[GitHub] [incubator-mxnet] ZheyuYe commented on issue #17327: np.ndarray indexing after hybridize

[GitBox <gi...@apache.org>]

ZheyuYe commented on issue #17327: np.ndarray indexing after hybridize
URL: https://github.com/apache/incubator-mxnet/issues/17327#issuecomment-575180346
 
 
   @sxjscience 
   
   ```
   import numpy as np
   import mxnet as mx
   import numpy.testing as npt
   
   sequence = mx.nd.array(np.random.normal(0, 1, (8, 32, 768)), dtype=np.float32)
   # pick_ids: [batch_size, picked_index]
   pick_ids = mx.nd.random.randint(0, 31, (8,2), dtype=np.int32)
   
   # original approach with nd.ndarray
   idx_arange = mx.nd.contrib.arange_like(pick_ids.reshape((-1, )), axis=0)
   batch_idx = mx.nd.broadcast_div(idx_arange, mx.nd.array([2],dtype=np.int32))
   # batch_idx_1d = [0,0,1,1,2,2,...]
   # pick_ids_1d = [1,2,4,0,3,4,2,3,5...]
   batch_idx_1d = batch_idx.reshape((1, -1))
   pick_ids_1d = pick_ids.reshape((1, -1))
   position_idx = mx.nd.concat(batch_idx_1d, pick_ids_1d, dim=0)
   encoded = mx.nd.gather_nd(sequence, position_idx)
   ground_truth = encoded.reshape_like(pick_ids, lhs_begin=-2, lhs_end=-1, rhs_begin=0)
   
   # new implementation in deep numpy
   mx.npx.set_np()
   sequence = sequence.as_np_ndarray()
   pick_ids = pick_ids.as_np_ndarray()
   
   idx_arange = mx.npx.arange_like(pick_ids.reshape((-1, )), axis=0)
   batch_idx = mx.np.floor(idx_arange / 2).astype(np.int32)
   
   encoded = sequence[batch_idx, pick_ids.reshape((-1,))]
   np_out = mx.npx.reshape_like(encoded, pick_ids, lhs_begin=-2, lhs_end=-1, rhs_begin=0)
   
   npt.assert_allclose(ground_truth.asnumpy(), np_out.asnumpy(), rtol=1e-5, atol=1e-5)
   ```
   I was aimed to pick the items from the sequence with shape (8, 2, 768) whereas the `mn.npx.pick` can not handle it. Under the deep numpy enviorment, I used the basic indexing as numpy operation as `encoded = sequence[batch_idx, pick_ids.reshape((-1,))]` which would fail after hybridize() raising the below **Error**
   
   > IndexError: Only integer, slice, or tuple of these types are supported! Received key=(<_Symbol albertmodel0_floor0>, <_Symbol albertmodel0_reshape4>)

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