If I reshape one_hot to **(depth)**, the **one_hot_matrix_test()** is happy, but

**new_y_test = y_test.map(one_hot_matrix)**

is not, producing a long stack of grief followed by **ValueError: Shape must be rank 1 but is rank 0 for ‘{{node Reshape}} = Reshape[T=DT_FLOAT, Tshape=DT_INT32](one_hot, Reshape/shape)’ with input shapes: [6], [].**

If I reshape to **(depth,1)**, now **new_y_test = y_test.map(one_hot_matrix)** is happy but **one_hot_matrix_test()** is not, because it expects

**tf.Tensor([0. 1. 0. 0.], shape=(4,), dtype=float32)**, (ie a one-dimensional vector vs. a single column matrix).

So I can either get 60% or 80% depending on which version I submit. Is the expected result of **one_hot_matrix_test()** just wrong?