def tick_layers_input_data(self, domain):
"""
Add value from layer.input_data to neurons.level
"""
ticks = domain.ticks
for layer in domain.layers:
if layer.input_data is None and layer.input_data_cache is None:
continue
data = layer.input_data
layer.input_data = None
input_data_vector = layer.input_data_cache
if input_data_vector is None:
input_data_vector = StandaloneVector()
if isinstance(data, basestring):
input_data_vector.from_bytes(data)
else:
input_data_vector.set_data(data)
assert len(input_data_vector) == layer.length, \
"Domain '%s': len(input_data_vector)=%s, layer.length=%s" \
% (domain.name, len(input_data_vector), layer.length)
layer.input_data_cache = input_data_vector
length = len(input_data_vector)
if not length:
return
input_data_vector.to_device(self)
# only one layer with the same dims as input data
assert length == len(layer.neurons_metadata.level)
self.program.tick_numpy_input_data_uint8(
self.queue, (length,), None,
# data
input_data_vector.device_data_pointer,
# layer
types.address(layer.neurons_metadata.address),
# neurons
domain.neurons.level.device_data_pointer
).wait()
if layer.input_expire <= ticks:
layer.input_data = None
layer.input_data_cache = None
def tick_synapses(self, domain):
length = domain.neurons.length
if not length:
return
self.program.tick_synapses(
self.queue, (length,), None,
# domain
types.synapse_level(domain.learn_rate),
types.synapse_level(domain.learn_threshold),
types.tick(domain.spike_learn_threshold),
types.tick(domain.spike_forget_threshold),
# neurons
domain.neurons.level.device_data_pointer,
domain.neurons.flags.device_data_pointer,
domain.neurons.spike_tick.device_data_pointer,
# synapses
domain.synapses.level.device_data_pointer,
domain.synapses.pre.device_data_pointer,
domain.synapses.post.device_data_pointer,
domain.synapses.learn.device_data_pointer,
domain.synapses.flags.device_data_pointer,
# pre-neuron - synapse index
domain.pre_synapse_index.key.device_data_pointer,
domain.pre_synapse_index.value.device_data_pointer,
# post-neuron - synapse index
domain.post_synapse_index.key.device_data_pointer,
domain.post_synapse_index.value.device_data_pointer
).wait()
# download layers stats from device once
# per domain.config['stat_size'] ticks
if domain.ticks % domain.config['stat_size'] == 0:
domain.stat_vector.data.fill(0)
self.program.update_layers_stat(
self.queue, (domain.neurons.length,), None,
# domain
types.tick(domain.ticks),
types.address(domain.config['stat_size']),
types.address(domain.stat_fields),
# layers
domain.layers_stat.device_data_pointer,
domain.layers_vector.max_vitality.device_data_pointer,
# neurons
domain.neurons.flags.device_data_pointer,
domain.neurons.spike_tick.device_data_pointer,
domain.neurons.layer.device_data_pointer,
domain.neurons.vitality.device_data_pointer
).wait()
domain.layers_stat.from_device(self)
stat_length = len(domain.stat_vector)
for layer_address in range(len(domain.layers)):
layer_stat_start = \
domain.stat_fields \
* layer_address
domain.stat_vector.data += domain.layers_stat.data[
layer_stat_start : layer_stat_start + stat_length
]
self.program.init_layers_stat(
self.queue, (len(domain.layers_stat),), None,
domain.layers_stat.device_data_pointer
).wait()
if len(domain.synapses):
# count synapses stats
domain.stat_vector.to_device(self)
self.program.update_synapses_stat(
self.queue, (len(domain.synapses),), None,
domain.stat_vector.device_data_pointer,
# synapses
domain.synapses.learn.device_data_pointer,
domain.synapses.flags.device_data_pointer
).wait()
domain.stat_vector.from_device(self)
domain.stat_set('stat_size', domain.config['stat_size'])
# 0 - total spikes (one per neuron) per self.config['stat_size']
# ticks
domain.stat_set('total_spikes', domain.stat_vector.data[0])
# 1 - number of the dead neurons
domain.stat_set('dead_neurons', domain.stat_vector.data[1])
# 2 - number of synapses with flag IS_STRENGTHENED
domain.stat_set('strengthened_synapses', domain.stat_vector.data[2])
# 3 - neurons tiredness = sum(layer.max_vitality - neuron.vitality)
domain.stat_set('neurons_tiredness', domain.stat_vector.data[3])
# 4 - synapse learn level
domain.stat_set('synapse_learn_level', domain.stat_vector.data[4])
