From 8d4c453bbb7980491d539bbe574d5e729c90a097 Mon Sep 17 00:00:00 2001
From: Haonan <yu239@users.noreply.github.com>
Date: Wed, 9 Nov 2016 17:24:37 -0800
Subject: [PATCH] set mixedlayer output size according to input operator (#414)
* set mixedlayer output size according to input operator
* change from num_channel to num_channels for conv_operator (the old one is
really misleading because all the others are num_channels)
* also changed the arg name in projections.py
---
.../paddle/trainer_config_helpers/layers.py | 43 ++++++++++---------
.../tests/configs/projections.py | 2 +-
.../tests/layers_test_config.py | 4 +-
3 files changed, 27 insertions(+), 22 deletions(-)
diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py
index 49f0ff3289..6b5d39a471 100644
--- a/python/paddle/trainer_config_helpers/layers.py
+++ b/python/paddle/trainer_config_helpers/layers.py
@@ -590,7 +590,7 @@ class MixedLayerType(LayerOutput):
def __exit__(self, *args, **kwargs):
del args, kwargs # unused parameter to suppress warning
assert len(self.inputs) != 0
- MixedLayer(
+ ml = MixedLayer(
name=self.name,
size=self.size,
active_type=self.activation.name,
@@ -598,6 +598,9 @@ class MixedLayerType(LayerOutput):
inputs=self.inputs,
**ExtraLayerAttribute.to_kwargs(self.layer_attr)
)
+ # update the size which might be computed inside MixedLayer
+ # according to the operator's output size
+ self.size = ml.config.size
@wrap_name_default("mixed")
@@ -2045,7 +2048,7 @@ def concat_layer(input, act=None, name=None, layer_attr=None, bias_attr=None):
if layer_type == LayerType.CONCAT_LAYER:
assert not bias_attr
-
+
Layer(
name=name, type=layer_type,
inputs=[x.name for x in input] if is_concat_layer else input,
@@ -2623,7 +2626,7 @@ def out_prod_layer(input1, input2, name=None, layer_attr=None):
assert isinstance(input1, LayerOutput)
assert isinstance(input2, LayerOutput)
Layer(name=name,
- type="out_prod",
+ type=LayerType.OUT_PROD_LAYER,
inputs=[input1.name, input2.name],
**ExtraLayerAttribute.to_kwargs(layer_attr))
return LayerOutput(name=name,
@@ -2790,7 +2793,7 @@ def beam_search(step, input, bos_id, eos_id, beam_size,
def __cost_input__(input, label, weight=None):
"""
- inputs and parents for cost layers.
+ inputs and parents for cost layers.
"""
ipts = [Input(input.name), Input(label.name)]
parents = [input, label]
@@ -2799,7 +2802,7 @@ def __cost_input__(input, label, weight=None):
ipts.append(Input(weight.name))
parents.append(weight)
return ipts, parents
-
+
@wrap_name_default()
@layer_support()
@@ -2884,7 +2887,7 @@ def classification_cost(input, label, weight=None, name=None,
def conv_operator(img, filter, filter_size, num_filters,
- num_channel=None, stride=1, padding=0,
+ num_channels=None, stride=1, padding=0,
filter_size_y=None, stride_y=None, padding_y=None):
"""
Different from img_conv_layer, conv_op is an Operator, which can be used
@@ -2914,8 +2917,8 @@ def conv_operator(img, filter, filter_size, num_filters,
:type filter_size_y: int
:param num_filters: channel of output data.
:type num_filters: int
- :param num_channel: channel of input data.
- :type num_channel: int
+ :param num_channels: channel of input data.
+ :type num_channels: int
:param stride: The x dimension of the stride.
:type stride: int
:param stride_y: The y dimension of the stride.
@@ -2934,19 +2937,19 @@ def conv_operator(img, filter, filter_size, num_filters,
if padding_y is None:
padding_y = padding
- if num_channel is None:
- num_channel = img.num_filters
+ if num_channels is None:
+ num_channels = img.num_filters
assert isinstance(filter, LayerOutput)
if filter.size is not None:
- filter.size = filter_size * filter_size_y * num_filters * num_channel
+ filter.size = filter_size * filter_size_y * num_filters * num_channels
op = ConvOperator(input_layer_names=[img.name, filter.name],
num_filters=num_filters,
conv_conf=Conv(filter_size=filter_size,
padding=padding,
stride=stride,
- channels=num_channel,
+ channels=num_channels,
filter_size_y=filter_size_y,
padding_y=padding_y,
stride_y=stride_y,
@@ -2986,8 +2989,8 @@ def conv_projection(input, filter_size, num_filters,
:type filter_size_y: int
:param num_filters: channel of output data.
:type num_filters: int
- :param num_channel: channel of input data.
- :type num_channel: int
+ :param num_channels: channel of input data.
+ :type num_channels: int
:param stride: The x dimension of the stride.
:type stride: int
:param stride_y: The y dimension of the stride.
@@ -3478,15 +3481,15 @@ def maxout_layer(input,
- Input: output of a conv layer.
- Output: feature map size same as input. Channel is (input channel) / groups.
- So groups should be larger than 1, and the num of channels should be able
+ So groups should be larger than 1, and the num of channels should be able
to devided by groups.
- Please refer to Paper:
+ Please refer to Paper:
- Maxout Networks: http://www.jmlr.org/proceedings/papers/v28/goodfellow13.pdf
- Multi-digit Number Recognition from Street View \
Imagery using Deep Convolutional Neural Networks: \
https://arxiv.org/pdf/1312.6082v4.pdf
-
+
The simple usage is:
.. code-block:: python
@@ -3731,9 +3734,9 @@ def nce_layer(input, label, num_classes, weight=None,
:param weight: weight layer, can be None(default)
:type weight: LayerOutput
:param num_classes: number of classes.
- :type num_classes: int
+ :type num_classes: int
:param num_neg_samples: number of negative samples. Default is 10.
- :type num_neg_samples: int
+ :type num_neg_samples: int
:param neg_distribution: The distribution for generating the random negative labels.
A uniform distribution will be used if not provided.
If not None, its length must be equal to num_classes.
@@ -3754,7 +3757,7 @@ def nce_layer(input, label, num_classes, weight=None,
assert isinstance(neg_distribution, collections.Sequence)
assert len(neg_distribution) == num_classes
assert sum(neg_distribution) == 1
-
+
ipts_for_layer = []
parents = []
for each_input in input:
diff --git a/python/paddle/trainer_config_helpers/tests/configs/projections.py b/python/paddle/trainer_config_helpers/tests/configs/projections.py
index 4066c5bc6e..51194b5a2a 100644
--- a/python/paddle/trainer_config_helpers/tests/configs/projections.py
+++ b/python/paddle/trainer_config_helpers/tests/configs/projections.py
@@ -35,7 +35,7 @@ flt = data_layer(name='filter', size=3*3*1*64)
with mixed_layer() as m7:
m7 += conv_operator(img=img, filter=flt, num_filters=64,
- num_channel=1, filter_size=3)
+ num_channels=1, filter_size=3)
end = mixed_layer(input=[full_matrix_projection(input=m5),
trans_full_matrix_projection(input=m6),
diff --git a/python/paddle/trainer_config_helpers/tests/layers_test_config.py b/python/paddle/trainer_config_helpers/tests/layers_test_config.py
index faaab9107d..26be84f122 100644
--- a/python/paddle/trainer_config_helpers/tests/layers_test_config.py
+++ b/python/paddle/trainer_config_helpers/tests/layers_test_config.py
@@ -29,9 +29,11 @@ z1 = mixed_layer(act=LinearActivation(),
filter=y1,
filter_size=1,
num_filters=5,
- num_channel=5,
+ num_channels=5,
stride=1)])
+assert z1.size > 0
+
y2 = fc_layer(input=y, size=15)
cos1 = cos_sim(a=x1, b=y1)