zxros10
47 lines
1.4 KiB
Python
47 lines
1.4 KiB
Python
import tensorflow as tf
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from onnx_tf.common import exception
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from onnx_tf.handlers.backend_handler import BackendHandler
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from onnx_tf.handlers.handler import onnx_op
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from onnx_tf.handlers.handler import partial_support
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from onnx_tf.handlers.handler import ps_description
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from onnx_tf.handlers.handler import tf_func
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@onnx_op("CumSum")
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@tf_func(tf.math.cumsum)
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@partial_support(True)
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@ps_description(
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"CumSum inputs in uint32/uint64 " + "are not supported in Tensorflow."
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)
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class CumSum(BackendHandler):
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@classmethod
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def args_check(cls, node, **kwargs):
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supported_dtype = [
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tf.bfloat16, tf.half, tf.float32, tf.float64, tf.uint8, tf.uint16,
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tf.int8, tf.int16, tf.int32, tf.int64, tf.complex64, tf.complex128
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]
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x = kwargs["tensor_dict"][node.inputs[0]]
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if x.dtype not in supported_dtype:
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exception.OP_UNSUPPORTED_EXCEPT(
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"CumSum input in " + str(x.dtype) + " which", "Tensorflow")
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@classmethod
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def version_11(cls, node, **kwargs):
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tensor_dict = kwargs["tensor_dict"]
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x = tensor_dict[node.inputs[0]]
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inputs = [x]
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if len(node.inputs) > 1:
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# optional 0-D tensor, range [-rank(x), rank(x)-1]
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axis = tensor_dict[node.inputs[1]]
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inputs.append(axis)
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attrs = {
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"exclusive": bool(node.attrs.get("exclusive", 0)),
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"reverse": bool(node.attrs.get("reverse", 0))
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}
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return [cls.make_tensor_from_onnx_node(node, inputs=inputs, attrs=attrs)]
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