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out[i] = t.name in self.between_tensors AttributeError: 'TFDeepExplainer' object has no attribute 'between_tensors'.

Hi everybody! I'm using tensorflow 2.3 and I'm having an issue when i try to call a function that returns a keras.Model . AttributeError: 'Tensor' object has no attribute 'numpy' Tensorflow 2.3

11.02.2019 · AttributeError: 'TFDeep' object has no attribute 'between_tensors' I see what the _init_between_tensors is doing and I assume there is something unusual about the graph (I am attaching that as well). Any feedback will be highly appreciated!

28.10.2020 · It seems there are TF2.0 integration issues in SHAP. I am also running DeepExplainer for tensor flow model in TF>2.0 and getting errors. Need to degrade to TF1 or disable features that are causing the issues running Deep Explainer. ... AttributeError: 'TFDeep' object has no attribute 'between_tensors'

28.07.2021 · AttributeError: 'TFDeep' object has no attribute 'between_tensors' #2114. Open wenbostar opened this issue Jul 28, 2021 · 5 comments Open ... 'TFDeep' object has no attribute 'between_tensors' Does anyone know how to fix this? The text was updated successfully, ...

I'm trying to compute shap values using DeepExplainer, but I get the following error: keras is no longer supported, please use tf.keras instead.

I am trying to generate SHAP values for a model with two input ... AttributeError: 'TFDeep' object has no attribute 'between_tensors'.

16.09.2018 · tensor = tf.multiply (ndarray, 42) tensor.numpy () # throw AttributeError: 'Tensor' object has no attribute 'numpy'. I use anaconda 3 with tensorflow 1.14.0. I upgraded tensorflow with the command below. conda update tensorflow. now tensorflow is 2.0.0, issue fixed. Try this to see if it resolves your issue.

30.04.2020 · calling shap.DeepExplainer(model, x_train) results in LookupError: gradient registry has no entry for: shap_TensorListStack and err: 'TFDeepExplainer' object has no attribute 'between_tensors calling shap.DeepExplainer((model.layers[0].input, model.layers[-1].output), x_train) results in NameError: name 'Model' is not defined .

23.04.2021 · I want to run a code. It is written in Python3 using Tensorflow. I could run the code, but when the code was running, I tried to run another code with some changes in a separate Anaconda Prompt. Th...

04.04.2019 · I'm using TF 2.0, my function does not have a decorator, tf.eagerly() returns True and I still get the same AttributeError: 'Tensor' object has no attribute 'numpy'. 👍 65 Haakam21, sosoIrving, Shashank9830, deZakelijke, Ilyushin, tnfru, dandawg, desertnaut, begoechavarren, rohitfattepur, and 55 more reacted with thumbs up emoji

20.02.2020 · AttributeError: 'TFDeepExplainer' object has no attribute 'between_tensors' out[i] = t.name in self.between_tensors AttributeError: 'TFDeepExplainer' object has no attribute 'between_tensors' This is due to the fact that in deep_tf#L236 init_between_tensors is called, but it is expected to be there in deep_tf#L232.

TF2 runs Eager Execution by default, thus removing the need for Sessions. If you want to run static graphs, the more proper way is to use tf.function() in TF2. While Session can still be accessed via tf.compat.v1.Session() in TF2, I would discourage using it. It may be helpful to demonstrate this difference by comparing the difference in hello worlds: