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# pylint: disable=g-bad-file-header
# Copyright 2016 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.
# ==============================================================================
"""Ops for BrainTree v2 tree evaluation."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import threading
from tensorflow.python.framework import load_library
from tensorflow.python.framework import ops
from tensorflow.python.framework import tensor_shape
from tensorflow.python.platform import resource_loader
from tensorflow.python.platform import tf_logging as logging
INFERENCE_OPS_FILE = '_inference_ops.so'
_inference_ops = None
_ops_lock = threading.Lock()
ops.NoGradient('TreePredictions')
@ops.RegisterShape('TreePredictions')
def TreePredictions(op):
"""Shape function for TreePredictions Op."""
num_points = op.inputs[0].get_shape()[0].value
sparse_shape = op.inputs[3].get_shape()
if sparse_shape.ndims == 2:
num_points = sparse_shape[0].value
num_classes = op.inputs[7].get_shape()[1].value
# The output of TreePredictions is
# [node_pcw(evaluate_tree(x), c) for c in classes for x in input_data].
return [tensor_shape.TensorShape([num_points, num_classes - 1])]
# Workaround for the fact that importing tensorflow imports contrib
# (even if a user isn't using this or any other contrib op), but
# there's not yet any guarantee that the shared object exists.
# In which case, "import tensorflow" will always crash, even for users that
# never use contrib.
def Load():
"""Load the inference ops library and return the loaded module."""
with _ops_lock:
global _inference_ops
if not _inference_ops:
ops_path = resource_loader.get_path_to_datafile(INFERENCE_OPS_FILE)
logging.info('data path: %s', ops_path)
_inference_ops = load_library.load_op_library(ops_path)
assert _inference_ops, 'Could not load inference_ops.so'
return _inference_ops
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