tensorflow/WORKSPACE
Christian Sigg 36d0f2e194 Simplify initialization of bazel repositories that TensorFlow depends on.
Repositories depending on TensorFlow should use the content of the WORKSPACE file to initialize TensorFlow and its dependencies. This will make it much less likely for us to break dependent projects when we add/change TensorFlow's dependencies.

PiperOrigin-RevId: 345391447
Change-Id: Ia5f66a341247d0da491e40aee39f460ac10d5c9b
2020-12-02 23:58:52 -08:00

21 lines
626 B
Python

workspace(name = "org_tensorflow")
# Initialize the TensorFlow repository and all dependencies.
#
# The cascade of load() statements and workspace() calls works around the
# restriction that load() statements need to be at the top of .bzl files.
# E.g. we can not retrieve a new repository with http_archive and then load()
# a macro from that repository in the same file.
load("@//tensorflow:workspace3.bzl", "workspace")
workspace()
load("@//tensorflow:workspace2.bzl", "workspace")
workspace()
load("@//tensorflow:workspace1.bzl", "workspace")
workspace()
load("@//tensorflow:workspace0.bzl", "workspace")
workspace()