def batch(actionLists):
'''Internal batcher for lists of actions'''
atnTensor, idxTensor = [], []
keyTensor, lenTensor = [], []
#Pack inner set
for actionList in actionLists:
keys, atns, idxs = [], [], []
for key, atn, idx in actionList:
atns.append(np.array(atn))
idxs.append(idx)
keys.append(key)
idxs = np.array(idxs)
keys = np.array(keys)
atns, lens = utils.pack(atns)
atnTensor.append(atns)
idxTensor.append(idxs)
keyTensor.append(keys)
lenTensor.append(lens)
#Pack outer set
idxTensor, _ = utils.pack(idxTensor)
atnTensor, _ = utils.pack(atnTensor)
keyTensor, _ = utils.pack(keyTensor)
lenTensor = utils.pack(lenTensor)
return atnTensor, idxTensor, keyTensor, lenTensor
def batchInputs(actionLists):
atnTensor = []
atnTensorLens = []
atnLens = []
atnLenLens = []
for actions in actionLists:
tensor = []
for atn, atnArgList in actions.items():
dat = []
for atnArg in atnArgList:
atn, arg = atnArg.action, atnArg.args
atnArg = np.array([atn, arg])
dat.append(atnArg)
tensor.append(np.array(dat))
tensor, lens = utils.pack(tensor)
atnTensor.append(tensor)
atnLens.append(lens)
atnTensor, atnTensorLens = utils.pack(atnTensor)
atnLens, atnLenLens = utils.pack(atnLens)
return atnTensor, atnTensorLens, atnLens, atnLenLens
def batch(stims):
'''Internal batcher for lists of stimuli'''
batch = {}
#Process into set of sets
for stim in stims:
#Outer set
for stat, stimSet in stim.items():
if stat not in batch:
batch[stat] = [[], defaultdict(list)]
#Inner set
keys, vals = stimSet
batch[stat][0].append(keys)
for attr, val in vals.items():
val = np.array(val).reshape(-1)
batch[stat][1][attr].append(val)
#Pack values
for group, stat in batch.items():
keys, stat = stat
for attr, vals in stat.items():
vals, _ = utils.pack(vals)
batch[group][1][attr] = vals
return batch