zhutian
40 lines
1023 B
Python
40 lines
1023 B
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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@onnx_op("Flatten")
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@tf_func(tf.layers.flatten)
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class Flatten(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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shape = tf.shape(x)
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x_rank = len(x.shape)
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axis = node.attrs.get("axis", 1)
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if axis == 1 and x_rank > 1:
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return [cls.make_tensor_from_onnx_node(node, **kwargs)]
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if axis == 0:
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cal_shape = (1, -1)
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else:
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cal_shape = (tf.reduce_prod(shape[0:axis]),
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tf.reduce_prod(shape[axis:tf.size(shape)]))
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return [tf.reshape(x, cal_shape)]
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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_9(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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