def __init__(self, inputlayers, outputlayers):
"""
:type inputlayers: list
:param inputlayers: List of Lasagne input layers.
:type outputlayers: list
:param outputlayers: List of output layers.
"""
# Init superclass
super(lasagnelayer, self).__init__()
# Make sure lasagne is available
assert las is not None, "Lasagne could not be imported."
# Meta
self.inputlayers = pyk.delist(inputlayers)
self.outputlayers = pyk.delist(outputlayers)
# Get inpshape from lasagne
self.lasinpshape = pyk.delist(
[list(il.shape) for il in pyk.obj2list(self.inputlayers)])
# Parse layer info
parsey = netutils.parselayerinfo(dim=2,
allowsequences=True,
numinp=pyk.smartlen(inputlayers),
issequence=False,
inpshape=self.lasinpshape)
self.dim = parsey['dim']
self.inpdim = parsey['inpdim']
self.allowsequences = parsey['allowsequences']
self.issequence = parsey['issequence']
self.numinp = parsey['numinp']
# Read parameters
self._params = las.layers.get_all_params(self.outputlayers)
self._cparams = [
netutils.getshared(like=param, value=1.) for param in self.params
]
# Name parameters right
self.nameparams()
# Shape inference
self.inpshape = parsey['inpshape']
# Check numout for consistency
assert self.numout == pyk.smartlen(self.outputlayers), "Number of outputs doesn't match " \
"the given number of output-layers"
self.x, self.y = netutils.makelayerxy(self.inpdim, self.outdim,
id(self))
def func(*args, **kwargs):
# Compute argument length
arglen = max([pyk.smartlen(arg) for arg in list(args) + list(kwargs.values())])
# Convert arguments to list
args = [pyk.obj2list(arg) if not len(pyk.obj2list(arg)) == 1 else pyk.obj2list(arg)*arglen for arg in args]
kwargs = {kw: pyk.obj2list(arg) if not len(pyk.obj2list(arg)) == 1 else pyk.obj2list(arg)*arglen
for kw, arg in kwargs.items()}
# Make sure list sizes check out
assert all([pyk.smartlen(arg) == arglen for arg in args]) if pyk.smartlen(arg) != 0 else True, \
"Input lists must all have the same length."
assert all([pyk.smartlen(kwarg) == pyk.smartlen(kwargs.values()[0]) == arglen for kwarg in kwargs.values()]) \
if pyk.smartlen(kwargs) != 0 else True, "Keyword argument vectors must have the same length (= argument " \
"vector length)"
# Run the loop (can be done with a long-ass list comprehension, but I don't see the point)
res = []
if not len(kwargs) == 0 and not len(args) == 0:
for arg, kwarg in zip(zip(*args), zip(*kwargs.values())):
res.append(fun(*arg, **{kw: kwa for kw, kwa in zip(kwargs.keys(), kwarg)}))
else:
if len(kwargs) == 0:
res = [fun(*arg) for arg in zip(*args)]
elif len(args) == 0:
res = [fun(**{kw: kwa for kw, kwa in zip(kwargs.keys(), kwarg)}) for kwarg in zip(*kwargs.values())]
else:
return []
# Return results
return pyk.delist(res)
def __call__(self, *args, **kwargs):
# This function wraps the compiled theano function.
# ------------------------------------------------------
# Don't allow args if self.inputs is a dictionary. This is because the user can not be expected to know
# exactly how a dictionary is ordered.
args = list(args)
if isinstance(self.inputs, dict):
assert args == [], "Antipasti function object expects keyword arguments because the " \
"provided input was a dict."
if isinstance(self.inputs, list):
assert kwargs == {}, "Keywords could not be parsed by the Antipasti function object."
# Flatten kwargs or args
if args:
funcargs = list(pyk.flatten(args))
else:
funcargs = list(pyk.flatten(kwargs.values()))
# Evaluate function
outlist = pyk.obj2list(self._thfunction(*funcargs), ndarray2list=False)
# Parse output list
expoutputs = self.outputs.values() if isinstance(
self.outputs, dict) else self.outputs
expoutputs = pyk.obj2list(expoutputs, ndarray2list=False)
# Make sure the theano function has returned the correct number of outputs
assert len(outlist) == len(list(pyk.flatten(expoutputs))), "Number of outputs returned by the theano function " \
"is not consistent with the number of expected " \
"outputs."
# Unflatten theano function output (outlist)
# Get list with sublist lengths
lenlist = [pyk.smartlen(expoutput) for expoutput in expoutputs]
# Unflatten outlist
outputs = pyk.unflatten(outlist, lenlist)
# Write to dictionary if self.outputs is a dictionary
if isinstance(self.outputs, dict):
outputs = {
outname: outvar
for outname, outvar in zip(self.outputs.keys(), outputs)
}
elif isinstance(self.outputs, list):
outputs = tuple(outputs)
else:
outputs = pyk.delist(outputs)
return outputs
def feedforward(self, inp=None):
if inp is None:
inp = self.x
else:
self.x = inp
# Loop over connections, merge and append to a buffer
out = []
for connum, conn in enumerate(self.connections):
if pyk.smartlen(conn) == 1:
out.append(inp[pyk.delist(pyk.obj2list(conn))])
else:
if self.merge:
out.append(self.mergelayers[connum].feedforward(inp=[inp[node] for node in conn]))
else:
out.append([inp[node] for node in conn])
self.y = out
return self.y
def feedforward(self, inp=None):
if inp is None:
inp = self.x
else:
self.x = inp
# Loop over connections, merge and append to a buffer
out = []
for connum, conn in enumerate(self.connections):
if pyk.smartlen(conn) == 1:
out.append(inp[pyk.delist(pyk.obj2list(conn))])
else:
if self.merge:
out.append(self.mergelayers[connum].feedforward(
inp=[inp[node] for node in conn]))
else:
out.append([inp[node] for node in conn])
self.y = out
return self.y
def __init__(self,
connections,
merge=True,
dim=2,
issequence=False,
inpshape=None):
"""
:type connections: list
:param connections: List of connections. E.g.: [[0, 1], 1, [0, 1, 2]] would merge inputs 0 & 1 and write to
first output slot, 1 to second output slot and 0, 1 & 2 merged to the third output slot.
:param dim:
:param issequence:
:param inpshape:
:return:
"""
super(circuitlayer, self).__init__()
# Compute the number of i/o slots
self.numinp = len(pyk.unique(list(pyk.flatten(connections))))
self.numout = len(connections)
self.merge = bool(merge)
# TODO Fix this
assert self.numinp != 1, "Circuit layer must have atleast 2 inputs. Consider using a replicatelayer."
# Parse
dim = [
dim,
] * self.numinp if isinstance(dim,
int) and self.numinp is not None else dim
issequence = [issequence, ] * self.numinp if isinstance(issequence, bool) and self.numinp is not None \
else issequence
# Parse inpshape if numinp, dim, issequence is given
if self.numinp is not None and dim is not None and inpshape is None:
if 3 in dim:
# issequence doesn't matter, inpshape can still be filled
inpshape = [[
None,
] * 5 for _ in dim]
else:
# dim is 2, but input might still be sequential
if issequence is None:
pass
else:
if issequence:
# issequence is false and dim = 2, ergo 2D data
inpshape = [[
None,
] * 4 for _ in dim]
else:
# issequence is true, ergo 2D sequential data
inpshape = [[
None,
] * 5 for _ in dim]
# Meta
self.connections = connections
self.dim = dim if dim is not None else [{
4: 2,
5: 2
}[len(ishp)] for ishp in inpshape]
self.allowsequences = True
self.issequence = [idim == 2 and len(ishp) == 5 for idim, ishp in zip(self.dim, inpshape)] \
if issequence is None else issequence
self.inpdim = [
len(ishp) if ishp is not None else 5 if iisseq else {
2: 4,
3: 5
}[idim]
for ishp, iisseq, idim in zip(inpshape, self.issequence, self.dim)
]
# Check if inpdim is consistent
assert all([indim == self.inpdim[0] for indim in self.inpdim
]), "Can't concatenate 2D with 3D inputs."
# Make merge layers
self.mergelayers = [
mergelayer(numinp=len(conn),
dim=[self.dim[node] for node in conn],
issequence=[self.issequence[node] for node in conn],
inpshape=[inpshape[node] for node in conn])
if pyk.smartlen(conn) != 1 else None for conn in self.connections
]
# Shape inference
self.inpshape = list(inpshape) if inpshape is not None else [[
None,
] * indim for indim in self.inpdim]
# Containers for input and output
self.x = pyk.delist([
T.tensor('floatX', [
False,
] * indim,
name='x{}:'.format(inpnum) + str(id(self)))
for inpnum, indim in enumerate(self.inpdim)
])
self.y = pyk.delist([
T.tensor('floatX', [
False,
] * self.inpdim[pyk.obj2list(self.connections[outnum])[0]],
name='y:' + str(id(self)))
for outnum in range(self.numout)
])
def parselayerinfo(dim=None,
inpdim=None,
issequence=None,
allowsequences=None,
numinp=None,
inpshape=None,
verbose=True):
parsey = {
'dim': dim,
'inpdim': inpdim,
'issequence': issequence,
'allowsequences': allowsequences,
'numinp': numinp,
'inpshape': inpshape
}
# Parse from inpshape
if parsey['inpshape'] is not None:
# Make sure inpshape is a list
assert isinstance(
parsey['inpshape'],
list), "inpshape must be a list, e.g. [None, 3, None, None]."
# Fetch number of inputs
if pyk.islistoflists(parsey['inpshape']):
_numinp = len(parsey['inpshape'])
_inpdim = [len(ishp) for ishp in parsey['inpshape']]
else:
_numinp = 1
_inpdim = len(parsey['inpshape'])
# Write to parsed (if not written already)
# numinp
parsey['numinp'] = _numinp if parsey['numinp'] is None else parsey[
'numinp']
# Consistency check
assert parsey['numinp'] == _numinp, "The provided inpshape requires numinp = {}, " \
"but the value given was {}".format(_numinp, parsey['numinp'])
# inpdim
parsey['inpdim'] = _inpdim if parsey['inpdim'] is None else parsey[
'inpdim']
assert parsey['inpdim'] == _inpdim, "The provided inpshape requires inpdim = {}, " \
"but the value given was {}".format(_inpdim, parsey['inpdim'])
# Check if dim, inpdim, issequence or allowsequences is a list of multiple elements and numinp is not given.
if parsey['numinp'] is None:
for argname in ['dim', 'inpdim', 'issequence', 'allowsequences']:
if isinstance(parsey[argname], list):
parsey['numinp'] = len(parsey[argname])
# Parse from numinp
if parsey['numinp'] is not None:
for argname, argtype in zip(
['dim', 'inpdim', 'issequence', 'allowsequences'],
[int, int, bool, bool]):
if isinstance(parsey[argname], argtype) and parsey['numinp'] > 1:
# If numinp is > 1 and allowseqences or issequence or inpdim or dim is bool or bool or int or int,
# assume that the user (or the author) is too lazy to type in a list.
parsey[argname] = [
parsey[argname],
] * parsey['numinp']
elif isinstance(parsey[argname], list) and parsey['numinp'] > 1:
# If the user was not lazy, make sure the given list sizes check out
assert len(parsey[argname]) == parsey['numinp'], \
"{} must be a {} or a list of length {} (= numinp).".format(argname, argtype, parsey['numinp'])
# Check if inpshape is consistent
if parsey['inpshape'] is not None and parsey['numinp'] > 1:
assert pyk.islistoflists(parsey['inpshape']) and len(
parsey['inpshape']) == parsey['numinp']
else:
if verbose:
warn("Guessing that numinp = 1.")
# Guess numinp = 1.
parsey['numinp'] = 1
# Parse allowsequences
# At this point, allowsequences must be known (or no conclusions can be drawn on issequence and dim)
if parsey['allowsequences'] is None:
if verbose:
warn("Guessing that sequences are allowed.")
parsey['allowsequences'] = pyk.delist([
True,
] * parsey['numinp'])
else:
# Okay, so it's known if sequences are allowed. Check if issequence is consistent.
if pyk.obj2list(parsey['allowsequences']) == [
False,
] * parsey['numinp'] and parsey['issequence'] is not None:
# If sequences are not allowed, make sure issequence is False
assert pyk.obj2list(parsey['issequence']) == [False,] * parsey['numinp'], \
"Input(s) are not allowed to be sequential, yet they are."
# Parse issequence
if parsey['issequence'] is not None:
# Delist issequence
parsey['issequence'] = pyk.delist(parsey['issequence']) \
if isinstance(parsey['issequence'], list) else parsey['issequence']
# Check if issequence is consistent with everything
if isinstance(parsey['issequence'], list):
assert len(parsey['issequence']) == parsey['numinp'], "issequence must be a list of the same lenght as " \
"numinp = {} if numinp > 1.".format(parsey['numinp'])
# Check if consistent with allowsequences. At this point, issequence may have None's.
assert all([(bool(isseq) and allowseq) or not isseq
for isseq, allowseq in zip(pyk.obj2list(parsey['issequence']),
pyk.obj2list(parsey['allowsequences']))]), \
"Input is a sequence although it's not allowed to. " \
"issequence = {}, allowsequences = {}.".format(parsey['issequence'], parsey['allowsequences'])
else:
if verbose:
warn("Guessing that input(s) is(are) not sequential.")
parsey['issequence'] = pyk.delist([
False,
] * parsey['numinp'])
# Parse inpdim
# Compute expected inpdim from what's known
# Check in from issequence
_inpdim = pyk.delist(
[5 if isseq else None for isseq in pyk.obj2list(parsey['issequence'])])
# Check in from dim
if parsey['dim'] is not None:
_inpdim = pyk.delist([
5 if d == 3 else indim for d, indim in zip(
pyk.obj2list(parsey['dim']), pyk.obj2list(_inpdim))
])
_inpdim = pyk.delist([
4 if (d == 2 and not isseq) else indim for d, indim, isseq in zip(
pyk.obj2list(parsey['dim']), pyk.obj2list(_inpdim),
pyk.obj2list(parsey['issequence']))
])
if parsey['inpdim'] is None:
# Make sure there are no None's remaining in _inpdim
assert None not in pyk.obj2list(
_inpdim
), "Input dimensionality could not be parsed due to missing information."
parsey['inpdim'] = _inpdim
else:
assert pyk.smartlen(parsey['inpdim']) == pyk.smartlen(_inpdim), \
"Expected {} elements in inpdim, got {}.".format(pyk.smartlen(_inpdim), pyk.smartlen(parsey['inpdim']))
# Check consistency with the expected _inpdim
assert all([_indim == indim for _indim, indim in zip(pyk.obj2list(_inpdim), pyk.obj2list(parsey['inpdim']))
if _indim is not None]), \
"Provided inpdim is inconsistent with either dim or issequence."
# Parse dim
# Compute expected _inpdim from what's known
_dim = pyk.delist([
2 if (indim == 4 or isseq) else 3 for indim, isseq in zip(
pyk.obj2list(parsey['inpdim']), pyk.obj2list(parsey['issequence']))
])
# Check in from dim
if parsey['dim'] is None:
parsey['dim'] = _dim
else:
assert parsey[
'dim'] == _dim, "Given dim ({}) is not consistent with expectation ({})".format(
parsey['dim'], _dim)
# Reparse inpshape
if parsey['inpshape'] is None:
parsey['inpshape'] = pyk.delist([[
None,
] * indim for indim in pyk.obj2list(parsey['inpdim'])])
# Return parsey :(
return parsey
def __init__(self, connections, merge=True, dim=2, issequence=False, inpshape=None):
"""
:type connections: list
:param connections: List of connections. E.g.: [[0, 1], 1, [0, 1, 2]] would merge inputs 0 & 1 and write to
first output slot, 1 to second output slot and 0, 1 & 2 merged to the third output slot.
:param dim:
:param issequence:
:param inpshape:
:return:
"""
super(circuitlayer, self).__init__()
# Compute the number of i/o slots
self.numinp = len(pyk.unique(list(pyk.flatten(connections))))
self.numout = len(connections)
self.merge = bool(merge)
# Parse
dim = [dim, ] * self.numinp if isinstance(dim, int) and self.numinp is not None else dim
issequence = [issequence, ] * self.numinp if isinstance(issequence, bool) and self.numinp is not None \
else issequence
# Parse inpshape if numinp, dim, issequence is given
if self.numinp is not None and dim is not None and inpshape is None:
if 3 in dim:
# issequence doesn't matter, inpshape can still be filled
inpshape = [[None, ] * 5 for _ in dim]
else:
# dim is 2, but input might still be sequential
if issequence is None:
pass
else:
if issequence:
# issequence is false and dim = 2, ergo 2D data
inpshape = [[None, ] * 4 for _ in dim]
else:
# issequence is true, ergo 2D sequential data
inpshape = [[None, ] * 5 for _ in dim]
# Meta
self.connections = connections
self.dim = dim if dim is not None else [{4: 2, 5: 2}[len(ishp)] for ishp in inpshape]
self.allowsequences = True
self.issequence = [idim == 2 and len(ishp) == 5 for idim, ishp in zip(self.dim, inpshape)] \
if issequence is None else issequence
self.inpdim = [len(ishp) if ishp is not None else 5 if iisseq else {2: 4, 3: 5}[idim]
for ishp, iisseq, idim in zip(inpshape, self.issequence, self.dim)]
# Check if inpdim is consistent
assert all([indim == self.inpdim[0] for indim in self.inpdim]), "Can't concatenate 2D with 3D inputs."
# Make merge layers
self.mergelayers = [mergelayer(numinp=len(conn),
dim=[self.dim[node] for node in conn],
issequence=[self.issequence[node] for node in conn],
inpshape=[inpshape[node] for node in conn])
if pyk.smartlen(conn) != 1 else None for conn in self.connections]
# Shape inference
self.inpshape = list(inpshape) if inpshape is not None else [[None, ] * indim for indim in self.inpdim]
# Containers for input and output
self.x = pyk.delist([T.tensor('floatX', [False, ] * indim, name='x{}:'.format(inpnum) + str(id(self)))
for inpnum, indim in enumerate(self.inpdim)])
self.y = pyk.delist([T.tensor('floatX', [False, ] * self.inpdim[pyk.obj2list(self.connections[outnum])[0]],
name='y:' + str(id(self)))
for outnum in range(self.numout)])
