Wrap unsqueeze & squeeze ops

python/paddle/fluid/layers/nn.py

@@ -84,6 +84,8 @@ __all__ = [
     'one_hot',
     'autoincreased_step_counter',
     'reshape',
+    'squeeze',
+    'unsqueeze',
     'lod_reset',
     'lrn',
     'pad',
@@ -4483,6 +4485,86 @@ def reshape(x, shape, actual_shape=None, act=None, inplace=True, name=None):
 
     return helper.append_activation(out)
 
+def squeeze(x, axes, inplace=False, name=None):
+    """
+    Remove single-dimensional entries from the shape of a tensor. Takes a 
+    parameter axes with a list of axes to squeeze. If axes is not provided, all 
+    the single dimensions will be removed from the shape. If an axis is 
+    selected with shape entry not equal to one, an error is raised.
+        
+    Examples:
+    Case 1:
+      Given 
+        X.shape = (1, 3, 1, 5)
+      and
+        axes = [0]
+      we get:
+        Out.shape = (3, 1, 5)
+      Case 2:
+        Given
+          X.shape = (1, 3, 1, 5)
+        and 
+          axes = []
+        we get:
+          Out.shape = (3, 5)
+    
+    Args:
+        x (Variable): The input variable to be squeezed.
+        axes (list): List of integers, indicating the dimensions to be squeezed.
+        name (str): Name for this layers.
+
+    Returns:
+        Variable: Output squeezed variable.
+
+    Examples:
+        .. code-block:: python
+
+            x = layers.data(name='x', shape=[5, 1, 10])
+            y = layers.sequeeze(x, axes=[1])
+    """
+    helper = LayerHelper("squeeze", **locals())
+    out = helper.create_tmp_variable(dtype=x.dtype)
+    helper.append_op(
+        type="squeeze",
+        inputs={"X": x},
+        attrs={"axes": axes},
+        outputs={"Out": out})
+
+    return out 
+    
+def unsqueeze(x, axes, inplace=False, name=None):
+    """
+    Insert single-dimensional entries to the shape of a tensor. Takes one 
+    required argument axes, a list of dimensions that will be inserted. 
+    Dimension indices in axes are as seen in the output tensor. 
+
+    For example: 
+      Given a tensor such that tensor with shape [3, 4, 5], 
+      then Unsqueezed tensor with axes=[0, 4] has shape [1, 3, 4, 5, 1].
+    
+    Args:
+        x (Variable): The input variable to be unsqueezed.
+        axes (list): List of integers, indicating the dimensions to be inserted.
+        name (str): Name for this layers.
+
+    Returns:
+        Variable: Output unsqueezed variable.
+
+    Examples:
+        .. code-block:: python
+
+            x = layers.data(name='x', shape=[5, 10])
+            y = layers.unsequeeze(x, axes=[1])
+    """
+    helper = LayerHelper("unsqueeze", **locals())
+    out = helper.create_tmp_variable(dtype=x.dtype)
+    helper.append_op(
+        type="unsqueeze",
+        inputs={"X": x},
+        attrs={"axes": axes},
+        outputs={"Out": out})
+
+    return out 
 
 def lod_reset(x, y=None, target_lod=None):
     """

python/paddle/fluid/tests/unittests/test_layers.py

@@ -240,6 +240,22 @@ class TestBook(unittest.TestCase):
             self.assertIsNotNone(layers.softmax(hid))
         print(str(program))
 
+    def test_sequence_unsqueeze(self):
+        program = Program()
+        with program_guard(program):
+            x = layers.data(name='x', shape=[8,2], dtype='float32')
+            out = layers.unsqueeze(x=x, axes=[1])
+            self.assertIsNotNone(out)
+        print(str(program))
+   
+    def test_squeeze(self):
+        program = Program()
+        with program_guard(program):
+            x = layers.data(name='x', shape=[1, 1, 4], dtype='float32')
+            out = layers.squeeze(x=x, axes=[0])
+            self.assertIsNotNone(out)
+        print(str(program))
+
     def test_lrn(self):
         program = Program()
         with program_guard(program):
@@ -261,6 +277,7 @@ class TestBook(unittest.TestCase):
             out = layers.sequence_reshape(input=x, new_dim=16)
             self.assertIsNotNone(out)
         print(str(program))
+    
 
     def test_im2sequence(self):
         program = Program()