STT-tensorflow/tensorflow/python/training/saving/BUILD
Bruce Fontaine c27b834b49 Wrap save/restore logic in tf.function when in eager mode. This allows parallel saving and restoring when using multiple devices.
PiperOrigin-RevId: 317719780
Change-Id: Ifb7e34f708da4121b49fb38d8dad046d45fedc42
2020-06-22 13:23:14 -07:00

77 lines
1.6 KiB
Python

# Description:
# Low-level utilities for reading and writing checkpoints.
load("//tensorflow:tensorflow.bzl", "cuda_py_test")
package(
default_visibility = [
"//tensorflow:internal",
],
licenses = ["notice"], # Apache 2.0
)
exports_files(["LICENSE"])
py_library(
name = "checkpoint_options",
srcs = ["checkpoint_options.py"],
deps = [
"//tensorflow/python:tf_export",
],
)
py_library(
name = "functional_saver",
srcs = ["functional_saver.py"],
srcs_version = "PY2AND3",
deps = [
":checkpoint_options",
":saveable_hook",
":saveable_object",
":saveable_object_util",
"//tensorflow/python/eager:def_function",
],
)
cuda_py_test(
name = "functional_saver_test",
size = "medium",
srcs = [
"functional_saver_test.py",
],
deps = [
":checkpoint_options",
":functional_saver",
":saveable_hook",
"//tensorflow/python/eager:remote",
"//tensorflow/python/eager:test",
],
)
py_library(
name = "saveable_object",
srcs = ["saveable_object.py"],
srcs_version = "PY2AND3",
)
py_library(
name = "saveable_hook",
srcs = ["saveable_hook.py"],
deps = [
"//tensorflow/python:constant_op",
"//tensorflow/python/training/tracking:base",
],
)
py_library(
name = "saveable_object_util",
srcs = ["saveable_object_util.py"],
srcs_version = "PY2AND3",
deps = [
"//tensorflow/python:resource_variable_ops",
"//tensorflow/python:variables",
"//tensorflow/python/training/tracking:base",
"@six_archive//:six",
],
)