ValueError: Failed to convert a NumPy array to a Tensor - keras

Question

I used `
x_train = np.array([np.array(val) for val in x_train])
y_train = np.array([np.array(val) for val in y_train])
`
but I failed to convert numpy to tensor
My code is `
x_train = np.array([np.array(val) for val in x_train])
y_train = np.array([np.array(val) for val in y_train])
model.fit(x_train,y_train,epochs =5,batch_size = 128,validation_split = 0.2,shuffle =True)
test_loss,test_acc = model.evaluate(x_test,y_test)
print('Test loss',test_loss)
print('Accuracy',test_acc)
`
Error:
ValueError Traceback (most recent call last)
<ipython-input-39-43fd775bb14b> in <module>
1 x_train = np.array([np.array(val) for val in x_train])
2 y_train = np.array([np.array(val) for val in y_train])
----> 3 model.fit(x_train,y_train,epochs =5,batch_size = 128,validation_split = 0.2,shuffle =True)
4 test_loss,test_acc = model.evaluate(x_test,y_test)
5 print('Test loss',test_loss)
1 frames
/usr/local/lib/python3.7/dist-packages/tensorflow/python/framework/constant_op.py in convert_to_eager_tensor(value, ctx, dtype)
100 dtype = dtypes.as_dtype(dtype).as_datatype_enum
101 ctx.ensure_initialized()
--> 102 return ops.EagerTensor(value, ctx.device_name, dtype)
103
104
ValueError: Failed to convert a NumPy array to a Tensor (Unsupported object type numpy.ndarray).
My model:
`
model = tf.keras.Sequential([
tf.keras.layers.Embedding(words,embed_size,input_shape =(x_train.shape[0],)),
tf.keras.layers.Conv1D(128,3,activation = 'relu'),
tf.keras.layers.MaxPooling1D(),
tf.keras.layers.LSTM(128,activation = 'tanh'),
tf.keras.layers.Dense(10,activation='relu',input_dim=300),
tf.keras.layers.Dense(1,activation='sigmoid',input_dim=300) ])
model.summary()
`

Answer 1

The error you are getting is because of the data type of an array, as Tensorflow models do not support Object data type, So, try to cast these tensors. I am casting it to float32.
x_train = np.array([np.array(val) for val in x_train])
y_train = np.array([np.array(val) for val in y_train])
x_train = tf.cast(x_train , dtype=tf.float32)
y_train = tf.cast(y_train , dtype=tf.float32)