classner / barrista Goto Github PK

if isinstance(_obj_type.__dict__[_fieldname], property):
if isinstance(getattr(_tmp_layer_param, _propname), _obj_type):

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'

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']

$ 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>