def __init__(
self,
blob_name: str,
color_space: str,
num_attempts: int,
random_seed: Optional[int],
random_area: Sequence[float],
random_aspect_ratio: Sequence[float],
name: str,
):
module_util.Module.__init__(self, name)
seed, has_seed = flow.random.gen_seed(random_seed)
self.op_module_builder = (
flow.user_op_module_builder("ofrecord_image_decoder_random_crop")
.InputSize("in", 1)
.Output("out")
.Attr("name", blob_name)
.Attr("color_space", color_space)
.Attr("num_attempts", num_attempts)
.Attr("random_area", random_area)
.Attr("random_aspect_ratio", random_aspect_ratio)
.Attr("has_seed", has_seed)
.Attr("seed", seed)
.CheckAndComplete()
)
self.op_module_builder.user_op_module.InitOpKernel()
def __init__(
self,
dtype: dtype_util.dtype,
random_seed: Optional[int],
name: str,
):
module_util.Module.__init__(self, name)
seed, has_seed = flow.random.gen_seed(random_seed)
self.op_module_builder = (
flow.user_op_module_builder("bernoulli").InputSize(
"in", 1).Output("out").Attr("dtype", dtype).Attr(
"has_seed", has_seed).Attr("seed",
seed).CheckAndComplete())
self.op_module_builder.user_op_module.InitOpKernel()
def __init__(
self,
batch_size: str,
probability: float,
random_seed: Optional[int],
name: str,
):
module_util.Module.__init__(self, name)
seed, has_seed = flow.random.gen_seed(random_seed)
self.op_module_builder = (
flow.user_op_module_builder("coin_flip").Output("out").Attr(
"batch_size",
batch_size).Attr("probability", probability).Attr(
"has_seed", has_seed).Attr("seed",
seed).CheckAndComplete())
self.op_module_builder.user_op_module.InitOpKernel()