zhutian
46 lines
1.4 KiB
Python
46 lines
1.4 KiB
Python
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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from onnx_tf.common.tf_helper import tf_shape
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@onnx_op("ArgMax")
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@tf_func(tf.argmax)
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class ArgMax(BackendHandler):
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@classmethod
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def get_attrs_processor_param(cls):
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return {"default": {"axis": 0}}
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@classmethod
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def _common(cls, node, **kwargs):
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axis = node.attrs.get("axis", 0)
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keepdims = node.attrs.get("keepdims", 1)
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select_last_index = node.attrs.get("select_last_index", 0)
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if select_last_index == 0:
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arg_max = cls.make_tensor_from_onnx_node(node, **kwargs)
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else:
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# reverse the input and apply argmax on that to get last occurrence of max
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x = kwargs["tensor_dict"][node.inputs[0]]
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x = tf.reverse(x, axis=[axis])
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arg_max = cls.make_tensor_from_onnx_node(node, inputs=[x], **kwargs)
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# adjust indices to account for the reverse
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arg_max = tf_shape(x)[axis] - arg_max - 1
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if keepdims == 1:
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return [tf.expand_dims(arg_max, axis=axis)]
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return [arg_max]
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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_11(cls, node, **kwargs):
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return cls._common(node, **kwargs)
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@classmethod
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def version_12(cls, node, **kwargs):
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return cls._common(node, **kwargs)
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