From 3b0e43aa6ab4f30ca960537b13f600cc36d6066e Mon Sep 17 00:00:00 2001 From: chengduoZH Date: Wed, 30 Aug 2017 23:09:58 +0800 Subject: [PATCH] add config parse --- proto/ModelConfig.proto | 2 + python/paddle/trainer/config_parser.py | 90 +++++++++++++++++-- .../paddle/trainer_config_helpers/layers.py | 15 +++- .../tests/configs/test_BatchNorm3D.py | 17 ++++ .../tests/layers_test.py | 2 +- 5 files changed, 112 insertions(+), 14 deletions(-) create mode 100644 python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py diff --git a/proto/ModelConfig.proto b/proto/ModelConfig.proto index 95c236ad88..0525fb9dc3 100644 --- a/proto/ModelConfig.proto +++ b/proto/ModelConfig.proto @@ -515,6 +515,8 @@ message LayerConfig { // for HuberRegressionLoss optional double delta = 57 [ default = 1.0 ]; + // for 3D data + optional double depth = 58 [ default = 1 ]; } message EvaluatorConfig { diff --git a/python/paddle/trainer/config_parser.py b/python/paddle/trainer/config_parser.py index c11037c3c8..bc9aacaf11 100644 --- a/python/paddle/trainer/config_parser.py +++ b/python/paddle/trainer/config_parser.py @@ -1172,6 +1172,20 @@ def get_img_size(input_layer_name, channels): return img_size, img_size_y +def get_img3d_size(input_layer_name, channels): + input = g_layer_map[input_layer_name] + img_pixels = input.size / channels + img_size = input.width + img_size_y = input.height + img_size_z = input.depth + + config_assert( + img_size * img_size_y * img_size_z == img_pixels, + "Input layer %s: Incorrect input image size %d * %d * %d for input image pixels %d" + % (input_layer_name, img_size, img_size_y, img_size_z, img_pixels)) + return img_size, img_size_y, img_size_z + + def parse_bilinear(bilinear, input_layer_name, bilinear_conf): parse_image(bilinear, input_layer_name, bilinear_conf.image_conf) bilinear_conf.out_size_x = bilinear.out_size_x @@ -1224,6 +1238,12 @@ def parse_image(image, input_layer_name, image_conf): get_img_size(input_layer_name, image_conf.channels) +def parse_image3d(image, input_layer_name, image_conf): + image_conf.channels = image.channels + image_conf.img_size, image_conf.img_size_y, image_conf.img_size_z = \ + get_img3d_size(input_layer_name, image_conf.channels) + + def parse_norm(norm, input_layer_name, norm_conf): norm_conf.norm_type = norm.norm_type config_assert( @@ -1585,6 +1605,9 @@ class LayerBase(object): self.config.height = height self.config.width = width + def set_layer_depth(self, depth): + self.config.depth = depth + def set_cnn_layer(self, input_layer_name, height, @@ -1788,11 +1811,19 @@ class DetectionOutputLayer(LayerBase): @config_layer('data') class DataLayer(LayerBase): - def __init__(self, name, size, height=None, width=None, device=None): + def __init__(self, + name, + size, + depth=None, + height=None, + width=None, + device=None): super(DataLayer, self).__init__( name, 'data', size, inputs=[], device=device) if height and width: self.set_layer_height_width(height, width) + if depth: + self.set_layer_depth(depth) ''' @@ -2077,6 +2108,7 @@ class BatchNormLayer(LayerBase): name, inputs, bias=True, + img3D=False, use_global_stats=True, moving_average_fraction=0.9, batch_norm_type=None, @@ -2121,15 +2153,33 @@ class BatchNormLayer(LayerBase): input_layer = self.get_input_layer(0) image_conf = self.config.inputs[0].image_conf - parse_image(self.inputs[0].image, input_layer.name, image_conf) - - # Only pass the width and height of input to batch_norm layer - # when either of it is non-zero. - if input_layer.width != 0 or input_layer.height != 0: - self.set_cnn_layer(name, image_conf.img_size_y, image_conf.img_size, - image_conf.channels, False) + if img3D: + parse_image3d(self.inputs[0].image, input_layer.name, image_conf) + # Only pass the width and height of input to batch_norm layer + # when either of it is non-zero. + if input_layer.width != 0 or input_layer.height != 0: + self.set_cnn_layer( + input_layer_name=name, + depth=image_conf.img_size_z, + height=image_conf.img_size_y, + width=image_conf.img_size, + channels=image_conf.channels, + is_print=True) + else: + self.set_layer_size(input_layer.size) else: - self.set_layer_size(input_layer.size) + parse_image(self.inputs[0].image, input_layer.name, image_conf) + # Only pass the width and height of input to batch_norm layer + # when either of it is non-zero. + if input_layer.width != 0 or input_layer.height != 0: + self.set_cnn_layer( + input_layer_name=name, + height=image_conf.img_size_y, + width=image_conf.img_size, + channels=image_conf.channels, + is_print=True) + else: + self.set_layer_size(input_layer.size) psize = self.calc_parameter_size(image_conf) dims = [1, psize] @@ -2139,6 +2189,28 @@ class BatchNormLayer(LayerBase): self.create_bias_parameter(bias, psize) + def set_cnn_layer(self, + input_layer_name, + depth=None, + height=None, + width=None, + channels=None, + is_print=True): + depthIsNone = False + if depth is None: + depth = 1 + depthIsNone = True + size = depth * height * width * channels + self.set_layer_size(size) + self.set_layer_height_width(height, width) + self.set_layer_depth(depth) + if is_print and depthIsNone: + print("output for %s: c = %d, h = %d, w = %d, size = %d" % + (input_layer_name, channels, height, width, size)) + elif is_print: + print("output for %s: c = %d, d = %d, h = %d, w = %d, size = %d" % + (input_layer_name, channels, depth, height, width, size)) + def calc_parameter_size(self, image_conf): return image_conf.channels diff --git a/python/paddle/trainer_config_helpers/layers.py b/python/paddle/trainer_config_helpers/layers.py index a525ce71d0..35c84ad597 100755 --- a/python/paddle/trainer_config_helpers/layers.py +++ b/python/paddle/trainer_config_helpers/layers.py @@ -166,6 +166,7 @@ class LayerType(object): EXCONVTRANS_LAYER = 'exconvt' CUDNNCONV_LAYER = 'cudnn_conv' POOL_LAYER = 'pool' + POOL3D_LAYER = 'pool3d' BATCH_NORM_LAYER = 'batch_norm' NORM_LAYER = 'norm' SUM_TO_ONE_NORM_LAYER = 'sum_to_one_norm' @@ -894,7 +895,8 @@ def mixed_layer(size=0, @layer_support() -def data_layer(name, size, height=None, width=None, layer_attr=None): +def data_layer(name, size, depth=None, height=None, width=None, + layer_attr=None): """ Define DataLayer For NeuralNetwork. @@ -921,15 +923,18 @@ def data_layer(name, size, height=None, width=None, layer_attr=None): type=LayerType.DATA, name=name, size=size, + depth=depth, height=height, width=width, **ExtraLayerAttribute.to_kwargs(layer_attr)) + if depth is None: + depth = 1 num_filters = None if height is not None and width is not None: - num_filters = size / (width * height) - assert num_filters * width * height == size, \ - "size=%s width=%s height=%s" % (size, width, height) + num_filters = size / (width * height * depth) + assert num_filters * width * height * depth == size, \ + "size=%s width=%s height=%s depth=%s" % (size, width, height, depth) return LayerOutput(name, LayerType.DATA, size=size, num_filters=num_filters) @@ -2799,6 +2804,7 @@ def img_cmrnorm_layer(input, def batch_norm_layer(input, act=None, name=None, + img3D=False, num_channels=None, bias_attr=None, param_attr=None, @@ -2885,6 +2891,7 @@ def batch_norm_layer(input, (batch_norm_type == "cudnn_batch_norm") l = Layer( name=name, + img3D=img3D, inputs=Input( input.name, image=Image(channels=num_channels), **param_attr.attr), active_type=act.name, diff --git a/python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py b/python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py new file mode 100644 index 0000000000..af694382b6 --- /dev/null +++ b/python/paddle/trainer_config_helpers/tests/configs/test_BatchNorm3D.py @@ -0,0 +1,17 @@ +from paddle.trainer_config_helpers import * + +settings(batch_size=1000, learning_rate=1e-4) + +data = data_layer(name='data', size=180, width=30, height=6) +# +batchNorm = batch_norm_layer(data, num_channels=1) +# +outputs(batchNorm) + +# # +data3D = data_layer(name='data3D22', size=120 * 3, width=20, height=6, depth=3) +# +print(data3D) +batchNorm3D = batch_norm_layer(data3D, num_channels=1, img3D=True) +# +outputs(batchNorm3D) diff --git a/python/paddle/trainer_config_helpers/tests/layers_test.py b/python/paddle/trainer_config_helpers/tests/layers_test.py index 05902ea293..68c8e128cb 100644 --- a/python/paddle/trainer_config_helpers/tests/layers_test.py +++ b/python/paddle/trainer_config_helpers/tests/layers_test.py @@ -16,4 +16,4 @@ from paddle.trainer.config_parser import parse_config_and_serialize if __name__ == '__main__': parse_config_and_serialize( - 'trainer_config_helpers/tests/layers_test_config.py', '') + 'trainer_config_helpers/tests/configs/test_BatchNorm3D.py', '') -- GitLab