def test_argmax_pushdown_bias():
x = tensor.dmatrix()
b = tensor.dvector()
out = tensor.argmax(softmax_with_bias(x, b), axis=-1)
env = gof.Env(
[x,b],
[out])
theano.compile.mode.optdb.query(
theano.compile.mode.OPT_FAST_RUN).optimize(env)
#print 'AFTER'
#for node in env.toposort():
# print node.op
assert len(env.toposort()) == 4
assert isinstance(env.toposort()[0].op, tensor.DimShuffle)
assert isinstance(env.toposort()[1].op, tensor.Elemwise)
assert isinstance(env.toposort()[2].op, tensor.MaxAndArgmax)
assert str(env.toposort()[3].op) == 'OutputGuard'
x = tensor.dmatrix()
b = tensor.dvector()
out = tensor.max_and_argmax(softmax_with_bias(x, b), axis=-1)[0]
env = gof.Env(
[x,b],
[out])
backup = config.warn.argmax_pushdown_bug
config.warn.argmax_pushdown_bug = False
try:
theano.compile.mode.optdb.query(
theano.compile.mode.OPT_FAST_RUN).optimize(env)
finally:
config.warn.argmax_pushdown_bug = backup
#print 'AFTER'
#for node in env.toposort():
# print node.op
assert len(env.toposort()) == 3
assert isinstance(env.toposort()[0].op, SoftmaxWithBias)
assert isinstance(env.toposort()[1].op, tensor.CAReduce)
assert isinstance(env.toposort()[1].op.scalar_op, theano.scalar.Maximum)
assert str(env.toposort()[2].op) == 'OutputGuard'
def test_argmax_pushdown_bias():
x = tensor.dmatrix()
b = tensor.dvector()
out = tensor.argmax(softmax_with_bias(x, b), axis=-1)
env = gof.Env([x, b], [out])
theano.compile.mode.optdb.query(
theano.compile.mode.OPT_FAST_RUN).optimize(env)
#print 'AFTER'
#for node in env.toposort():
# print node.op
assert len(env.toposort()) == 4
assert isinstance(env.toposort()[0].op, tensor.DimShuffle)
assert isinstance(env.toposort()[1].op, tensor.Elemwise)
assert isinstance(env.toposort()[2].op, tensor.MaxAndArgmax)
assert str(env.toposort()[3].op) == 'OutputGuard'
x = tensor.dmatrix()
b = tensor.dvector()
out = tensor.max_and_argmax(softmax_with_bias(x, b), axis=-1)[0]
env = gof.Env([x, b], [out])
backup = config.warn.argmax_pushdown_bug
config.warn.argmax_pushdown_bug = False
try:
theano.compile.mode.optdb.query(
theano.compile.mode.OPT_FAST_RUN).optimize(env)
finally:
config.warn.argmax_pushdown_bug = backup
#print 'AFTER'
#for node in env.toposort():
# print node.op
assert len(env.toposort()) == 3
assert isinstance(env.toposort()[0].op, SoftmaxWithBias)
assert isinstance(env.toposort()[1].op, tensor.CAReduce)
assert isinstance(env.toposort()[1].op.scalar_op, theano.scalar.Maximum)
assert str(env.toposort()[2].op) == 'OutputGuard'
def f(a, b):
return softmax_with_bias(a, b)[:, 1]
def test_infer_shape(self):
fff = theano.function([],
outputs=softmax_with_bias(
numpy.random.rand(3, 4),
numpy.random.rand(4)).shape)
assert all(fff() == [3, 4])
def f(a, b):
return softmax_with_bias(a, b)[:,3]
def test_infer_shape(self):
fff=theano.function([],outputs=softmax_with_bias(numpy.random.rand(3,4),numpy.random.rand(4)).shape)
assert all(fff()==[3,4])