[GitHub] Ishitori opened a new issue #12700: Add support of dot product (GEMM) for float16 on CPU

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

Ishitori opened a new issue #12700: Add support of dot product (GEMM) for float16 on CPU
URL: https://github.com/apache/incubator-mxnet/issues/12700
 
 
   ## Description
   Currently dot product for float16 is supported only on GPU (was added https://github.com/apache/incubator-mxnet/issues/10531), but is not supported on CPU. It would be great to add it to CPU for fast inference.
   
   
   
   Package used (Python/R/Scala/Julia):
   Python, mxnet 1.3.0
   
   ## Error Message:
   ```
   Traceback (most recent call last):
     File "<stdin>", line 1, in <module>
     File "/home/anaconda3/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py", line 189, in __repr__
       return '\n%s\n<%s %s @%s>' % (str(self.asnumpy()),
     File "/home/anaconda3/lib/python3.6/site-packages/mxnet/ndarray/ndarray.py", line 1972, in asnumpy
       ctypes.c_size_t(data.size)))
     File "/home/anaconda3/lib/python3.6/site-packages/mxnet/base.py", line 252, in check_call
       raise MXNetError(py_str(_LIB.MXGetLastError()))
   mxnet.base.MXNetError: [13:42:46] src/operator/tensor/./dot-inl.h:83: Check failed: outputs[0].type_flag_ == kFloat32 || outputs[0].type_flag_ == kFloat64 || (outputs[0].type_flag_ == kFloat16 && ctx.run_ctx.ctx.dev_mask() == mshadow::gpu::kDevMask) dot only supports float32/float64 for CPU, and float16/float32/float64 for GPU
   ```
   
   ## Minimum reproducible example
   ```
   a = mx.nd.array([1,2,3], dtype="float16")
   b = mx.nd.array([1,2,3], dtype="float16")
   mx.nd.dot(a, b.T)
   ```
   ## Steps to reproduce
   
   1. Run the Minimum reproducible example and see the exception
   
   ## What have you tried to solve it?
   
   1. There is nothing can be done, only either work with GPU or do float32 math.

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