[GitHub] asitstands commented on a change in pull request #10970: [MXNET-424] dtype option for multinomial

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

asitstands commented on a change in pull request #10970: [MXNET-424] dtype option for multinomial
URL: https://github.com/apache/incubator-mxnet/pull/10970#discussion_r189154689
 
 

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 File path: src/operator/random/sample_multinomial_op.h
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 @@ -155,9 +158,11 @@ void SampleMultinomialForward(const nnvm::NodeAttrs& attrs,
     Tensor<xpu, 1, float> uniform =
       ctx.requested[1].get_space_typed<xpu, 1, float>(Shape1(N*M), s);
     prnd->SampleUniform(&uniform, 0, 1);
-    Kernel<SampleMultinomialKernel, xpu>::Launch(
-      s, N, K, M, inputs[0].dptr<DType>(), uniform.dptr_, outputs[0].dptr<int>(),
-      param.get_prob ? outputs[1].dptr<DType>() : nullptr);
+    MSHADOW_TYPE_SWITCH(outputs[0].type_flag_, IType, {
 
 Review comment:
   Sometimes the multinomial samples need further processing in floating point arithmetic, so the samples need to be copied into a new array of floating point type which slow down the training. For example, in RBM, the samples need to be applied by `linalg.gemm` which supports only floating point arrays.

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