def run_backward(self, num_runs):
""" Run the backward path of an operator in a loop
"""
with core.DeviceScope(self.op_bench.dev):
op = self.op_bench.backward()
if not workspace.RunOperatorMultiple(op, num_runs):
raise ValueError("Unable to run operator gradient test case: {}".format(self.test_name))
def run_forward(self, num_runs, print_per_iter=False):
""" Run the forward path of an operator in a loop
"""
with core.DeviceScope(self.op_bench.dev):
op = self.op_bench.forward()
if not workspace.RunOperatorMultiple(op, num_runs):
raise ValueError("Unable to run operator test case: {}".format(self.test_name))
def test_sparse_to_dense_mask_invalid_inputs(self):
op = core.CreateOperator(
'SparseToDenseMask',
['indices', 'values', 'default', 'lengths'],
['output'],
mask=[999999999, 2],
max_skipped_indices=3)
workspace.FeedBlob(
'indices',
np.array([2000000000000, 999999999, 2, 3, 4, 5], dtype=np.int32))
workspace.FeedBlob(
'values',
np.array([1, 2, 3, 4, 5, 6], dtype=np.float))
workspace.FeedBlob('default', np.array(-1, dtype=np.float))
workspace.FeedBlob('lengths', np.array([6], dtype=np.int32))
try:
workspace.RunOperatorOnce(op)
except RuntimeError:
self.fail("Exception raised with only one negative index")
# 3 invalid inputs should throw.
workspace.FeedBlob(
'indices',
np.array([-1, 1, 2, 3, 4, 5], dtype=np.int32))
with self.assertRaises(RuntimeError):
workspace.RunOperatorMultiple(op, 3)
def run_forward(self, num_runs):
""" Run the forward path of an operator in a loop
"""
if not workspace.RunOperatorMultiple(self.op_bench.forward(),
num_runs):
raise ValueError("Unable to run operator test case: {}".format(
self.test_name))
def benchmark_func(num_runs):
if not workspace.RunOperatorMultiple(op, num_runs):
raise RuntimeError('Unable to run operator test case ' % test_name)
