experiments/STT-tensorflow
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[XLA:Python] Guard NCCL usage by if_cuda rather than if_nccl.

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if_nccl turns out to be true for non-GPU builds too.

Technically there are cases where CUDA is enabled but NCCL is not, but these cases do not apply when building XLA:Python.

PiperOrigin-RevId: 298917852
Change-Id: I06a8f3206ff5baa19aa6b9f4bdf2512e02a79eb6
This commit is contained in:
Peter Hawkins 2020-03-04 12:54:16 -08:00 committed by TensorFlower Gardener
parent 6c26c995db
commit ca8d8fbf7b
1 changed files with 3 additions and 5 deletions
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8
tensorflow/compiler/xla/python/BUILD
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@ -1,9 +1,7 @@
load("//tensorflow/core/platform:build_config.bzl", "pyx_library")
load("//tensorflow/compiler/xla:xla.bzl", "xla_py_test_deps")
load("//tensorflow:tensorflow.bzl", "py_test", "tf_cc_test")
# buildifier: disable=same-origin-load
load("//tensorflow:tensorflow.bzl", "if_nccl")
load("@local_config_cuda//cuda:build_defs.bzl", "if_cuda")
# buildifier: disable=same-origin-load
load("//tensorflow:tensorflow.bzl", "pybind_extension")
@ -298,7 +296,7 @@ cc_library(
name = "nvidia_gpu_device",
srcs = ["nvidia_gpu_device.cc"],
hdrs = ["nvidia_gpu_device.h"],
copts = if_nccl(["-DNCCL_ENABLED=1"]),
copts = if_cuda(["-DNCCL_ENABLED=1"]),
deps = [
":local_client",
"//tensorflow/compiler/xla/service/gpu:gpu_executable_run_options",
@ -310,7 +308,7 @@ cc_library(
"//tensorflow/core:bfc_allocator",
"//tensorflow/core:gpu_mem_allocator",
"//tensorflow/stream_executor:tf_allocator_adapter",
] + if_nccl(["@local_config_nccl//:nccl"]),
] + if_cuda(["@local_config_nccl//:nccl"]),
)
config_setting(