From 985e4ab62dc6ca2eb023d8c1e0c633dc235c847a Mon Sep 17 00:00:00 2001 From: Yu Yang Date: Tue, 28 Nov 2017 15:35:36 +0800 Subject: [PATCH] Add Python wrap of conv2d_transpose and its unittest (#5946) * Add Python wrap of conv2d_transpose and its unittest * Follow comments * Fix format --- paddle/operators/conv_transpose_op.cc | 18 ++-- paddle/operators/detail/send_recv.proto | 6 +- python/paddle/v2/fluid/layers.py | 93 ++++++++++++++++++++- python/paddle/v2/fluid/tests/test_layers.py | 9 ++ 4 files changed, 112 insertions(+), 14 deletions(-) diff --git a/paddle/operators/conv_transpose_op.cc b/paddle/operators/conv_transpose_op.cc index 3e55ef036a7..314b577d006 100644 --- a/paddle/operators/conv_transpose_op.cc +++ b/paddle/operators/conv_transpose_op.cc @@ -74,12 +74,12 @@ Conv2DTransposeOpMaker::Conv2DTransposeOpMaker( "The format of output tensor is also NCHW."); AddAttr>( "strides", - "(vector defalut:{1, 1}), the strides(h_stride, w_stride) of " + "(vector default:{1, 1}), the strides(h_stride, w_stride) of " "convolution transpose operator.") .SetDefault({1, 1}); AddAttr>( "paddings", - "(vector defalut:{0, 0}), the paddings(h_pad, w_pad) of convolution " + "(vector default:{0, 0}), the paddings(h_pad, w_pad) of convolution " "transpose operator.") .SetDefault({0, 0}); AddComment(R"DOC( @@ -101,8 +101,8 @@ Example: Output: Output shape: (N, C_out, H_out, W_out) where - H_out = (H_in - 1) * strides[0] - 2 * paddings[0] + filter_size[0]; - W_out = (W_in - 1) * strides[1] - 2 * paddings[1] + filter_size[1]; + H_out = (H_in - 1) * strides[0] - 2 * paddings[0] + H_f; + W_out = (W_in - 1) * strides[1] - 2 * paddings[1] + W_f; )DOC"); } @@ -130,12 +130,12 @@ Conv3DTransposeOpMaker::Conv3DTransposeOpMaker( "the number of channels, D is the depth of the feature, H is the " "height of the feature, and W is the width of the feature."); AddAttr>("strides", - "(vector defalut:{1, 1, 1}), the " + "(vector default:{1, 1, 1}), the " "strides{d_stride, h_stride, w_stride} of " "convolution transpose operator.") .SetDefault({1, 1, 1}); AddAttr>("paddings", - "(vector defalut:{0, 0, 0}), paddings(d_pad, " + "(vector default:{0, 0, 0}), paddings(d_pad, " "h_pad, w_pad) of convolution transpose operator.") .SetDefault({0, 0, 0}); AddComment(R"DOC( @@ -158,9 +158,9 @@ Example: Output: Output shape: (N, C_out, D_out, H_out, W_out) where - D_out = (D_in - 1) * strides[0] - 2 * paddings[0] + filter_size[0]; - H_out = (H_in - 1) * strides[1] - 2 * paddings[1] + filter_size[1]; - W_out = (W_in - 1) * strides[2] - 2 * paddings[2] + filter_size[2]; + D_out = (D_in - 1) * strides[0] - 2 * paddings[0] + D_f; + H_out = (H_in - 1) * strides[1] - 2 * paddings[1] + H_f; + W_out = (W_in - 1) * strides[2] - 2 * paddings[2] + W_f; )DOC"); } diff --git a/paddle/operators/detail/send_recv.proto b/paddle/operators/detail/send_recv.proto index 66f84678b3c..962c7d59819 100644 --- a/paddle/operators/detail/send_recv.proto +++ b/paddle/operators/detail/send_recv.proto @@ -17,7 +17,7 @@ syntax = "proto3"; package sendrecv; service SendRecvService { - // For parameter server round-robin like hashing, do not split tensors. + // For parameter server round-robin like hashing, do not split tensors. // Send and recv only one tensor rpc SendVariable(VariableMessage) returns (VariableMessage) {} } @@ -32,6 +32,4 @@ message VariableMessage { bytes serialized = 2; } -message VoidMessage { - -} \ No newline at end of file +message VoidMessage {} \ No newline at end of file diff --git a/python/paddle/v2/fluid/layers.py b/python/paddle/v2/fluid/layers.py index 5a76c79db1d..6adfac3a32c 100644 --- a/python/paddle/v2/fluid/layers.py +++ b/python/paddle/v2/fluid/layers.py @@ -1,7 +1,7 @@ import core import proto.framework_pb2 as framework_pb2 from framework import OpProtoHolder, Variable, Program, Operator -from initializer import Constant, Normal, Xavier +from initializer import Constant, Normal, Xavier, Initializer from paddle.v2.fluid.layer_helper import LayerHelper, unique_name import re import cStringIO @@ -1587,6 +1587,97 @@ def array_length(array, main_program=None): return tmp +def conv2d_transpose(input, + num_filters, + output_size=None, + filter_size=None, + padding=None, + stride=None, + param_attr=None, + param_initializer=None, + main_program=None, + startup_program=None): + """ + The transpose of conv2d layer. + + This layer is also known as deconvolution layer. + + Args: + input(Variable): The input image with [N, C, H, W] format. + num_filters(int): The number of filter. It is as same as the output + image channel. + output_size(int|tuple|None): The output image size. If output size is a + tuple, it must contain two integers, (image_H, image_W). This + parameter only works when filter_size is None. + filter_size(int|tuple|None): The filter size. If filter_size is a tuple, + it must contain two integers, (filter_size_H, filter_size_W). + Otherwise, the filter will be a square. None if use output size to + calculate filter_size + padding(int|tuple): The padding size. If padding is a tuple, it must + contain two integers, (padding_H, padding_W). Otherwise, the + padding_H = padding_W = padding. + stride(int|tuple): The stride size. If stride is a tuple, it must + contain two integers, (stride_H, stride_W). Otherwise, the + stride_H = stride_W = stride. + param_attr: Parameter Attribute. + param_initializer(Initializer): Parameter Initializer. Default is Xavier + main_program(Program): the main program + startup_program(Program): the startup program + + Returns: + Variable: Output image. + """ + helper = LayerHelper("conv2d_transpose", **locals()) + if not isinstance(input, Variable): + raise TypeError("Input of conv2d_transpose must be Variable") + input_channel = input.shape[1] + + op_attr = dict() + + if isinstance(padding, int): + op_attr['paddings'] = [padding, padding] + elif padding is not None: + op_attr['paddings'] = padding + + if isinstance(stride, int): + op_attr['strides'] = stride + elif stride is not None: + op_attr['strides'] = stride + + if filter_size is None: + if output_size is None: + raise ValueError("output_size must be set when filter_size is None") + if isinstance(output_size, int): + output_size = [output_size, output_size] + + padding = op_attr.get('paddings', [0, 0]) + stride = op_attr.get('strides', [1, 1]) + + h_in = input.shape[2] + w_in = input.shape[3] + filter_size_h = output_size[0] - (h_in - 1) * stride[0] + 2 * padding[0] + filter_size_w = output_size[1] - (w_in - 1) * stride[1] + 2 * padding[1] + filter_size = [filter_size_h, filter_size_w] + elif isinstance(filter_size, int): + filter_size = [filter_size, filter_size] + + filter_shape = [input_channel, num_filters] + filter_size + img_filter = helper.create_parameter( + dtype=input.dtype, + shape=filter_shape, + attr=helper.param_attr, + initializer=param_initializer) + + out = helper.create_tmp_variable(dtype=input.dtype) + helper.append_op( + type='conv2d_transpose', + inputs={'Input': [input], + 'Filter': [img_filter]}, + outputs={'Output': out}, + attrs=op_attr) + return out + + class ConditionalBlockGuard(BlockGuard): def __init__(self, block): if not isinstance(block, ConditionalBlock): diff --git a/python/paddle/v2/fluid/tests/test_layers.py b/python/paddle/v2/fluid/tests/test_layers.py index 87dc6d1a627..62b2a0f9a11 100644 --- a/python/paddle/v2/fluid/tests/test_layers.py +++ b/python/paddle/v2/fluid/tests/test_layers.py @@ -65,6 +65,15 @@ class TestBook(unittest.TestCase): print str(program) + def test_conv2d_transpose(self): + program = Program() + kwargs = {'main_program': program} + img = layers.data( + name='pixel', shape=[3, 2, 2], dtype='float32', **kwargs) + layers.conv2d_transpose( + input=img, num_filters=10, output_size=28, **kwargs) + print str(program) + def test_recognize_digits_conv(self): program = Program() -- GitLab