def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('load_file', 'sigma'):
op.delete_option(option)
op.add_option("show-filters", "show_filters", StringOptionParser, "Show filters of specified layer", default="")
op.add_option("norm-filters", "norm_filters", BooleanOptionParser, "Individually normalize filters shown with --show-filters", default=0)
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("smooth-test-errors", "smooth_test_errors", BooleanOptionParser, "Use running average for test error plot?", default=0)
op.add_option("output-layer", "output_layer", StringOptionParser, "Output layer that the cost is computed from", default="")
op.add_option("show-mse", "show_mse", BooleanOptionParser, "Show mse error (or PSNR error)", default=False)
op.add_option("step", "step", IntegerOptionParser, "Step of x axis", default=1)
op.add_option("patch-perbatch", "patch_perbatch", IntegerOptionParser, "Num of patches per batch", default=4096)
op.add_option("result-path", "result_path", StringOptionParser, "Path to store the PSNR curve", default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser, "Show predictions made by given softmax on test set", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("write-features", "write_features", StringOptionParser, "Write test data features from given layer", default="", requires=['feature-path'])
op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
#----my options----------
op.add_option("hist-features", "hist_features", StringOptionParser,
"plot histogram of feature activation", default="")
op.add_option("hist-test", "hist_test", BooleanOptionParser,
"True: plot hist of test data, False: plot hist of training data", default=True )
op.add_option("nn-analysis", "nn_analysis", StringOptionParser,
"run inference on training mode for many times and analysis output", default="")
#op.add_option("data-provider", "dp_type", StringOptionParser, "Data provider", default="default")
#op.add_option("write-mv-result", "write_mv_result", StringOptionParser, "Write test data multiview features to file", default="", requires=['feature-path'])
op.add_option("write-mv-result", "write_mv_result", StringOptionParser, "Write test data multiview features to file", default="" )
op.add_option("write-mv-mc-result", "write_mv_mc_result", StringOptionParser, "Write test data multiview features on MC inferenceto file", default="" )
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range', 'cam_test', 'test_one'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser, "Show predictions made by given softmax on test set", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("write-features", "write_features", StringOptionParser, "Write test data features from given layer", default="", requires=['feature-path'])
op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
#add options here for streaming from the camera: send the results rather then save to file?
op.add_option("show-preds-patch","show_preds_patch", StringOptionParser, "Show patch predictions made by given softmax on test set", default="")
op.add_option("show-preds-patch-total","show_preds_patch_total", StringOptionParser, "Show patch predictions made by given softmax on test set in total image", default="")
op.add_option("write-features-stream", "write_features_stream", StringOptionParser, "Stream test data features from given layer", default="", requires=['cam_test'])
op.add_option("cam-test", "test_from_camera", BooleanOptionParser, "Get Test Batches from OpenNI Device?", default=0)#0? can i leave it False?
#op.add_option("send-features", "send_features", StringOptionParser, "Send the test data features (probabilities) from given layer", default="", requires=['receiver-path'])
#op.add_option("receiver-path", "receiver_path", StringOptionParser, "Send test data features to this (address?) (use with --send-features)", default="")
#the above options should trigger an option in the net: test-one, and test-from-camera?: unlimited test batches, continuous until ctrl+c...
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('data_path_train', 'data_path_test', 'dp_type_train', 'dp_type_test', 'gpu', 'rnorm_const', 'img_provider_file', 'load_file', 'train_batch_range', 'test_batch_range', 'verbose'):
op.delete_option(option)
op.add_option("test-only", "test_only", BooleanOptionParser, "Test and quit?", default=1)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser, "Show predictions made by given softmax on test set", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("write-features", "write_features", StringOptionParser, "Write test data features from given layer", default="", requires=['feature-path'])
op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
op.add_option("write-pixel-proj", "write_pixel_proj", StringOptionParser, "Write the projection of some response on pixel space", default = "", requires=['response_idx'])
op.add_option("multiview", "mult_view", IntegerOptionParser, "Number of views for multi-view testing", default=1)
op.add_option("scaleview", "scale_view", FloatOptionParser, "Scaling factor of the views in multi-view testing", default=1.0)
op.add_option("bbxfile", "bbx_file", StringOptionParser, "Contains ground truth bounding box for each image", default="")
op.add_option("imglist", "img_list", StringOptionParser, "Image list file", default="")
op.add_option("clusterfile", "cluster_file", StringOptionParser, "Cluster center saved in pickle format", default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range', 'multiview_test'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", ListOptionParser(IntegerOptionParser), "Cost function return value index for --show-cost", default=[])
# op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", IntegerOptionParser,
"Show predictions made by given softmax on test or predicting set. 1:test set 2:predicting set", default=0)
op.add_option("pred-batch-range", "pred_batch_range", RangeOptionParser, "Data batch range: predicting set")
op.add_option("logsoftmax", "logsoftmax", StringOptionParser, "name of logsoftmax typed layer", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("write-features-train", "write_features_train", StringOptionParser, "Write train data features from given layer", default='', requires=[])
op.add_option("write-features-test", "write_features_test", StringOptionParser, "Write test data features from given layer", default='', requires=[])
op.add_option("write-features-pred", "write_features_pred", StringOptionParser, "Write prediction data features from given layer", default='', requires=[])
# op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
op.add_option("show-layer-weights-biases", "show_layer_weights_biases", IntegerOptionParser, "Show evolution of layer-wise mean absolute of weights, weightsInc, bias, biasInc", default=0)
op.add_option("confusion-mat", "confusion_mat", IntegerOptionParser, "plot confusion matrix", default=0)
op.add_option("test-meta", "test_meta", StringOptionParser, "meta file for testing data used in plotting confusion matrix", default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range', 'data_path', 'minibatch_size', 'layer_params', 'batch_size', 'test_only', 'test_one', 'shuffle_data', 'crop_one_border', 'external_meta_path'):
op.delete_option(option)
op.add_option('mode', 'mode', StringOptionParser, "The mode for evaluation")
op.add_option('images-folder', 'images_folder', StringOptionParser, 'The folder for testing images')
op.add_option('mean-image-path', 'mean_image_path', StringOptionParser, 'The path for mean image')
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range', 'data_path', 'minibatch_size', 'layer_params', 'batch_size', 'test_only', 'test_one', 'shuffle_data', 'crop_one_border'):
op.delete_option(option)
op.add_option('do-pose-evaluation', 'do_pose_evaluation', StringOptionParser, 'Specify the output layer of pose')
op.add_option('inputstream', 'inputstream', StringOptionParser, 'Specify the type of camera to use [imgcamera|cvcamera]')
op.add_option('outputdir', 'outputdir', StringOptionParser, 'Specify the directory for saving outputs')
op.add_option('crop-image', 'crop_image', StringOptionParser, 'Specify the method to crop image to square input patch [faceubd]')
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range',
'minibatch_size', 'data_path', 'dp_type'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser,
"Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser,
"Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser,
"Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser,
"Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser,
"Don't combine filter channels into RGB in layer given to --show-filters",
default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser,
"Convert RGB filters to YUV in layer given to --show-filters",
default=False)
op.add_option("channels", "channels", IntegerOptionParser,
"Number of channels in layer given to --show-filters \
(fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser,
"Show predictions made by given softmax on test set", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser,
"Show only mistaken predictions (to be used with --show-preds)",
default=False, requires=['show_preds'])
op.add_option("write-features", "write_features", StringOptionParser,
"Write test data features from given layer",
default="", requires=['feature-path'])
op.add_option("feature-path", "feature_path", StringOptionParser,
"Write test data features to this path (to be used with --write-features)",
default="")
op.add_option("show-layers", "show_layers", StringOptionParser,
"Show configurations of a layer", default="")
op.add_option("output-one", "output_one", BooleanOptionParser,
"Output to one file", default=False)
op.add_option("feature-file", "feature_file", StringOptionParser,
"Write test data features to this file (to be used with --output-one)",
default="")
op.add_option("write-predictions", "write_predictions", StringOptionParser,
"Write predictions to a file", default="")
# requires=['logreg_name']
op.add_option("multiview-test", "multiview_test", BooleanOptionParser,
"Cropped DP: test on multiple patches?", default=False)
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range',
'test_batch_range', 'data_path',
'minibatch_size', 'layer_params', 'batch_size',
'test_only', 'test_one', 'shuffle_data',
'crop_one_border', 'external_meta_path'):
op.delete_option(option)
op.add_option('mode', 'mode', StringOptionParser,
"The mode for evaluation")
op.add_option('images-folder', 'images_folder', StringOptionParser,
'The folder for testing images')
op.add_option('mean-image-path', 'mean_image_path', StringOptionParser,
'The path for mean image')
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
op.add_option("epochs2",
"num_epochs2",
IntegerOptionParser,
"Number of epochs with noise learning",
default=0)
op.add_option("noise-eps",
"noise_eps",
FloatOptionParser,
"Learning rate of noise matrix",
default=0.001)
op.add_option("noise-wc",
"noise_wc",
FloatOptionParser,
"Weight cost on noise matrix",
default=0.1)
op.add_option("noise-level",
"noise_level",
FloatOptionParser,
"Amount of incorrect training labels",
default=0.0)
op.add_option("noise-true",
"noise_true",
BooleanOptionParser,
"Use true noise matrix",
default=0)
op.add_option("noise-Qpath",
"noise_Qpath",
StringOptionParser,
"Path to noise matrix Q",
default="data/mixing-offdiag-2.npy")
op.options["dp_type"].default = "cifar"
op.options["data_path"].default = "/home/sainbar/data/cifar-10/train"
op.options["save_path"].default = "/tmp/cifar-10/"
op.options["test_batch_range"].default = [6]
op.options[
"layer_def"].default = "./example-layers/layers-18pct-noisy.cfg"
op.options[
"layer_params"].default = "./example-layers/layer-params-18pct-noisy.cfg"
op.options["testing_freq"].default = 10
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser, "Show predictions made by given softmax on test set", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("write-features", "write_features", StringOptionParser, "Write test data features from given layer", default="", requires=['feature-path'])
op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range', 'test_batch_range'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser, "Show predictions made by given softmax on test set", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("write-features", "write_features", StringOptionParser, "Write test data features from given layer", default="", requires=['feature-path'])
op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
op.add_option("save-to-file", "save_to_file", StringOptionParser, "Save the plot to file", default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'inner_size', 'train_batch_range', 'test_batch_range', 'multiview_test', 'data_path', 'pca_noise', 'scalar_mean'):
op.delete_option(option)
op.add_option("show-cost", "show_cost", StringOptionParser, "Show specified objective function", default="")
op.add_option("show-filters", "show_filters", StringOptionParser, "Show learned filters in specified layer", default="")
op.add_option("norm-filters", "norm_filters", BooleanOptionParser, "Individually normalize filters shown with --show-filters", default=0)
op.add_option("input-idx", "input_idx", IntegerOptionParser, "Input index for layer given to --show-filters", default=0)
op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option("no-rgb", "no_rgb", BooleanOptionParser, "Don't combine filter channels into RGB in layer given to --show-filters", default=False)
op.add_option("yuv-to-rgb", "yuv_to_rgb", BooleanOptionParser, "Convert RGB filters to YUV in layer given to --show-filters", default=False)
op.add_option("channels", "channels", IntegerOptionParser, "Number of channels in layer given to --show-filters (fully-connected layers only)", default=0)
op.add_option("show-preds", "show_preds", StringOptionParser, "Show predictions made by given softmax on test set", default="")
op.add_option("save-preds", "save_preds", StringOptionParser, "Save predictions to given path instead of showing them", default="")
op.add_option("only-errors", "only_errors", BooleanOptionParser, "Show only mistaken predictions (to be used with --show-preds)", default=False, requires=['show_preds'])
op.add_option("local-plane", "local_plane", IntegerOptionParser, "Local plane to show", default=0)
op.add_option("smooth-test-errors", "smooth_test_errors", BooleanOptionParser, "Use running average for test error plot?", default=1)
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range',
'test_batch_range', 'data_path',
'minibatch_size', 'layer_params', 'batch_size',
'test_only', 'test_one', 'shuffle_data',
'crop_one_border'):
op.delete_option(option)
op.add_option('do-pose-evaluation', 'do_pose_evaluation',
StringOptionParser, 'Specify the output layer of pose')
op.add_option(
'inputstream', 'inputstream', StringOptionParser,
'Specify the type of camera to use [imgcamera|cvcamera]')
op.add_option('outputdir', 'outputdir', StringOptionParser,
'Specify the directory for saving outputs')
op.add_option(
'crop-image', 'crop_image', StringOptionParser,
'Specify the method to crop image to square input patch [faceubd]')
op.options['load_file'].default = None
return op
def get_op(self, n_epochs=None, params_file=None,
train_range='1-5', test_range='6'):
from convnet import ConvNet
op = ConvNet.get_options_parser()
load_dic = None
for option in op.get_options_list():
option.set_default()
op.set_value('data_path',
os.path.expanduser('~/data/cifar-10-py-colmajor/'))
op.set_value('dp_type', 'cifar')
op.set_value('inner_size', '24')
op.set_value('gpu', '0')
op.set_value('testing_freq', '25')
op.set_value('layer_path', 'layers/')
op.set_value('layer_def', self.network_type.layer_file)
op.set_value('layer_params',
params_file or self.network_type.layer_params_file)
op.set_value('train_batch_range', train_range)
op.set_value('test_batch_range', test_range)
if n_epochs is not None:
op.set_value('num_epochs', n_epochs, parse=False)
checkpoint_path = os.path.join(save_dir, self.checkpoint_name())
if os.path.exists(checkpoint_path):
op.set_value('load_file', checkpoint_path)
load_dic = ConvNet.load_checkpoint(checkpoint_path)
old_op = load_dic['op']
old_options = dict(old_op.options)
old_op.merge_from(op)
op.options, old_op.options = old_op.options, old_options
else:
op.set_value('save_file_override', checkpoint_path)
return op, load_dic
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'inner_size',
'train_batch_range', 'test_batch_range',
'multiview_test', 'data_path', 'pca_noise',
'scalar_mean'):
op.delete_option(option)
op.add_option("show-cost",
"show_cost",
StringOptionParser,
"Show specified objective function",
default="")
op.add_option("show-filters",
"show_filters",
StringOptionParser,
"Show learned filters in specified layer",
default="")
op.add_option(
"norm-filters",
"norm_filters",
BooleanOptionParser,
"Individually normalize filters shown with --show-filters",
default=0)
op.add_option("input-idx",
"input_idx",
IntegerOptionParser,
"Input index for layer given to --show-filters",
default=0)
op.add_option("cost-idx",
"cost_idx",
IntegerOptionParser,
"Cost function return value index for --show-cost",
default=0)
op.add_option(
"no-rgb",
"no_rgb",
BooleanOptionParser,
"Don't combine filter channels into RGB in layer given to --show-filters",
default=False)
op.add_option(
"yuv-to-rgb",
"yuv_to_rgb",
BooleanOptionParser,
"Convert RGB filters to YUV in layer given to --show-filters",
default=False)
op.add_option(
"channels",
"channels",
IntegerOptionParser,
"Number of channels in layer given to --show-filters (fully-connected layers only)",
default=0)
op.add_option("show-preds",
"show_preds",
StringOptionParser,
"Show predictions made by given softmax on test set",
default="")
op.add_option("save-preds",
"save_preds",
StringOptionParser,
"Save predictions to given path instead of showing them",
default="")
op.add_option(
"only-errors",
"only_errors",
BooleanOptionParser,
"Show only mistaken predictions (to be used with --show-preds)",
default=False,
requires=['show_preds'])
op.add_option("local-plane",
"local_plane",
IntegerOptionParser,
"Local plane to show",
default=0)
op.add_option("smooth-test-errors",
"smooth_test_errors",
BooleanOptionParser,
"Use running average for test error plot?",
default=1)
op.add_option("save_figure",
"save_figure",
StringOptionParser,
"Output file to save filters",
default="")
op.options['load_file'].default = None
return op
""" View the options used to create a checkpoint
python view_options.py --load-file <checkpoint>
"""
from convnet import ConvNet
from python_util.gpumodel import IGPUModel
op = ConvNet.get_options_parser()
op, load_dic = IGPUModel.parse_options(op)
model = ConvNet(op, load_dic)
model.op.print_values()
print "========================="
model.print_model_state()
def objective(layer_file_name, param_file_name, save_file_name):
def logprob_errors(error_output):
error_types, n = error_output
logprob = error_types['logprob'][0] / n
classifier = error_types['logprob'][1] / n
logprob = np.inf if np.isnan(logprob) else logprob
classifier = np.inf if np.isnan(classifier) else classifier
return logprob, classifier
real_stdout = sys.stdout
sys.stdout = open(save_file_name + '.log', 'w')
convnet = None
try:
# set up options
op = ConvNet.get_options_parser()
for option in op.get_options_list():
option.set_default()
op.set_value('data_path', os.path.expanduser('~/data/cifar-10-py-colmajor/'))
op.set_value('dp_type', 'cifar')
op.set_value('inner_size', '24')
op.set_value('gpu', '0')
op.set_value('testing_freq', '25')
op.set_value('train_batch_range', '1-5')
op.set_value('test_batch_range', '6')
op.set_value('num_epochs', n_epochs, parse=False)
op.set_value('layer_def', layer_file_name)
op.set_value('layer_params', param_file_name)
op.set_value('save_file_override', save_file_name)
convnet = ConvNet(op, None)
# train for three epochs and make sure error is okay
convnet.num_epochs = 3
convnet.train()
logprob, error = logprob_errors(convnet.train_outputs[-1])
if not (error > 0 and error < 0.85):
# should get at most 85% error after three epochs
print "\naborted (%s, %s)" % (logprob, error)
return logprob, error
# train for full epochs
convnet.num_epochs = n_epochs
convnet.train()
logprob, error = logprob_errors(convnet.get_test_error())
print "\nfinished (%s, %s)" % (logprob, error)
return logprob, error
except RuntimeError:
print "\nerrored at epoch %d" % (convnet.epoch)
return np.inf, 1.0
finally:
if convnet is not None:
convnet.destroy_model_lib()
print "\n" # end any pending lines to ensure flush
sys.stdout.flush()
sys.stdout.close()
sys.stdout = real_stdout
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file'):
op.delete_option(option)
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range',
'test_batch_range'):
op.delete_option(option)
op.add_option("show-cost",
"show_cost",
StringOptionParser,
"Show specified objective function",
default="")
op.add_option("show-filters",
"show_filters",
StringOptionParser,
"Show learned filters in specified layer",
default="")
op.add_option("input-idx",
"input_idx",
IntegerOptionParser,
"Input index for layer given to --show-filters",
default=0)
op.add_option("cost-idx",
"cost_idx",
IntegerOptionParser,
"Cost function return value index for --show-cost",
default=0)
op.add_option(
"no-rgb",
"no_rgb",
BooleanOptionParser,
"Don't combine filter channels into RGB in layer given to --show-filters",
default=False)
op.add_option(
"yuv-to-rgb",
"yuv_to_rgb",
BooleanOptionParser,
"Convert RGB filters to YUV in layer given to --show-filters",
default=False)
op.add_option(
"channels",
"channels",
IntegerOptionParser,
"Number of channels in layer given to --show-filters (fully-connected layers only)",
default=0)
op.add_option("show-preds",
"show_preds",
StringOptionParser,
"Show predictions made by given softmax on test set",
default="")
op.add_option(
"only-errors",
"only_errors",
BooleanOptionParser,
"Show only mistaken predictions (to be used with --show-preds)",
default=False,
requires=['show_preds'])
op.add_option("write-features",
"write_features",
StringOptionParser,
"Write test data features from given layer",
default="",
requires=['feature-path'])
op.add_option(
"feature-path",
"feature_path",
StringOptionParser,
"Write test data features to this path (to be used with --write-features)",
default="")
#----my options----------
op.add_option("hist-features",
"hist_features",
StringOptionParser,
"plot histogram of feature activation",
default="")
op.add_option(
"hist-test",
"hist_test",
BooleanOptionParser,
"True: plot hist of test data, False: plot hist of training data",
default=True)
op.add_option(
"nn-analysis",
"nn_analysis",
StringOptionParser,
"run inference on training mode for many times and analysis output",
default="")
#op.add_option("data-provider", "dp_type", StringOptionParser, "Data provider", default="default")
#op.add_option("write-mv-result", "write_mv_result", StringOptionParser, "Write test data multiview features to file", default="", requires=['feature-path'])
op.add_option("write-mv-result",
"write_mv_result",
StringOptionParser,
"Write test data multiview features to file",
default="")
op.add_option(
"write-mv-mc-result",
"write_mv_mc_result",
StringOptionParser,
"Write test data multiview features on MC inferenceto file",
default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('gpu', 'load_file', 'train_batch_range',
'test_batch_range', 'multiview_test'):
op.delete_option(option)
op.add_option("show-cost",
"show_cost",
StringOptionParser,
"Show specified objective function",
default="")
op.add_option("show-filters",
"show_filters",
StringOptionParser,
"Show learned filters in specified layer",
default="")
op.add_option("input-idx",
"input_idx",
IntegerOptionParser,
"Input index for layer given to --show-filters",
default=0)
op.add_option("cost-idx",
"cost_idx",
ListOptionParser(IntegerOptionParser),
"Cost function return value index for --show-cost",
default=[])
# op.add_option("cost-idx", "cost_idx", IntegerOptionParser, "Cost function return value index for --show-cost", default=0)
op.add_option(
"no-rgb",
"no_rgb",
BooleanOptionParser,
"Don't combine filter channels into RGB in layer given to --show-filters",
default=False)
op.add_option(
"yuv-to-rgb",
"yuv_to_rgb",
BooleanOptionParser,
"Convert RGB filters to YUV in layer given to --show-filters",
default=False)
op.add_option(
"channels",
"channels",
IntegerOptionParser,
"Number of channels in layer given to --show-filters (fully-connected layers only)",
default=0)
op.add_option(
"show-preds",
"show_preds",
IntegerOptionParser,
"Show predictions made by given softmax on test or predicting set. 1:test set 2:predicting set",
default=0)
op.add_option("pred-batch-range", "pred_batch_range",
RangeOptionParser, "Data batch range: predicting set")
op.add_option("logsoftmax",
"logsoftmax",
StringOptionParser,
"name of logsoftmax typed layer",
default="")
op.add_option(
"only-errors",
"only_errors",
BooleanOptionParser,
"Show only mistaken predictions (to be used with --show-preds)",
default=False,
requires=['show_preds'])
op.add_option("write-features-train",
"write_features_train",
StringOptionParser,
"Write train data features from given layer",
default='',
requires=[])
op.add_option("write-features-test",
"write_features_test",
StringOptionParser,
"Write test data features from given layer",
default='',
requires=[])
op.add_option("write-features-pred",
"write_features_pred",
StringOptionParser,
"Write prediction data features from given layer",
default='',
requires=[])
# op.add_option("feature-path", "feature_path", StringOptionParser, "Write test data features to this path (to be used with --write-features)", default="")
op.add_option(
"show-layer-weights-biases",
"show_layer_weights_biases",
IntegerOptionParser,
"Show evolution of layer-wise mean absolute of weights, weightsInc, bias, biasInc",
default=0)
op.add_option("confusion-mat",
"confusion_mat",
IntegerOptionParser,
"plot confusion matrix",
default=0)
op.add_option(
"test-meta",
"test_meta",
StringOptionParser,
"meta file for testing data used in plotting confusion matrix",
default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
for option in list(op.options):
if option not in ('load_file', 'sigma'):
op.delete_option(option)
op.add_option("show-filters",
"show_filters",
StringOptionParser,
"Show filters of specified layer",
default="")
op.add_option(
"norm-filters",
"norm_filters",
BooleanOptionParser,
"Individually normalize filters shown with --show-filters",
default=0)
op.add_option("input-idx",
"input_idx",
IntegerOptionParser,
"Input index for layer given to --show-filters",
default=0)
op.add_option(
"no-rgb",
"no_rgb",
BooleanOptionParser,
"Don't combine filter channels into RGB in layer given to --show-filters",
default=False)
op.add_option(
"yuv-to-rgb",
"yuv_to_rgb",
BooleanOptionParser,
"Convert RGB filters to YUV in layer given to --show-filters",
default=False)
op.add_option(
"channels",
"channels",
IntegerOptionParser,
"Number of channels in layer given to --show-filters (fully-connected layers only)",
default=0)
op.add_option("show-cost",
"show_cost",
StringOptionParser,
"Show specified objective function",
default="")
op.add_option("cost-idx",
"cost_idx",
IntegerOptionParser,
"Cost function return value index for --show-cost",
default=0)
op.add_option("smooth-test-errors",
"smooth_test_errors",
BooleanOptionParser,
"Use running average for test error plot?",
default=0)
op.add_option("output-layer",
"output_layer",
StringOptionParser,
"Output layer that the cost is computed from",
default="")
op.add_option("show-mse",
"show_mse",
BooleanOptionParser,
"Show mse error (or PSNR error)",
default=False)
op.add_option("step",
"step",
IntegerOptionParser,
"Step of x axis",
default=1)
op.add_option("patch-perbatch",
"patch_perbatch",
IntegerOptionParser,
"Num of patches per batch",
default=4096)
op.add_option("result-path",
"result_path",
StringOptionParser,
"Path to store the PSNR curve",
default="")
op.options['load_file'].default = None
return op
def get_options_parser(cls):
op = ConvNet.get_options_parser()
op.add_option("test-on-images", "test_on_images", BooleanOptionParser, "Test On Images", default=False)
return op
