exports_files(["LICENSE"])
-load("//tensorflow/core:platform/default/build_config_root.bzl", "if_static")
-
py_library(
name = "proto",
srcs = [
"//tensorflow/contrib/proto/python/ops:encode_proto_op_py",
],
)
-
-py_library(
- name = "proto_pip",
- data = [
- "//tensorflow/contrib/proto/python/kernel_tests:test_messages",
- ] + if_static(
- [],
- otherwise = ["//tensorflow/contrib/proto/python/kernel_tests:libtestexample.so"],
- ),
- deps = [
- ":proto",
- "//tensorflow/contrib/proto/python/kernel_tests:py_test_deps",
- ],
-)
+++ /dev/null
-package(default_visibility = ["//visibility:public"])
-
-licenses(["notice"]) # Apache 2.0
-
-exports_files(["LICENSE"])
-
-# Much of the work in this BUILD file actually happens in the corresponding
-# build_defs.bzl, which creates an individual testcase for each example .pbtxt
-# file in this directory.
-#
-load(":build_defs.bzl", "decode_proto_test_suite")
-load(":build_defs.bzl", "encode_proto_test_suite")
-
-# This expands to a tf_py_test for each test file.
-# It defines the test_suite :decode_proto_op_tests.
-decode_proto_test_suite(
- name = "decode_proto_tests",
- examples = glob(["*.pbtxt"]),
-)
-
-# This expands to a tf_py_test for each test file.
-# It defines the test_suite :encode_proto_op_tests.
-encode_proto_test_suite(
- name = "encode_proto_tests",
- examples = glob(["*.pbtxt"]),
-)
-
-# Below here are tests that are not tied to an example text proto.
-filegroup(
- name = "test_messages",
- srcs = glob(["*.pbtxt"]),
-)
-
-load("//tensorflow:tensorflow.bzl", "tf_py_test")
-load("//tensorflow:tensorflow.bzl", "tf_cc_shared_object")
-load("//tensorflow/core:platform/default/build_config_root.bzl", "if_static")
-load("//tensorflow/core:platform/default/build_config.bzl", "tf_proto_library")
-
-tf_py_test(
- name = "decode_proto_fail_test",
- size = "small",
- srcs = ["decode_proto_fail_test.py"],
- additional_deps = [
- ":py_test_deps",
- "//third_party/py/numpy",
- "//tensorflow/contrib/proto:proto",
- ],
- data = if_static(
- [],
- otherwise = [":libtestexample.so"],
- ),
-)
-
-py_library(
- name = "test_case",
- srcs = ["test_case.py"],
- deps = ["//tensorflow/python:client_testlib"],
-)
-
-py_library(
- name = "py_test_deps",
- deps = [
- ":test_case",
- ":test_example_proto_py",
- ],
-)
-
-tf_proto_library(
- name = "test_example_proto",
- srcs = ["test_example.proto"],
- cc_api_version = 2,
- protodeps = ["//tensorflow/core:protos_all"],
-)
-
-tf_cc_shared_object(
- name = "libtestexample.so",
- linkstatic = 1,
- deps = [
- ":test_example_proto_cc",
- ],
-)
+++ /dev/null
-"""BUILD rules for generating file-driven proto test cases.
-
-The decode_proto_test_suite() and encode_proto_test_suite() rules take a list
-of text protos and generates a tf_py_test() for each one.
-"""
-
-load("//tensorflow:tensorflow.bzl", "tf_py_test")
-load("//tensorflow:tensorflow.bzl", "register_extension_info")
-load("//tensorflow/core:platform/default/build_config_root.bzl", "if_static")
-
-def _test_name(test, path):
- return "%s_%s_test" % (test, path.split("/")[-1].split(".")[0])
-
-def decode_proto_test_suite(name, examples):
- """Build the decode_proto py_test for each test filename."""
- for test_filename in examples:
- tf_py_test(
- name = _test_name("decode_proto", test_filename),
- srcs = ["decode_proto_op_test.py"],
- size = "small",
- data = [test_filename] + if_static(
- [],
- otherwise = [":libtestexample.so"],
- ),
- main = "decode_proto_op_test.py",
- args = [
- "--message_text_file=\"%s/%s\"" % (native.package_name(), test_filename),
- ],
- additional_deps = [
- ":py_test_deps",
- "//third_party/py/numpy",
- "//tensorflow/contrib/proto:proto",
- ],
- )
- native.test_suite(
- name = name,
- tests = [":" + _test_name("decode_proto", test_filename)
- for test_filename in examples],
- )
-
-def encode_proto_test_suite(name, examples):
- """Build the encode_proto py_test for each test filename."""
- for test_filename in examples:
- tf_py_test(
- name = _test_name("encode_proto", test_filename),
- srcs = ["encode_proto_op_test.py"],
- size = "small",
- data = [test_filename] + if_static(
- [],
- otherwise = [":libtestexample.so"],
- ),
- main = "encode_proto_op_test.py",
- args = [
- "--message_text_file=\"%s/%s\"" % (native.package_name(), test_filename),
- ],
- additional_deps = [
- ":py_test_deps",
- "//third_party/py/numpy",
- "//tensorflow/contrib/proto:proto",
- ],
- )
- native.test_suite(
- name = name,
- tests = [":" + _test_name("encode_proto", test_filename)
- for test_filename in examples],
- )
-
-register_extension_info(
- extension_name = "decode_proto_test_suite",
- label_regex_map = {
- "deps": "deps:decode_example_.*",
- })
-
-register_extension_info(
- extension_name = "encode_proto_test_suite",
- label_regex_map = {
- "deps": "deps:encode_example_.*",
- })
+++ /dev/null
-# =============================================================================
-# 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.
-# =============================================================================
-
-# Python3 preparedness imports.
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-
-from tensorflow.contrib import proto
-from tensorflow.contrib.proto.python.kernel_tests import test_case
-from tensorflow.python.framework import dtypes
-from tensorflow.python.framework import errors
-from tensorflow.python.platform import test
-
-
-class DecodeProtoFailTest(test_case.ProtoOpTestCase):
- """Test failure cases for DecodeToProto."""
-
- def _TestCorruptProtobuf(self, sanitize):
- """Test failure cases for DecodeToProto."""
-
- # The goal here is to check the error reporting.
- # Testing against a variety of corrupt protobufs is
- # done by fuzzing.
- corrupt_proto = 'This is not a binary protobuf'
-
- # Numpy silently truncates the strings if you don't specify dtype=object.
- batch = np.array(corrupt_proto, dtype=object)
- msg_type = 'tensorflow.contrib.proto.TestCase'
- field_names = ['sizes']
- field_types = [dtypes.int32]
-
- with self.test_session() as sess:
- ctensor, vtensor = proto.decode_proto(
- batch,
- message_type=msg_type,
- field_names=field_names,
- output_types=field_types,
- sanitize=sanitize)
- with self.assertRaisesRegexp(errors.DataLossError,
- 'Unable to parse binary protobuf'
- '|Failed to consume entire buffer'):
- _ = sess.run([ctensor] + vtensor)
-
- def testCorrupt(self):
- self._TestCorruptProtobuf(sanitize=False)
-
- def testSanitizerCorrupt(self):
- self._TestCorruptProtobuf(sanitize=True)
-
-
-if __name__ == '__main__':
- test.main()
+++ /dev/null
-# =============================================================================
-# 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.
-# =============================================================================
-"""Table-driven test for decode_proto op.
-
-This test is run once with each of the *.TestCase.pbtxt files
-in the test directory.
-"""
-# Python3 preparedness imports.
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-
-from google.protobuf import text_format
-
-from tensorflow.contrib import proto
-from tensorflow.contrib.proto.python.kernel_tests import test_case
-from tensorflow.contrib.proto.python.kernel_tests import test_example_pb2
-from tensorflow.python.framework import dtypes
-from tensorflow.python.platform import flags
-from tensorflow.python.platform import test
-
-FLAGS = flags.FLAGS
-
-flags.DEFINE_string('message_text_file', None,
- 'A file containing a text serialized TestCase protobuf.')
-
-
-class DecodeProtoOpTest(test_case.ProtoOpTestCase):
-
- def _compareValues(self, fd, vs, evs):
- """Compare lists/arrays of field values."""
-
- if len(vs) != len(evs):
- self.fail('Field %s decoded %d outputs, expected %d' %
- (fd.name, len(vs), len(evs)))
- for i, ev in enumerate(evs):
- # Special case fuzzy match for float32. TensorFlow seems to mess with
- # MAX_FLT slightly and the test doesn't work otherwise.
- # TODO(nix): ask on TF list about why MAX_FLT doesn't pass through.
- if fd.cpp_type == fd.CPPTYPE_FLOAT:
- # Numpy isclose() is better than assertIsClose() which uses an absolute
- # value comparison.
- self.assertTrue(
- np.isclose(vs[i], ev), 'expected %r, actual %r' % (ev, vs[i]))
- elif fd.cpp_type == fd.CPPTYPE_STRING:
- # In Python3 string tensor values will be represented as bytes, so we
- # reencode the proto values to match that.
- self.assertEqual(vs[i], ev.encode('ascii'))
- else:
- # Doubles and other types pass through unscathed.
- self.assertEqual(vs[i], ev)
-
- def _compareRepeatedPrimitiveValue(self, batch_shape, sizes, fields,
- field_dict):
- """Compare protos of type RepeatedPrimitiveValue.
-
- Args:
- batch_shape: the shape of the input tensor of serialized messages.
- sizes: int matrix of repeat counts returned by decode_proto
- fields: list of test_example_pb2.FieldSpec (types and expected values)
- field_dict: map from field names to decoded numpy tensors of values
- """
-
- # Check that expected values match.
- for field in fields:
- values = field_dict[field.name]
- self.assertEqual(dtypes.as_dtype(values.dtype), field.dtype)
-
- fd = field.expected.DESCRIPTOR.fields_by_name[field.name]
-
- # Values has the same shape as the input plus an extra
- # dimension for repeats.
- self.assertEqual(list(values.shape)[:-1], batch_shape)
-
- # Nested messages are represented as TF strings, requiring
- # some special handling.
- if field.name == 'message_value':
- vs = []
- for buf in values.flat:
- msg = test_example_pb2.PrimitiveValue()
- msg.ParseFromString(buf)
- vs.append(msg)
- evs = getattr(field.expected, field.name)
- if len(vs) != len(evs):
- self.fail('Field %s decoded %d outputs, expected %d' %
- (fd.name, len(vs), len(evs)))
- for v, ev in zip(vs, evs):
- self.assertEqual(v, ev)
- continue
-
- # This can be a little confusing. For testing we are using
- # RepeatedPrimitiveValue in two ways: it's the proto that we
- # decode for testing, and it's used in the expected value as a
- # union type. The two cases are slightly different: this is the
- # second case.
- # We may be fetching the uint64_value from the test proto, but
- # in the expected proto we store it in the int64_value field
- # because TensorFlow doesn't support unsigned int64.
- tf_type_to_primitive_value_field = {
- dtypes.float32:
- 'float_value',
- dtypes.float64:
- 'double_value',
- dtypes.int32:
- 'int32_value',
- dtypes.uint8:
- 'uint8_value',
- dtypes.int8:
- 'int8_value',
- dtypes.string:
- 'string_value',
- dtypes.int64:
- 'int64_value',
- dtypes.bool:
- 'bool_value',
- # Unhandled TensorFlow types:
- # DT_INT16 DT_COMPLEX64 DT_QINT8 DT_QUINT8 DT_QINT32
- # DT_BFLOAT16 DT_QINT16 DT_QUINT16 DT_UINT16
- }
- tf_field_name = tf_type_to_primitive_value_field.get(field.dtype)
- if tf_field_name is None:
- self.fail('Unhandled tensorflow type %d' % field.dtype)
-
- self._compareValues(fd, values.flat,
- getattr(field.expected, tf_field_name))
-
- def _runDecodeProtoTests(self, fields, case_sizes, batch_shape, batch,
- message_type, message_format, sanitize,
- force_disordered=False):
- """Run decode tests on a batch of messages.
-
- Args:
- fields: list of test_example_pb2.FieldSpec (types and expected values)
- case_sizes: expected sizes array
- batch_shape: the shape of the input tensor of serialized messages
- batch: list of serialized messages
- message_type: descriptor name for messages
- message_format: format of messages, 'text' or 'binary'
- sanitize: whether to sanitize binary protobuf inputs
- force_disordered: whether to force fields encoded out of order.
- """
-
- if force_disordered:
- # Exercise code path that handles out-of-order fields by prepending extra
- # fields with tag numbers higher than any real field. Note that this won't
- # work with sanitization because that forces reserialization using a
- # trusted decoder and encoder.
- assert not sanitize
- extra_fields = test_example_pb2.ExtraFields()
- extra_fields.string_value = 'IGNORE ME'
- extra_fields.bool_value = False
- extra_msg = extra_fields.SerializeToString()
- batch = [extra_msg + msg for msg in batch]
-
- # Numpy silently truncates the strings if you don't specify dtype=object.
- batch = np.array(batch, dtype=object)
- batch = np.reshape(batch, batch_shape)
-
- field_names = [f.name for f in fields]
- output_types = [f.dtype for f in fields]
-
- with self.test_session() as sess:
- sizes, vtensor = proto.decode_proto(
- batch,
- message_type=message_type,
- field_names=field_names,
- output_types=output_types,
- message_format=message_format,
- sanitize=sanitize)
-
- vlist = sess.run([sizes] + vtensor)
- sizes = vlist[0]
- # Values is a list of tensors, one for each field.
- value_tensors = vlist[1:]
-
- # Check that the repeat sizes are correct.
- self.assertTrue(
- np.all(np.array(sizes.shape) == batch_shape + [len(field_names)]))
-
- # Check that the decoded sizes match the expected sizes.
- self.assertEqual(len(sizes.flat), len(case_sizes))
- self.assertTrue(
- np.all(sizes.flat == np.array(
- case_sizes, dtype=np.int32)))
-
- field_dict = dict(zip(field_names, value_tensors))
-
- self._compareRepeatedPrimitiveValue(batch_shape, sizes, fields,
- field_dict)
-
- def testBinary(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- batch = [primitive.SerializeToString() for primitive in case.primitive]
- self._runDecodeProtoTests(
- case.field,
- case.sizes,
- list(case.shape),
- batch,
- 'tensorflow.contrib.proto.RepeatedPrimitiveValue',
- 'binary',
- sanitize=False)
-
- def testBinaryDisordered(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- batch = [primitive.SerializeToString() for primitive in case.primitive]
- self._runDecodeProtoTests(
- case.field,
- case.sizes,
- list(case.shape),
- batch,
- 'tensorflow.contrib.proto.RepeatedPrimitiveValue',
- 'binary',
- sanitize=False,
- force_disordered=True)
-
- def testPacked(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- # Now try with the packed serialization.
- # We test the packed representations by loading the same test cases
- # using PackedPrimitiveValue instead of RepeatedPrimitiveValue.
- # To do this we rely on the text format being the same for packed and
- # unpacked fields, and reparse the test message using the packed version
- # of the proto.
- packed_batch = [
- # Note: float_format='.17g' is necessary to ensure preservation of
- # doubles and floats in text format.
- text_format.Parse(
- text_format.MessageToString(
- primitive, float_format='.17g'),
- test_example_pb2.PackedPrimitiveValue()).SerializeToString()
- for primitive in case.primitive
- ]
-
- self._runDecodeProtoTests(
- case.field,
- case.sizes,
- list(case.shape),
- packed_batch,
- 'tensorflow.contrib.proto.PackedPrimitiveValue',
- 'binary',
- sanitize=False)
-
- def testText(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- # Note: float_format='.17g' is necessary to ensure preservation of
- # doubles and floats in text format.
- text_batch = [
- text_format.MessageToString(
- primitive, float_format='.17g') for primitive in case.primitive
- ]
-
- self._runDecodeProtoTests(
- case.field,
- case.sizes,
- list(case.shape),
- text_batch,
- 'tensorflow.contrib.proto.RepeatedPrimitiveValue',
- 'text',
- sanitize=False)
-
- def testSanitizerGood(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- batch = [primitive.SerializeToString() for primitive in case.primitive]
- self._runDecodeProtoTests(
- case.field,
- case.sizes,
- list(case.shape),
- batch,
- 'tensorflow.contrib.proto.RepeatedPrimitiveValue',
- 'binary',
- sanitize=True)
-
-
-if __name__ == '__main__':
- test.main()
+++ /dev/null
-# =============================================================================
-# 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.
-# =============================================================================
-"""Table-driven test for encode_proto op.
-
-This test is run once with each of the *.TestCase.pbtxt files
-in the test directory.
-
-It tests that encode_proto is a lossless inverse of decode_proto
-(for the specified fields).
-"""
-# Python3 readiness boilerplate
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import numpy as np
-
-from google.protobuf import text_format
-
-from tensorflow.contrib import proto
-from tensorflow.contrib.proto.python.kernel_tests import test_case
-from tensorflow.contrib.proto.python.kernel_tests import test_example_pb2
-from tensorflow.python.framework import dtypes
-from tensorflow.python.ops import array_ops
-from tensorflow.python.platform import flags
-from tensorflow.python.platform import test
-
-FLAGS = flags.FLAGS
-
-flags.DEFINE_string('message_text_file', None,
- 'A file containing a text serialized TestCase protobuf.')
-
-
-class EncodeProtoOpTest(test_case.ProtoOpTestCase):
-
- def testBadInputs(self):
- # Invalid field name
- with self.test_session():
- with self.assertRaisesOpError('Unknown field: non_existent_field'):
- proto.encode_proto(
- sizes=[[1]],
- values=[np.array([[0.0]], dtype=np.int32)],
- message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
- field_names=['non_existent_field']).eval()
-
- # Incorrect types.
- with self.test_session():
- with self.assertRaisesOpError(
- 'Incompatible type for field double_value.'):
- proto.encode_proto(
- sizes=[[1]],
- values=[np.array([[0.0]], dtype=np.int32)],
- message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
- field_names=['double_value']).eval()
-
- # Incorrect shapes of sizes.
- with self.test_session():
- with self.assertRaisesOpError(
- r'sizes should be batch_size \+ \[len\(field_names\)\]'):
- sizes = array_ops.placeholder(dtypes.int32)
- values = array_ops.placeholder(dtypes.float64)
- proto.encode_proto(
- sizes=sizes,
- values=[values],
- message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
- field_names=['double_value']).eval(feed_dict={
- sizes: [[[0, 0]]],
- values: [[0.0]]
- })
-
- # Inconsistent shapes of values.
- with self.test_session():
- with self.assertRaisesOpError(
- 'Values must match up to the last dimension'):
- sizes = array_ops.placeholder(dtypes.int32)
- values1 = array_ops.placeholder(dtypes.float64)
- values2 = array_ops.placeholder(dtypes.int32)
- (proto.encode_proto(
- sizes=[[1, 1]],
- values=[values1, values2],
- message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
- field_names=['double_value', 'int32_value']).eval(feed_dict={
- values1: [[0.0]],
- values2: [[0], [0]]
- }))
-
- def _testRoundtrip(self, in_bufs, message_type, fields):
-
- field_names = [f.name for f in fields]
- out_types = [f.dtype for f in fields]
-
- with self.test_session() as sess:
- sizes, field_tensors = proto.decode_proto(
- in_bufs,
- message_type=message_type,
- field_names=field_names,
- output_types=out_types)
-
- out_tensors = proto.encode_proto(
- sizes,
- field_tensors,
- message_type=message_type,
- field_names=field_names)
-
- out_bufs, = sess.run([out_tensors])
-
- # Check that the re-encoded tensor has the same shape.
- self.assertEqual(in_bufs.shape, out_bufs.shape)
-
- # Compare the input and output.
- for in_buf, out_buf in zip(in_bufs.flat, out_bufs.flat):
- in_obj = test_example_pb2.RepeatedPrimitiveValue()
- in_obj.ParseFromString(in_buf)
-
- out_obj = test_example_pb2.RepeatedPrimitiveValue()
- out_obj.ParseFromString(out_buf)
-
- # Check that the deserialized objects are identical.
- self.assertEqual(in_obj, out_obj)
-
- # Check that the input and output serialized messages are identical.
- # If we fail here, there is a difference in the serialized
- # representation but the new serialization still parses. This could
- # be harmless (a change in map ordering?) or it could be bad (e.g.
- # loss of packing in the encoding).
- self.assertEqual(in_buf, out_buf)
-
- def testRoundtrip(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- in_bufs = [primitive.SerializeToString() for primitive in case.primitive]
-
- # np.array silently truncates strings if you don't specify dtype=object.
- in_bufs = np.reshape(np.array(in_bufs, dtype=object), list(case.shape))
- return self._testRoundtrip(
- in_bufs, 'tensorflow.contrib.proto.RepeatedPrimitiveValue', case.field)
-
- def testRoundtripPacked(self):
- with open(FLAGS.message_text_file, 'r') as fp:
- case = text_format.Parse(fp.read(), test_example_pb2.TestCase())
-
- # Now try with the packed serialization.
- # We test the packed representations by loading the same test cases
- # using PackedPrimitiveValue instead of RepeatedPrimitiveValue.
- # To do this we rely on the text format being the same for packed and
- # unpacked fields, and reparse the test message using the packed version
- # of the proto.
- in_bufs = [
- # Note: float_format='.17g' is necessary to ensure preservation of
- # doubles and floats in text format.
- text_format.Parse(
- text_format.MessageToString(
- primitive, float_format='.17g'),
- test_example_pb2.PackedPrimitiveValue()).SerializeToString()
- for primitive in case.primitive
- ]
-
- # np.array silently truncates strings if you don't specify dtype=object.
- in_bufs = np.reshape(np.array(in_bufs, dtype=object), list(case.shape))
- return self._testRoundtrip(
- in_bufs, 'tensorflow.contrib.proto.PackedPrimitiveValue', case.field)
-
-
-if __name__ == '__main__':
- test.main()
+++ /dev/null
-primitive {
- double_value: -1.7976931348623158e+308
- double_value: 2.2250738585072014e-308
- double_value: 1.7976931348623158e+308
- float_value: -3.402823466e+38
- float_value: 1.175494351e-38
- float_value: 3.402823466e+38
- int64_value: -9223372036854775808
- int64_value: 9223372036854775807
- uint64_value: 0
- uint64_value: 18446744073709551615
- int32_value: -2147483648
- int32_value: 2147483647
- fixed64_value: 0
- fixed64_value: 18446744073709551615
- fixed32_value: 0
- fixed32_value: 4294967295
- bool_value: false
- bool_value: true
- string_value: ""
- string_value: "I refer to the infinite."
- uint32_value: 0
- uint32_value: 4294967295
- sfixed32_value: -2147483648
- sfixed32_value: 2147483647
- sfixed64_value: -9223372036854775808
- sfixed64_value: 9223372036854775807
- sint32_value: -2147483648
- sint32_value: 2147483647
- sint64_value: -9223372036854775808
- sint64_value: 9223372036854775807
-}
-shape: 1
-sizes: 3
-sizes: 3
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-sizes: 2
-field {
- name: "double_value"
- dtype: DT_DOUBLE
- expected {
- double_value: -1.7976931348623158e+308
- double_value: 2.2250738585072014e-308
- double_value: 1.7976931348623158e+308
- }
-}
-field {
- name: "float_value"
- dtype: DT_FLOAT
- expected {
- float_value: -3.402823466e+38
- float_value: 1.175494351e-38
- float_value: 3.402823466e+38
- }
-}
-field {
- name: "int64_value"
- dtype: DT_INT64
- expected {
- int64_value: -9223372036854775808
- int64_value: 9223372036854775807
- }
-}
-field {
- name: "uint64_value"
- dtype: DT_INT64
- expected {
- int64_value: 0
- int64_value: -1
- }
-}
-field {
- name: "int32_value"
- dtype: DT_INT32
- expected {
- int32_value: -2147483648
- int32_value: 2147483647
- }
-}
-field {
- name: "fixed64_value"
- dtype: DT_INT64
- expected {
- int64_value: 0
- int64_value: -1 # unsigned is 18446744073709551615
- }
-}
-field {
- name: "fixed32_value"
- dtype: DT_INT32
- expected {
- int32_value: 0
- int32_value: -1 # unsigned is 4294967295
- }
-}
-field {
- name: "bool_value"
- dtype: DT_BOOL
- expected {
- bool_value: false
- bool_value: true
- }
-}
-field {
- name: "string_value"
- dtype: DT_STRING
- expected {
- string_value: ""
- string_value: "I refer to the infinite."
- }
-}
-field {
- name: "uint32_value"
- dtype: DT_INT32
- expected {
- int32_value: 0
- int32_value: -1 # unsigned is 4294967295
- }
-}
-field {
- name: "sfixed32_value"
- dtype: DT_INT32
- expected {
- int32_value: -2147483648
- int32_value: 2147483647
- }
-}
-field {
- name: "sfixed64_value"
- dtype: DT_INT64
- expected {
- int64_value: -9223372036854775808
- int64_value: 9223372036854775807
- }
-}
-field {
- name: "sint32_value"
- dtype: DT_INT32
- expected {
- int32_value: -2147483648
- int32_value: 2147483647
- }
-}
-field {
- name: "sint64_value"
- dtype: DT_INT64
- expected {
- int64_value: -9223372036854775808
- int64_value: 9223372036854775807
- }
-}
+++ /dev/null
-primitive {
- message_value {
- double_value: 23.5
- }
-}
-shape: 1
-sizes: 1
-field {
- name: "message_value"
- dtype: DT_STRING
- expected {
- message_value {
- double_value: 23.5
- }
- }
-}
+++ /dev/null
-primitive {
- bool_value: true
-}
-shape: 1
-sizes: 1
-sizes: 0
-field {
- name: "bool_value"
- dtype: DT_BOOL
- expected {
- bool_value: true
- }
-}
-field {
- name: "double_value"
- dtype: DT_DOUBLE
- expected {
- double_value: 0.0
- }
-}
+++ /dev/null
-primitive {
- fixed32_value: 4294967295
- uint32_value: 4294967295
-}
-shape: 1
-sizes: 1
-sizes: 1
-field {
- name: "fixed32_value"
- dtype: DT_INT64
- expected {
- int64_value: 4294967295
- }
-}
-field {
- name: "uint32_value"
- dtype: DT_INT64
- expected {
- int64_value: 4294967295
- }
-}
+++ /dev/null
-primitive {
- double_value: 23.5
- double_value: 123.0
- bool_value: true
-}
-primitive {
- double_value: 3.1
- bool_value: false
-}
-shape: 2
-sizes: 2
-sizes: 1
-sizes: 1
-sizes: 1
-field {
- name: "double_value"
- dtype: DT_DOUBLE
- expected {
- double_value: 23.5
- double_value: 123.0
- double_value: 3.1
- double_value: 0.0
- }
-}
-field {
- name: "bool_value"
- dtype: DT_BOOL
- expected {
- bool_value: true
- bool_value: false
- }
-}
+++ /dev/null
-primitive {
- double_value: 23.5
- bool_value: true
-}
-primitive {
- double_value: 44.0
- bool_value: false
-}
-primitive {
- double_value: 3.14159
- bool_value: true
-}
-primitive {
- double_value: 1.414
- bool_value: true
-}
-primitive {
- double_value: -32.2
- bool_value: false
-}
-primitive {
- double_value: 0.0001
- bool_value: true
-}
-shape: 3
-shape: 2
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-sizes: 1
-field {
- name: "double_value"
- dtype: DT_DOUBLE
- expected {
- double_value: 23.5
- double_value: 44.0
- double_value: 3.14159
- double_value: 1.414
- double_value: -32.2
- double_value: 0.0001
- }
-}
-field {
- name: "bool_value"
- dtype: DT_BOOL
- expected {
- bool_value: true
- bool_value: false
- bool_value: true
- bool_value: true
- bool_value: false
- bool_value: true
- }
-}
+++ /dev/null
-primitive {
- double_value: 23.5
- bool_value: true
-}
-shape: 1
-sizes: 1
-sizes: 1
-field {
- name: "double_value"
- dtype: DT_DOUBLE
- expected {
- double_value: 23.5
- }
-}
-field {
- name: "bool_value"
- dtype: DT_BOOL
- expected {
- bool_value: true
- }
-}
+++ /dev/null
-# =============================================================================
-# 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.
-# =============================================================================
-"""Test case base for testing proto operations."""
-
-# Python3 preparedness imports.
-from __future__ import absolute_import
-from __future__ import division
-from __future__ import print_function
-
-import ctypes as ct
-import os
-
-from tensorflow.python.platform import test
-
-
-class ProtoOpTestCase(test.TestCase):
-
- def __init__(self, methodName='runTest'): # pylint: disable=invalid-name
- super(ProtoOpTestCase, self).__init__(methodName)
- lib = os.path.join(os.path.dirname(__file__), 'libtestexample.so')
- if os.path.isfile(lib):
- ct.cdll.LoadLibrary(lib)
+++ /dev/null
-// Test description and protos to work with it.
-//
-// Many of the protos in this file are for unit tests that haven't been written yet.
-
-syntax = "proto2";
-
-import "tensorflow/core/framework/types.proto";
-
-package tensorflow.contrib.proto;
-
-// A TestCase holds a proto and a bunch of assertions
-// about how it should decode.
-message TestCase {
- // A batch of primitives to be serialized and decoded.
- repeated RepeatedPrimitiveValue primitive = 1;
- // The shape of the batch.
- repeated int32 shape = 2;
- // Expected sizes for each field.
- repeated int32 sizes = 3;
- // Expected values for each field.
- repeated FieldSpec field = 4;
-};
-
-// FieldSpec describes the expected output for a single field.
-message FieldSpec {
- optional string name = 1;
- optional tensorflow.DataType dtype = 2;
- optional RepeatedPrimitiveValue expected = 3;
-};
-
-message TestValue {
- optional PrimitiveValue primitive_value = 1;
- optional EnumValue enum_value = 2;
- optional MessageValue message_value = 3;
- optional RepeatedMessageValue repeated_message_value = 4;
- optional RepeatedPrimitiveValue repeated_primitive_value = 6;
-}
-
-message PrimitiveValue {
- optional double double_value = 1;
- optional float float_value = 2;
- optional int64 int64_value = 3;
- optional uint64 uint64_value = 4;
- optional int32 int32_value = 5;
- optional fixed64 fixed64_value = 6;
- optional fixed32 fixed32_value = 7;
- optional bool bool_value = 8;
- optional string string_value = 9;
- optional bytes bytes_value = 12;
- optional uint32 uint32_value = 13;
- optional sfixed32 sfixed32_value = 15;
- optional sfixed64 sfixed64_value = 16;
- optional sint32 sint32_value = 17;
- optional sint64 sint64_value = 18;
-}
-
-// NOTE: This definition must be kept in sync with PackedPrimitiveValue.
-message RepeatedPrimitiveValue {
- repeated double double_value = 1;
- repeated float float_value = 2;
- repeated int64 int64_value = 3;
- repeated uint64 uint64_value = 4;
- repeated int32 int32_value = 5;
- repeated fixed64 fixed64_value = 6;
- repeated fixed32 fixed32_value = 7;
- repeated bool bool_value = 8;
- repeated string string_value = 9;
- repeated bytes bytes_value = 12;
- repeated uint32 uint32_value = 13;
- repeated sfixed32 sfixed32_value = 15;
- repeated sfixed64 sfixed64_value = 16;
- repeated sint32 sint32_value = 17;
- repeated sint64 sint64_value = 18;
- repeated PrimitiveValue message_value = 19;
-}
-
-// A PackedPrimitiveValue looks exactly the same as a RepeatedPrimitiveValue
-// in the text format, but the binary serializion is different.
-// We test the packed representations by loading the same test cases
-// using this definition instead of RepeatedPrimitiveValue.
-// NOTE: This definition must be kept in sync with RepeatedPrimitiveValue
-// in every way except the packed=true declaration.
-message PackedPrimitiveValue {
- repeated double double_value = 1 [packed = true];
- repeated float float_value = 2 [packed = true];
- repeated int64 int64_value = 3 [packed = true];
- repeated uint64 uint64_value = 4 [packed = true];
- repeated int32 int32_value = 5 [packed = true];
- repeated fixed64 fixed64_value = 6 [packed = true];
- repeated fixed32 fixed32_value = 7 [packed = true];
- repeated bool bool_value = 8 [packed = true];
- repeated string string_value = 9;
- repeated bytes bytes_value = 12;
- repeated uint32 uint32_value = 13 [packed = true];
- repeated sfixed32 sfixed32_value = 15 [packed = true];
- repeated sfixed64 sfixed64_value = 16 [packed = true];
- repeated sint32 sint32_value = 17 [packed = true];
- repeated sint64 sint64_value = 18 [packed = true];
- repeated PrimitiveValue message_value = 19;
-}
-
-message EnumValue {
- enum Color {
- RED = 0;
- ORANGE = 1;
- YELLOW = 2;
- GREEN = 3;
- BLUE = 4;
- INDIGO = 5;
- VIOLET = 6;
- };
- optional Color enum_value = 14;
- repeated Color repeated_enum_value = 15;
-}
-
-
-message InnerMessageValue {
- optional float float_value = 2;
- repeated bytes bytes_values = 8;
-}
-
-message MiddleMessageValue {
- repeated int32 int32_values = 5;
- optional InnerMessageValue message_value = 11;
- optional uint32 uint32_value = 13;
-}
-
-message MessageValue {
- optional double double_value = 1;
- optional MiddleMessageValue message_value = 11;
-}
-
-message RepeatedMessageValue {
- message NestedMessageValue {
- optional float float_value = 2;
- repeated bytes bytes_values = 8;
- }
-
- repeated NestedMessageValue message_values = 11;
-}
-
-// Message containing fields with field numbers higher than any field above. An
-// instance of this message is prepended to each binary message in the test to
-// exercise the code path that handles fields encoded out of order of field
-// number.
-message ExtraFields {
- optional string string_value = 1776;
- optional bool bool_value = 1777;
-}
"//tensorflow/contrib/labeled_tensor:labeled_tensor_pip",
"//tensorflow/contrib/nn:nn_py",
"//tensorflow/contrib/predictor:predictor_pip",
- "//tensorflow/contrib/proto:proto_pip",
"//tensorflow/contrib/receptive_field:receptive_field_pip",
"//tensorflow/contrib/rpc:rpc_pip",
"//tensorflow/contrib/session_bundle:session_bundle_pip",
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