def _UnbatchGrad(op, grad): # pylint: disable=invalid-name
return [
gen_batch_ops.unbatch_grad(op.inputs[0],
op.inputs[1],
grad,
op.inputs[2],
shared_name="unbatch_gradient_{}".format(
op.name)), None, None
]
def _UnbatchGrad(op, grad): # pylint: disable=invalid-name
return [
gen_batch_ops.unbatch_grad(
op.inputs[0],
op.inputs[1],
grad,
op.inputs[2],
shared_name="unbatch_gradient_{}".format(op.name)), None, None
]
def testUnbatchGradInvalidBatchId(self):
with self.assertRaises(errors.InvalidArgumentError):
self.evaluate(
gen_batch_ops.unbatch_grad(
original_input=constant_op.constant([1]),
batch_index=constant_op.constant([
[0, 0],
],
dtype=dtypes.int64),
grad=constant_op.constant([
1,
]),
id=constant_op.constant([
1,
], dtype=dtypes.int64)))
def testUnbatchGradInvalidArgs(self):
original_input = random_ops.random_uniform(shape=(3, 1),
dtype=dtypes.float64,
maxval=None)
batch_index = random_ops.random_uniform(shape=(3, 1),
dtype=dtypes.int64,
maxval=65536)
grad = random_ops.random_uniform(shape=(3, 1),
dtype=dtypes.float64,
maxval=None)
batch_id = random_ops.random_uniform(shape=(3, 1),
dtype=dtypes.int64,
maxval=65536)
with self.assertRaises(errors.InvalidArgumentError):
self.evaluate(
gen_batch_ops.unbatch_grad(original_input=original_input,
batch_index=batch_index,
grad=grad,
id=batch_id,
container="",
shared_name="",
name=""))
