariables were used, such as in RNNs. This is a much simpler fix. I added RNN mixed precision tests, because RNNs use tf.functions, which did not work with mixed precision before this change. PiperOrigin-RevId: 257684192
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由 A. Unique TensorFlower 提交于
Fix build with libc++, which follows recent changes to the specification of std::variant, disallowing certain implicit conversions during initialization. PiperOrigin-RevId: 257683060
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由 Rohan Jain 提交于
PiperOrigin-RevId: 257679909
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由 Juhyun Lee 提交于
This is prep work to introduce shared variables to GeneratedCode. PiperOrigin-RevId: 257677195
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由 Jacques Pienaar 提交于
Previously the name used for an output's occurrence was not incremented resulting in it being reusable. Also forward a fix from the other UniqueName call (these should be extracted into a common class). PiperOrigin-RevId: 257673679
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由 Eugene Brevdo 提交于
Limit the stack trace to 5 frames. PiperOrigin-RevId: 257673667
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由 Dan Ringwalt 提交于
When rotating by 45 degrees with nearest interpolation, we have to round to break the tie between input pixels, and rounding seems to be platform-specific. PiperOrigin-RevId: 257672941
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由 Andy Ly 提交于
[Grappler] Check layout agnostic ops Const fanin dimensions in GenericLayoutOptimizer if they can be permuted. PiperOrigin-RevId: 257669361
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由 Nupur Garg 提交于
PiperOrigin-RevId: 257668719
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由 Mihai Maruseac 提交于
PiperOrigin-RevId: 257666993
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 257666441
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 257665916
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 257663555
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由 William Chargin 提交于
Now that TensorBoard 1.14.0 has been released, our nightlies have moved up to 1.15.x alphas. PiperOrigin-RevId: 257662026
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由 Peter Hawkins 提交于
PiperOrigin-RevId: 257660458
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由 Penporn Koanantakool 提交于
PiperOrigin-RevId: 257656880
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由 Guangda Lai 提交于
Make TF-TRT python tests 2.0 compatible by adding v2 only tests and decorating all existing tests with run_v1_only. PiperOrigin-RevId: 257653149
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由 Guangda Lai 提交于
since GraphConverter is not used elsewhere. PiperOrigin-RevId: 257653003
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 257650763
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由 Pavithra Vijay 提交于
Fix issue - in multi-output model if class weight is specified just for some outputs the weights get incorrectly mapped to placeholders PiperOrigin-RevId: 257650645
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由 A. Unique TensorFlower 提交于
This allows for the attribute to hold symbolic references to other operations than FuncOp. This also allows for removing the dependence on FuncOp from the base Builder. PiperOrigin-RevId: 257650017
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由 Andy Ly 提交于
PiperOrigin-RevId: 257648888
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由 A. Unique TensorFlower 提交于
Occasionally tensorflow::HistogramFixedWidthFunctor::Compute triggers a segmentation fault 11. It happens when the argument i of index_to_bin() is negative, which is caused by casting a big (x-a)/step int64 value that exceeds int32 range to int32. Switching the order of cwiseMin and cast fixes the problem. PiperOrigin-RevId: 257647164
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由 A. Unique TensorFlower 提交于
PiperOrigin-RevId: 257646455
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 257644752
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由 Ashwin Murthy 提交于
PiperOrigin-RevId: 257644235
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由 Sanjoy Das 提交于
//tools/target_cpu:haswell isn't present in open source. PiperOrigin-RevId: 257644093
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由 Derek Murray 提交于
This change replaces an std::function<> instance variable that has the same value for every KernelAndDevice object with a static local variable. PiperOrigin-RevId: 257641403
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由 A. Unique TensorFlower 提交于
Add detection_responder which allows each platform to process the person detection output in its own way. For example, sparkfun_edge lights up the yellow LED for no person and the green LED for person, and toggles the blue LED on each run. PiperOrigin-RevId: 257638242
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由 Gaurav Jain 提交于
PiperOrigin-RevId: 257637727
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由 Ihor Indyk 提交于
[tf.data] Increase the number of `iterator.get_next()` calls to 10000 (from 1000) in `map_and_interleave` autotuning benchmark to decrease variance of the output. PiperOrigin-RevId: 257624991
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由 Prakalp Srivastava 提交于
If the return of a function is an unsigned tensor type, it was being modeled as standard int type, losing information that the return is unsigned. PiperOrigin-RevId: 257623093
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由 TensorFlower Gardener 提交于
Merge pull request #30299 from ROCmSoftwarePlatform:google_upstream_rocm_stream_executor_updates_190701 PiperOrigin-RevId: 257617613
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- 11 7月, 2019 5 次提交
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由 Sergei Lebedev 提交于
PiperOrigin-RevId: 257614950
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由 Peter Hawkins 提交于
Also move RegisterCpuCustomCallTarget into the main Python binding module (xla.cc) since it is unrelated to anything else in local_client.*. PiperOrigin-RevId: 257612668
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由 Edward Loper 提交于
In NestedStructureCoder: fixed bug where a TensorSpec with name=None would get deserialized with name=''. PiperOrigin-RevId: 257610414
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由 TensorFlower Gardener 提交于
PiperOrigin-RevId: 257610259
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由 Peter Hawkins 提交于
Currently on CPU and GPU there is no limit to how many operations the host can enqueue on the device stream. On GPU this doesn't usually cause a problem because the allocator is logically synchronized to the tail of the compute stream, and so we can free and reuse memory for operations enqueued on the stream. On CPU, the allocator is logically synchronized to the head of the compute stream, which means that the allocator cannot reuse buffers between operations enqueued on the stream. This means that the memory usage is proportional to the number of enqueued operations, which can rapidly blow up. Add a semaphore class and use it to set a moderate limit on the depth of the queue (32). The existing "synchronous" mode, used on TPU at present, is a special case of this support where the queue depth is 1. This may help with https://github.com/google/jax/issues/928 . PiperOrigin-RevId: 257606960
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