"//tensorflow/contrib/optimizer_v2:optimizer_v2_py",
"//tensorflow/contrib/periodic_resample:init_py",
"//tensorflow/contrib/predictor",
+ "//tensorflow/contrib/proto",
"//tensorflow/contrib/quantization:quantization_py",
"//tensorflow/contrib/quantize:quantize_graph",
"//tensorflow/contrib/autograph",
from tensorflow.contrib import opt
from tensorflow.contrib import periodic_resample
from tensorflow.contrib import predictor
+from tensorflow.contrib import proto
from tensorflow.contrib import quantization
from tensorflow.contrib import quantize
from tensorflow.contrib import recurrent
GENERATE_PYTHON_OP_LIB("cudnn_rnn_ops")
GENERATE_PYTHON_OP_LIB("data_flow_ops")
GENERATE_PYTHON_OP_LIB("dataset_ops")
-GENERATE_PYTHON_OP_LIB("decode_proto_ops")
-GENERATE_PYTHON_OP_LIB("encode_proto_ops")
+GENERATE_PYTHON_OP_LIB("decode_proto_ops"
+ DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/tf_python/tensorflow/contrib/proto/python/ops/gen_decode_proto_op.py)
+GENERATE_PYTHON_OP_LIB("encode_proto_ops"
+ DESTINATION ${CMAKE_CURRENT_BINARY_DIR}/tf_python/tensorflow/contrib/proto/python/ops/gen_encode_proto_op.py)
GENERATE_PYTHON_OP_LIB("image_ops")
GENERATE_PYTHON_OP_LIB("io_ops")
GENERATE_PYTHON_OP_LIB("linalg_ops")
import numpy as np
-from tensorflow.contrib import proto
+from tensorflow.contrib.proto import decode_proto
from tensorflow.contrib.proto.python.kernel_tests import test_case
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import errors
field_types = [dtypes.int32]
with self.test_session() as sess:
- ctensor, vtensor = proto.decode_proto(
+ ctensor, vtensor = decode_proto(
batch,
message_type=msg_type,
field_names=field_names,
from google.protobuf import text_format
-from tensorflow.contrib import proto
+from tensorflow.contrib.proto import decode_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
output_types = [f.dtype for f in fields]
with self.test_session() as sess:
- sizes, vtensor = proto.decode_proto(
+ sizes, vtensor = decode_proto(
batch,
message_type=message_type,
field_names=field_names,
from google.protobuf import text_format
-from tensorflow.contrib import proto
+from tensorflow.contrib.proto import decode_proto
+from tensorflow.contrib.proto import encode_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
# Invalid field name
with self.test_session():
with self.assertRaisesOpError('Unknown field: non_existent_field'):
- proto.encode_proto(
+ encode_proto(
sizes=[[1]],
values=[np.array([[0.0]], dtype=np.int32)],
message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
with self.test_session():
with self.assertRaisesOpError(
'Incompatible type for field double_value.'):
- proto.encode_proto(
+ encode_proto(
sizes=[[1]],
values=[np.array([[0.0]], dtype=np.int32)],
message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
r'sizes should be batch_size \+ \[len\(field_names\)\]'):
sizes = array_ops.placeholder(dtypes.int32)
values = array_ops.placeholder(dtypes.float64)
- proto.encode_proto(
+ encode_proto(
sizes=sizes,
values=[values],
message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
sizes = array_ops.placeholder(dtypes.int32)
values1 = array_ops.placeholder(dtypes.float64)
values2 = array_ops.placeholder(dtypes.int32)
- (proto.encode_proto(
+ (encode_proto(
sizes=[[1, 1]],
values=[values1, values2],
message_type='tensorflow.contrib.proto.RepeatedPrimitiveValue',
out_types = [f.dtype for f in fields]
with self.test_session() as sess:
- sizes, field_tensors = proto.decode_proto(
+ sizes, field_tensors = decode_proto(
in_bufs,
message_type=message_type,
field_names=field_names,
output_types=out_types)
- out_tensors = proto.encode_proto(
+ out_tensors = encode_proto(
sizes,
field_tensors,
message_type=message_type,