def _tick_input_data(self, domain):
"""
Process data from other domains
"""
ticks = domain.ticks
ret = []
for layer in self._input:
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
ret.append([
layer.config['name'],
np.reshape(input_data_vector.data, (layer.height, layer.width))
])
if layer.input_expire <= ticks:
layer.input_data = None
layer.input_data_cache = None
if ret:
self.receive_data(domain, ret)
def tick_layers_input_data(self, domain):
import numpy as np
for layer_index, layer in enumerate(domain.layers):
if not layer.input_data:
continue
input_data_vector = StandaloneVector()
data = layer.input_data
if isinstance(data, basestring):
input_data_vector.from_bytes(data)
else:
input_data_vector.set_data(data)
check = np.zeros(40, dtype=np.uint8)
check.fill(layer_index)
assert list(input_data_vector.data) == list(check)
domain.stat_inc('test_io_input')
ret = super(IOBaseTesterSimpleCheck,
self).tick_layers_input_data(domain)
assert layer.input_data is None
return ret
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 register_input_layer_data(self, layer_index, data):
"""
Send data over network
"""
vector = StandaloneVector().set_data(data)
self.pub_data('NP', str(layer_index), vector.bytes())
def check_input(expire):
import numpy
from openre import OpenRE
from openre.vector import StandaloneVector
from openre import neurons
import logging
# remote domains
config = {
'layers': [
{
'name': 'Input',
'width': 10,
'height': 10,
'is_inhibitory': False,
'threshold': 128,
'relaxation': 0,
'connect': [
{
'name': 'V2',
'radius': 1,
'shift': [0, 0],
},
],
},
{
'name': 'V2',
'width': 10,
'height': 10,
'relaxation': 0,
},
],
'domains': [
{
'name' : 'D1',
'device' : {
'type': 'OpenCL',
'threshold_inc': 0,
'threshold_dec': 0
},
'layers' : [
{'name': 'Input', 'shape': [0, 0, 5, 5], 'expire': expire},
{'name': 'Input', 'shape': [0, 5, 5, 5], 'expire': expire},
{'name': 'Input', 'shape': [5, 0, 5, 5], 'expire': expire},
{'name': 'Input', 'shape': [5, 5, 5, 5], 'expire': expire},
],
},
{
'name' : 'D2',
'device' : {
'type': 'OpenCL',
'threshold_inc': 0,
'threshold_dec': 0
},
'layers' : [
{'name': 'V2'},
],
},
],
}
ore = OpenRE(config)
ore.deploy()
device1 = ore.domains[0].device
device2 = ore.domains[1].device
D1 = ore.domains[0]
D2 = ore.domains[1]
arr = numpy.arange(0, 200, 2, dtype=numpy.uint8)
#arr = StandaloneVector(numpy.reshape(arr, (10, 10)))
arr = numpy.reshape(arr, (10, 10))
l0 = arr[0:5, 0:5]
l1 = arr[5:10, 0:5]
l2 = arr[0:5, 5:10]
l3 = arr[5:10, 5:10]
# somewhere here we will send packet to the input device
# and in input device will receive it:
layer_data = [l0, l1, l2, l3]
for layer_index, data in enumerate(layer_data):
if layer_index % 2:
D1.register_input_layer_data(
layer_index,
StandaloneVector(data).bytes()
)
else:
D1.register_input_layer_data(
layer_index,
data
)
neurons_length = 0
for layer_index, data in enumerate(layer_data):
layer = D1.layers[layer_index]
vector = StandaloneVector()
if isinstance(layer.input_data, basestring):
vector.from_bytes(layer.input_data)
else:
vector.set_data(layer.input_data)
assert list(vector.data) == list(numpy.ravel(data))
assert len(vector.data) == len(numpy.ravel(data))
neurons_length += len(vector.data)
assert len(D1.neurons.level) == neurons_length
D1.neurons.level.data[:] = 0
D1.neurons.level.to_device(device1)
D2.neurons.level.data[:] = 0
D2.neurons.level.to_device(device2)
ore.tick()
D1.neurons.from_device(device1)
D2.neurons.from_device(device2)
level_check \
= numpy.ravel(numpy.concatenate(layer_data)).astype(numpy.uint32)
level_check[level_check >= 128] -= 128
assert list(D1.neurons.level.data) == list(level_check)
flags_check = numpy.ravel(numpy.concatenate(layer_data))
flags_check[flags_check < 128] = neurons.IS_TRANSMITTER
flags_check[flags_check >= 128] = neurons.IS_TRANSMITTER | neurons.IS_SPIKED
assert list(flags_check) == list(D1.neurons.flags.data)
# check D2 neuron level
flags2_check = numpy.ravel(numpy.concatenate(layer_data))
level2_check = numpy.copy(D2.synapses.level.data)
level2_check[flags2_check < 128] = 0
neurons2_level = numpy.reshape(
D2.neurons.level.data[0:len(level2_check)],
(10, 10)
)
l20 = neurons2_level[0:5, 0:5]
l21 = neurons2_level[5:10, 0:5]
l22 = neurons2_level[0:5, 5:10]
l23 = neurons2_level[5:10, 5:10]
layer2_data = [l20, l21, l22, l23]
# D2 neuron level should be eq to synapses levels
assert list(numpy.ravel(numpy.concatenate(layer2_data))) \
== list(level2_check)
try:
for pass_num in range(2, 4):
ore.tick()
D1.neurons.from_device(device1)
D2.neurons.from_device(device2)
if expire and expire >= pass_num:
level_check = level_check \
+ numpy.ravel(numpy.concatenate(layer_data))
level_check[level_check >= 128] -= 128
assert list(D1.neurons.level.data) == list(level_check)
if not expire or expire < pass_num:
for layer_index, data in enumerate(layer_data):
assert layer.input_data_cache is None
assert layer.input_data is None
except AssertionError:
logging.warn('Expire #%s, pass #%s', expire, pass_num)
raise