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From GitBox <...@apache.org>
Subject [GitHub] [tvm] masahi commented on issue #8295: [AMP] Vulkan Support for Mixed Precision Pass
Date Thu, 22 Jul 2021 10:36:25 GMT

masahi commented on issue #8295:
URL: https://github.com/apache/tvm/issues/8295#issuecomment-884813492


   I can confirm that TF2 ssd mobilenet v2 can be converted to fp16 and runs on vulkan (AMD)
and opencl (Intel Ice lake), if I disable vectorization on fp16 at https://github.com/apache/tvm/blob/main/python/tvm/topi/cuda/injective.py#L54-L55
(cc @Lunderberg).
   
   But the output from fp16 is a bit off compared to fp32 (on both vk and ocl):
   ```
   fp32
   Mean Squared Error of output 0 and shape (1, 100, 4) is 9.562732618023824e-15
   Mean Squared Error of output 1 and shape (1, 100) is 0.0
   Mean Squared Error of output 2 and shape (1, 100) is 4.539840725570343e-13
   Mean Squared Error of output 3 and shape (1,) is 0.0
   Mean Squared Error of output 4 and shape (1, 12804, 4) is 3.1784283863710294e-13
   Mean Squared Error of output 5 and shape (1, 12804, 91) is 2.194374375133825
   
   fp16
   Mean Squared Error of output 0 and shape (1, 100, 4) is 0.01756046526134014
   Mean Squared Error of output 1 and shape (1, 100) is 8.5600004196167
   Mean Squared Error of output 2 and shape (1, 100) is 5.59057809823571e-07
   Mean Squared Error of output 3 and shape (1,) is 0.0
   Mean Squared Error of output 4 and shape (1, 12804, 4) is 5.098227120470256e-07
   Mean Squared Error of output 5 and shape (1, 12804, 91) is 2.664001463870136e-09
   ``` 


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