def mutate(self, input_shape, output_shape, mutate_options, entropy):
"""Randomly alter all aspects of the layer stack."""
mutagen = mutate.Mutagen(mutate_options, entropy)
self.optimizer.mutate(mutagen)
shape = self.mutate_layers("image", self.image_layers, input_shape, None, mutagen)
expand_output = None if self.flatten else output_shape
shape = self.mutate_layers("expand", self.expand_layers, shape, expand_output, mutagen)
if self.flatten:
shape = convnet.flatten_output_shape(shape)
return self.mutate_layers("hidden", self.hidden_layers, shape, output_shape, mutagen)
def parameter_count(self, input_shape):
count = 0
shape = input_shape
for layer in itertools.chain(self.image_layers, self.expand_layers):
count += layer.parameter_count(shape)
shape = layer.output_shape(shape)
if self.flatten:
shape = convnet.flatten_output_shape(shape)
for layer in self.hidden_layers:
count += layer.parameter_count(shape)
shape = layer.output_shape(shape)
return count
def make_safe(self, input_shape, output_shape):
"""Try to fix any layer settings to make compatible with the specified input and output shapes."""
shape = input_shape
for layer in self.image_layers:
shape = layer.make_safe(shape, None)
for layer in self.expand_layers:
is_output_layer = (layer == self.expand_layers[-1] and not self.flatten)
shape = layer.make_safe(shape, output_shape if is_output_layer else None)
if self.flatten:
shape = convnet.flatten_output_shape(shape)
for layer in self.hidden_layers:
is_output_layer = (layer == self.hidden_layers[-1])
shape = layer.make_safe(shape, output_shape if is_output_layer else None)
return shape
def construct(self, input_shape, output_shape=None):
"""Construct the convnet operations for this stack."""
operations = []
shape = input_shape
for layer in self.image_layers:
shape = layer.construct(shape, operations)
for layer in self.expand_layers:
shape = layer.construct(shape, operations)
if self.flatten:
operations.append(convnet.create_flatten())
shape = convnet.flatten_output_shape(shape)
for layer in self.hidden_layers:
shape = layer.construct(shape, operations)
if output_shape and shape != output_shape:
if convnet.can_slice(shape, output_shape):
operations.append(convnet.create_slice(output_shape))
return operations
