zhutian
38 lines
980 B
Python
38 lines
980 B
Python
import copy
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import tensorflow as tf
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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 tf_func
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@onnx_op("Dropout")
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@tf_func(tf.nn.dropout)
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class Dropout(BackendHandler):
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@classmethod
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def _common(cls, node, **kwargs):
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x = kwargs["tensor_dict"][node.inputs[0]]
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attrs = copy.deepcopy(node.attrs)
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if cls.SINCE_VERSION >= 7 or attrs.pop("is_test", 0) == 1:
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return [x]
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attrs["keep_prob"] = 1 - attrs.pop("ratio", 0.5)
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return [cls.make_tensor_from_onnx_node(node, attrs=attrs, **kwargs)]
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@classmethod
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def version_1(cls, node, **kwargs):
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return cls._common(node, **kwargs)
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@classmethod
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def version_6(cls, node, **kwargs):
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return cls._common(node, **kwargs)
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@classmethod
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def version_7(cls, node, **kwargs):
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return cls._common(node, **kwargs)
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@classmethod
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def version_10(cls, node, **kwargs):
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return cls._common(node, **kwargs)
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