blocks|key|4730926|text|result["outputs"].float_val应该是一个python列表|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4730927|entityMap^0|0|R|0^^$0|@$1|2|3|4|5|6|7|H|8|@$9|I|A|J|B|C]]|D|@]|E|$]]|$1|F|3|-4|5|6|7|K|8|@]|D|@]|E|$]]]|G|$]]

<code>result["outputs"].float_val</code> should be a python list

blocks|key|3740982|text|答案是：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3740983|floats+=+result.outputs['outputs'].float_val|code-block|syntax|javascript|3740984|entityMap^0|0|0^^$0|@$1|2|3|4|5|6|7|I|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|J|8|@]|9|@]|A|$E|F]]|$1|G|3|-4|5|6|7|K|8|@]|9|@]|A|$]]]|H|$]]

The answer is:

<pre><code>floats = result.outputs['outputs'].float_val
</code></pre>

blocks|key|4730951|text|如果要将整个PredictResponse转换为numpy数组(包括其维度)|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4730952|​|4730953|<script+src="https://gist.github.com/eavidan/22ad044f909e5739ceca9ff9e6feaa43.js"></script>|code-block|syntax|javascript|4730954|4730955|entityMap^0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@]|9|@]|A|$]]|$1|D|3|E|5|F|7|N|8|@]|9|@]|A|$G|H]]|$1|I|3|C|5|6|7|O|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|P|8|@]|9|@]|A|$]]]|K|$]]

If you would like to convert the entire PredictResponse to a numpy array (including its dimentions)

<div class="snippet" data-lang="js" data-hide="false" data-console="true" data-babel="false">
<div class="snippet-code">
<pre class="snippet-code-html lang-html prettyprint-override"><code>&lt;script src="https://gist.github.com/eavidan/22ad044f909e5739ceca9ff9e6feaa43.js"&gt;&lt;/script&gt;</code></pre>
</div>
</div>

blocks|key|3741023|text|这个答案适用于tensorflow服务-api-python3+3+1.8.0|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3741024|result.outputs['your+key+name'].float_val+#key+name+in+your+case+is+outputs|offset|length|style|CODE|3741025|这将返回一个重复的标量容器对象。可以传递给python+()或np.array()等|3741026|entityMap^0|0|0|23|0|0^^$0|@$1|2|3|4|5|6|7|L|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|M|8|@$D|N|E|O|F|G]]|9|@]|A|$]]|$1|H|3|I|5|6|7|P|8|@]|9|@]|A|$]]|$1|J|3|-4|5|6|7|Q|8|@]|9|@]|A|$]]]|K|$]]

This answer is for tensorflow-serving-api-python3 1.8.0

<code>result.outputs['your key name'].float_val #key name in your case is outputs</code>

This will return a repeated scalar container object. Which can be passed to python list() or np.array() etc

blocks|key|4730980|text|您通常希望恢复一个张量，具有一个形状(而不仅仅是一个长的浮子列表)。下面是操作步骤：|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4730981|outputs_tensor_proto+=+result.outputs["outputs"]
shape+=+tf.TensorShape(outputs_tensor_proto.tensor_shape)
outputs+=+tf.constant(outputs_tensor_proto.float_val,+shape=shape)|code-block|syntax|javascript|4730982|如果您希望得到一个NumPy数组，那么只需替换最后一行：|4730983|outputs+=+np.array(outputs_tensor_proto.float_val).reshape(shape.as_list())|4730984|如果您根本不想依赖TensorFlow库，出于某种原因：|4730985|outputs_tensor_proto+=+result.outputs["outputs"]
shape+=+[dim.size+for+dim+in+outputs_tensor_proto.tensor_shape.dim]
outputs+=+np.array(outputs_tensor_proto.float_val).reshape(shape)|4730986|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|R|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|S|8|@]|9|@]|A|$]]|$1|I|3|J|5|D|7|T|8|@]|9|@]|A|$E|F]]|$1|K|3|L|5|6|7|U|8|@]|9|@]|A|$]]|$1|M|3|N|5|D|7|V|8|@]|9|@]|A|$E|F]]|$1|O|3|-4|5|6|7|W|8|@]|9|@]|A|$]]]|P|$]]

You generally want to recover a tensor, with a shape (not just a long list of floats). Here's how:

<pre class="lang-py prettyprint-override"><code>outputs_tensor_proto = result.outputs["outputs"]
shape = tf.TensorShape(outputs_tensor_proto.tensor_shape)
outputs = tf.constant(outputs_tensor_proto.float_val, shape=shape)
</code></pre>

If you prefer to get a NumPy array, then just replace the last line:

<pre class="lang-py prettyprint-override"><code>outputs = np.array(outputs_tensor_proto.float_val).reshape(shape.as_list())
</code></pre>

If you don't want to depend on the TensorFlow library at all, for some reason:

<pre class="lang-py prettyprint-override"><code>outputs_tensor_proto = result.outputs["outputs"]
shape = [dim.size for dim in outputs_tensor_proto.tensor_shape.dim]
outputs = np.array(outputs_tensor_proto.float_val).reshape(shape)
</code></pre>

I am running a prediction on a tensorflow-serving model, and I get back this <code>PredictResponse</code> object as output:

Result: 

<pre><code>outputs {
 key: "outputs"
 value {
 dtype: DT_FLOAT
 tensor_shape {
 dim {
 size: 1
 }
 dim {
 size: 20
 }
 }
 float_val: 0.000343723397236
 float_val: 0.999655127525
 float_val: 3.96821117632e-11
 float_val: 1.20521548297e-09
 float_val: 2.09611101809e-08
 float_val: 1.46216549979e-09
 float_val: 3.87274603497e-08
 float_val: 1.83520256769e-08
 float_val: 1.47733780764e-08
 float_val: 8.00914179422e-08
 float_val: 2.29388191997e-07
 float_val: 6.27798826258e-08
 float_val: 1.08802950649e-07
 float_val: 4.39628813353e-08
 float_val: 7.87182985462e-10
 float_val: 1.31638898893e-07
 float_val: 1.42612295306e-08
 float_val: 3.0768305237e-07
 float_val: 1.12661648899e-08
 float_val: 1.68554503688e-08
 }
}
</code></pre>

I would like to get the out the float vals as a list. Or, alternatively, return the value/index of the argmax float_val! 

This is generated by:

<blockquote>
 stub = prediction_service_pb2.beta_create_PredictionService_stub(channel)
 result = stub.Predict(request, 200.0)
</blockquote>

Thanks for your help in advance.

How to retrieve float_val from a PredictResponse object?

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

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我正在tensorflow服务模型上运行一个预测，并将这个PredictResponse对象作为输出返回：结果：outputs {  key: "outputs"  value {    dtype: DT_FLOAT    tensor_shape {      dim {        size: 1      }...

问如何从float_val对象中检索PredictResponse？
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问如何从float_val对象中检索PredictResponse？EN