zhutian
45 lines
1.3 KiB
Python
45 lines
1.3 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.handlers.handler import partial_support
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from onnx_tf.handlers.handler import ps_description
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@onnx_op("Cast")
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@tf_func(tf.cast)
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@partial_support(True)
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@ps_description("Cast string to float32/float64/int32/int64 " +
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"are not supported in Tensorflow.")
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class Cast(BackendHandler):
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@classmethod
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def get_attrs_processor_param(cls):
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return {"rename": {"to": "dtype"}}
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@classmethod
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def version_1(cls, node, **kwargs):
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return [cls.make_tensor_from_onnx_node(node, **kwargs)]
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@classmethod
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def version_6(cls, node, **kwargs):
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return [cls.make_tensor_from_onnx_node(node, **kwargs)]
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@classmethod
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def version_9(cls, node, **kwargs):
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inp = kwargs["tensor_dict"][node.inputs[0]]
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to_type = node.attrs.get("to")
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if to_type == tf.string:
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return [tf.as_string(inp)]
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if inp.dtype == tf.string:
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if to_type not in [tf.float32, tf.float64, tf.int32, tf.int64]:
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raise RuntimeError(
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"Cast string to type {} is not supported in Tensorflow.".format(
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to_type))
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return [tf.strings.to_number(inp, to_type)]
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return [cls.make_tensor_from_onnx_node(node, **kwargs)]
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