Merge pull request #43159 from ROCmSoftwarePlatform:google-upstream-disabled-rocm-tests

PiperOrigin-RevId: 337844806
Change-Id: I4847456394a8e2a7c4fad542ec360e77833bef99
This commit is contained in:
TensorFlower Gardener 2020-10-19 06:54:01 -07:00
commit ba79107f74
4 changed files with 13 additions and 0 deletions

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@ -436,6 +436,7 @@ distribute_py_test(
tags = [ tags = [
"broken", # b/170975619 "broken", # b/170975619
"multi_and_single_gpu", "multi_and_single_gpu",
"no_rocm",
"no_windows_gpu", "no_windows_gpu",
"notsan", "notsan",
], ],

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@ -19,6 +19,9 @@ from __future__ import print_function
import gc import gc
import tensorflow as tf import tensorflow as tf
from tensorflow.python.platform import test as test_lib
layers = tf.keras.layers layers = tf.keras.layers
optimizers = tf.keras.optimizers optimizers = tf.keras.optimizers
@ -150,6 +153,10 @@ class GradientCheckpointTest(tf.test.TestCase):
def test_does_not_raise_oom_exception(self): def test_does_not_raise_oom_exception(self):
if not _limit_gpu_memory(): if not _limit_gpu_memory():
self.skipTest('No virtual GPUs found') self.skipTest('No virtual GPUs found')
if test_lib.is_built_with_rocm():
self.skipTest(
'ROCm MIOpen does not support searching for memory-limited'
'solvers yet so skip the subtest which would result in OOM.')
n_step = 2 n_step = 2
losses = _train_with_recompute(n_step) losses = _train_with_recompute(n_step)
self.assertLen(losses, n_step) self.assertLen(losses, n_step)

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@ -69,6 +69,7 @@ py_test(
], ],
python_version = "PY3", python_version = "PY3",
srcs_version = "PY2AND3", srcs_version = "PY2AND3",
tags = ["no_rocm"],
deps = [ deps = [
":policy", ":policy",
"//tensorflow/python:client_testlib", "//tensorflow/python:client_testlib",

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@ -159,6 +159,10 @@ class LayerCorrectnessTest(keras_parameterized.TestCase):
input_data: A Numpy array with the data of the input. If None, input data input_data: A Numpy array with the data of the input. If None, input data
will be randomly generated will be randomly generated
""" """
if f32_layer_fn == convolutional.ZeroPadding2D and \
test.is_built_with_rocm():
return
if isinstance(input_shape[0], int): if isinstance(input_shape[0], int):
input_shapes = [input_shape] input_shapes = [input_shape]
else: else: