[XLA] Delete OOM test.

It doesn't seem to serve a useful purpose, isn't actually enabled, and is a pain to maintain.

PiperOrigin-RevId: 219202422

tensorflow/compiler/tests/BUILD

@@ -294,33 +294,6 @@ tf_xla_py_test(
     ],
 )
 
-tf_xla_py_test(
-    name = "oom_test",
-    size = "medium",
-    srcs = ["oom_test.py"],
-    # TODO(b/80081500): Re-enable on GPU. Disabled on 2018-05-21.
-    disabled_backends = [
-        "cpu",
-        "cpu_ondemand",
-        "gpu",
-    ],
-    tags = [
-        # Allocates very large amounts of memory and does not work under TSAN.
-        "notsan",
-        "optonly",  # Times out frequently in fastbuild.
-    ],
-    deps = [
-        ":xla_test",
-        "//tensorflow/python:array_ops",
-        "//tensorflow/python:array_ops_gen",
-        "//tensorflow/python:framework",
-        "//tensorflow/python:gradient_checker",
-        "//tensorflow/python:gradients",
-        "//tensorflow/python:math_ops",
-        "//tensorflow/python:platform_test",
-    ],
-)
-
 tf_xla_py_test(
     name = "conv2d_test",
     size = "medium",

tensorflow/compiler/tests/oom_test.py

@@ -1,76 +0,0 @@
-# Copyright 2018 The TensorFlow Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# ==============================================================================
-"""Functional tests for out-of-memory conditions."""
-
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-from tensorflow.compiler.tests import xla_test
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
-from tensorflow.python.ops import array_ops
-from tensorflow.python.ops import math_ops
-from tensorflow.python.ops import nn_ops
-from tensorflow.python.platform import googletest
-
-
-class OutOfMemoryTest(xla_test.XLATestCase):
-
-  def testOutputOutOfMemory(self):
-    """Allocates tensors until out of memory.
-
-    Generates a large rank-1 tensor. The tensor is an output of an XLA
-    computation, not constant.
-
-    Check that a ResourceExhaustedError is raised and can be caught.
-
-    We spin in a loop generating larger and larger tensors until an OOM event
-    happens. We may be running sandboxed, so have a small host memory limit, so
-    any hardcoded value is unlikely to land in the sweet spot between device
-    memory size and host memory size with stability.
-    """
-
-    def test_loop():
-      size = int(2e8)
-      while True:
-        with self.cached_session():
-          # Force the compiled code to not be constant by feeding in a
-          # parameter.
-          p = array_ops.placeholder(dtypes.float32, shape=[2, 1, 1])
-          with self.test_scope():
-            # Create a computation that produces a large R1 tensor as an
-            # intermediate result.  Reduce it down so that if this file was
-            # compiled without --config=cuda, we don't force a D2H copy of a
-            # large tensor and potentially OOM the host.
-            #
-            # This is a bit tricky because XLA:GPU doesn't currently support RNG
-            # ops.  Here we rely on the fact that XLA doesn't do algebraic
-            # simplifications on conv(<ones>, <filter>).
-            c = math_ops.reduce_sum(
-                nn_ops.convolution(
-                    array_ops.ones([1, size, 1]),
-                    p,
-                    padding='SAME',
-                    data_format='NWC'))
-
-            c.eval(feed_dict={p: [[[1.0]], [[2.0]]]})
-            size *= 2
-
-    self.assertRaises(errors.ResourceExhaustedError, test_loop)
-
-
-if __name__ == '__main__':
-  googletest.main()