add config helper for sequence slice layer.

doc/api/v2/config/layer.rst

@@ -257,6 +257,11 @@ seq_concat
 ..  autoclass:: paddle.v2.layer.seq_concat
     :noindex:
 
+seq_slice
+---------
+..  autoclass:: paddle.v2.layer.seq_slice
+    :noindex:
+
 Reshaping Layers
 ================
 

python/paddle/trainer/config_parser.py

@@ -2657,6 +2657,51 @@ class SubSequenceLayer(LayerBase):
         self.create_bias_parameter(bias, size)
 
 
+@config_layer('seq_slice')
+class SeqSliceLayer(LayerBase):
+    def __init__(self, name, inputs, starts, ends, bias=False, **xargs):
+        if isinstance(inputs, list):
+            assert len(inputs) == 1, ('the first input of sequence slice layer '
+                                      'is a single sequence input.')
+        else:
+            inputs = [inputs]
+
+        if starts is not None:
+            if isinstance(starts, list):
+                assert len(starts) == 1, (
+                    'the start indices for sequence slice layer cannot '
+                    'be a list having more than one element.')
+                starts = starts[0]
+            inputs.append(starts)
+
+        if ends is not None:
+            if isinstance(ends, list):
+                assert len(ends) == 1, (
+                    'the end indices for sequence slice layer cannot '
+                    'be a list having more than one element.')
+                ends = ends[0]
+            inputs.append(ends)
+        assert len(inputs) >= 2, (
+            'the sequence slice layer has at least two inputs.')
+
+        super(SeqSliceLayer, self).__init__(
+            name, 'seq_slice', 0, inputs=inputs, **xargs)
+        input_layer0 = self.get_input_layer(0)
+        size = input_layer0.size
+        self.set_layer_size(size)
+
+        if len(inputs) == 3:
+            assert (
+                self.get_input_layer(1).size == self.get_input_layer(2).size), (
+                    'If start and end indices are both given to'
+                    'sequence slice layer, they should have the same width.')
+        elif len(inputs) == 2:
+            if starts is not None:
+                self.config.select_first = True
+            else:
+                self.config.select_first = False
+
+
 @config_layer('out_prod')
 class OuterProdLayer(LayerBase):
     def __init__(self, name, inputs, device=None):

python/paddle/trainer_config_helpers/layers.py

@@ -131,6 +131,7 @@ __all__ = [
     'crop_layer',
     'clip_layer',
     'slice_projection',
+    'seq_slice_layer',
 ]
 
 
@@ -225,6 +226,7 @@ class LayerType(object):
     PRELU = 'prelu'
     CROP_LAYER = 'crop'
     CLIP_LAYER = 'clip'
+    SEQ_SLICE = 'seq_slice'
 
     @staticmethod
     def is_layer_type(type_name):
@@ -6119,3 +6121,69 @@ def clip_layer(input, min, max, name=None):
         max=max)
     return LayerOutput(
         name, LayerType.CLIP_LAYER, parents=[input], size=input.size)
+
+
+@wrap_name_default()
+def seq_slice_layer(input, starts, ends, name=None):
+    """
+    seq_slice_layer will return one or several sub-sequences from the
+    input sequence layer given start and end indices.
+
+        - If only start indices are given, and end indices are set to None,
+          this layer slices the input sequence from the given start indices
+          to its end.
+        - If only end indices are given, and start indices are set to None,
+          this layer slices the input sequence from its beginning to the
+          given end indices.
+        - If start and end indices are both given, they should have the same
+          number of elements.
+
+    If start or end indices contains more than one elements, the input sequence
+    will be sliced for multiple times.
+
+
+    .. code-block:: python
+
+        seq_silce = seq_slice_layer(input=input_seq,
+                                    starts=start_pos, ends=end_pos)
+
+    :param name: name of this layer.
+    :type name: basestring
+    :param input: input for this layer, it should be a sequence.
+    :type input: LayerOutput
+    :param starts: start indices to slice the input sequence.
+    :type starts: LayerOutput|None
+    :param ends: end indices to slice the input sequence.
+    :type ends: LayerOutput|None
+    :return: LayerOutput object.
+    :rtype: LayerOutput
+
+    """
+
+    assert isinstance(input, LayerOutput), (
+        'The first input of seq_slice layer must be a PaddlePaddle layer.')
+
+    if starts is not None:
+        assert isinstance(starts, LayerOutput), (
+            'The start indices for seq_slice layer '
+            'must be a PaddlePaddle layer.')
+    if ends is not None:
+        assert isinstance(ends, LayerOutput), (
+            'The end indices for seq_slice layer must be a PaddlePaddle layer.')
+    assert starts is not None or ends is not None, (
+        'start and end indices '
+        'cannot be set to None at the same time, at least one of '
+        'them should be given.')
+    if starts is not None and ends is not None:
+        assert starts.size == ends.size, (
+            'If start and end indices are both given to seq_slice_layer, '
+            'they should have the same width.')
+
+    Layer(
+        name=name,
+        type=LayerType.SEQ_SLICE,
+        inputs=input.name,
+        starts=starts.name if starts is not None else None,
+        ends=ends.name if ends is not None else None)
+    return LayerOutput(
+        name, LayerType.SEQ_SLICE, parents=[input], size=input.size)

python/paddle/trainer_config_helpers/tests/configs/file_list.sh

@@ -7,6 +7,7 @@ test_rnn_group shared_fc shared_lstm shared_gru test_cost_layers_with_weight
 test_spp_layer test_bilinear_interp test_maxout test_bi_grumemory math_ops
 test_seq_concat_reshape test_pad test_smooth_l1 test_multiplex_layer
 test_prelu_layer test_row_conv test_detection_output_layer test_multibox_loss_layer
-test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer)
+test_recursive_topology test_gated_unit_layer test_clip_layer test_row_l2_norm_layer
+test_seq_slice_layer)
 
 export whole_configs=(test_split_datasource)

python/paddle/trainer_config_helpers/tests/configs/protostr/test_seq_slice_layer.protostr

@@ -0,0 +1,79 @@
+type: "nn"
+layers {
+  name: "word"
+  type: "data"
+  size: 128
+  active_type: ""
+}
+layers {
+  name: "starts"
+  type: "data"
+  size: 5
+  active_type: ""
+}
+layers {
+  name: "ends"
+  type: "data"
+  size: 5
+  active_type: ""
+}
+layers {
+  name: "__seq_slice_layer_0__"
+  type: "seq_slice"
+  size: 128
+  active_type: ""
+  inputs {
+    input_layer_name: "word"
+  }
+  inputs {
+    input_layer_name: "starts"
+  }
+  inputs {
+    input_layer_name: "ends"
+  }
+}
+layers {
+  name: "__seq_slice_layer_1__"
+  type: "seq_slice"
+  size: 128
+  active_type: ""
+  inputs {
+    input_layer_name: "word"
+  }
+  inputs {
+    input_layer_name: "starts"
+  }
+  select_first: true
+}
+layers {
+  name: "__seq_slice_layer_2__"
+  type: "seq_slice"
+  size: 128
+  active_type: ""
+  inputs {
+    input_layer_name: "word"
+  }
+  inputs {
+    input_layer_name: "ends"
+  }
+  select_first: false
+}
+input_layer_names: "word"
+output_layer_names: "__seq_slice_layer_0__"
+output_layer_names: "__seq_slice_layer_1__"
+output_layer_names: "__seq_slice_layer_2__"
+sub_models {
+  name: "root"
+  layer_names: "word"
+  layer_names: "starts"
+  layer_names: "ends"
+  layer_names: "__seq_slice_layer_0__"
+  layer_names: "__seq_slice_layer_1__"
+  layer_names: "__seq_slice_layer_2__"
+  input_layer_names: "word"
+  output_layer_names: "__seq_slice_layer_0__"
+  output_layer_names: "__seq_slice_layer_1__"
+  output_layer_names: "__seq_slice_layer_2__"
+  is_recurrent_layer_group: false
+}
+

python/paddle/trainer_config_helpers/tests/configs/test_seq_slice_layer.py

@@ -0,0 +1,13 @@
+#!/usr/bin/env python
+#coding=utf-8
+from paddle.trainer_config_helpers import *
+
+input_seq = data_layer("word", size=128)
+starts = data_layer("starts", size=5)
+ends = data_layer("ends", size=5)
+
+seq_slice1 = seq_slice_layer(input=input_seq, starts=starts, ends=ends)
+seq_slice2 = seq_slice_layer(input=input_seq, starts=starts, ends=None)
+seq_slice3 = seq_slice_layer(input=input_seq, starts=None, ends=ends)
+
+outputs(seq_slice1, seq_slice2, seq_slice3)