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Posted to commits@mxnet.apache.org by GitBox <gi...@apache.org> on 2019/10/21 23:39:10 UTC

[GitHub] [incubator-mxnet] sxjscience opened a new issue #16576: [Numpy][Bug] einsum bug

sxjscience opened a new issue #16576: [Numpy][Bug] einsum bug
URL: https://github.com/apache/incubator-mxnet/issues/16576
 
 
   Example:
   ```python
   import mxnet as mx
   import numpy as np
   import numpy.testing as npt
   from mxnet.gluon import HybridBlock
   
   
   
   class MultiNDimBatchDot1(HybridBlock):
       def hybrid_forward(self, F, lhs, rhs):
           """
   
           Parameters
           ----------
           F
           lhs :
               Shape (N0, N1, T0, C)
           rhs :
               Shape (N0, N1, T1, C)
   
           Returns
           -------
           ret :
               Shape (N0, N1, T0, T1)
           """
           return F.batch_dot(F.reshape(lhs, (-3, 0, 0)),
                              F.reshape(rhs, (-3, 0, 0)), transpose_b=True).reshape((-4, -1, 8, 0, 0))
   
   
   class MultiNDimBatchDot2(HybridBlock):
       def hybrid_forward(self, F, lhs, rhs):
           """
   
           Parameters
           ----------
           F
           lhs :
               Shape (N0, N1, T0, C)
           rhs :
               Shape (N0, N1, T1, C)
   
           Returns
           -------
           ret :
               Shape (N0, N1, T0, T1)
           """
           return F.np.einsum('abiz,abjz->abij', lhs, rhs)
   
   
   batch_dot1 = MultiNDimBatchDot1()
   
   
   batch_dot1.hybridize()
   
   lhs = mx.np.array(np.random.normal(0, 1, (64, 8, 128, 512)), dtype=np.float32, ctx=mx.cpu())
   rhs = mx.np.array(np.random.normal(0, 1, (64, 8, 128, 512)), dtype=np.float32, ctx=mx.cpu())
   mx.npx.waitall()
   
   gt = np.einsum('abiz,abjz->abij', lhs.asnumpy(), rhs.asnumpy())
   out = batch_dot1(lhs.as_nd_ndarray(), rhs.as_nd_ndarray())
   
   npt.assert_allclose(gt, out.asnumpy(), rtol=1E-3, atol=1E-3)
   
   
   mx.npx.set_np()
   batch_dot2 = MultiNDimBatchDot2()
   batch_dot2.hybridize()
   
   out2 = batch_dot2(lhs, rhs)
   npt.assert_allclose(gt, out2.asnumpy(), rtol=1E-3, atol=1E-3)
   ```
   
   The CPU results are not correct.
   
   Also, if we use the gpu, it will trigger a segfault:
   
   ```python
   import mxnet as mx
   import numpy as np
   import numpy.testing as npt
   from mxnet.gluon import HybridBlock
   
   
   
   class MultiNDimBatchDot1(HybridBlock):
       def hybrid_forward(self, F, lhs, rhs):
           """
   
           Parameters
           ----------
           F
           lhs :
               Shape (N0, N1, T0, C)
           rhs :
               Shape (N0, N1, T1, C)
   
           Returns
           -------
           ret :
               Shape (N0, N1, T0, T1)
           """
           return F.batch_dot(F.reshape(lhs, (-3, 0, 0)),
                              F.reshape(rhs, (-3, 0, 0)), transpose_b=True).reshape((-4, -1, 8, 0, 0))
   
   
   class MultiNDimBatchDot2(HybridBlock):
       def hybrid_forward(self, F, lhs, rhs):
           """
   
           Parameters
           ----------
           F
           lhs :
               Shape (N0, N1, T0, C)
           rhs :
               Shape (N0, N1, T1, C)
   
           Returns
           -------
           ret :
               Shape (N0, N1, T0, T1)
           """
           return F.np.einsum('abiz,abjz->abij', lhs, rhs)
   
   
   batch_dot1 = MultiNDimBatchDot1()
   
   
   batch_dot1.hybridize()
   
   lhs = mx.np.array(np.random.normal(0, 1, (64, 8, 128, 512)), dtype=np.float32, ctx=mx.gpu())
   rhs = mx.np.array(np.random.normal(0, 1, (64, 8, 128, 512)), dtype=np.float32, ctx=mx.gpu())
   mx.npx.waitall()
   
   gt = np.einsum('abiz,abjz->abij', lhs.asnumpy(), rhs.asnumpy())
   out = batch_dot1(lhs.as_nd_ndarray(), rhs.as_nd_ndarray())
   
   npt.assert_allclose(gt, out.asnumpy(), rtol=1E-3, atol=1E-3)
   
   
   mx.npx.set_np()
   batch_dot2 = MultiNDimBatchDot2()
   batch_dot2.hybridize()
   
   out2 = batch_dot2(lhs, rhs)
   npt.assert_allclose(gt, out2.asnumpy(), rtol=1E-3, atol=1E-3)
   ```

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