write input.py

python/paddle/nn/functional/input.py

@@ -11,3 +11,96 @@
 # 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.
+
+from __future__ import print_function
+import warnings
+from ...fluid.framework import Variable, in_dygraph_mode
+from ...fluid.layer_helper import LayerHelper
+from ...fluid.layers import core
+from ...fluid.data_feeder import check_variable_and_dtype, check_dtype
+
+__all__ = ['one_hot']
+
+
+def one_hot(x, num_classes, name=None):
+    """
+    :alias_main: paddle.nn.functional.one_hot
+	:alias: paddle.nn.functional.one_hot,paddle.nn.functional.common.one_hot
+	:old_api: paddle.fluid.one_hot
+
+    The operator converts each id in the input 'x' to an one-hot vector with a
+    num_classes length. The value in the vector dimension corresponding to the id
+    is 1, and the value in the remaining dimension is 0.
+
+    The shape of output Tensor is generated by appending num_classes dimension
+    behind the last dimension of the 'x' shape.
+
+    .. code-block:: text
+
+        Example 1:
+
+        input:
+            x.shape = [4, 1]
+            x.data = [1, 1, 3, 0]
+            num_classes = 4
+
+        output:
+            Out.shape = [4, 4]
+            Out.data = [[0., 1., 0., 0.],
+                        [0., 1., 0., 0.],
+                        [0., 0., 0., 1.],
+                        [1., 0., 0., 0.]]
+
+        Example 2:
+
+        input:
+            x.shape = [4, 1]
+            x.data = [1, 1, 5, 0]
+            num_classes = 4
+
+        output: Throw an exception for Illegal value
+            The second dimension in X is 5, which is greater than num_classes,
+            so it throws an exception.
+
+
+    Args:
+        x(Tensor): Tensor with shape :math:`[N_1, N_2, ..., N_k]` ,
+            which contains at least one dimension. The data type is int32 or int64.
+        num_classes(int): An integer defining the num_classes of the one hot dimension. If input 'x'
+            is word id, num_classes is generally the dictionary size.
+
+    Returns:
+        Tensor: The one-hot representations of 'x'. A Tensor with type float32.
+
+    Examples:
+        .. code-block:: python
+
+            import paddle.fluid as fluid
+            # Correspond to the first example above, where label.shape is 4 and one_hot_label.shape is [4, 4].
+            label = fluid.data(name="label", shape=[4, 1], dtype="int64")
+            one_hot_label = fluid.one_hot(x=label, num_classes=4)
+    """
+    check_variable_and_dtype(x, 'input', ['int32', 'int64'], 'one_hot_v2')
+    helper = LayerHelper("one_hot_v2", **locals())
+
+    one_hot_out = helper.create_variable_for_type_inference(dtype='float32')
+
+    if in_dygraph_mode():
+        return core.ops.one_hot_v2(x, 'depth', num_classes,
+                                   'allow_out_of_range', False)
+    else:
+        if not isinstance(num_classes, Variable):
+            # user attribute 
+            inputs = {'X': x}
+            attrs = {'depth': num_classes, 'allow_out_of_range': False}
+        else:
+            num_classes.stop_gradient = True
+            inputs = {'X': x, 'depth_tensor': num_classes}
+            attrs = {'allow_out_of_range': False}
+        helper.append_op(
+            type="one_hot_v2",
+            inputs=inputs,
+            attrs=attrs,
+            outputs={'Out': one_hot_out},
+            stop_gradient=True)
+        return one_hot_out