Drop a dimension of a tensor in Tensorflow

python tensorflow slice tensor
lamhoangtung picture lamhoangtung · Sep 22, 2018 · Viewed 9.2k times · Source

I have a tensor that have shape (50, 100, 1, 512) and i want to reshape it or drop the third dimension so that the new tensor have shape (50, 100, 512).

I have tried tf.slice with tf.squeeze:

a = tf.slice(a, [50, 100, 1, 512], [50, 100, 1, 512])
b = tf.squeeze(a)

Everything seem working when i tried to print the shape of a and b but when i start training my model this error came

tensorflow.python.framework.errors_impl.InvalidArgumentError: Expected size[0] in [0, 0], but got 50
     [[Node: Slice = Slice[Index=DT_INT32, T=DT_FLOAT, _device="/job:localhost/replica:0/task:0/device:CPU:0"](MaxPool_2, Slice/begin, Slice/size)]]

Are there any problem with my slice. How can i fix it. Thanks

Answer

Jagadeesh Dondeti picture Jagadeesh Dondeti · Sep 22, 2018

Generally tf.squeeze will drop the dimensions. 

a = tf.constant([[[1,2,3],[3,4,5]]])

The above tensor shape is [1,2,3]. After performing squeeze operation,

b = tf.squeeze(a)

Now, Tensor shape is [2,3]

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