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Change links to point to main (tensorflow#1134)
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texasmichelle authored Dec 4, 2020
1 parent b7148bc commit e3a5711
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Showing 6 changed files with 11 additions and 11 deletions.
2 changes: 1 addition & 1 deletion .github/disabled-workflows/swift-format.yml
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Expand Up @@ -2,7 +2,7 @@ name: swift-format

on:
pull_request:
branches: [ master ]
branches: [ main ]

jobs:
swift-format:
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2 changes: 1 addition & 1 deletion CONTRIBUTING.md
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Expand Up @@ -57,7 +57,7 @@ make sure your changes are consistent with the guidelines.
#### License

Include a license at the top of new files.
* [License example](https://github.com/tensorflow/swift-apis/blob/master/Sources/TensorFlow/Layer.swift)
* [License example](https://github.com/tensorflow/swift-apis/blob/main/Sources/TensorFlow/Layer.swift)

#### Swift coding style

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8 changes: 4 additions & 4 deletions Documentation/X10/API_GUIDE.md
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Expand Up @@ -174,7 +174,7 @@ after the optimizer step explicitly synchronizes the CPU and the X10 device.
The internal data representation of X10 tensors is opaque to the user. This
allows XLA to control a tensor's memory layout for better performance.

[x10_lib]: https://github.com/tensorflow/swift-apis/tree/master/Sources/x10
[copying]: https://github.com/tensorflow/swift-apis/tree/master/Sources/TensorFlow/Core/CopyableToDevice.swift
[training]: https://github.com/tensorflow/swift-apis/tree/master/Sources/x10/swift_bindings/training_loop.swift
[low-level]: https://github.com/tensorflow/swift-apis/blob/master/Sources/TensorFlow/Core/MixedPrecision.swift
[x10_lib]: https://github.com/tensorflow/swift-apis/tree/main/Sources/x10
[copying]: https://github.com/tensorflow/swift-apis/tree/main/Sources/TensorFlow/Core/CopyableToDevice.swift
[training]: https://github.com/tensorflow/swift-apis/tree/main/Sources/x10/swift_bindings/training_loop.swift
[low-level]: https://github.com/tensorflow/swift-apis/blob/main/Sources/TensorFlow/Core/MixedPrecision.swift
4 changes: 2 additions & 2 deletions README.md
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Expand Up @@ -194,10 +194,10 @@ participating.
[s4tf]: https://github.com/tensorflow/swift
[integrated]: https://github.com/apple/swift/tree/tensorflow#customize-tensorflow-support
[blank_colab]: https://colab.research.google.com/notebook#create=true&language=swift
[usage]: https://github.com/tensorflow/swift/blob/master/Usage.md
[usage]: https://github.com/tensorflow/swift/blob/main/Usage.md
[gradient]: https://www.tensorflow.org/swift/api_docs/Functions#/s:10TensorFlow8gradient2at2in13TangentVectorQzx_AA0A0Vyq_GxXEtAA14DifferentiableRzAA0aB13FloatingPointR_r0_lF
[swift-models]: https://github.com/tensorflow/swift-models
[toolchain]: https://github.com/tensorflow/swift/blob/master/Installation.md
[toolchain]: https://github.com/tensorflow/swift/blob/main/Installation.md
[bazel]: https://docs.bazel.build/versions/master/install.html
[bazelisk]: https://github.com/bazelbuild/bazelisk
[configure.py]: https://github.com/tensorflow/tensorflow/blob/master/configure.py
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4 changes: 2 additions & 2 deletions Sources/x10/xla_client/mesh_service.cc
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Expand Up @@ -265,12 +265,12 @@ MeshClient* MeshClient::Get() {
MeshClient::MeshClient(const std::string& address) : impl_(new Impl(address)) {
int64 connect_wait_seconds =
sys_util::GetEnvInt("XRT_MESH_CONNECT_WAIT", 300);
TF_LOG(INFO) << "Waiting to connect to client mesh master ("
TF_LOG(INFO) << "Waiting to connect to client mesh ("
<< connect_wait_seconds << " seconds) " << address;
XLA_CHECK(impl_->channel->WaitForConnected(
std::chrono::system_clock::now() +
std::chrono::seconds(connect_wait_seconds)))
<< "Failed to connect to client mesh master: " << address;
<< "Failed to connect to client mesh: " << address;
}

MeshClient::~MeshClient() {}
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2 changes: 1 addition & 1 deletion Sources/x10/xla_client/xrt_computation_client.cc
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Expand Up @@ -1602,7 +1602,7 @@ void XrtComputationClient::InitializeDevices(
auto it = options_.workers_map.find(worker);
XLA_CHECK(it != options_.workers_map.end());

TF_VLOG(1) << "Configuring TPU for master worker " << worker.name << ":"
TF_VLOG(1) << "Configuring TPU for worker " << worker.name << ":"
<< worker.task_no << " at " << it->second;
tensorflow::tpu::TopologyProto worker_topology_proto =
InitializeAndFetchTopology(worker.name, worker.task_no, it->second,
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