def tick_layers_output_data(self, domain):
"""
Convert layer ticks to numpy array
(if layer.config.get('output') is True)
"""
length = len(domain.output_index.address)
if not length:
return
output_index = domain.output_index
self.program.tick_numpy_output_data_uint8(
self.queue, (length,), None,
# domain
types.tick(domain.ticks),
# output index
output_index.address.device_data_pointer,
output_index.data.device_data_pointer,
output_index.tick.device_data_pointer,
# neurons
domain.neurons.flags.device_data_pointer
).wait()
# find all source consumers and cache it
if self._source_cache is None:
self._source_cache = {}
cache = self._source_cache
for layer in domain.layers:
if 'output' not in layer.config:
continue
source_id = layer.config['output']
cache[source_id] = []
net = domain.net
# consumers
for other_domain in net.domains:
for layer_index, layer in enumerate(other_domain.layers):
if not layer.config.get('input'):
continue
source_id = layer.config['input']
# not our source
if source_id not in cache:
continue
cache[source_id].append([other_domain, layer_index])
for input_index, input_row in enumerate(
other_domain.config['device'].get('input', [])
):
source_id = input_row['name']
# not our source
if source_id not in cache:
continue
cache[source_id].append([other_domain, input_index])
domain.neurons.flags.from_device(self)
output_index.data.from_device(self)
cache = self._source_cache
for source_id, data in output_index.data_to_send():
for consumer_domain, layer_index in cache[source_id]:
consumer_domain.register_input_layer_data(layer_index, data)
def tick_neurons(self, domain):
length = domain.neurons.length
if not length:
return
self.tick_layers_input_data(domain)
self.program.tick_neurons(
self.queue, (length,), None,
# domain
types.tick(domain.ticks),
# layers
domain.layers_vector.threshold.device_data_pointer,
domain.layers_vector.relaxation.device_data_pointer,
domain.layers_vector.spike_cost.device_data_pointer,
domain.layers_vector.max_vitality.device_data_pointer,
# neurons
domain.neurons.level.device_data_pointer,
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,
domain.neurons.threshold.device_data_pointer
).wait()
self.tick_layers_output_data(domain)
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])
