Merge pull request #30011 from angersson:master

PiperOrigin-RevId: 254269843

CONTRIBUTING.md

@@ -168,11 +168,11 @@ There are two ways to run TensorFlow unit tests.
     [GPU developer Dockerfile](https://github.com/tensorflow/tensorflow/blob/master/tensorflow/tools/dockerfiles/dockerfiles/devel-gpu.Dockerfile)
     for the required packages. Alternatively, use the said
     [Docker images](https://hub.docker.com/r/tensorflow/tensorflow/tags/), e.g.,
-    `tensorflow/tensorflow:nightly-devel` and
-    `tensorflow/tensorflow:nightly-devel-gpu` for development to avoid
-    installing the packages directly on your system (in which case remember to
-    change directory from `/root` to `/tensorflow` once you get into the running
-    container so `bazel` can find the `tensorflow` workspace).
+    `tensorflow/tensorflow:devel` and `tensorflow/tensorflow:devel-gpu` for
+    development to avoid installing the packages directly on your system (in
+    which case remember to change directory from `/root` to `/tensorflow` once
+    you get into the running container so `bazel` can find the `tensorflow`
+    workspace).
 
     Once you have the packages installed, you can run a specific unit test in
     bazel by doing as follows:

tensorflow/tools/dockerfiles/assembler.py

@@ -32,13 +32,13 @@ import collections
 import copy
 import errno
 import itertools
+import json
 import multiprocessing
 import os
 import platform
 import re
 import shutil
 import sys
-import json
 
 from absl import app
 from absl import flags
@@ -162,6 +162,7 @@ flags.DEFINE_string(
 # Note: can add python references with e.g.
 # !!python/name:builtins.str
 # !!python/name:__main__.funcname
+# (but this may not be considered safe?)
 SCHEMA_TEXT = """
 header:
   type: string
@@ -475,13 +476,13 @@ def main(argv):
 
   # Read the full spec file, used for everything
   with open(FLAGS.spec_file, 'r') as spec_file:
-    tag_spec = yaml.load(spec_file)
+    tag_spec = yaml.safe_load(spec_file)
 
   # Get existing partial contents
   partials = gather_existing_partials(FLAGS.partial_dir)
 
   # Abort if spec.yaml is invalid
-  schema = yaml.load(SCHEMA_TEXT)
+  schema = yaml.safe_load(SCHEMA_TEXT)
   v = TfDockerTagValidator(schema, partials=partials)
   if not v.validate(tag_spec):
     eprint('> Error: {} is an invalid spec! The errors are:'.format(

tensorflow/tools/dockerfiles/dockerfiles/devel-cpu-jupyter.Dockerfile

@@ -92,6 +92,7 @@ RUN ${PIP} --no-cache-dir install \
     scipy \
     sklearn \
     pandas \
+    future \
     portpicker \
     && test "${USE_PYTHON_3_NOT_2}" -eq 1 && true || ${PIP} --no-cache-dir install \
     enum34

tensorflow/tools/dockerfiles/dockerfiles/devel-cpu.Dockerfile

@@ -92,6 +92,7 @@ RUN ${PIP} --no-cache-dir install \
     scipy \
     sklearn \
     pandas \
+    future \
     portpicker \
     && test "${USE_PYTHON_3_NOT_2}" -eq 1 && true || ${PIP} --no-cache-dir install \
     enum34

tensorflow/tools/dockerfiles/dockerfiles/devel-gpu-jupyter.Dockerfile

@@ -124,6 +124,7 @@ RUN ${PIP} --no-cache-dir install \
     scipy \
     sklearn \
     pandas \
+    future \
     portpicker \
     && test "${USE_PYTHON_3_NOT_2}" -eq 1 && true || ${PIP} --no-cache-dir install \
     enum34

tensorflow/tools/dockerfiles/dockerfiles/devel-gpu.Dockerfile

@@ -124,6 +124,7 @@ RUN ${PIP} --no-cache-dir install \
     scipy \
     sklearn \
     pandas \
+    future \
     portpicker \
     && test "${USE_PYTHON_3_NOT_2}" -eq 1 && true || ${PIP} --no-cache-dir install \
     enum34

tensorflow/tools/dockerfiles/partials/ubuntu/bazel.partial.Dockerfile

@@ -19,6 +19,7 @@ RUN ${PIP} --no-cache-dir install \
     scipy \
     sklearn \
     pandas \
+    future \
     portpicker \
     && test "${USE_PYTHON_3_NOT_2}" -eq 1 && true || ${PIP} --no-cache-dir install \
     enum34