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CODEOWNERS
# Where component owners are known, add them here. /tensorflow/c/eager @qqfish /tensorflow/core/common_runtime/eager @qqfish /tenosrflow/core/debug @caisq /tensorflow/core/kernels/mkl/ @penpornk /tensorflow/core/kernels/sparse/ @penpornk /tensorflow/core/nccl/ @azaks2 @chsigg /tensorflow/python/autograph/ @mdanatg /tensorflow/python/debug @caisq /tensorflow/python/eager @rohan100jain /tensorflow/tools/docs/ @markdaoust
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ci/devinfra/docker_windows/Dockerfile
"--quiet", "--wait", "--nocache", \ "--add", "Microsoft.VisualStudio.Workload.VCTools", \ "--add", "Microsoft.VisualStudio.Component.VC.Tools.x86.x64", \ "--add", "Microsoft.VisualStudio.Component.Windows10SDK.19041" -Wait; \ Start-Process -FilePath C:/TEMP/vs_buildtools.exe -ArgumentList "--installPath", "C:/VS", \ "--quiet", "--wait", "--nocache", "--includeOptional", \
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tensorflow/c/eager/parallel_device/parallel_device_lib.cc
std::string component_summary; TF_RETURN_IF_ERROR(component->SummarizeValue(component_summary)); absl::StrAppend(&summary, component_index == 0 ? "" : ", ", "\"", summarized_devices[component_index], "\": ", component_summary); } summary += "}"; return absl::OkStatus(); } } // namespace parallel_device
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tensorflow/c/eager/immediate_execution_tensor_handle.h
// // -1 indicates an unknown axis length; this is unreachable for most standard // ImmediateExecutionTensorHandles, but comes up for example when computing // the shape of a parallel tensor with component shapes differing across // devices. virtual Status Dim(int dim_index, int64_t* dim) const = 0; // Returns the device which created the handle. virtual const char* DeviceName(Status* status) const = 0;
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tensorflow/c/eager/parallel_device/parallel_device_lib.h
public: // Construct a ParallelTensor from TensorHandles placed on the component // devices of a ParallelDevice. If called, ParallelTensor::Shape inspects // `components` to determine a shape. static std::unique_ptr<ParallelTensor> FromTensorHandles( const ParallelDevice& parallel_device, std::vector<TensorHandlePtr> components, TF_Status* status);
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tensorflow/c/eager/parallel_device/parallel_device.h
// two component devices, running `x = TPUReplicatedInput(inputs=[a, b])` on the // parallel device creates a parallel tensor `x` with `a` on the first of // `underlying_devices` and `b` on the second. Running `a_unpacked, b_unpacked = // TPUReplicatedOutput(input=x, num_replicas=2)` un-packs the parallel tensor // into its components. //
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CONTRIBUTING.md
``` For example, to run all tests under tensorflow/python, do: ```bash bazel test ${flags} //tensorflow/python/... ``` For a single component e.g. softmax op: ```bash bazel test ${flags} tensorflow/python/kernel_tests/nn_ops:softmax_op_test ``` For a single/parameterized test e.g. `test_capture_variables` in
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tensorflow/c/eager/parallel_device/parallel_device_testlib.cc
std::array<TensorHandlePtr, 2> components; ExtractPerDeviceValues(context, read.get(), &components, status.get()); ASSERT_TRUE(TF_GetCode(status.get()) == TF_OK) << TF_Message(status.get()); ExpectScalarEq<float>(components[0].get(), 20.); ExpectScalarEq<float>(components[1].get(), 20.); std::string first_device = TFE_TensorHandleBackingDeviceName(components[0].get(), status.get());
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tensorflow/c/eager/parallel_device/parallel_device_test.cc
components[0] = negative_one_cpu.get(); components[1] = negative_one_cpu.get(); TensorHandlePtr first_negative_one = CreatePerDeviceValues( context.get(), components, first_device_name, status.get()); ASSERT_EQ(TF_GetCode(status.get()), TF_OK) << TF_Message(status.get()); components[0] = first_negative_one.get(); components[1] = negative_one_cpu.get();
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RELEASE.md
`tf.data.Options()`. * Support cancellation of long-running `reduce`. * Now we use `dataset` node name as prefix instead of the op name, to identify the component correctly in metrics, for pipelines with repeated components. * Improve the performance of datasets using `from_tensors()`. * Promoting `unbatch` from experimental to core API.
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