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def get_updates(model,  loss):
  updates = [] 
  grad = SomeLibrary.grad(model.params, loss)
  for param, g in zip(model.params, grad):
    updates.append((params, param + model.lr * g)) 
  return updates

def murderbot():
  model = make_model() 
  while True:

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'''
super ugly. but works. 
'''
import subprocess
import time

while True:
    ps = subprocess.Popen(['qstat'], stdout=subprocess.PIPE).communicate()[0]
    jid = int(ps.split("\n")[2].split(" ")[0])

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class Lambda(Layer):
    '''Used for evaluating an arbitrary Theano / TensorFlow expression
    on the output of the previous layer.

    # Examples

    ```python
        # add a x -> x^2 layer
        model.add(Lambda(lambda x: x ** 2))
    ```

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'''
use as:
some_data = DataLayer(K.variable(some_tensor,dtype=whatever), ...)
next_layer = Dense(some_number)
out_tensor = next_layer(some_data.tensor)
'''
class DataLayer(Layer):
    '''TODO: dosctring
    '''
    def __init__(self, input_tensor, input_dtype=None, name=None):