def tensor(self, shapes, dtype='float32', device='cpu'):
""" A wapper function to create C2 tensor filled with random data.
The name/label of the tensor is returned and it is available
throughout the benchmark execution phase.
Args:
shapes: int or a sequence of ints to defining the shapes of the tensor
dtype: use the dtypes from numpy
(https://docs.scipy.org/doc/numpy/user/basics.types.html)
Return:
C2 tensor of dtype
"""
return self.feed_tensor(benchmark_utils.numpy_random(dtype, *shapes),
device)
def tensor(self, shapes, dtype='float32'):
""" A wapper function to create C2 tensor filled with random data.
The name/label of the tensor is returned and it is available
throughout the benchmark execution phase.
Args:
shapes: int or a sequence of ints to defining the shapes of the tensor
dtype: use the dtypes from numpy
(https://docs.scipy.org/doc/numpy/user/basics.types.html)
Return:
C2 tensor of dtype
"""
blob_name = 'blob_' + str(Caffe2BenchmarkBase.tensor_index)
workspace.FeedBlob(blob_name, benchmark_utils.numpy_random(dtype, *shapes))
Caffe2BenchmarkBase.tensor_index += 1
return blob_name
