pylearn: doc/seriestables.txt comparison

comparison doc/seriestables.txt @ 929:34d1cd516f76

Added other targets (printing to stdout, notably) to seriestables, and corresponding doc

author	fsavard
date	Thu, 15 Apr 2010 09:11:14 -0400
parents	fdb63e4e042d
children

comparison

equal deleted inserted replaced

-:87d416e1f4fd
+:34d1cd516f76
 		# suppose all_params is a list [layer1_W, layer1_b, ...]
 		# where each element is a shared (as in theano.shared) array
 		series['params'].append((epoch,), all_params)
+Other targets for appending (e.g. printing to stdout)
+-----------------------------------------------------
+SeriesTables was created with an HDF5 file in mind, but often, for debugging,
+it's useful to be able to redirect the series elsewhere, notably the standard
+output. A mechanism was added to do just that.
+What you do is you create a ``AppendTarget`` instance (or more than one) and
+pass it as an argument to the Series constructor. For example, to print every
+row appended to the standard output, you use StdoutAppendTarget.
+If you want to skip appending to the HDF5 file entirely, this is also
+possible. You simply specify ``skip_hdf5_append=True`` in the constructor. You
+still need to pass in a valid HDF5 file, though, even though nothing will be
+written to it (for, err, legacy reasons).
+Here's an example:
+.. code-block:: python
+	def create_series(num_hidden_layers):
+		# Replace series we don't want to save with DummySeries, e.g.
+		# series['training_error'] = DummySeries()
+		series = {}
+		basedir = os.getcwd()
+		h5f = tables.openFile(os.path.join(basedir, "series.h5"), "w")
+		# Here we create the new target, with a message prepended
+		# before every row is printed to stdout
+		stdout_target = \
+			StdoutAppendTarget( \
+				prepend='\n-----------------\nValidation error',
+				indent_str='\t')
+		# Notice here we won't even write to the HDF5 file
+		series['validation_error'] = \
+			ErrorSeries(error_name="validation_error",
+				table_name="validation_error",
+				hdf5_file=h5f,
+				index_names=('epoch',),
+				other_targets=[stdout_target],
+				skip_hdf5_append=True)
+		return series
+Now calls to series['validation_error'].append() will print to stdout outputs
+like::
+	----------------
+	Validation error
+		timestamp : 1271202144
+		cpuclock : 0.12
+		epoch : 1
+		validation_error : 30.0
+	----------------
+	Validation error
+		timestamp : 1271202144
+		cpuclock : 0.12
+		epoch : 2
+		validation_error : 26.0
 Visualizing in vitables
 -----------------------
 vitables_ is a program with which you can easily explore an HDF5 ``.h5`` file. Here's a screenshot in which I visualize series produced for the preceding example:
 .. _vitables: http://vitables.berlios.de/
 .. image:: images/vitables_example_series.png

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comparison doc/seriestables.txt @ 929:34d1cd516f76