def construct_objective(self):
with tf.name_scope("objective"):
self.total_loss = 0
self.total_constraints = 0
self.loss_by_layer.clear()
self.error_by_layer.clear()
for name, layer in sorted(self.layers.items()):
assert isinstance(layer, LayerBase)
with reuse_name_scope(layer.tf_scope_name):
loss = layer.get_loss_value()
error = layer.get_error_value()
constraints = layer.get_constraints_value()
if loss is not None:
tf.summary.scalar("loss_%s" % layer.name, loss)
if error is not None:
tf.summary.scalar("error_%s" % layer.name, error)
if loss is not None:
self.loss_by_layer[name] = loss
self.total_loss += loss
if error is not None:
self.error_by_layer[name] = error
if constraints is not None:
self.total_constraints += constraints
tf.summary.scalar("loss", self.total_loss)
tf.summary.scalar("constraints", self.total_constraints)
self.total_objective = self.total_loss + self.total_constraints
tf.summary.scalar("objective", self.total_objective)
def helper_variable_scope():
"""
:rtype: tf.VariableScope
"""
from TFUtil import reuse_name_scope
with reuse_name_scope("IO", absolute=True) as scope:
yield scope
def add_layer(self, name, layer_class, **layer_desc):
"""
:param str name:
:param (()->LayerBase)|LayerBase layer_class:
"""
layer_desc = layer_desc.copy()
assert "name" not in layer_desc
assert "network" not in layer_desc
assert "output" not in layer_desc
layer_desc["name"] = name
layer_desc["network"] = self
debug_print_layer_output_template = self._config and self._config.bool("debug_print_layer_output_template", False)
debug_print_layer_output_shape = self._config and self._config.bool("debug_print_layer_output_shape", False)
with reuse_name_scope(layer_class.cls_get_tf_scope_name(name)):
output = layer_class.get_out_data_from_opts(**layer_desc)
if debug_print_layer_output_template:
print("layer %r output: %r" % (name, output))
layer = layer_class(output=output, **layer_desc)
layer.post_init()
if debug_print_layer_output_shape:
layer.output.placeholder = tf.Print(
layer.output.placeholder, [layer_class.cls_get_tf_scope_name(name), "shape:", tf.shape(layer.output.placeholder)],
summarize=10, name="debug_print_layer_output_shape")
assert layer.output
assert layer.output.placeholder is not None
assert layer.output.size_placeholder is not None
self.layers[name] = layer
if layer.recurrent:
self.recurrent = True
return layer
def get_var_assigner(self, var):
"""
:param tf.Variable var:
"""
if var in self._assigner_cache:
return self._assigner_cache[var]
with reuse_name_scope("var_assigner"):
assigner = VariableAssigner(var)
self._assigner_cache[var] = assigner
return assigner
def _add_layer(self, name, layer_class, **layer_desc):
"""
:param str name:
:param ()->LayerBase layer_class:
"""
with reuse_name_scope(layer_class.cls_get_tf_scope_name(name)):
layer = layer_class(name=name, network=self, **layer_desc)
assert layer.output
assert layer.output.placeholder is not None
assert layer.output.size_placeholder is not None
self.layers[name] = layer
if layer.recurrent:
self.recurrent = True
return layer
def add_layer(self, name, layer_class, **layer_desc):
"""
:param str name:
:param (()->LayerBase)|LayerBase layer_class:
"""
from Util import help_on_type_error_wrong_args
layer_desc = layer_desc.copy()
assert "name" not in layer_desc
assert "network" not in layer_desc
assert "output" not in layer_desc
layer_desc["name"] = name
layer_desc["network"] = self
debug_print_layer_output_template = self._config and self._config.bool(
"debug_print_layer_output_template", False)
debug_print_layer_output_sizes = self._config and self._config.bool(
"debug_print_layer_output_sizes", False)
debug_print_layer_output_shape = self._config and self._config.bool(
"debug_print_layer_output_shape", False)
with reuse_name_scope(layer_class.cls_get_tf_scope_name(name)):
try:
output = layer_class.get_out_data_from_opts(**layer_desc)
if debug_print_layer_output_template:
print("layer %r output: %r" % (name, output))
layer = layer_class(output=output, **layer_desc)
except TypeError:
help_on_type_error_wrong_args(cls=layer_class,
kwargs=list(layer_desc.keys()))
raise
layer.post_init()
if debug_print_layer_output_sizes:
print("layer %r output sizes: %r" %
(name, output.size_placeholder))
if debug_print_layer_output_shape:
layer.output.placeholder = tf.Print(
layer.output.placeholder, [
layer_class.cls_get_tf_scope_name(name), "shape:",
tf.shape(layer.output.placeholder)
],
summarize=10,
name="debug_print_layer_output_shape")
assert layer.output
assert layer.output.placeholder is not None
layer.output.placeholder.set_shape(layer.output.batch_shape)
assert layer.output.size_placeholder is not None
self.layers[name] = layer
if layer.recurrent:
self.recurrent = True
return layer
def add_layer(self, name, layer_class, **layer_desc):
"""
:param str name:
:param (()->LayerBase)|LayerBase layer_class:
"""
layer_desc = layer_desc.copy()
assert "name" not in layer_desc
assert "network" not in layer_desc
assert "output" not in layer_desc
layer_desc["name"] = name
layer_desc["network"] = self
with reuse_name_scope(layer_class.cls_get_tf_scope_name(name)):
output = layer_class.get_out_data_from_opts(**layer_desc)
layer = layer_class(output=output, **layer_desc)
layer.post_init()
assert layer.output
assert layer.output.placeholder is not None
assert layer.output.size_placeholder is not None
self.layers[name] = layer
if layer.recurrent:
self.recurrent = True
return layer
