ValueError: Dimensions must be equal, but are 75 and 8 for

[paktiger]

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04): Windows 10
• TensorFlow version and how it was installed (source or binary): Version: 2.7.0
• TensorFlow-Addons version and how it was installed (source or binary): 0.15.0
• Python version: 3.8
• Is GPU used? (yes/no): no

Describe the bug I am using a text dataset on BiLSTM-CRF and I am using Keras for BiLSTM and TensorFlow-addons for CRF layer but When I train the BiLSTM-CRF model it generates the following error: ValueError: Dimensions must be equal, but are 75 and 8 for '{{node mean_absolute_error/sub}} = Sub[T=DT_INT32](model_1/crf_1/ReverseSequence_1, mean_absolute_error/Cast)' with input shapes: [?,75], [?,75,8].

A clear and concise description of what the bug is. model.compile('rmsprop', loss='mean_absolute_error', metrics=['accuracy']) history = model.fit(X_tr, np.array(y_tr), batch_size=22, epochs=20, validation_split=0.1, verbose=1) The following is the model summary

`Model: "model_1"

---

Layer (type) Output Shape Param #

input_2 (InputLayer) [(None, 75)] 0

embedding_1 (Embedding) (None, 75, 20) 259240

bidirectional_1 (Bidirectio (None, 75, 150) 57600
nal)

time_distributed_1 (TimeDis (None, 75, 75) 11325
tributed)

crf_1 (CRF) [(None, 75), 688
(None, 75, 8),
(None,),
(8, 8)]

================================================================= Total params: 328,853 Trainable params: 328,853 Non-trainable params: 0 _________________________________________________________________` Code to reproduce the issue

Provide a reproducible test case that is the bare minimum necessary to generate the problem.

Other info / logs

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