zhutian
37 lines
1.0 KiB
Python
37 lines
1.0 KiB
Python
import copy
|
|
import tensorflow as tf
|
|
|
|
from onnx_tf.handlers.backend_handler import BackendHandler
|
|
from onnx_tf.handlers.handler import onnx_op
|
|
from onnx_tf.handlers.handler import tf_func
|
|
|
|
|
|
@onnx_op("Compress")
|
|
@tf_func(tf.gather)
|
|
class Compress(BackendHandler):
|
|
|
|
@classmethod
|
|
def _common(cls, node, **kwargs):
|
|
attrs = copy.deepcopy(node.attrs)
|
|
tensor_dict = kwargs["tensor_dict"]
|
|
x = tensor_dict[node.inputs[0]]
|
|
condition = tensor_dict[node.inputs[1]]
|
|
|
|
x = tf.reshape(x, [-1]) if node.attrs.get("axis") is None else x
|
|
|
|
indices = tf.constant(list(range(condition.shape[0])), dtype=tf.int64)
|
|
not_zero = tf.not_equal(condition, tf.zeros_like(condition))
|
|
attrs['indices'] = tf.boolean_mask(indices, not_zero)
|
|
|
|
return [
|
|
cls.make_tensor_from_onnx_node(node, inputs=[x], attrs=attrs, **kwargs)
|
|
]
|
|
|
|
@classmethod
|
|
def version_9(cls, node, **kwargs):
|
|
return cls._common(node, **kwargs)
|
|
|
|
@classmethod
|
|
def version_11(cls, node, **kwargs):
|
|
return cls._common(node, **kwargs)
|