#!/usr/bin/env python
# -*- coding: utf-8 -*-
import theano.tensor as T
import inspect
def wrap_core(func, train_config, *args):
spec = inspect.getargspec(func)
params = spec.args[-len(spec.defaults):]
default_values = spec.defaults
kwargs = dict(zip(params, default_values))
if train_config:
for param, default in zip(params, default_values):
config_val = train_config.get(param, default)
kwargs[param] = config_val
return list(func(*args, **kwargs))
def multiple_l2_norm(tensors):
"""
Get the L2 norm of multiple tensors.
This function is taken from blocks.
"""
# Another way for doing this, I don't know which one is fast
# return T.sqrt(sum(T.sum(t ** 2) for t in tensors))
flattened = [T.as_tensor_variable(t).flatten() for t in tensors]
flattened = [(t if t.ndim > 0 else t.dimshuffle('x'))
for t in flattened]
joined = T.join(0, *flattened)
return T.sqrt(T.sqr(joined).sum())
