def test_model_function_mode(): pars = ParameterSet() weights = pars.declare((2, 3)) pars.alloc() inpt = T.matrix() output = T.dot(inpt, weights) pars.data[...] = np.random.standard_normal(pars.data.shape) model = Model() model.exprs = {'inpt': inpt, 'output': output} model.parameters = pars mode = theano.Mode() f = model.function(['inpt'], 'output', mode=mode) actual_mode = f.theano_func.maker.mode assert actual_mode is mode, 'wrong mode: %s' % actual_mode model.mode = theano.Mode() f = model.function(['inpt'], 'output') actual_mode = f.theano_func.maker.mode # Maybe a weird way to compare modes, but it seems to get the job done. equal = actual_mode.__dict__ == mode.__dict__ assert equal, 'wrong mode: (%s != %s)' % (actual_mode, mode)
def test_model_function_mode(): pars = ParameterSet(weights=(2, 3)) inpt = T.matrix() output = T.dot(inpt, pars.weights) pars.data[...] = np.random.standard_normal(pars.data.shape) model = Model() model.exprs = {"inpt": inpt, "output": output} model.parameters = pars mode = theano.Mode() f = model.function(["inpt"], "output", mode=mode) actual_mode = f.theano_func.maker.mode assert actual_mode is mode, "wrong mode: %s" % actual_mode model.mode = theano.Mode() f = model.function(["inpt"], "output") actual_mode = f.theano_func.maker.mode # Maybe a weird way to compare modes, but it seems to get the job done. equal = actual_mode.__dict__ == mode.__dict__ assert equal, "wrong mode: (%s != %s)" % (actual_mode, mode)