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52d082bade
* Update to device_batchnorm_forward base class to include all template parameters for problem description
* Add batchnorm forward instances and external api
* Add batchnorm forward profiler module which uses the external api
* Add some comments in batchnorm_forward example to explain the dimensions in lengths[]
* Replace the reference_batchnorm_forward_nhwc_c by generic reference_batchnorm_forward
* Improvement to the batchnorm infer base API
* Add batchnorm forward client example which shows using the batchnorm forward external API
* Add test for batchnorm forward
* Tuning the batchnorm profiler initialized values and error threshold
* Add support for bhalf_t in instances/external api/tests
* Add support for int8_t in instances/external api/tests
* Add support for double in instances/external api/tests
* Let ScaleDataType and BiasDataType be same as XDataType and YDataType when creating instances
* Checking before running best instance in batchnorm_fwd_nhwc client example
* Add checking for YElementwiseOp in batchnorm_forward external API
* Add more types in batchnorm forward profiler
* Add more test lengths
Co-authored-by: rocking5566 <ChunYu.Lai@amd.com>
[ROCm/composable_kernel commit: 4e6a5575be]
Instructions for batchnorm nhwc Example
Run batchnorm forward nhwc
# -D <xxx> : input 4-d tensor lengths
# -v <x> : verification (0=no, 1=yes)
#arg1: data type (0: fp16, 1: fp32, 3: int8, 5: bp16, 6: fp64)
#arg2: 1/0 to indicate whether to update the moving average and variance (0=no, 1=yes)
#arg3: 1/0 to indicate whether to save result mean/invVariance (0=no, 1=yes)
#arg4: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
#arg5: time kernel (0=no, 1=yes)
./bin/example_batchnorm_forward -D 128,16,16,1024 -v 1 0 0 1 2 1
Result
./bin/example_batchnorm_forward -D 128,16,16,1024 -v 1 0 0 1 2 1
launch_and_time_kernel: grid_dim {64, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
launch_and_time_kernel: grid_dim {120, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
launch_and_time_kernel: grid_dim {120, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
Perf: 2.08231 ms, 354.519 GB/s
Result
./bin/example_batchnorm_forward -D 128,16,16,1024 -v 1 0 1 0 2 0
echo $?
0
Run batchnorm infer nhwc
# -D <xxx> : input 4-d tensor lengths
# -v <x> : verification (0=no, 1=yes)
#arg1: data type (0: fp16, 1: fp32, 3: int8, 5: bp16, 6: fp64)
#arg2: initialization (0=no init, 1=single integer value, 2=scope integer value, 3=decimal value)
#arg3: time kernel (0=no, 1=yes)
./bin/example_batchnorm_infer -D 128,16,16,1024 -v 1 0 2 1
Result
./bin/example_batchnorm_infer -D 128,16,16,1024 -v 1 0 2 1
launch_and_time_kernel: grid_dim {120, 1, 1}, block_dim {256, 1, 1}
Warm up 1 time
Start running 10 times...
Perf: 1.28235 ms, 523.329 GB/s