[GitHub] haojin2 commented on issue #10550: [MXNET-320] Support elemwise_add/sub between dense and csr tensors

[GitBox]

haojin2 commented on issue #10550: [MXNET-320] Support elemwise_add/sub between 
dense and csr tensors
URL: https://github.com/apache/incubator-mxnet/pull/10550#issuecomment-384366007
 
 
   Benchmark Script:
   ```python
   import mxnet as mx
   import numpy as np
   from mxnet.test_utils import rand_ndarray, assert_almost_equal
   import time
   
   def measure_cost(repeat, a, b, out=None):
       # start bench
       start = time.time()
       results = []
       for i in range(repeat):
           results.append(mx.nd.elemwise_add(a, b, out=out))
       for result in results:
           result.wait_to_read()
       end = time.time()
       diff = end - start
       return diff / repeat
   
   def measure_fallback(repeat, a):
       # start bench
       start = time.time()
       results = []
       for i in range(repeat):
           results.append(a.tostype('default'))
       for result in results:
           result.wait_to_read()
       end = time.time()
       diff = end - start
       return diff / repeat
   
   def main():
       shape = (1000000, 512)
       dns = np.random.uniform(size=shape)
       context = mx.gpu(0)
       # context = mx.cpu()
       mx_dns = mx.nd.array(dns, ctx=context)
       for density in [0.01, 0.005, 0.001, 0.0005, 0.0001]:
           mx_csr = rand_ndarray(shape=shape, stype='csr', 
density=density).as_in_context(context)
           mx_csr_dns = mx_csr.tostype('default')
           sparse_cost = 0.0
           dns_cost = 0.0
           mx.nd.waitall()
           #warmup
           dns = mx_dns.asnumpy()
           mx.nd.elemwise_add(mx_dns, mx_csr, out=mx_dns)
           dns = dns + mx_csr_dns.asnumpy()
           assert_almost_equal(mx_dns.asnumpy(), dns, atol=1e-5, rtol=1e-4)
           mx.nd.waitall()
           for i in range(100):
               sparse_cost += measure_cost(1, mx_dns, mx_csr, out=mx_dns)
               # dns_cost += measure_fallback(1, mx_csr)
               dns_cost += measure_cost(1, mx_dns, mx_csr_dns, out=mx_dns)
           print("%.2f %%" % (density*100), dns_cost / sparse_cost)
   
           #warmup
           dns = mx_dns.asnumpy()
           check = mx.nd.elemwise_add(mx_dns, mx_csr)
           dns = dns + mx_csr_dns.asnumpy()
           assert_almost_equal(check.asnumpy(), dns, atol=1e-5, rtol=1e-4)
           mx.nd.waitall()
           for i in range(100):
               sparse_cost += measure_cost(1, mx_dns, mx_csr)
               # dns_cost += measure_fallback(1, mx_csr)
               dns_cost += measure_cost(1, mx_dns, mx_csr_dns)
           print("%.2f %%" % (density*100), dns_cost / sparse_cost)
   
   
   if __name__ == "__main__":
       main()
   ```

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