def test_give_variables_names_small():
x = theano.tensor.matrix('x')
y = theano.tensor.dot(x, x)
fgraph = theano.FunctionGraph((x, ), (y, ))
give_variables_names(fgraph.variables)
assert all(var.name for var in fgraph.variables)
assert unique([var.name for var in fgraph.variables])
def test_give_variables_names_small():
x = theano.tensor.matrix('x')
y = theano.tensor.dot(x, x)
fgraph = theano.FunctionGraph((x,), (y,))
give_variables_names(fgraph.variables)
assert all(var.name for var in fgraph.variables)
assert unique([var.name for var in fgraph.variables])
def theano_graph_to_tuple_dag(i, o):
""" Converts a theano.FunctionGraph into a tuple-dag
This dag is of the form
{(outputs): {'fn': fn, 'args': inputs}, ...}
All keys are tuples
This format is used when some functions create multiple outputs.
It can be converted or simplified with functions in the root dag library.
"""
i, o = theano.gof.graph.clone(i, o)
variables = theano.gof.graph.variables(i, o)
apply_nodes = theano.gof.graph.list_of_nodes(i, o)
give_variables_names(variables)
newvars = {var: clone(var) for var in variables}
# Produces dag with inputs and outputs as tuples
dag = {tuple(map(newvars.__getitem__, node.outputs)):
{'fn' : node.op,
'args': tuple(map(newvars.__getitem__, node.inputs))}
for node in apply_nodes}
inputs = tuple(map(newvars.__getitem__, i))
outputs = tuple(map(newvars.__getitem__, o))
return dag, inputs, outputs
def test_give_variables_names():
x = theano.tensor.matrix('x')
y = x + 1
z = theano.tensor.dot(x, y)
variables = (x, y, z)
give_variables_names(variables)
assert all(var.name for var in variables)
assert unique([var.name for var in variables])
def test_give_variables_names():
x = theano.tensor.matrix('x')
y = x + 1
z = theano.tensor.dot(x, y)
variables = (x, y, z)
give_variables_names(variables)
assert all(var.name for var in variables)
assert unique([var.name for var in variables])
def test_give_variables_names_idempotence():
x = theano.tensor.matrix('x')
y = x + 1
z = theano.tensor.dot(x, y)
variables = (x, y, z)
give_variables_names(variables)
names = [var.name for var in variables]
give_variables_names(variables)
names2 = [var.name for var in variables]
assert names == names2
def test_give_variables_names_idempotence():
x = theano.tensor.matrix('x')
y = x + 1
z = theano.tensor.dot(x, y)
variables = (x, y, z)
give_variables_names(variables)
names = [var.name for var in variables]
give_variables_names(variables)
names2 = [var.name for var in variables]
assert names == names2
