zhutian
49 lines
1.2 KiB
Python
49 lines
1.2 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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@onnx_op("Gemm")
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class Gemm(BackendHandler):
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@classmethod
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def _common(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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x = tf.layers.flatten(x)
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y = tensor_dict[node.inputs[1]]
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if len(node.inputs) > 2:
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z = tensor_dict[node.inputs[2]]
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else:
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z = 0
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if node.attrs.get("transA", 0):
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x = tf.transpose(x)
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if node.attrs.get("transB", 0):
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y = tf.transpose(y)
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alpha = node.attrs.get("alpha", 1.0)
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beta = node.attrs.get("beta", 1.0)
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return [alpha * tf.matmul(x, y) + beta * z]
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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_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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