# 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. # ============================================================================== """Logical boolean operators: not, and, or.""" from tensorflow.python.framework import tensor_util from tensorflow.python.ops import control_flow_ops from tensorflow.python.ops import gen_math_ops def not_(a): """Functional form of "not".""" if tensor_util.is_tf_type(a): return _tf_not(a) return _py_not(a) def _tf_not(a): """Implementation of the "not_" operator for TensorFlow.""" return gen_math_ops.logical_not(a) def _py_not(a): """Default Python implementation of the "not_" operator.""" return not a def and_(a, b): """Functional form of "and". Uses lazy evaluation semantics.""" a_val = a() if tensor_util.is_tf_type(a_val): return _tf_lazy_and(a_val, b) return _py_lazy_and(a_val, b) def _tf_lazy_and(cond, b): """Lazy-eval equivalent of "and" for Tensors.""" # TODO(mdan): Enforce cond is scalar here? return control_flow_ops.cond(cond, b, lambda: cond) def _py_lazy_and(cond, b): """Lazy-eval equivalent of "and" in Python.""" return cond and b() def or_(a, b): """Functional form of "or". Uses lazy evaluation semantics.""" a_val = a() if tensor_util.is_tf_type(a_val): return _tf_lazy_or(a_val, b) return _py_lazy_or(a_val, b) def _tf_lazy_or(cond, b): """Lazy-eval equivalent of "or" for Tensors.""" # TODO(mdan): Enforce cond is scalar here? return control_flow_ops.cond(cond, lambda: cond, b) def _py_lazy_or(cond, b): """Lazy-eval equivalent of "or" in Python.""" return cond or b() def eq(a, b): """Functional form of "equal".""" if tensor_util.is_tf_type(a) or tensor_util.is_tf_type(b): return _tf_equal(a, b) return _py_equal(a, b) def _tf_equal(a, b): """Overload of "equal" for Tensors.""" return gen_math_ops.equal(a, b) def _py_equal(a, b): """Overload of "equal" that falls back to Python's default implementation.""" return a == b def not_eq(a, b): """Functional form of "not-equal".""" return not_(eq(a, b))