From 8d4c453bbb7980491d539bbe574d5e729c90a097 Mon Sep 17 00:00:00 2001 From: Haonan 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 49f0ff3289d..6b5d39a4715 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 4066c5bc6e0..51194b5a2a8 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 faaab9107d8..26be84f1221 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) -- GitLab