Port logical_ops to nn

python/paddle/fluid/layers/control_flow.py

@@ -21,7 +21,7 @@ from .. import core
 from ..framework import Program, Variable, Operator
 from ..layer_helper import LayerHelper, unique_name
 from ..initializer import force_init_on_cpu
-from .ops import logical_and, logical_not, logical_or
+from .nn import logical_and, logical_not, logical_or
 import numpy
 import warnings
 import six

python/paddle/fluid/layers/nn.py

@@ -133,6 +133,10 @@ __all__ = [
     'elementwise_max',
     'elementwise_min',
     'elementwise_pow',
+    'logical_and',
+    'logical_or',
+    'logical_xor',
+    'logical_not',
 ]
 
 
@@ -6616,3 +6620,100 @@ for func in [
             "act (basestring|None): Activation applied to the output.",
             "name (basestring|None): Name of the output."
         ])
+
+
+def _logical_op(op_name, x, y, name=None, out=None, binary_op=True):
+    helper = LayerHelper(op_name, **locals())
+
+    assert x.dtype == y.dtype
+
+    if out is None:
+        if name is None:
+            out = helper.create_tmp_variable(dtype=x.dtype)
+        else:
+            out = helper.create_variable(
+                name=name, dtype=x.dtype, persistable=False)
+
+    if binary_op:
+        helper.append_op(
+            type=op_name, inputs={"X": x,
+                                  "Y": y}, outputs={"Out": out})
+    else:
+        helper.append_op(type=op_name, inputs={"X": x}, outputs={"Out": out})
+
+    return out
+
+
+@templatedoc()
+def logical_and(x, y, name=None, out=None):
+    """
+    ${comment}
+
+    Args:
+        x(${x_type}): ${x_comment}
+        y(${y_type}): ${y_comment}
+        out(Tensor): Output tensor of logical operation.
+        name(basestring|None): Name of the output.
+
+    Returns:
+        out(${out_type}): ${out_comment}
+    """
+
+    return _logical_op(
+        op_name="logical_and", x=x, y=y, name=name, out=out, binary_op=True)
+
+
+@templatedoc()
+def logical_or(x, y, name=None, out=None):
+    """
+    ${comment}
+
+    Args:
+        x(${x_type}): ${x_comment}
+        y(${y_type}): ${y_comment}
+        out(Tensor): Output tensor of logical operation.
+        name(basestring|None): Name of the output.
+
+    Returns:
+        out(${out_type}): ${out_comment}
+    """
+
+    return _logical_op(
+        op_name="logical_or", x=x, y=y, name=name, out=out, binary_op=True)
+
+
+@templatedoc()
+def logical_xor(x, y, name=None, out=None):
+    """
+    ${comment}
+
+    Args:
+        x(${x_type}): ${x_comment}
+        y(${y_type}): ${y_comment}
+        out(Tensor): Output tensor of logical operation.
+        name(basestring|None): Name of the output.
+
+    Returns:
+        out(${out_type}): ${out_comment}
+    """
+
+    return _logical_op(
+        op_name="logical_xor", x=x, y=y, name=name, out=out, binary_op=True)
+
+
+@templatedoc()
+def logical_not(x, name=None, out=None):
+    """
+    ${comment}
+
+    Args:
+        x(${x_type}): ${x_comment}
+        out(Tensor): Output tensor of logical operation.
+        name(basestring|None): Name of the output.
+
+    Returns:
+        out(${out_type}): ${out_comment}
+    """
+
+    return _logical_op(
+        op_name="logical_not", x=x, y=None, name=name, out=out, binary_op=False)

python/paddle/fluid/layers/ops.py

@@ -41,10 +41,6 @@ __all__ = [
     'sigmoid_cross_entropy_with_logits',
     'clip',
     'clip_by_norm',
-    'logical_and',
-    'logical_or',
-    'logical_xor',
-    'logical_not',
     'uniform_random_batch_size_like',
     'gaussian_random',
     'sampling_id',