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2 issues (isinstance(), ConvolutionLayer()) when installing barrista #8

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youngminpark2559 opened this issue Jul 19, 2018 · 4 comments
Closed

2 issues (isinstance(), ConvolutionLayer()) when installing barrista #8

youngminpark2559 opened this issue Jul 19, 2018 · 4 comments

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@youngminpark2559
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youngminpark2559 commented Jul 19, 2018 •
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Hi. I'm a beginner of image processing with deep learning.
As I'm dealing with "tnestmeyer-reflectance filtering" code, I would need to install barrista library.
I fixed several parts from code to fit to my environment, mainly python and caffe path because I'm using them in conda environment.

I wonder 2 parts.

  1. In design.py, there are 2 parts like these:
if isinstance(_obj_type.__dict__[_fieldname], property):
if isinstance(getattr(_tmp_layer_param, _propname), _obj_type):

But that check codes fails, and I don't know why.
So, I commented those parts out, and then, code could go forward.
Does commenting them cause problem?

  1. When I run this kind of sentence:
    layers.append(ConvolutionLayer(**conv_params))
    fail log says like this:
ERROR: test_sgd (tests.SolverTestCase)
Test the stochastic gradient descent.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1903, in test_sgd
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

I explicitly write following parts down in every python files (showcase.py, tests.py) as official document informs.
I added them in upper area of python file like this.
tests.py

import unittest
import logging
logging.basicConfig(level=logging.WARN)
# I added
import barrista.config as cf
cf.LAYER_TYPES['AbsVal'] = []
cf.LAYER_TYPES['Accuracy'] = ['AccuracyParameter']
cf.LAYER_TYPES['ArgMax'] = ['ArgMaxParameter']
cf.LAYER_TYPES['BatchNorm'] = ['BatchNormParameter']
cf.LAYER_TYPES['Concat'] = ['ConcatParameter']
cf.LAYER_TYPES['ContrastiveLoss'] = ['ContrastiveLossParameter']
cf.LAYER_TYPES['Convolution'] = ['ConvolutionParameter']
cf.LAYER_TYPES['Data'] = ['DataParameter']
cf.LAYER_TYPES['Dropout'] = ['DropoutParameter']
cf.LAYER_TYPES['DummyData'] = ['DummyDataParameter']
cf.LAYER_TYPES['Embed'] = ['EmbedParameter']
cf.LAYER_TYPES['Eltwise'] = ['EltwiseParameter']
cf.LAYER_TYPES['EuclideanLoss'] = ['LossParameter']
cf.LAYER_TYPES['Exp'] = ['ExpParameter']
cf.LAYER_TYPES['Filter'] = []
cf.LAYER_TYPES['Flatten'] = ['FlattenParameter']
cf.LAYER_TYPES['HDF5Data'] = ['HDF5DataParameter']
cf.LAYER_TYPES['HDF5Output'] = ['HDF5OutputParameter']
cf.LAYER_TYPES['HingeLoss'] = ['HingeLossParameter']
cf.LAYER_TYPES['ImageData'] = ['ImageDataParameter']
cf.LAYER_TYPES['InfogainLoss'] = ['InfogainLossParameter']
cf.LAYER_TYPES['InnerProduct'] = ['InnerProductParameter']
cf.LAYER_TYPES['Log'] = ['LogParameter']
cf.LAYER_TYPES['LRN'] = ['LRNParameter']
# Do not add this layer! It is superfluous with this interface
# and might just be a source of bugs.
# 'MemoryData'] = ['MemoryDataParameter']
cf.LAYER_TYPES['MultinomialLogisticLoss'] = ['LossParameter']
cf.LAYER_TYPES['MVN'] = ['MVNParameter']
cf.LAYER_TYPES['Pooling'] = ['PoolingParameter']
cf.LAYER_TYPES['Power'] = ['PowerParameter']
cf.LAYER_TYPES['PReLU'] = ['PReLUParameter']
cf.LAYER_TYPES['Python'] = ['PythonParameter']
cf.LAYER_TYPES['Reduction'] = ['ReductionParameter']
cf.LAYER_TYPES['ReLU'] = ['ReLUParameter']
cf.LAYER_TYPES['Resample'] = []
cf.LAYER_TYPES['Reshape'] = ['ReshapeParameter']
cf.LAYER_TYPES['Scale'] = ['ScaleParameter']
cf.LAYER_TYPES['Sigmoid'] = ['SigmoidParameter']
cf.LAYER_TYPES['SigmoidCrossEntropyLoss'] = ['LossParameter']
cf.LAYER_TYPES['Silence'] = []
cf.LAYER_TYPES['Slice'] = ['SliceParameter']
cf.LAYER_TYPES['Softmax'] = ['SoftmaxParameter']
cf.LAYER_TYPES['SoftmaxWithLoss'] = ['SoftmaxParameter', 'LossParameter']
cf.LAYER_TYPES['Split'] = []
cf.LAYER_TYPES['SPP'] = ['SPPParameter']
cf.LAYER_TYPES['TanH'] = ['TanHParameter']
cf.LAYER_TYPES['Threshold'] = ['ThresholdParameter']
cf.LAYER_TYPES['VariableHingeLoss'] = ['LossParameter']
cf.LAYER_TYPES['WindowData'] = ['WindowDataParameter']

And following is log of fail and several outputs of print(), please give me some advice about what is wrong and how to resolve, thank you:

$ python setup.py test
running test
Searching for skdata
Best match: skdata 0.0.4
Processing skdata-0.0.4-py2.7.egg

Using /home/young/barrista/.eggs/skdata-0.0.4-py2.7.egg
Searching for lockfile
Best match: lockfile 0.12.2
Processing lockfile-0.12.2-py2.7.egg

Using /home/young/barrista/.eggs/lockfile-0.12.2-py2.7.egg
Searching for joblib
Best match: joblib 0.12.1
Processing joblib-0.12.1-py2.7.egg

Using /home/young/barrista/.eggs/joblib-0.12.1-py2.7.egg
running egg_info
writing requirements to barrista.egg-info/requires.txt
writing barrista.egg-info/PKG-INFO
writing top-level names to barrista.egg-info/top_level.txt
writing dependency_links to barrista.egg-info/dependency_links.txt
reading manifest file 'barrista.egg-info/SOURCES.txt'
writing manifest file 'barrista.egg-info/SOURCES.txt'
running build_ext
('CAFFE_PYTHON_FOLDER', '/home/young/.conda/pkgs/pytest-3.6.2-py27_0/lib/python2.7/site-packages/caffe')
('CAFFE_BIN_FOLDER', '/home/young/.conda/envs/py27caffegpu/bin')
test_running (tests.ExampleTestCase)
Run it. ... ('CAFFE_PYTHON_FOLDER', '/home/young/.conda/pkgs/pytest-3.6.2-py27_0/lib/python2.7/site-packages/caffe')
('CAFFE_BIN_FOLDER', '/home/young/.conda/envs/py27caffegpu/bin')
('_PYCAFFE_FOLDER', '/home/young/.conda/envs/py27caffegpu/lib/python2.7/site-packages/caffe')
iiii
('_obj_type pp', <class 'caffe_pb2.LogParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'BASE_FIELD_NUMBER', 'SHIFT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SCALE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.SoftmaxParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'AXIS_FIELD_NUMBER', 'DEFAULT', 'CUDNN', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.HingeLossParameter'>)
('list(_obj_type.__dict__.keys())', ['NORM_FIELD_NUMBER', '__module__', 'DESCRIPTOR', '__slots__', 'L2', 'L1', '__doc__', 'Norm'])
('_obj_type pp', <class 'caffe_pb2.ReLUParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'CUDNN', 'DEFAULT', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', 'NEGATIVE_SLOPE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ReductionParameter'>)
('list(_obj_type.__dict__.keys())', ['ReductionOp', '__module__', 'ASUM', 'AXIS_FIELD_NUMBER', 'OPERATION_FIELD_NUMBER', 'SUM', 'SUMSQ', 'COEFF_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__', 'MEAN'])
('_obj_type pp', <class 'caffe_pb2.SliceParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'SLICE_DIM_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SLICE_POINT_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.InnerProductParameter'>)
('list(_obj_type.__dict__.keys())', ['NUM_OUTPUT_FIELD_NUMBER', '__module__', 'BIAS_TERM_FIELD_NUMBER', 'TRANSPOSE_FIELD_NUMBER', 'AXIS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'BIAS_FILLER_FIELD_NUMBER', '__doc__', 'WEIGHT_FILLER_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.AccuracyParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'IGNORE_LABEL_FIELD_NUMBER', 'TOP_K_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.SPPParameter'>)
('list(_obj_type.__dict__.keys())', ['POOL_FIELD_NUMBER', 'Engine', '__module__', 'CUDNN', 'DEFAULT', 'MAX', 'PYRAMID_HEIGHT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', 'STOCHASTIC', 'AVE', 'PoolMethod', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.DropoutParameter'>)
('list(_obj_type.__dict__.keys())', ['DESCRIPTOR', '__module__', 'DROPOUT_RATIO_FIELD_NUMBER', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.InfogainLossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.DummyDataParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'DATA_FILLER_FIELD_NUMBER', 'SHAPE_FIELD_NUMBER', 'HEIGHT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'WIDTH_FIELD_NUMBER', 'CHANNELS_FIELD_NUMBER', 'NUM_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.WindowDataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', 'MEAN_FILE_FIELD_NUMBER', '__module__', 'CROP_SIZE_FIELD_NUMBER', 'CONTEXT_PAD_FIELD_NUMBER', 'CROP_MODE_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'BG_THRESHOLD_FIELD_NUMBER', 'ROOT_FOLDER_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'MIRROR_FIELD_NUMBER', 'FG_FRACTION_FIELD_NUMBER', 'CACHE_IMAGES_FIELD_NUMBER', 'SCALE_FIELD_NUMBER', 'FG_THRESHOLD_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.BatchNormParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'EPS_FIELD_NUMBER', 'MOVING_AVERAGE_FRACTION_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'USE_GLOBAL_STATS_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.DataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', 'MEAN_FILE_FIELD_NUMBER', '__module__', 'CROP_SIZE_FIELD_NUMBER', 'PREFETCH_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'SCALE_FIELD_NUMBER', 'DB', 'RAND_SKIP_FIELD_NUMBER', 'FORCE_ENCODED_COLOR_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'MIRROR_FIELD_NUMBER', 'BACKEND_FIELD_NUMBER', 'LMDB', '__doc__', 'LEVELDB'])
('_obj_type pp', <class 'caffe_pb2.ConcatParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'CONCAT_DIM_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ContrastiveLossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'MARGIN_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'LEGACY_VERSION_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.SoftmaxParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'AXIS_FIELD_NUMBER', 'DEFAULT', 'CUDNN', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.EmbedParameter'>)
('list(_obj_type.__dict__.keys())', ['NUM_OUTPUT_FIELD_NUMBER', '__module__', 'INPUT_DIM_FIELD_NUMBER', 'BIAS_TERM_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'BIAS_FILLER_FIELD_NUMBER', '__doc__', 'WEIGHT_FILLER_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.MVNParameter'>)
('list(_obj_type.__dict__.keys())', ['ACROSS_CHANNELS_FIELD_NUMBER', '__module__', 'EPS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'NORMALIZE_VARIANCE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.TanHParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'CUDNN', 'DEFAULT', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.HDF5OutputParameter'>)
('list(_obj_type.__dict__.keys())', ['FILE_NAME_FIELD_NUMBER', 'DESCRIPTOR', '__module__', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ScaleParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'NUM_AXES_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'BIAS_FILLER_FIELD_NUMBER', 'FILLER_FIELD_NUMBER', 'BIAS_TERM_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ReshapeParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'SHAPE_FIELD_NUMBER', 'NUM_AXES_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PReLUParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'FILLER_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'CHANNEL_SHARED_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PowerParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'SHIFT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SCALE_FIELD_NUMBER', 'POWER_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PythonParameter'>)
('list(_obj_type.__dict__.keys())', ['MODULE_FIELD_NUMBER', '__module__', 'PARAM_STR_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'LAYER_FIELD_NUMBER', '__doc__', 'SHARE_IN_PARALLEL_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.FlattenParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'END_AXIS_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ImageDataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', 'MEAN_FILE_FIELD_NUMBER', '__module__', 'CROP_SIZE_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'NEW_WIDTH_FIELD_NUMBER', 'RAND_SKIP_FIELD_NUMBER', 'ROOT_FOLDER_FIELD_NUMBER', 'NEW_HEIGHT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'MIRROR_FIELD_NUMBER', 'IS_COLOR_FIELD_NUMBER', 'SCALE_FIELD_NUMBER', 'SHUFFLE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ArgMaxParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'OUT_MAX_VAL_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'TOP_K_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PoolingParameter'>)
('list(_obj_type.__dict__.keys())', ['KERNEL_H_FIELD_NUMBER', '__module__', 'GLOBAL_POOLING_FIELD_NUMBER', 'DEFAULT', 'STRIDE_FIELD_NUMBER', 'KERNEL_SIZE_FIELD_NUMBER', 'CAFFE', 'PAD_W_FIELD_NUMBER', 'POOL_FIELD_NUMBER', 'CUDNN', 'PAD_FIELD_NUMBER', 'ENGINE_FIELD_NUMBER', 'STOCHASTIC', '__doc__', 'Engine', 'KERNEL_W_FIELD_NUMBER', 'STRIDE_H_FIELD_NUMBER', 'PoolMethod', 'MAX', 'DESCRIPTOR', '__slots__', 'PAD_H_FIELD_NUMBER', 'AVE', 'STRIDE_W_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.ExpParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'BASE_FIELD_NUMBER', 'SHIFT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SCALE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.EltwiseParameter'>)
('list(_obj_type.__dict__.keys())', ['STABLE_PROD_GRAD_FIELD_NUMBER', '__module__', 'EltwiseOp', 'OPERATION_FIELD_NUMBER', 'MAX', 'SUM', 'COEFF_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'PROD', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.HDF5DataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', '__module__', 'SOURCE_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SHUFFLE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ConvolutionParameter'>)
('list(_obj_type.__dict__.keys())', ['NUM_OUTPUT_FIELD_NUMBER', 'DILATION_FIELD_NUMBER', '__module__', 'AXIS_FIELD_NUMBER', 'DEFAULT', 'STRIDE_FIELD_NUMBER', 'BIAS_FILLER_FIELD_NUMBER', 'KERNEL_SIZE_FIELD_NUMBER', 'PAD_W_FIELD_NUMBER', 'Engine', 'FORCE_ND_IM2COL_FIELD_NUMBER', 'CUDNN', 'PAD_FIELD_NUMBER', 'GROUP_FIELD_NUMBER', 'ENGINE_FIELD_NUMBER', '__doc__', 'KERNEL_W_FIELD_NUMBER', 'STRIDE_H_FIELD_NUMBER', 'BIAS_TERM_FIELD_NUMBER', 'KERNEL_H_FIELD_NUMBER', 'WEIGHT_FILLER_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'PAD_H_FIELD_NUMBER', 'CAFFE', 'STRIDE_W_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.SigmoidParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'CUDNN', 'DEFAULT', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LRNParameter'>)
('list(_obj_type.__dict__.keys())', ['NORM_REGION_FIELD_NUMBER', 'ACROSS_CHANNELS', '__module__', 'BETA_FIELD_NUMBER', 'CUDNN', 'K_FIELD_NUMBER', 'ALPHA_FIELD_NUMBER', 'DEFAULT', '__doc__', 'DESCRIPTOR', '__slots__', 'NormRegion', 'ENGINE_FIELD_NUMBER', 'CAFFE', 'Engine', 'WITHIN_CHANNEL', 'LOCAL_SIZE_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.ThresholdParameter'>)
('list(_obj_type.__dict__.keys())', ['DESCRIPTOR', '__module__', '__slots__', 'THRESHOLD_FIELD_NUMBER', '__doc__'])
Traceback (most recent call last):
  File "/home/young/barrista/examples/showcase.py", line 106, in <module>
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'
ERROR
test_instantiation (tests.LayerSpecificationTestCase)
Test instantiation. ... ('_PYCAFFE_FOLDER', '/home/young/.conda/envs/py27caffegpu/lib/python2.7/site-packages/caffe')
iiii
('_obj_type pp', <class 'caffe_pb2.LogParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'BASE_FIELD_NUMBER', 'SHIFT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SCALE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.SoftmaxParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'AXIS_FIELD_NUMBER', 'DEFAULT', 'CUDNN', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.HingeLossParameter'>)
('list(_obj_type.__dict__.keys())', ['NORM_FIELD_NUMBER', '__module__', 'DESCRIPTOR', '__slots__', 'L2', 'L1', '__doc__', 'Norm'])
('_obj_type pp', <class 'caffe_pb2.ReLUParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'CUDNN', 'DEFAULT', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', 'NEGATIVE_SLOPE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ReductionParameter'>)
('list(_obj_type.__dict__.keys())', ['ReductionOp', '__module__', 'ASUM', 'AXIS_FIELD_NUMBER', 'OPERATION_FIELD_NUMBER', 'SUM', 'SUMSQ', 'COEFF_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__', 'MEAN'])
('_obj_type pp', <class 'caffe_pb2.SliceParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'SLICE_DIM_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SLICE_POINT_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.InnerProductParameter'>)
('list(_obj_type.__dict__.keys())', ['NUM_OUTPUT_FIELD_NUMBER', '__module__', 'BIAS_TERM_FIELD_NUMBER', 'TRANSPOSE_FIELD_NUMBER', 'AXIS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'BIAS_FILLER_FIELD_NUMBER', '__doc__', 'WEIGHT_FILLER_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.AccuracyParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'IGNORE_LABEL_FIELD_NUMBER', 'TOP_K_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.SPPParameter'>)
('list(_obj_type.__dict__.keys())', ['POOL_FIELD_NUMBER', 'Engine', '__module__', 'CUDNN', 'DEFAULT', 'MAX', 'PYRAMID_HEIGHT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', 'STOCHASTIC', 'AVE', 'PoolMethod', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.DropoutParameter'>)
('list(_obj_type.__dict__.keys())', ['DESCRIPTOR', '__module__', 'DROPOUT_RATIO_FIELD_NUMBER', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.InfogainLossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.DummyDataParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'DATA_FILLER_FIELD_NUMBER', 'SHAPE_FIELD_NUMBER', 'HEIGHT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'WIDTH_FIELD_NUMBER', 'CHANNELS_FIELD_NUMBER', 'NUM_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.WindowDataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', 'MEAN_FILE_FIELD_NUMBER', '__module__', 'CROP_SIZE_FIELD_NUMBER', 'CONTEXT_PAD_FIELD_NUMBER', 'CROP_MODE_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'BG_THRESHOLD_FIELD_NUMBER', 'ROOT_FOLDER_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'MIRROR_FIELD_NUMBER', 'FG_FRACTION_FIELD_NUMBER', 'CACHE_IMAGES_FIELD_NUMBER', 'SCALE_FIELD_NUMBER', 'FG_THRESHOLD_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.BatchNormParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'EPS_FIELD_NUMBER', 'MOVING_AVERAGE_FRACTION_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'USE_GLOBAL_STATS_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.DataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', 'MEAN_FILE_FIELD_NUMBER', '__module__', 'CROP_SIZE_FIELD_NUMBER', 'PREFETCH_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'SCALE_FIELD_NUMBER', 'DB', 'RAND_SKIP_FIELD_NUMBER', 'FORCE_ENCODED_COLOR_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'MIRROR_FIELD_NUMBER', 'BACKEND_FIELD_NUMBER', 'LMDB', '__doc__', 'LEVELDB'])
('_obj_type pp', <class 'caffe_pb2.ConcatParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'CONCAT_DIM_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ContrastiveLossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'MARGIN_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'LEGACY_VERSION_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.SoftmaxParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'AXIS_FIELD_NUMBER', 'DEFAULT', 'CUDNN', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.EmbedParameter'>)
('list(_obj_type.__dict__.keys())', ['NUM_OUTPUT_FIELD_NUMBER', '__module__', 'INPUT_DIM_FIELD_NUMBER', 'BIAS_TERM_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'BIAS_FILLER_FIELD_NUMBER', '__doc__', 'WEIGHT_FILLER_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.MVNParameter'>)
('list(_obj_type.__dict__.keys())', ['ACROSS_CHANNELS_FIELD_NUMBER', '__module__', 'EPS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'NORMALIZE_VARIANCE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.TanHParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'CUDNN', 'DEFAULT', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LossParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'NormalizationMode', 'NORMALIZATION_FIELD_NUMBER', 'NONE', 'NORMALIZE_FIELD_NUMBER', 'VALID', 'DESCRIPTOR', '__slots__', 'FULL', 'IGNORE_LABEL_FIELD_NUMBER', 'BATCH_SIZE', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.HDF5OutputParameter'>)
('list(_obj_type.__dict__.keys())', ['FILE_NAME_FIELD_NUMBER', 'DESCRIPTOR', '__module__', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ScaleParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'NUM_AXES_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'BIAS_FILLER_FIELD_NUMBER', 'FILLER_FIELD_NUMBER', 'BIAS_TERM_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ReshapeParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'SHAPE_FIELD_NUMBER', 'NUM_AXES_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PReLUParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'FILLER_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'CHANNEL_SHARED_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PowerParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'SHIFT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SCALE_FIELD_NUMBER', 'POWER_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PythonParameter'>)
('list(_obj_type.__dict__.keys())', ['MODULE_FIELD_NUMBER', '__module__', 'PARAM_STR_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'LAYER_FIELD_NUMBER', '__doc__', 'SHARE_IN_PARALLEL_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.FlattenParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'END_AXIS_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ImageDataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', 'MEAN_FILE_FIELD_NUMBER', '__module__', 'CROP_SIZE_FIELD_NUMBER', 'SOURCE_FIELD_NUMBER', 'NEW_WIDTH_FIELD_NUMBER', 'RAND_SKIP_FIELD_NUMBER', 'ROOT_FOLDER_FIELD_NUMBER', 'NEW_HEIGHT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'MIRROR_FIELD_NUMBER', 'IS_COLOR_FIELD_NUMBER', 'SCALE_FIELD_NUMBER', 'SHUFFLE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ArgMaxParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'AXIS_FIELD_NUMBER', 'OUT_MAX_VAL_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'TOP_K_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.PoolingParameter'>)
('list(_obj_type.__dict__.keys())', ['KERNEL_H_FIELD_NUMBER', '__module__', 'GLOBAL_POOLING_FIELD_NUMBER', 'DEFAULT', 'STRIDE_FIELD_NUMBER', 'KERNEL_SIZE_FIELD_NUMBER', 'CAFFE', 'PAD_W_FIELD_NUMBER', 'POOL_FIELD_NUMBER', 'CUDNN', 'PAD_FIELD_NUMBER', 'ENGINE_FIELD_NUMBER', 'STOCHASTIC', '__doc__', 'Engine', 'KERNEL_W_FIELD_NUMBER', 'STRIDE_H_FIELD_NUMBER', 'PoolMethod', 'MAX', 'DESCRIPTOR', '__slots__', 'PAD_H_FIELD_NUMBER', 'AVE', 'STRIDE_W_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.ExpParameter'>)
('list(_obj_type.__dict__.keys())', ['__module__', 'BASE_FIELD_NUMBER', 'SHIFT_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SCALE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.EltwiseParameter'>)
('list(_obj_type.__dict__.keys())', ['STABLE_PROD_GRAD_FIELD_NUMBER', '__module__', 'EltwiseOp', 'OPERATION_FIELD_NUMBER', 'MAX', 'SUM', 'COEFF_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'PROD', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.HDF5DataParameter'>)
('list(_obj_type.__dict__.keys())', ['BATCH_SIZE_FIELD_NUMBER', '__module__', 'SOURCE_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'SHUFFLE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.ConvolutionParameter'>)
('list(_obj_type.__dict__.keys())', ['NUM_OUTPUT_FIELD_NUMBER', 'DILATION_FIELD_NUMBER', '__module__', 'AXIS_FIELD_NUMBER', 'DEFAULT', 'STRIDE_FIELD_NUMBER', 'BIAS_FILLER_FIELD_NUMBER', 'KERNEL_SIZE_FIELD_NUMBER', 'PAD_W_FIELD_NUMBER', 'Engine', 'FORCE_ND_IM2COL_FIELD_NUMBER', 'CUDNN', 'PAD_FIELD_NUMBER', 'GROUP_FIELD_NUMBER', 'ENGINE_FIELD_NUMBER', '__doc__', 'KERNEL_W_FIELD_NUMBER', 'STRIDE_H_FIELD_NUMBER', 'BIAS_TERM_FIELD_NUMBER', 'KERNEL_H_FIELD_NUMBER', 'WEIGHT_FILLER_FIELD_NUMBER', 'DESCRIPTOR', '__slots__', 'PAD_H_FIELD_NUMBER', 'CAFFE', 'STRIDE_W_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.SigmoidParameter'>)
('list(_obj_type.__dict__.keys())', ['Engine', '__module__', 'CUDNN', 'DEFAULT', 'DESCRIPTOR', '__slots__', 'CAFFE', 'ENGINE_FIELD_NUMBER', '__doc__'])
('_obj_type pp', <class 'caffe_pb2.LRNParameter'>)
('list(_obj_type.__dict__.keys())', ['NORM_REGION_FIELD_NUMBER', 'ACROSS_CHANNELS', '__module__', 'BETA_FIELD_NUMBER', 'CUDNN', 'K_FIELD_NUMBER', 'ALPHA_FIELD_NUMBER', 'DEFAULT', '__doc__', 'DESCRIPTOR', '__slots__', 'NormRegion', 'ENGINE_FIELD_NUMBER', 'CAFFE', 'Engine', 'WITHIN_CHANNEL', 'LOCAL_SIZE_FIELD_NUMBER'])
('_obj_type pp', <class 'caffe_pb2.ThresholdParameter'>)
('list(_obj_type.__dict__.keys())', ['DESCRIPTOR', '__module__', '__slots__', 'THRESHOLD_FIELD_NUMBER', '__doc__'])
ok
test_to_pbuf (tests.LayerSpecificationTestCase)
Test protobuf conversion. ... ok
test_ActivationMonitor (tests.MonitoringTestCase)
Test the ``ActivationMonitor``. ... ('ConvolutionLayer p', ['__call__', '__class__', '__closure__', '__code__', '__defaults__', '__delattr__', '__dict__', '__doc__', '__format__', '__get__', '__getattribute__', '__globals__', '__hash__', '__init__', '__module__', '__name__', '__new__', '__reduce__', '__reduce_ex__', '__repr__', '__setattr__', '__sizeof__', '__str__', '__subclasshook__', 'func_closure', 'func_code', 'func_defaults', 'func_dict', 'func_doc', 'func_globals', 'func_name'])
ERROR
test_Checkpointer (tests.MonitoringTestCase)
Test the ``Checkpointer``. ... ERROR
test_CyclingDataMonitor (tests.MonitoringTestCase)
Test the cycling data monitor. ... WARNING: Logging before InitGoogleLogging() is written to STDERR
I0719 14:32:48.771303 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpx3H4Ie.prototxt
I0719 14:32:48.771337 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:48.771356 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.165976 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 3
    }
    shape {
      dim: 3
    }
  }
}
I0719 14:32:49.166049 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.166069 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.166079 28507 net.cpp:380] input -> a
I0719 14:32:49.166101 28507 net.cpp:380] input -> b
I0719 14:32:49.166146 28507 net.cpp:122] Setting up input
I0719 14:32:49.166162 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.166174 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.166183 28507 net.cpp:137] Memory required for data: 24
I0719 14:32:49.166194 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.166204 28507 net.cpp:242] This network produces output a
I0719 14:32:49.166220 28507 net.cpp:242] This network produces output b
I0719 14:32:49.166231 28507 net.cpp:255] Network initialization done.
ok
test_CyclingDataMonitor_augmentation (tests.MonitoringTestCase)
Test the cycling data monitor color data augmentation capability. ... I0719 14:32:49.168090 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpPLhEv_.prototxt
I0719 14:32:49.168112 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.168125 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.168161 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 5
      dim: 5
    }
    shape {
      dim: 3
    }
  }
}
I0719 14:32:49.168197 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.168210 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.168223 28507 net.cpp:380] input -> a
I0719 14:32:49.168238 28507 net.cpp:380] input -> b
I0719 14:32:49.168256 28507 net.cpp:122] Setting up input
I0719 14:32:49.168272 28507 net.cpp:129] Top shape: 1 3 5 5 (75)
I0719 14:32:49.168284 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.168295 28507 net.cpp:137] Memory required for data: 312
I0719 14:32:49.168308 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.168316 28507 net.cpp:242] This network produces output a
I0719 14:32:49.168328 28507 net.cpp:242] This network produces output b
I0719 14:32:49.168339 28507 net.cpp:255] Network initialization done.
ok
test_CyclingDataMonitor_only_preload (tests.MonitoringTestCase)
Test the cycling data monitor preload capability. ... I0719 14:32:49.170176 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpBCSait.prototxt
I0719 14:32:49.170197 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.170203 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.170246 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 3
    }
    shape {
      dim: 3
    }
  }
}
I0719 14:32:49.170277 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.170292 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.170305 28507 net.cpp:380] input -> a
I0719 14:32:49.170320 28507 net.cpp:380] input -> b
I0719 14:32:49.170337 28507 net.cpp:122] Setting up input
I0719 14:32:49.170351 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.170362 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.170372 28507 net.cpp:137] Memory required for data: 24
I0719 14:32:49.170383 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.170393 28507 net.cpp:242] This network produces output a
I0719 14:32:49.170406 28507 net.cpp:242] This network produces output b
I0719 14:32:49.170418 28507 net.cpp:255] Network initialization done.
ok
test_CyclingDataMonitor_padding (tests.MonitoringTestCase)
Test the cycling data monitor padding capability. ... I0719 14:32:49.171355 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpkF61x8.prototxt
I0719 14:32:49.171373 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.171380 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.171417 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 3
      dim: 3
      dim: 10
      dim: 10
    }
    shape {
      dim: 3
      dim: 3
      dim: 7
      dim: 7
    }
  }
}
I0719 14:32:49.171454 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.171471 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.171483 28507 net.cpp:380] input -> a
I0719 14:32:49.171500 28507 net.cpp:380] input -> b
I0719 14:32:49.171517 28507 net.cpp:122] Setting up input
I0719 14:32:49.171530 28507 net.cpp:129] Top shape: 3 3 10 10 (900)
I0719 14:32:49.171542 28507 net.cpp:129] Top shape: 3 3 7 7 (441)
I0719 14:32:49.171552 28507 net.cpp:137] Memory required for data: 5364
I0719 14:32:49.171563 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.171573 28507 net.cpp:242] This network produces output a
I0719 14:32:49.171583 28507 net.cpp:242] This network produces output b
I0719 14:32:49.171594 28507 net.cpp:255] Network initialization done.
ok
test_CyclingDataMonitor_resizing (tests.MonitoringTestCase)
Test the cycling data monitor resizing capability. ... I0719 14:32:49.173616 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpxQl2hx.prototxt
I0719 14:32:49.173636 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.173642 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.173682 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 3
      dim: 3
      dim: 10
      dim: 10
    }
    shape {
      dim: 3
      dim: 3
      dim: 5
      dim: 5
    }
  }
}
I0719 14:32:49.173727 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.173750 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.173761 28507 net.cpp:380] input -> a
I0719 14:32:49.173776 28507 net.cpp:380] input -> b
I0719 14:32:49.173794 28507 net.cpp:122] Setting up input
I0719 14:32:49.173808 28507 net.cpp:129] Top shape: 3 3 10 10 (900)
I0719 14:32:49.173821 28507 net.cpp:129] Top shape: 3 3 5 5 (225)
I0719 14:32:49.173832 28507 net.cpp:137] Memory required for data: 4500
I0719 14:32:49.173844 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.173856 28507 net.cpp:242] This network produces output a
I0719 14:32:49.173867 28507 net.cpp:242] This network produces output b
I0719 14:32:49.173879 28507 net.cpp:255] Network initialization done.
ok
test_FilterMonitor (tests.MonitoringTestCase)
Test the ``FilterMonitor``. ... ERROR
test_GradientMonitor (tests.MonitoringTestCase)
Test the ``GradientMonitor``. ... ERROR
test_JSONLogger (tests.MonitoringTestCase)
Test the ``JSONLogger``. ... ERROR
test_ProgressIndicator (tests.MonitoringTestCase)
Test the ``ProgressIndicator``. ... ERROR
test_ResizingMonitor (tests.MonitoringTestCase)
Test the resizing monitor. ... ERROR
test_ResizingMonitor_fixed_scale (tests.MonitoringTestCase)
Test the resizing monitor scaling capability. ... I0719 14:32:49.190246 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmp_DRfLz.prototxt
I0719 14:32:49.190271 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.190285 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.190330 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 5
      dim: 5
    }
    shape {
      dim: 1
      dim: 1
      dim: 5
      dim: 5
    }
  }
}
I0719 14:32:49.190364 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.190379 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.190392 28507 net.cpp:380] input -> a
I0719 14:32:49.190410 28507 net.cpp:380] input -> b
I0719 14:32:49.190431 28507 net.cpp:122] Setting up input
I0719 14:32:49.190446 28507 net.cpp:129] Top shape: 1 3 5 5 (75)
I0719 14:32:49.190459 28507 net.cpp:129] Top shape: 1 1 5 5 (25)
I0719 14:32:49.190469 28507 net.cpp:137] Memory required for data: 400
I0719 14:32:49.190480 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.190491 28507 net.cpp:242] This network produces output a
I0719 14:32:49.190502 28507 net.cpp:242] This network produces output b
I0719 14:32:49.190515 28507 net.cpp:255] Network initialization done.
ok
test_ResizingMonitor_random_scale (tests.MonitoringTestCase)
Test the resizing monitor random scale capability. ... I0719 14:32:49.193156 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpAIw1dt.prototxt
I0719 14:32:49.193178 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.193189 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.193224 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 5
      dim: 5
    }
    shape {
      dim: 1
      dim: 1
      dim: 5
      dim: 5
    }
  }
}
I0719 14:32:49.193264 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.193277 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.193289 28507 net.cpp:380] input -> a
I0719 14:32:49.193306 28507 net.cpp:380] input -> b
I0719 14:32:49.193323 28507 net.cpp:122] Setting up input
I0719 14:32:49.193336 28507 net.cpp:129] Top shape: 1 3 5 5 (75)
I0719 14:32:49.193347 28507 net.cpp:129] Top shape: 1 1 5 5 (25)
I0719 14:32:49.193357 28507 net.cpp:137] Memory required for data: 400
I0719 14:32:49.193364 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.193373 28507 net.cpp:242] This network produces output a
I0719 14:32:49.193382 28507 net.cpp:242] This network produces output b
I0719 14:32:49.193392 28507 net.cpp:255] Network initialization done.
ok
test_RotatingMirroringMonitor (tests.MonitoringTestCase)
Test the rotating mirroring monitor. ... I0719 14:32:49.557796 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmp9cpDZe.prototxt
I0719 14:32:49.557822 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.557829 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.557878 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 5
      dim: 5
    }
    shape {
      dim: 1
      dim: 1
      dim: 5
      dim: 5
    }
  }
}
I0719 14:32:49.557914 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.557930 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.557945 28507 net.cpp:380] input -> a
I0719 14:32:49.557961 28507 net.cpp:380] input -> b
I0719 14:32:49.557982 28507 net.cpp:122] Setting up input
I0719 14:32:49.557997 28507 net.cpp:129] Top shape: 1 3 5 5 (75)
I0719 14:32:49.558012 28507 net.cpp:129] Top shape: 1 1 5 5 (25)
I0719 14:32:49.558022 28507 net.cpp:137] Memory required for data: 400
I0719 14:32:49.558029 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.558040 28507 net.cpp:242] This network produces output a
I0719 14:32:49.558051 28507 net.cpp:242] This network produces output b
I0719 14:32:49.558064 28507 net.cpp:255] Network initialization done.
ok
test_RotatingMirroringMonitor_mirroring (tests.MonitoringTestCase)
Test the rotating mirroring monitor mirroring capability. ... I0719 14:32:49.559469 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmp0kTiXw.prototxt
I0719 14:32:49.559489 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.559495 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.559533 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 5
      dim: 5
    }
    shape {
      dim: 1
      dim: 1
      dim: 5
      dim: 5
    }
  }
}
I0719 14:32:49.559566 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.559581 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.559594 28507 net.cpp:380] input -> a
I0719 14:32:49.559609 28507 net.cpp:380] input -> b
I0719 14:32:49.559628 28507 net.cpp:122] Setting up input
I0719 14:32:49.559641 28507 net.cpp:129] Top shape: 1 3 5 5 (75)
I0719 14:32:49.559653 28507 net.cpp:129] Top shape: 1 1 5 5 (25)
I0719 14:32:49.559662 28507 net.cpp:137] Memory required for data: 400
I0719 14:32:49.559672 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.559684 28507 net.cpp:242] This network produces output a
I0719 14:32:49.559693 28507 net.cpp:242] This network produces output b
I0719 14:32:49.559705 28507 net.cpp:255] Network initialization done.
ok
test_RotatingMirroringMonitor_mirroring_swapvalues (tests.MonitoringTestCase)
Test the rotating mirroring monitor mirroring swap capability. ... I0719 14:32:49.560933 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmp2JLRXA.prototxt
I0719 14:32:49.560953 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.560959 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.560997 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 1
      dim: 3
      dim: 5
      dim: 5
    }
    shape {
      dim: 1
      dim: 1
      dim: 5
      dim: 5
    }
  }
}
I0719 14:32:49.561034 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.561049 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.561061 28507 net.cpp:380] input -> a
I0719 14:32:49.561079 28507 net.cpp:380] input -> b
I0719 14:32:49.561097 28507 net.cpp:122] Setting up input
I0719 14:32:49.561112 28507 net.cpp:129] Top shape: 1 3 5 5 (75)
I0719 14:32:49.561138 28507 net.cpp:129] Top shape: 1 1 5 5 (25)
I0719 14:32:49.561148 28507 net.cpp:137] Memory required for data: 400
I0719 14:32:49.561159 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.561170 28507 net.cpp:242] This network produces output a
I0719 14:32:49.561180 28507 net.cpp:242] This network produces output b
I0719 14:32:49.561192 28507 net.cpp:255] Network initialization done.
ok
test_StaticDataMonitor (tests.MonitoringTestCase)
Test the static data monitor. ... I0719 14:32:49.562469 28507 upgrade_proto.cpp:67] Attempting to upgrade input file specified using deprecated input fields: /tmp/tmpHccI6P.prototxt
I0719 14:32:49.562489 28507 upgrade_proto.cpp:70] Successfully upgraded file specified using deprecated input fields.
W0719 14:32:49.562494 28507 upgrade_proto.cpp:72] Note that future Caffe releases will only support input layers and not input fields.
I0719 14:32:49.562531 28507 net.cpp:51] Initializing net from parameters: 
name: "DCNN"
force_backward: false
state {
  phase: TRAIN
  level: 0
  stage: "fit"
}
debug_info: false
layer {
  name: "input"
  type: "Input"
  top: "a"
  top: "b"
  input_param {
    shape {
      dim: 3
    }
    shape {
      dim: 3
    }
  }
}
I0719 14:32:49.562559 28507 layer_factory.hpp:77] Creating layer input
I0719 14:32:49.562573 28507 net.cpp:84] Creating Layer input
I0719 14:32:49.562585 28507 net.cpp:380] input -> a
I0719 14:32:49.562602 28507 net.cpp:380] input -> b
I0719 14:32:49.562619 28507 net.cpp:122] Setting up input
I0719 14:32:49.562633 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.562645 28507 net.cpp:129] Top shape: 3 (3)
I0719 14:32:49.562654 28507 net.cpp:137] Memory required for data: 24
I0719 14:32:49.562665 28507 net.cpp:200] input does not need backward computation.
I0719 14:32:49.562675 28507 net.cpp:242] This network produces output a
I0719 14:32:49.562687 28507 net.cpp:242] This network produces output b
I0719 14:32:49.562700 28507 net.cpp:255] Network initialization done.
ok
test_copy (tests.NetSpecificationTestCase)
Test the method ``copy``. ... ERROR
test_get_predict_net_specification (tests.NetSpecificationTestCase)
Test the method ``get_predict_net_specification``. ... ok
test_initialization (tests.NetSpecificationTestCase)
Test initialization and checks. ... ok
test_instantiate (tests.NetSpecificationTestCase)
Test the method ``instatiate``. ... ERROR
test_prototxt_conversion (tests.NetSpecificationTestCase)
Test the prototxt conversion methods. ... ERROR
test_to_pbuf_message (tests.NetSpecificationTestCase)
Test the method ``to_pbuf_message``. ... ('conv_params p', {'Convolution_kernel_size': 3, 'Convolution_num_output': 32, 'Convolution_pad': 1})
ERROR
test_visualize (tests.NetSpecificationTestCase)
Test the ``visualize`` function. ... ERROR
test_dual_net_use (tests.NetTestCase)
Test the specification of a prediction net. ... ERROR
test_instantiation (tests.NetTestCase)
Test ``Net`` constructors. ... ERROR
test_load_blobs_from (tests.NetTestCase)
Test the loading method. ... ERROR
test_multiinput (tests.NetTestCase)
Test multiinput prediction. ... ERROR
test_multioutput (tests.NetTestCase)
Test multioutput prediction. ... ERROR
test_predict (tests.NetTestCase)
Test the ``predict`` method. ... ERROR
test_predict_sliding_window (tests.NetTestCase)
Test the ``predict_sliding_window`` method. ... ERROR
test_predict_sliding_window_eq_out (tests.NetTestCase)
Test the ``predict_sliding_window`` method with full size output. ... ERROR
test_predict_upscaling (tests.NetTestCase)
Test the ``predict`` method upscaling capability. ... ERROR
test_reshape_blob (tests.NetTestCase)
Test the reshaping of a blob across nets. ... ERROR
test_visualize (tests.NetTestCase)
Test the ``visualize`` function. ... ERROR
test_adadelta (tests.SolverTestCase)
Test the Adadelta solver. ... ERROR
test_adagrad (tests.SolverTestCase)
Test the AdaGrad solver. ... ERROR
test_adam (tests.SolverTestCase)
Test the ADAM solver. ... ERROR
test_fit (tests.SolverTestCase)
Test the fit function. ... ERROR
test_nesterov (tests.SolverTestCase)
Test the nesterov solver. ... ERROR
test_restore (tests.SolverTestCase)
Test the ``restore`` method. ... ERROR
test_rmsprop (tests.SolverTestCase)
Test the RMSProp solver. ... ERROR
test_sgd (tests.SolverTestCase)
Test the stochastic gradient descent. ... ERROR
test_pad (tests.ToolsTestCase)
Test the padding function. ... ok

======================================================================
ERROR: test_running (tests.ExampleTestCase)
Run it.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1759, in test_running
    subprocess.check_call([sys.executable,"/home/young/barrista/examples/showcase.py"])
  File "/home/young/.conda/envs/py27caffegpu/lib/python2.7/subprocess.py", line 190, in check_call
    raise CalledProcessError(retcode, cmd)
CalledProcessError: Command '['/home/young/.conda/envs/py27caffegpu/bin/python', '/home/young/barrista/examples/showcase.py']' returned non-zero exit status 1

======================================================================
ERROR: test_ActivationMonitor (tests.MonitoringTestCase)
Test the ``ActivationMonitor``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1141, in test_ActivationMonitor
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_weight_filler'

======================================================================
ERROR: test_Checkpointer (tests.MonitoringTestCase)
Test the ``Checkpointer``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1012, in test_Checkpointer
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_FilterMonitor (tests.MonitoringTestCase)
Test the ``FilterMonitor``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1195, in test_FilterMonitor
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_weight_filler'

======================================================================
ERROR: test_GradientMonitor (tests.MonitoringTestCase)
Test the ``GradientMonitor``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1065, in test_GradientMonitor
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_weight_filler'

======================================================================
ERROR: test_JSONLogger (tests.MonitoringTestCase)
Test the ``JSONLogger``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 415, in test_JSONLogger
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_ProgressIndicator (tests.MonitoringTestCase)
Test the ``ProgressIndicator``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 361, in test_ProgressIndicator
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_ResizingMonitor (tests.MonitoringTestCase)
Test the resizing monitor.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 718, in test_ResizingMonitor
    Convolution_num_output=1))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_copy (tests.NetSpecificationTestCase)
Test the method ``copy``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 237, in test_copy
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_instantiate (tests.NetSpecificationTestCase)
Test the method ``instatiate``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 289, in test_instantiate
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_prototxt_conversion (tests.NetSpecificationTestCase)
Test the prototxt conversion methods.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 198, in test_prototxt_conversion
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_to_pbuf_message (tests.NetSpecificationTestCase)
Test the method ``to_pbuf_message``.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 161, in test_to_pbuf_message
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_visualize (tests.NetSpecificationTestCase)
Test the ``visualize`` function.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 267, in test_visualize
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_dual_net_use (tests.NetTestCase)
Test the specification of a prediction net.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1272, in test_dual_net_use
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_instantiation (tests.NetTestCase)
Test ``Net`` constructors.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1241, in test_instantiation
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_load_blobs_from (tests.NetTestCase)
Test the loading method.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1371, in test_load_blobs_from
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_multiinput (tests.NetTestCase)
Test multiinput prediction.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1417, in test_multiinput
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_multioutput (tests.NetTestCase)
Test multioutput prediction.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1464, in test_multioutput
    tops=['conv1_out']))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_predict (tests.NetTestCase)
Test the ``predict`` method.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1599, in test_predict
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_predict_sliding_window (tests.NetTestCase)
Test the ``predict_sliding_window`` method.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1519, in test_predict_sliding_window
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_predict_sliding_window_eq_out (tests.NetTestCase)
Test the ``predict_sliding_window`` method with full size output.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1574, in test_predict_sliding_window_eq_out
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_predict_upscaling (tests.NetTestCase)
Test the ``predict`` method upscaling capability.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1679, in test_predict_upscaling
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_reshape_blob (tests.NetTestCase)
Test the reshaping of a blob across nets.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1321, in test_reshape_blob
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_visualize (tests.NetTestCase)
Test the ``visualize`` function.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1720, in test_visualize
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_adadelta (tests.SolverTestCase)
Test the Adadelta solver.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 2326, in test_adadelta
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_adagrad (tests.SolverTestCase)
Test the AdaGrad solver.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 2415, in test_adagrad
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_adam (tests.SolverTestCase)
Test the ADAM solver.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 2498, in test_adam
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_fit (tests.SolverTestCase)
Test the fit function.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1782, in test_fit
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_nesterov (tests.SolverTestCase)
Test the nesterov solver.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 2034, in test_nesterov
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_restore (tests.SolverTestCase)
Test the ``restore`` method.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1853, in test_restore
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_weight_filler'

======================================================================
ERROR: test_rmsprop (tests.SolverTestCase)
Test the RMSProp solver.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 2169, in test_rmsprop
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

======================================================================
ERROR: test_sgd (tests.SolverTestCase)
Test the stochastic gradient descent.
----------------------------------------------------------------------
Traceback (most recent call last):
  File "/home/young/barrista/tests.py", line 1903, in test_sgd
    layers.append(ConvolutionLayer(**conv_params))
TypeError: ConvolutionLayer() got an unexpected keyword argument 'Convolution_kernel_size'

----------------------------------------------------------------------
Ran 48 tests in 3.104s

FAILED (errors=32)
Test failed: <unittest.runner.TextTestResult run=48 errors=32 failures=0>
error: Test failed: <unittest.runner.TextTestResult run=48 errors=32 failures=0>
@youngminpark2559
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First, I found something strange part like this:
('CAFFE_PYTHON_FOLDER', '/home/young/.conda/pkgs/pytest-3.6.2-py27_0/lib/python2.7/site-packages/caffe')
I think pytest-3.6.2-py27_0 part should be py27caffegpu which is name of conda environment.
I'm going to check it first.

@youngminpark2559
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Author

I fixed the paths but issues look same

@classner
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Hi youngmtool!

Unfortunately, barrista is unmaintained with the rise of the pythonic widely spread deep learning frameworks. If you still want/need to use it, as I figure is your case, I recommend using precisely the caffe version linked (however, this may make problems with more recent versions of CUDA :( ), if necessary within a docker image. There should still be Docker images floating around with CUDA7 and corresponding CuDNN versions.

I'm not sure what your first reported error comes from. Commenting out those lines is not an option, this leads to the other failures (barrista will not have parsed the layer properties). If you don't already, please use Python 2.7.

@youngminpark2559
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Ah, right. Thanks for reply and all information. It helped a lot. I'll try to follow your advice.

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@classner @youngminpark2559