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# to you under the Apache License, Version 2.0 (the
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#
# http://www.apache.org/licenses/LICENSE-2.0
#
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import numpy as np
import tvm
import tvm.testing
from tvm import relax
from tvm.script import relax as R
def test_op_size():
@tvm.script.ir_module
class Module:
@R.function
def main(x: R.Tensor((2, 3), "float32")) -> R.Tensor((), "int64"):
return R.size(x)
x_np = np.random.rand(2, 3).astype("float32")
x = tvm.runtime.tensor(x_np)
target = tvm.target.Target("llvm")
ex = relax.build(Module, target)
vm = relax.VirtualMachine(ex, tvm.cpu())
res = vm["main"](x)
assert res.numpy() == 6
def test_op_size_dynamic():
@tvm.script.ir_module
class Module:
@R.function
def main(x: R.Tensor(("m", "n"), "float32")) -> R.Tensor((), "int64"):
return R.size(x)
x_np = np.random.rand(4, 5).astype("float32")
x = tvm.runtime.tensor(x_np)
target = tvm.target.Target("llvm")
ex = relax.build(Module, target)
vm = relax.VirtualMachine(ex, tvm.cpu())
res = vm["main"](x)
assert res.numpy() == 20
if __name__ == "__main__":
tvm.testing.main()