def _install_queue(self):
"""
"""
if not self.use_queue or self.queue_installed:
for layer in self.features + self.labels + self.task_weights:
layer.pre_queue = True
return
names = []
shapes = []
pre_q_inputs = []
q = InputFifoQueue(shapes, names, in_layers=pre_q_inputs)
q.name = "%s_%s" % (q.__class__.__name__, len(self.layers) + 1)
for layer in self.features + self.labels + self.task_weights:
pre_q_input = layer.create_pre_q(self.batch_size)
shapes.append(pre_q_input.shape)
names.append(pre_q_input.name)
pre_q_inputs.append(pre_q_input)
layer.in_layers.append(q)
self.nxgraph.add_edge(q.name, layer.name)
self._add_layer(q)
self.input_queue = q
self.queue_installed = True
def _install_queue(self):
"""
"""
if not self.use_queue or self.queue_installed:
for layer in self.features + self.labels + self.task_weights:
layer.pre_queue = True
return
inputs = self.features + self.labels + self.task_weights
if len(inputs) == 0:
return
names = []
shapes = []
pre_q_inputs = []
q = InputFifoQueue(shapes, names, in_layers=pre_q_inputs)
q.name = "%s_%s" % (q.__class__.__name__, len(self.layers) + 1)
for layer in inputs:
pre_q_input = layer.create_pre_q()
shapes.append(pre_q_input.shape)
names.append(pre_q_input.name)
pre_q_inputs.append(pre_q_input)
layer.in_layers.append(q)
self._add_layer(q)
self.input_queue = q
self.queue_installed = True
def test_input_fifo_queue(self):
"""Test InputFifoQueue can be invoked."""
batch_size = 10
n_features = 5
in_tensor = np.random.rand(batch_size, n_features)
tf.reset_default_graph()
with self.test_session() as sess:
in_tensor = TensorWrapper(
tf.convert_to_tensor(in_tensor, dtype=tf.float32), name="input")
InputFifoQueue([(batch_size, n_features)], ["input"])(in_tensor)
def _install_queue(self):
if self.input_queue is not None:
return
names = []
shapes = []
pre_q_inputs = []
for layer in self.features + self.labels + self.task_weights:
pre_q_input = layer.create_pre_q(self.batch_size)
shapes.append(pre_q_input.shape)
names.append(pre_q_input.name)
self.add_layer(pre_q_input)
pre_q_inputs.append(pre_q_input)
q = InputFifoQueue(shapes, names)
self.add_layer(q, pre_q_inputs)
for layer in self.features + self.labels + self.task_weights:
self._add_parent(layer, q)
self.input_queue = q
