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authorGravatar Sanjoy Das <sanjoy@google.com>2018-09-11 12:03:48 -0700
committerGravatar TensorFlower Gardener <gardener@tensorflow.org>2018-09-11 12:08:47 -0700
commita9e73ddb3d40514af4144278f6450e5c1c806f8b (patch)
treebec80a4b76a44928c71378d1abbf73769d4a84e7 /tensorflow/compiler/xla/tests
parent29c3c08f23e14eaff1dbd7a3c66139314c045574 (diff)
Make exhaustive_f32_elementwise_op_test build again and mark it as broken
It was not running as part of TAP and there have been some regressions. Mark it as broken while we figure out what's going on to unblock b/114790989. PiperOrigin-RevId: 212494775
Diffstat (limited to 'tensorflow/compiler/xla/tests')
-rw-r--r--tensorflow/compiler/xla/tests/BUILD1
-rw-r--r--tensorflow/compiler/xla/tests/exhaustive_f32_elementwise_op_test.cc10
2 files changed, 6 insertions, 5 deletions
diff --git a/tensorflow/compiler/xla/tests/BUILD b/tensorflow/compiler/xla/tests/BUILD
index d0bda45cf8..30e3077edb 100644
--- a/tensorflow/compiler/xla/tests/BUILD
+++ b/tensorflow/compiler/xla/tests/BUILD
@@ -647,6 +647,7 @@ xla_test(
],
shard_count = 48,
tags = [
+ "broken",
"manual",
"notap",
],
diff --git a/tensorflow/compiler/xla/tests/exhaustive_f32_elementwise_op_test.cc b/tensorflow/compiler/xla/tests/exhaustive_f32_elementwise_op_test.cc
index 738f2600d4..51b50d456e 100644
--- a/tensorflow/compiler/xla/tests/exhaustive_f32_elementwise_op_test.cc
+++ b/tensorflow/compiler/xla/tests/exhaustive_f32_elementwise_op_test.cc
@@ -45,22 +45,22 @@ class ExhaustiveF32ElementwiseOpTest
i < known_incorrect_range.second) {
// If the operation is known to be buggy on a specific input clamp that
// input to 0 under the assumption that the op is at least correct on 0.
- input_literal->Set({i - begin}, 0.0f);
+ input_literal.Set({i - begin}, 0.0f);
} else {
- input_literal->Set({i - begin}, tensorflow::bit_cast<float, int>(i));
+ input_literal.Set({i - begin}, tensorflow::bit_cast<float, int>(i));
}
}
TF_ASSERT_OK_AND_ASSIGN(std::unique_ptr<GlobalData> input_data,
- client_->TransferToServer(*input_literal));
+ client_->TransferToServer(input_literal));
- auto input = Parameter(&builder, 0, input_literal->shape(), "input");
+ auto input = Parameter(&builder, 0, input_literal.shape(), "input");
enqueue_op(&builder, input);
std::vector<float> expected_result;
expected_result.reserve(input_size);
for (int64 i = 0; i < input_size; i++) {
- expected_result.push_back(evaluate_op(input_literal->Get<float>({i})));
+ expected_result.push_back(evaluate_op(input_literal.Get<float>({i})));
}
ComputeAndCompareR1<float>(&builder, expected_result, {input_data.get()},