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# Licensed to the Apache Software Foundation (ASF) under one
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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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"""Test scheduling and running a dot product."""
import numpy as np
import tvm
import tvm.testing
from tvm import te
@tvm.testing.requires_llvm
def test_dot():
"""Test dot product."""
arr_length = 12
arr_length_tvm = tvm.runtime.convert(arr_length)
placeholder_a = te.placeholder((arr_length_tvm,), name="A")
placeholder_b = te.placeholder((arr_length_tvm,), name="B")
reduce_axis_k = te.reduce_axis((0, arr_length_tvm), "k")
result_c = te.compute(
(),
lambda: te.sum(
placeholder_a[reduce_axis_k] * placeholder_b[reduce_axis_k], axis=reduce_axis_k
),
name="C",
)
schedule = te.create_schedule(result_c.op)
def verify(target):
f = tvm.driver.build(schedule, [placeholder_a, placeholder_b, result_c], target)
# verify
dev = tvm.cpu(0)
buff_a = tvm.nd.array(
np.random.uniform(size=(arr_length,)).astype(placeholder_a.dtype), dev
)
buff_b = tvm.nd.array(
np.random.uniform(size=(arr_length,)).astype(placeholder_b.dtype), dev
)
buff_c = tvm.nd.array(np.zeros((), dtype=result_c.dtype), dev)
f(buff_a, buff_b, buff_c)
tvm.testing.assert_allclose(
buff_c.numpy(), np.dot(buff_a.numpy(), buff_b.numpy()), rtol=1e-4
)
verify("llvm")
if __name__ == "__main__":
test_dot()