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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 tvm
from tvm.script import tir as T
def test_meta_programming_matmul():
def matmul_generator(M: int, N: int, K: int, dtype: str):
@T.prim_func
def matmul(a: T.handle, b: T.handle, c: T.handle) -> None:
A = T.match_buffer(a, [M, K], dtype=dtype)
B = T.match_buffer(b, [N, K], dtype=dtype)
C = T.match_buffer(c, [M, N], dtype=dtype)
for i, j, k in T.grid(M, N, K):
with T.block():
vi, vj, vk = T.axis.remap("SSR", [i, j, k])
with T.init():
C[vi, vj] = T.float32(0)
C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vj, vk]
return matmul
@T.prim_func
def matmul_128_128_128_fp16(a: T.handle, b: T.handle, c: T.handle) -> None:
A = T.match_buffer(a, [128, 128], dtype="float16")
B = T.match_buffer(b, [128, 128], dtype="float16")
C = T.match_buffer(c, [128, 128], dtype="float16")
for i, j, k in T.grid(128, 128, 128):
with T.block():
vi, vj, vk = T.axis.remap("SSR", [i, j, k])
with T.init():
C[vi, vj] = T.float32(0)
C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vj, vk]
f = matmul_generator(128, 128, 128, "float16").with_attr("global_symbol", "main")
tvm.ir.assert_structural_equal(f, matmul_128_128_128_fp16.with_attr("global_symbol", "main"))
def test_meta_programming_uncaptured_var():
def generate_erf(dtype):
@T.prim_func
def main(A: T.Buffer((1,), dtype), C: T.Buffer((1,), dtype)):
for i in range(1):
with T.block("C"):
C[i] = T.erf(A[i])
return main
@T.prim_func
def fp32(A: T.Buffer((1,), "float32"), C: T.Buffer((1,), "float32")):
for i in range(1):
with T.block("C"):
C[i] = T.erf(A[i])
@T.prim_func
def fp16(A: T.Buffer((1,), "float16"), C: T.Buffer((1,), "float16")):
for i in range(1):
with T.block("C"):
C[i] = T.erf(A[i])
tvm.ir.assert_structural_equal(fp16.with_attr("global_symbol", "main"), generate_erf("float16"))
tvm.ir.assert_structural_equal(fp32.with_attr("global_symbol", "main"), generate_erf("float32"))
if __name__ == "__main__":
test_meta_programming_matmul()
test_meta_programming_uncaptured_var()