zhutian
30 lines
781 B
Python
30 lines
781 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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@onnx_op("QuantizeLinear")
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class QuantizeLinear(BackendHandler):
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@classmethod
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def version_10(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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y_scale = tensor_dict[node.inputs[1]]
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x = tf.cast(x, tf.float32)
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y = tf.divide(x, y_scale)
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y = tf.round(y)
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if len(node.inputs) == 3:
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y_zero_point = tensor_dict[node.inputs[2]]
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y_dtype = y_zero_point.dtype
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y_zero_point = tf.cast(y_zero_point, tf.float32)
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y = tf.add(y, y_zero_point)
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else: # y_zero_point default dtype = uint8
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y_dtype = tf.uint8
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y = tf.saturate_cast(y, y_dtype)
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return [y]
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