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-rw-r--r--tensorflow/compiler/tests/adam_test.py7
-rw-r--r--tensorflow/compiler/tests/ftrl_test.py7
-rw-r--r--tensorflow/compiler/tests/reduce_ops_test.py2
-rw-r--r--tensorflow/compiler/xla/literal_test.cc4
-rw-r--r--tensorflow/compiler/xla/service/hlo_evaluator_test.cc4
-rw-r--r--tensorflow/compiler/xla/tests/bfloat16_test.cc4
-rw-r--r--tensorflow/compiler/xla/tests/reduce_window_test.cc2
-rw-r--r--tensorflow/core/lib/bfloat16/bfloat16.h4
-rw-r--r--tensorflow/python/kernel_tests/sparse_matmul_op_test.py2
9 files changed, 19 insertions, 17 deletions
diff --git a/tensorflow/compiler/tests/adam_test.py b/tensorflow/compiler/tests/adam_test.py
index 0d2e4d0296..df0f21471a 100644
--- a/tensorflow/compiler/tests/adam_test.py
+++ b/tensorflow/compiler/tests/adam_test.py
@@ -22,6 +22,7 @@ import numpy as np
from tensorflow.compiler.tests import xla_test
from tensorflow.python.framework import constant_op
+from tensorflow.python.framework import dtypes
from tensorflow.python.ops import array_ops
from tensorflow.python.ops import resource_variable_ops
from tensorflow.python.ops import variable_scope
@@ -53,7 +54,7 @@ class AdamOptimizerTest(xla_test.XLATestCase):
def testBasic(self):
for dtype in self.float_types:
# TODO: test fails for float16 due to excessive precision requirements.
- if dtype == np.float16:
+ if dtype in [np.float16, dtypes.bfloat16.as_numpy_dtype]:
continue
with self.test_session(), self.test_scope():
variable_scope.get_variable_scope().set_use_resource(True)
@@ -95,7 +96,7 @@ class AdamOptimizerTest(xla_test.XLATestCase):
def testTensorLearningRate(self):
for dtype in self.float_types:
# TODO: test fails for float16 due to excessive precision requirements.
- if dtype == np.float16:
+ if dtype in [np.float16, dtypes.bfloat16.as_numpy_dtype]:
continue
with self.test_session(), self.test_scope():
variable_scope.get_variable_scope().set_use_resource(True)
@@ -137,7 +138,7 @@ class AdamOptimizerTest(xla_test.XLATestCase):
def testSharing(self):
for dtype in self.float_types:
# TODO: test fails for float16 due to excessive precision requirements.
- if dtype == np.float16:
+ if dtype in [np.float16, dtypes.bfloat16.as_numpy_dtype]:
continue
with self.test_session(), self.test_scope():
variable_scope.get_variable_scope().set_use_resource(True)
diff --git a/tensorflow/compiler/tests/ftrl_test.py b/tensorflow/compiler/tests/ftrl_test.py
index 7ca50b02d9..1c9a8a82fa 100644
--- a/tensorflow/compiler/tests/ftrl_test.py
+++ b/tensorflow/compiler/tests/ftrl_test.py
@@ -29,7 +29,6 @@ from tensorflow.python.training import adagrad
from tensorflow.python.training import ftrl
from tensorflow.python.training import gradient_descent
-
class FtrlOptimizerTest(xla_test.XLATestCase):
def initVariableAndGradient(self, dtype):
@@ -196,7 +195,11 @@ class FtrlOptimizerTest(xla_test.XLATestCase):
# Validate updated params
self.assertAllCloseAccordingToType(
- np.array([-7.66718769, -10.91273689]), var0.eval(), rtol=1e-4)
+ np.array([-7.66718769, -10.91273689]),
+ var0.eval(),
+ rtol=1e-4,
+ bfloat16_rtol=1e-1,
+ bfloat16_atol=1e-1)
self.assertAllCloseAccordingToType(
np.array([-0.93460727, -1.86147261]), var1.eval(), rtol=1e-4)
diff --git a/tensorflow/compiler/tests/reduce_ops_test.py b/tensorflow/compiler/tests/reduce_ops_test.py
index 5ae5b1bc1d..132c59c32c 100644
--- a/tensorflow/compiler/tests/reduce_ops_test.py
+++ b/tensorflow/compiler/tests/reduce_ops_test.py
@@ -219,7 +219,7 @@ class ReduceOpPrecisionTest(xla_test.XLATestCase):
bf16_max = np.float32(dtypes.bfloat16.max)
f32_max = dtypes.float32.max
- value = min(bf16_max, f32_max - bf16_max)
+ value = min(bf16_max, f32_max - bf16_max) / 2
self._testReduceSum(
dtypes.bfloat16.as_numpy_dtype(value), dtypes.bfloat16.as_numpy_dtype,
itertools.permutations([bf16_max, value, bf16_max * (-1.0)], 3))
diff --git a/tensorflow/compiler/xla/literal_test.cc b/tensorflow/compiler/xla/literal_test.cc
index aef87e46d8..1043b73723 100644
--- a/tensorflow/compiler/xla/literal_test.cc
+++ b/tensorflow/compiler/xla/literal_test.cc
@@ -122,10 +122,10 @@ TEST_F(LiteralUtilTest, LiteralScalarToString) {
auto bf16_lit = LiteralUtil::CreateR0<bfloat16>(static_cast<bfloat16>(0.5f));
ASSERT_EQ("0.5", bf16_lit->ToString());
- // 3.14 will be truncated to 3.125 in bfloat16 format.
+ // 3.14 will be rounded to 3.14062 in bfloat16 format.
auto bf16_lit_truncated =
LiteralUtil::CreateR0<bfloat16>(static_cast<bfloat16>(3.14f));
- ASSERT_EQ("3.125", bf16_lit_truncated->ToString());
+ ASSERT_EQ("3.14062", bf16_lit_truncated->ToString());
auto bf16_lit_truncated2 =
LiteralUtil::CreateR0<bfloat16>(static_cast<bfloat16>(9.001f));
diff --git a/tensorflow/compiler/xla/service/hlo_evaluator_test.cc b/tensorflow/compiler/xla/service/hlo_evaluator_test.cc
index 4b8e6260ac..139d70374f 100644
--- a/tensorflow/compiler/xla/service/hlo_evaluator_test.cc
+++ b/tensorflow/compiler/xla/service/hlo_evaluator_test.cc
@@ -932,7 +932,7 @@ TEST_P(HloEvaluatorTest, Conv2DGeneralDimensionsReversed) {
// clang-format off
// Result dimensions: [feature=1, height=1, batch=1, width=2]
Array4D<float> expected_array({{{{2514, 2685}}}});
- Array4D<float> expected_array_bf16({{{{2512, 2672}}}});
+ Array4D<float> expected_array_bf16({{{{2512, 2688}}}});
// clang-format on
auto expected = LiteralUtil::CreateR4FromArray4D<float>(
use_bfloat16_ ? expected_array_bf16 : expected_array);
@@ -1009,7 +1009,7 @@ TEST_P(HloEvaluatorTest, Conv2DGeneralDimensions) {
// clang-format off
// Result dimensions: [feature=1, height=1, batch=1, width=2]
Array4D<float> expected_array({{{{2514, 2685}}}});
- Array4D<float> expected_array_bf16({{{{2512, 2672}}}});
+ Array4D<float> expected_array_bf16({{{{2512, 2688}}}});
// clang-format on
auto expected = LiteralUtil::CreateR4FromArray4D<float>(
use_bfloat16_ ? expected_array_bf16 : expected_array);
diff --git a/tensorflow/compiler/xla/tests/bfloat16_test.cc b/tensorflow/compiler/xla/tests/bfloat16_test.cc
index 6c20f654fe..65589b0d6a 100644
--- a/tensorflow/compiler/xla/tests/bfloat16_test.cc
+++ b/tensorflow/compiler/xla/tests/bfloat16_test.cc
@@ -65,7 +65,7 @@ XLA_TEST_F(Bfloat16Test, LogOperation) {
Log(x);
ComputeAndCompareR0<bfloat16>(&builder, static_cast<bfloat16>(1.387f), {},
- error_spec_);
+ ErrorSpec(0.01, 0.01));
}
XLA_TEST_F(Bfloat16Test, NegateScalarF16) {
@@ -110,7 +110,7 @@ XLA_TEST_F(Bfloat16Test, BatchNormTraining) {
{static_cast<bfloat16>(5), static_cast<bfloat16>(5)})
.get()});
- ComputeAndCompareTuple(&builder, *expected, {}, ErrorSpec(0.01));
+ ComputeAndCompareTuple(&builder, *expected, {}, ErrorSpec(0.01, 0.02));
}
XLA_TEST_F(Bfloat16Test, BatchNormGrad) {
diff --git a/tensorflow/compiler/xla/tests/reduce_window_test.cc b/tensorflow/compiler/xla/tests/reduce_window_test.cc
index 7c8b029675..049877b1d7 100644
--- a/tensorflow/compiler/xla/tests/reduce_window_test.cc
+++ b/tensorflow/compiler/xla/tests/reduce_window_test.cc
@@ -56,7 +56,7 @@ class ReduceWindowTestBase : public ClientLibraryTestBase {
public:
ErrorSpec DefaultErrorSpec() const {
if (use_bfloat16()) {
- return ErrorSpec(1e-1, 5e-2);
+ return ErrorSpec(2e-1, 6e-2);
} else {
return ErrorSpec(1e-3, 1e-3);
}
diff --git a/tensorflow/core/lib/bfloat16/bfloat16.h b/tensorflow/core/lib/bfloat16/bfloat16.h
index d6f3f26cd5..5c917e80c1 100644
--- a/tensorflow/core/lib/bfloat16/bfloat16.h
+++ b/tensorflow/core/lib/bfloat16/bfloat16.h
@@ -61,9 +61,7 @@ struct bfloat16 {
}
B16_DEVICE_FUNC explicit bfloat16(const float v) {
- // TODO(asabne) : change the below line to
- // value = round_to_bfloat16(v).value;
- value = truncate_to_bfloat16(v).value;
+ value = round_to_bfloat16(v).value;
}
B16_DEVICE_FUNC explicit bfloat16(const double val)
diff --git a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
index 4935ed6ca5..f50e39d6d5 100644
--- a/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
+++ b/tensorflow/python/kernel_tests/sparse_matmul_op_test.py
@@ -157,7 +157,7 @@ class MatMulGradientTest(test.TestCase):
m, [3, 4],
x_init_value=b.eval(),
delta=delta))
- self.assertLess(err, delta / 2.)
+ self.assertLessEqual(err, delta / 2.)
def testGradientInput(self):
for tr_a in [True, False]:
generated by cgit v1.2.3 (git 2.39.1) at 2024-06-18 12:03:06 +0000