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Consistent layer naming - addresses #1462 #1500

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4 changes: 2 additions & 2 deletions pylearn2/models/dbm/layer.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1524,7 +1524,7 @@ def __init__(self, n_classes, layer_name, irange = None,
assert isinstance(n_classes, py_integer_types)

self.output_space = VectorSpace(n_classes)
self.b = sharedX( np.zeros((n_classes,)), name = 'softmax_b')
self.b = sharedX( np.zeros((n_classes,)), name=layer_name+'_b')

if self.center:
b = self.b.get_value()
Expand Down Expand Up @@ -1624,7 +1624,7 @@ def set_input_space(self, space):
idx = rng.randint(0, self.input_dim)
W[idx, i] = rng.randn() * self.sparse_istdev

self.W = sharedX(W, 'softmax_W' )
self.W = sharedX(W, self.layer_name+'_W' )

self._params = [ self.b, self.W ]

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4 changes: 2 additions & 2 deletions pylearn2/models/maxout.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1226,14 +1226,14 @@ def handle_pool_shape(idx):
partial_sum=self.partial_sum,
rng=rng)
W, = self.transformer.get_params()
W.name = 'W'
W.name = self.layer_name + '_W'

if self.tied_b:
self.b = sharedX(np.zeros((self.detector_space.num_channels)) +
self.init_bias)
else:
self.b = sharedX(self.detector_space.get_origin() + self.init_bias)
self.b.name = 'b'
self.b.name = self.layer_name + '_b'

logger.info('Input shape: {0}'.format(self.input_space.shape))
logger.info(self.layer_name +
Expand Down
4 changes: 2 additions & 2 deletions pylearn2/models/mlp.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1187,7 +1187,7 @@ def __init__(self, n_classes, layer_name, irange=None,
self.output_space = VectorSpace(n_classes)
if not no_affine:
self.b = sharedX(np.zeros((n_classes - self.non_redundant,)),
name='softmax_b')
name=layer_name+'_b')
if init_bias_target_marginals:

y = init_bias_target_marginals.y
Expand Down Expand Up @@ -1331,7 +1331,7 @@ def set_input_space(self, space):
idx = rng.randint(0, self.input_dim)
W[idx, i] = rng.randn()

self.W = sharedX(W, 'softmax_W')
self.W = sharedX(W, self.layer_name+'_W')

self._params = [self.b, self.W]

Expand Down
2 changes: 1 addition & 1 deletion pylearn2/scripts/tutorials/convolutional_network/convolutional_network.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -229,7 +229,7 @@
" max_kernel_norm: 1.9365\n",
" }, !obj:pylearn2.models.mlp.Softmax {\n",
" max_col_norm: 1.9365,\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" istdev: .05\n",
" }\n",
Expand Down
4 changes: 2 additions & 2 deletions pylearn2/scripts/tutorials/jobman_integration.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -40,7 +40,7 @@
" dim: 500,\n",
" sparse_init: 15,\n",
" }, !obj:pylearn2.models.mlp.Softmax {\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" irange: 0.\n",
" }\n",
Expand Down Expand Up @@ -100,7 +100,7 @@
" dim: 500,\n",
" sparse_init: 15,\n",
" }, !obj:pylearn2.models.mlp.Softmax {\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" irange: 0.\n",
" }\n",
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6 changes: 3 additions & 3 deletions pylearn2/scripts/tutorials/multilayer_perceptron/multilayer_perceptron.ipynb
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Expand Up @@ -213,7 +213,7 @@
" dim: 500,\n",
" sparse_init: 15,\n",
" }, !obj:pylearn2.models.mlp.Softmax {\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" irange: 0.\n",
" }\n",
Expand Down Expand Up @@ -25405,7 +25405,7 @@
" dim: 1000,\n",
" sparse_init: 15\n",
" }, !obj:pylearn2.models.mlp.Softmax {\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" irange: 0.\n",
" }\n",
Expand Down Expand Up @@ -56634,7 +56634,7 @@
" dim: 500,\n",
" sparse_init: 15\n",
" }, !obj:pylearn2.models.mlp.Softmax {\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" irange: 0.\n",
" }\n",
Expand Down
2 changes: 1 addition & 1 deletion pylearn2/scripts/tutorials/stacked_autoencoders/stacked_autoencoders.ipynb
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Original file line number Diff line number Diff line change
Expand Up @@ -1989,7 +1989,7 @@
" },\n",
" !obj:pylearn2.models.mlp.Softmax {\n",
" max_col_norm: 1.9365,\n",
" layer_name: 'y',\n",
" layer_name: 'softmax',\n",
" n_classes: 10,\n",
" irange: .005\n",
" }\n",
Expand Down