From fabbf923dea96afe440014632a3a1cd0b490b071 Mon Sep 17 00:00:00 2001
From: mazharul <mazharul.islam@intel.com>
Date: Fri, 25 Sep 2020 11:46:04 -0700
Subject: [PATCH 1/8] [Intel MKL] Suppressing auto_mixed_precision_test for
non-avx512f machine like broadwell
---
tensorflow/python/BUILD | 2 +
tensorflow/python/framework/test_util.py | 7 +
.../grappler/auto_mixed_precision_test.py | 20 ++
tensorflow/python/util/util_wrapper.cc | 337 +++++++++---------
4 files changed, 198 insertions(+), 168 deletions(-)
diff --git a/tensorflow/python/BUILD b/tensorflow/python/BUILD
index d83d21907ce..fa18b6ece79 100644
--- a/tensorflow/python/BUILD
+++ b/tensorflow/python/BUILD
@@ -743,6 +743,8 @@ tf_python_pybind_extension(
":pybind11_lib",
"//third_party/python_runtime:headers",
"@pybind11",
+ "//tensorflow/core/platform:platform_port",
+
],
)
diff --git a/tensorflow/python/framework/test_util.py b/tensorflow/python/framework/test_util.py
index bbe28991098..6ce226ac5ae 100644
--- a/tensorflow/python/framework/test_util.py
+++ b/tensorflow/python/framework/test_util.py
@@ -44,6 +44,7 @@ from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tensorflow.core.protobuf import rewriter_config_pb2
from tensorflow.python import _pywrap_stacktrace_handler
+from tensorflow.python import _pywrap_utils
from tensorflow.python import _pywrap_util_port
from tensorflow.python import tf2
from tensorflow.python.client import device_lib
@@ -1802,6 +1803,12 @@ def _disable_test(execute_func):
return disable_test_impl
+# The description is just for documentation purposes.
+def disable_nonAVX512f(description): # pylint: disable=unused-argument
+ """Execute the test method only if avx512f is supported."""
+ execute_func = _pywrap_utils.IsBF16SupportedByOneDNNOnThisCPU()
+ return _disable_test(execute_func)
+
# The description is just for documentation purposes.
def disable_xla(description): # pylint: disable=unused-argument
"""Execute the test method only if xla is not enabled."""
diff --git a/tensorflow/python/grappler/auto_mixed_precision_test.py b/tensorflow/python/grappler/auto_mixed_precision_test.py
index 0066fcb9712..5c5501f129a 100644
--- a/tensorflow/python/grappler/auto_mixed_precision_test.py
+++ b/tensorflow/python/grappler/auto_mixed_precision_test.py
@@ -428,6 +428,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv_bn(self, mode):
"""Test graph with convolution followed by batch norm."""
@@ -459,6 +460,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv3d_bn(self, mode):
"""Test graph with convolution followed by batch norm."""
@@ -484,6 +486,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv3d(self, mode):
"""Test grad ops with convolution3d graph."""
@@ -516,6 +519,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
# MKL
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv_bn_dropout(self, mode):
"""Test dropout precision of convolution batch norm graph."""
@@ -575,6 +579,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
# TODO(benbarsdell): This test has not been tried with MKL.
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_depthwise_conv2d(self, mode):
"""Test grad ops with depthwise convolution2d graph."""
@@ -610,6 +615,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_simple_loop(self, mode):
"""Test graph with while loop."""
@@ -631,6 +637,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_loop_with_vars_intertwined(self, mode):
"""Test graph with intertwined while loops."""
@@ -655,6 +662,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_multi_paths(self, mode):
"""Test graph with multiple paths."""
@@ -684,6 +692,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_multi_paths_2(self, mode):
"""Test graph with multiple paths."""
@@ -717,6 +726,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda']) # MKL doesn't support bf16 Sigmoid
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_recurrent_lstm(self, mode):
"""Test graph with recurrent lstm."""
@@ -744,54 +754,63 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_1(self, mode):
self._run_simple_loop_test(mode, 'W', 'C', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_2(self, mode):
self._run_simple_loop_test(mode, 'C', 'C', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_3(self, mode):
self._run_simple_loop_test(mode, 'W', 'G', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_4(self, mode):
self._run_simple_loop_test(mode, 'W', 'gbg', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_5(self, mode):
self._run_simple_loop_test(mode, 'b', 'gWC', 'c')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_6(self, mode):
self._run_simple_loop_test(mode, 'b', 'CWCG', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_7(self, mode):
self._run_simple_loop_test(mode, 'C', 'GWCG', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_8(self, mode):
self._run_simple_loop_test(mode, 'C', 'CgbgWC', 'g')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_noninlined_funcdef(self, mode):
"""Test graph with non-inlined function subgraph.
@@ -820,6 +839,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
+ @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_ingraph_train_loop(self, mode):
"""Tests a graph containing a while loop around a training update.
diff --git a/tensorflow/python/util/util_wrapper.cc b/tensorflow/python/util/util_wrapper.cc
index 63c70d785cc..a310b5a7fb9 100644
--- a/tensorflow/python/util/util_wrapper.cc
+++ b/tensorflow/python/util/util_wrapper.cc
@@ -15,6 +15,7 @@ limitations under the License.
#include "pybind11/pybind11.h"
#include "pybind11/pytypes.h"
+#include "tensorflow/core/platform/cpu_info.h"
#include "tensorflow/python/lib/core/pybind11_lib.h"
#include "tensorflow/python/util/util.h"
@@ -34,25 +35,23 @@ PYBIND11_MODULE(_pywrap_utils, m) {
return tensorflow::PyoOrThrow(
tensorflow::swig::RegisterPyObject(name.ptr(), type.ptr()));
});
- m.def(
- "IsTensor",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsTensor(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsTensor",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsTensor(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Check if an object is a Tensor.
)pbdoc");
- m.def(
- "IsSequence",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsSequence(o.ptr());
- return result;
- },
- R"pbdoc(
+ m.def("IsSequence",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsSequence(o.ptr());
+ return result;
+ },
+ R"pbdoc(
Returns true if its input is a collections.Sequence (except strings).
Args:
@@ -62,16 +61,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
True if the sequence is a not a string and is a collections.Sequence or a
dict.
)pbdoc");
- m.def(
- "IsSequenceOrComposite",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsSequenceOrComposite(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsSequenceOrComposite",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsSequenceOrComposite(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns true if its input is a sequence or a `CompositeTensor`.
Args:
@@ -81,16 +79,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
True if the sequence is a not a string and is a collections.Sequence or a
dict or a CompositeTensor or a TypeSpec (except string and TensorSpec).
)pbdoc");
- m.def(
- "IsCompositeTensor",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsCompositeTensor(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsCompositeTensor",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsCompositeTensor(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns true if its input is a `CompositeTensor`.
Args:
@@ -99,16 +96,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if the sequence is a CompositeTensor.
)pbdoc");
- m.def(
- "IsTypeSpec",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsTypeSpec(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsTypeSpec",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsTypeSpec(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns true if its input is a `TypeSpec`, but is not a `TensorSpec`.
Args:
@@ -117,25 +113,23 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if the sequence is a `TypeSpec`, but is not a `TensorSpec`.
)pbdoc");
- m.def(
- "IsNamedtuple",
- [](const py::handle& o, bool strict) {
- return tensorflow::PyoOrThrow(
- tensorflow::swig::IsNamedtuple(o.ptr(), strict));
- },
- R"pbdoc(
+ m.def("IsNamedtuple",
+ [](const py::handle& o, bool strict) {
+ return tensorflow::PyoOrThrow(
+ tensorflow::swig::IsNamedtuple(o.ptr(), strict));
+ },
+ R"pbdoc(
Check if an object is a NamedTuple.
)pbdoc");
- m.def(
- "IsMapping",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsMapping(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsMapping",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsMapping(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns True if `instance` is a `collections.Mapping`.
Args:
@@ -144,16 +138,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if `instance` is a `collections.Mapping`.
)pbdoc");
- m.def(
- "IsMutableMapping",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsMutableMapping(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsMutableMapping",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsMutableMapping(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns True if `instance` is a `collections.MutableMapping`.
Args:
@@ -162,16 +155,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if `instance` is a `collections.MutableMapping`.
)pbdoc");
- m.def(
- "IsMappingView",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsMappingView(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsMappingView",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsMappingView(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns True if considered a mapping view for the purposes of Flatten()`.
Args:
@@ -180,16 +172,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if considered a mapping view for the purposes of Flatten().
)pbdoc");
- m.def(
- "IsAttrs",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsAttrs(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsAttrs",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsAttrs(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns True if `instance` is an instance of an `attr.s` decorated class.
Args:
@@ -198,36 +189,33 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if `instance` is an instance of an `attr.s` decorated class.
)pbdoc");
- m.def(
- "SameNamedtuples",
- [](const py::handle& o1, const py::handle& o2) {
- return tensorflow::PyoOrThrow(
- tensorflow::swig::SameNamedtuples(o1.ptr(), o2.ptr()));
- },
- R"pbdoc(
+ m.def("SameNamedtuples",
+ [](const py::handle& o1, const py::handle& o2) {
+ return tensorflow::PyoOrThrow(
+ tensorflow::swig::SameNamedtuples(o1.ptr(), o2.ptr()));
+ },
+ R"pbdoc(
Returns True if the two namedtuples have the same name and fields.
)pbdoc");
- m.def(
- "AssertSameStructure",
- [](const py::handle& o1, const py::handle& o2, bool check_types,
- bool expand_composites) {
- bool result = tensorflow::swig::AssertSameStructure(
- o1.ptr(), o2.ptr(), check_types, expand_composites);
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("AssertSameStructure",
+ [](const py::handle& o1, const py::handle& o2, bool check_types,
+ bool expand_composites) {
+ bool result = tensorflow::swig::AssertSameStructure(
+ o1.ptr(), o2.ptr(), check_types, expand_composites);
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns True if the two structures are nested in the same way.
)pbdoc");
- m.def(
- "Flatten",
- [](const py::handle& o, bool expand_composites) {
- return tensorflow::PyoOrThrow(
- tensorflow::swig::Flatten(o.ptr(), expand_composites));
- },
- R"pbdoc(
+ m.def("Flatten",
+ [](const py::handle& o, bool expand_composites) {
+ return tensorflow::PyoOrThrow(
+ tensorflow::swig::Flatten(o.ptr(), expand_composites));
+ },
+ R"pbdoc(
Returns a flat list from a given nested structure.
If `nest` is not a sequence, tuple, or dict, then returns a single-element
@@ -257,16 +245,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Raises:
TypeError: The nest is or contains a dict with non-sortable keys.
)pbdoc");
- m.def(
- "IsSequenceForData",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsSequenceForData(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsSequenceForData",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsSequenceForData(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns a true if `seq` is a Sequence or dict (except strings/lists).
NOTE(mrry): This differs from `tensorflow.python.util.nest.is_sequence()`,
@@ -281,13 +268,12 @@ PYBIND11_MODULE(_pywrap_utils, m) {
True if the sequence is a not a string or list and is a
collections.Sequence.
)pbdoc");
- m.def(
- "FlattenForData",
- [](const py::handle& o) {
- return tensorflow::PyoOrThrow(
- tensorflow::swig::FlattenForData(o.ptr()));
- },
- R"pbdoc(
+ m.def("FlattenForData",
+ [](const py::handle& o) {
+ return tensorflow::PyoOrThrow(
+ tensorflow::swig::FlattenForData(o.ptr()));
+ },
+ R"pbdoc(
Returns a flat sequence from a given nested structure.
If `nest` is not a sequence, this returns a single-element list: `[nest]`.
@@ -299,29 +285,27 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
A Python list, the flattened version of the input.
)pbdoc");
- m.def(
- "AssertSameStructureForData",
- [](const py::handle& o1, const py::handle& o2, bool check_types) {
- bool result = tensorflow::swig::AssertSameStructureForData(
- o1.ptr(), o2.ptr(), check_types);
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("AssertSameStructureForData",
+ [](const py::handle& o1, const py::handle& o2, bool check_types) {
+ bool result = tensorflow::swig::AssertSameStructureForData(
+ o1.ptr(), o2.ptr(), check_types);
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns True if the two structures are nested in the same way in particular tf.data.
)pbdoc");
- m.def(
- "IsResourceVariable",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsResourceVariable(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsResourceVariable",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsResourceVariable(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns 1 if `o` is a ResourceVariable.
Args:
@@ -330,16 +314,15 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if `instance` is a `ResourceVariable`.
)pbdoc");
- m.def(
- "IsVariable",
- [](const py::handle& o) {
- bool result = tensorflow::swig::IsVariable(o.ptr());
- if (PyErr_Occurred()) {
- throw py::error_already_set();
- }
- return result;
- },
- R"pbdoc(
+ m.def("IsVariable",
+ [](const py::handle& o) {
+ bool result = tensorflow::swig::IsVariable(o.ptr());
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
Returns 1 if `o` is a Variable.
Args:
@@ -348,4 +331,22 @@ PYBIND11_MODULE(_pywrap_utils, m) {
Returns:
True if `instance` is a `Variable`.
)pbdoc");
+ m.def("IsBF16SupportedByOneDNNOnThisCPU",
+ []() {
+ bool result = tensorflow::port::TestCPUFeature(
+ tensorflow::port::CPUFeature::AVX512F);
+ if (PyErr_Occurred()) {
+ throw py::error_already_set();
+ }
+ return result;
+ },
+ R"pbdoc(
+ Returns 1 if CPU has avx512f feature.
+
+ Args:
+ None
+
+ Returns:
+ True if CPU has avx512f feature.
+ )pbdoc");
}
From d0d3535077b0ad4caeaf72de145713d45ef6f9af Mon Sep 17 00:00:00 2001
From: Mazhar <58792511+noim210@users.noreply.github.com>
Date: Wed, 16 Dec 2020 11:11:29 -0800
Subject: [PATCH 2/8] Update auto_mixed_precision_test.py
---
tensorflow/python/grappler/auto_mixed_precision_test.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/tensorflow/python/grappler/auto_mixed_precision_test.py b/tensorflow/python/grappler/auto_mixed_precision_test.py
index 5c5501f129a..6f14ad17add 100644
--- a/tensorflow/python/grappler/auto_mixed_precision_test.py
+++ b/tensorflow/python/grappler/auto_mixed_precision_test.py
@@ -428,7 +428,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv_bn(self, mode):
"""Test graph with convolution followed by batch norm."""
From cf23bfbfd80a4b20f94e72dd605d3c95ed1e216b Mon Sep 17 00:00:00 2001
From: Mazhar <58792511+noim210@users.noreply.github.com>
Date: Wed, 16 Dec 2020 11:21:39 -0800
Subject: [PATCH 3/8] Update auto_mixed_precision_test.py
---
.../grappler/auto_mixed_precision_test.py | 36 +++++++++----------
1 file changed, 18 insertions(+), 18 deletions(-)
diff --git a/tensorflow/python/grappler/auto_mixed_precision_test.py b/tensorflow/python/grappler/auto_mixed_precision_test.py
index 6f14ad17add..594e1391529 100644
--- a/tensorflow/python/grappler/auto_mixed_precision_test.py
+++ b/tensorflow/python/grappler/auto_mixed_precision_test.py
@@ -460,7 +460,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv3d_bn(self, mode):
"""Test graph with convolution followed by batch norm."""
@@ -486,7 +486,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv3d(self, mode):
"""Test grad ops with convolution3d graph."""
@@ -519,7 +519,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
# MKL
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv_bn_dropout(self, mode):
"""Test dropout precision of convolution batch norm graph."""
@@ -579,7 +579,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
# TODO(benbarsdell): This test has not been tried with MKL.
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_depthwise_conv2d(self, mode):
"""Test grad ops with depthwise convolution2d graph."""
@@ -615,7 +615,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_simple_loop(self, mode):
"""Test graph with while loop."""
@@ -637,7 +637,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_loop_with_vars_intertwined(self, mode):
"""Test graph with intertwined while loops."""
@@ -662,7 +662,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_multi_paths(self, mode):
"""Test graph with multiple paths."""
@@ -692,7 +692,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_multi_paths_2(self, mode):
"""Test graph with multiple paths."""
@@ -726,7 +726,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda']) # MKL doesn't support bf16 Sigmoid
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_recurrent_lstm(self, mode):
"""Test graph with recurrent lstm."""
@@ -754,63 +754,63 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_1(self, mode):
self._run_simple_loop_test(mode, 'W', 'C', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_2(self, mode):
self._run_simple_loop_test(mode, 'C', 'C', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_3(self, mode):
self._run_simple_loop_test(mode, 'W', 'G', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_4(self, mode):
self._run_simple_loop_test(mode, 'W', 'gbg', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_5(self, mode):
self._run_simple_loop_test(mode, 'b', 'gWC', 'c')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_6(self, mode):
self._run_simple_loop_test(mode, 'b', 'CWCG', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_7(self, mode):
self._run_simple_loop_test(mode, 'C', 'GWCG', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_8(self, mode):
self._run_simple_loop_test(mode, 'C', 'CgbgWC', 'g')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_noninlined_funcdef(self, mode):
"""Test graph with non-inlined function subgraph.
From b27f331527f47bb1d5157836d18127b777814eb1 Mon Sep 17 00:00:00 2001
From: Mazhar <58792511+noim210@users.noreply.github.com>
Date: Wed, 16 Dec 2020 11:22:40 -0800
Subject: [PATCH 4/8] Update auto_mixed_precision_test.py
---
tensorflow/python/grappler/auto_mixed_precision_test.py | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/tensorflow/python/grappler/auto_mixed_precision_test.py b/tensorflow/python/grappler/auto_mixed_precision_test.py
index 594e1391529..2e29c1ee060 100644
--- a/tensorflow/python/grappler/auto_mixed_precision_test.py
+++ b/tensorflow/python/grappler/auto_mixed_precision_test.py
@@ -839,7 +839,7 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('test will fail with AVX512f e.g. brodwell')
+ @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_ingraph_train_loop(self, mode):
"""Tests a graph containing a while loop around a training update.
From d47153ffe3bc91e4aece66de889c996a0c633ca6 Mon Sep 17 00:00:00 2001
From: mazharul <mazharul.islam@intel.com>
Date: Mon, 21 Dec 2020 19:51:07 -0800
Subject: [PATCH 5/8] fixing the conflict for building
---
tensorflow/python/BUILD | 33 ---------------------------------
tensorflow/python/util/BUILD | 1 +
2 files changed, 1 insertion(+), 33 deletions(-)
diff --git a/tensorflow/python/BUILD b/tensorflow/python/BUILD
index e62c6b30275..d141220888e 100644
--- a/tensorflow/python/BUILD
+++ b/tensorflow/python/BUILD
@@ -463,35 +463,6 @@ alias(
actual = "//tensorflow/python/util:_pywrap_utils",
)
-tf_python_pybind_extension(
- name = "_pywrap_utils",
- srcs = ["util/util_wrapper.cc"],
- hdrs = ["util/util.h"],
- module_name = "_pywrap_utils",
- deps = [
- ":pybind11_lib",
- "//third_party/python_runtime:headers",
- "@pybind11",
- "//tensorflow/core/platform:platform_port",
-
- ],
-)
-
-tf_python_pybind_extension(
- name = "_pywrap_kernel_registry",
- srcs = ["util/kernel_registry_wrapper.cc"],
- hdrs = ["util/kernel_registry.h"],
- module_name = "_pywrap_kernel_registry",
- deps = [
- ":pybind11_lib",
- "//tensorflow/core:framework_headers_lib",
- "//tensorflow/core:lib_headers_for_pybind",
- "//tensorflow/core:protos_all_cc",
- "//third_party/python_runtime:headers",
- "@pybind11",
- ],
-)
-
tf_python_pybind_extension(
name = "_pywrap_quantize_training",
srcs = [
@@ -1620,7 +1591,6 @@ py_library(
deps = [
":platform",
"//tensorflow/python/util",
- # TODO(mdan): Remove this once the transitive dependency is fixed.
"//tensorflow/python/util:tf_stack",
],
)
@@ -2048,7 +2018,6 @@ cuda_py_test(
python_version = "PY3",
shard_count = 10,
tags = [
- "no_rocm",
"noasan",
"optonly",
],
@@ -2094,7 +2063,6 @@ tf_py_test(
srcs = ["framework/importer_test.py"],
main = "framework/importer_test.py",
python_version = "PY3",
- tags = ["no_rocm"],
deps = [
":array_ops",
":client_testlib",
@@ -4915,7 +4883,6 @@ cuda_py_test(
srcs = ["ops/nn_fused_batchnorm_test.py"],
python_version = "PY3",
shard_count = 24,
- tags = ["no_rocm"],
deps = [
":array_ops",
":client_testlib",
diff --git a/tensorflow/python/util/BUILD b/tensorflow/python/util/BUILD
index 32bb85a6a49..ec265c4ea46 100644
--- a/tensorflow/python/util/BUILD
+++ b/tensorflow/python/util/BUILD
@@ -76,6 +76,7 @@ tf_python_pybind_extension(
"//tensorflow/python:pybind11_lib",
"//third_party/python_runtime:headers",
"@pybind11",
+ "//tensorflow/core/platform:platform_port",
],
)
From 55975390697d667f6b4ab7bcc6a8a6bd5ba73204 Mon Sep 17 00:00:00 2001
From: mazharul <mazharul.islam@intel.com>
Date: Mon, 21 Dec 2020 19:52:06 -0800
Subject: [PATCH 6/8] updating the code after getting reviews about cuda test
run
---
tensorflow/python/framework/test_util.py | 7 ------
.../grappler/auto_mixed_precision_test.py | 25 ++++---------------
2 files changed, 5 insertions(+), 27 deletions(-)
diff --git a/tensorflow/python/framework/test_util.py b/tensorflow/python/framework/test_util.py
index 1e767d8d0ee..6b54f03e882 100644
--- a/tensorflow/python/framework/test_util.py
+++ b/tensorflow/python/framework/test_util.py
@@ -43,7 +43,6 @@ from google.protobuf import text_format
from tensorflow.core.framework import graph_pb2
from tensorflow.core.protobuf import rewriter_config_pb2
-from tensorflow.python import _pywrap_utils
from tensorflow.python import tf2
from tensorflow.python.client import device_lib
from tensorflow.python.client import pywrap_tf_session
@@ -1824,12 +1823,6 @@ def _disable_test(execute_func):
return disable_test_impl
-# The description is just for documentation purposes.
-def disable_nonAVX512f(description): # pylint: disable=unused-argument
- """Execute the test method only if avx512f is supported."""
- execute_func = _pywrap_utils.IsBF16SupportedByOneDNNOnThisCPU()
- return _disable_test(execute_func)
-
# The description is just for documentation purposes.
def disable_xla(description): # pylint: disable=unused-argument
"""Execute the test method only if xla is not enabled."""
diff --git a/tensorflow/python/grappler/auto_mixed_precision_test.py b/tensorflow/python/grappler/auto_mixed_precision_test.py
index ec2eefc1872..c0300aaadb5 100644
--- a/tensorflow/python/grappler/auto_mixed_precision_test.py
+++ b/tensorflow/python/grappler/auto_mixed_precision_test.py
@@ -50,6 +50,7 @@ from tensorflow.python.platform import sysconfig
from tensorflow.python.platform import test
from tensorflow.python.training import adam
from tensorflow.python.training import gradient_descent
+from tensorflow.python.util import _pywrap_utils
def _input(shape):
@@ -371,6 +372,10 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
self.skipTest('No GPU is available')
if mode == 'mkl' and not test_util.IsMklEnabled():
self.skipTest('MKL is not enabled')
+ # Test will fail on machines without AVX512f, e.g., Broadwell
+ isAVX512f = _pywrap_utils.IsBF16SupportedByOneDNNOnThisCPU()
+ if mode == 'mkl' and not isAVX512f:
+ self.skipTest('Skipping test due to non-AVX512f machine')
def _run_simple_loop_test(self, mode, inp, body, out):
"""Runs a test of a simple loop.
@@ -428,7 +433,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv_bn(self, mode):
"""Test graph with convolution followed by batch norm."""
@@ -460,7 +464,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv3d_bn(self, mode):
"""Test graph with convolution followed by batch norm."""
@@ -486,7 +489,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv3d(self, mode):
"""Test grad ops with convolution3d graph."""
@@ -517,7 +519,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_conv_bn_dropout(self, mode):
"""Test dropout precision of convolution batch norm graph."""
@@ -578,7 +579,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
# TODO(benbarsdell): This test has not been tried with MKL.
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_depthwise_conv2d(self, mode):
"""Test grad ops with depthwise convolution2d graph."""
@@ -614,7 +614,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_simple_loop(self, mode):
"""Test graph with while loop."""
@@ -636,7 +635,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_loop_with_vars_intertwined(self, mode):
"""Test graph with intertwined while loops."""
@@ -661,7 +659,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_multi_paths(self, mode):
"""Test graph with multiple paths."""
@@ -691,7 +688,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_multi_paths_2(self, mode):
"""Test graph with multiple paths."""
@@ -725,7 +721,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda']) # MKL doesn't support bf16 Sigmoid
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_recurrent_lstm(self, mode):
"""Test graph with recurrent lstm."""
@@ -753,63 +748,54 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_1(self, mode):
self._run_simple_loop_test(mode, 'W', 'C', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_2(self, mode):
self._run_simple_loop_test(mode, 'C', 'C', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_3(self, mode):
self._run_simple_loop_test(mode, 'W', 'G', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('v1 loop test')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_4(self, mode):
self._run_simple_loop_test(mode, 'W', 'gbg', 'W')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_5(self, mode):
self._run_simple_loop_test(mode, 'b', 'gWC', 'c')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_6(self, mode):
self._run_simple_loop_test(mode, 'b', 'CWCG', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_7(self, mode):
self._run_simple_loop_test(mode, 'C', 'GWCG', 'C')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_v1_only('b/138749235')
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_propagation_through_simple_loop_8(self, mode):
self._run_simple_loop_test(mode, 'C', 'CgbgWC', 'g')
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_noninlined_funcdef(self, mode):
"""Test graph with non-inlined function subgraph.
@@ -838,7 +824,6 @@ class AutoMixedPrecisionTest(test.TestCase, parameterized.TestCase):
@parameterized.parameters(['cuda', 'mkl'])
@test_util.run_deprecated_v1
- @test_util.disable_nonAVX512f('Test will fail on machines without AVX512f, e.g., Broadwell')
@test_util.disable_xla('This test does not pass with XLA')
def test_ingraph_train_loop(self, mode):
"""Tests a graph containing a while loop around a training update.
From 51659b29519a4cf6ec180a175baa0628d30004bb Mon Sep 17 00:00:00 2001
From: mazharul <mazharul.islam@intel.com>
Date: Tue, 22 Dec 2020 11:57:41 -0800
Subject: [PATCH 7/8] update the file with new master
---
tensorflow/python/BUILD | 4 ++++
1 file changed, 4 insertions(+)
diff --git a/tensorflow/python/BUILD b/tensorflow/python/BUILD
index d141220888e..96e01db5069 100644
--- a/tensorflow/python/BUILD
+++ b/tensorflow/python/BUILD
@@ -1591,6 +1591,7 @@ py_library(
deps = [
":platform",
"//tensorflow/python/util",
+ # TODO(mdan): Remove this once the transitive dependency is fixed.
"//tensorflow/python/util:tf_stack",
],
)
@@ -2018,6 +2019,7 @@ cuda_py_test(
python_version = "PY3",
shard_count = 10,
tags = [
+ "no_rocm",
"noasan",
"optonly",
],
@@ -2063,6 +2065,7 @@ tf_py_test(
srcs = ["framework/importer_test.py"],
main = "framework/importer_test.py",
python_version = "PY3",
+ tags = ["no_rocm"],
deps = [
":array_ops",
":client_testlib",
@@ -4883,6 +4886,7 @@ cuda_py_test(
srcs = ["ops/nn_fused_batchnorm_test.py"],
python_version = "PY3",
shard_count = 24,
+ tags = ["no_rocm"],
deps = [
":array_ops",
":client_testlib",
From e901c15b61f9c8649b3605c080af7dc00e5caacf Mon Sep 17 00:00:00 2001
From: mazharul <mazharul.islam@intel.com>
Date: Tue, 22 Dec 2020 12:07:21 -0800
Subject: [PATCH 8/8] fixing the order to make the lines lexicographic
---
tensorflow/python/util/BUILD | 2 +-
1 file changed, 1 insertion(+), 1 deletion(-)
diff --git a/tensorflow/python/util/BUILD b/tensorflow/python/util/BUILD
index 8ae6ca3d77d..80c87399710 100644
--- a/tensorflow/python/util/BUILD
+++ b/tensorflow/python/util/BUILD
@@ -73,10 +73,10 @@ tf_python_pybind_extension(
hdrs = ["util.h"],
module_name = "_pywrap_utils",
deps = [
+ "//tensorflow/core/platform:platform_port",
"//tensorflow/python:pybind11_lib",
"//third_party/python_runtime:headers",
"@pybind11",
- "//tensorflow/core/platform:platform_port",
],
)