wehub-resource-sync
87 lines
3.3 KiB
Python
87 lines
3.3 KiB
Python
# Licensed to the Apache Software Foundation (ASF) under one
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# or more contributor license agreements. See the NOTICE file
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# distributed with this work for additional information
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# regarding copyright ownership. The ASF licenses this file
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# to you under the Apache License, Version 2.0 (the
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# "License"); you may not use this file except in compliance
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# with the License. You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing,
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# software distributed under the License is distributed on an
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# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
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# KIND, either express or implied. See the License for the
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# specific language governing permissions and limitations
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# under the License.
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import tvm
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from tvm.script import tirx as T
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def test_meta_programming_matmul():
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def matmul_generator(M: int, N: int, K: int, dtype: str):
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@T.prim_func(s_tir=True)
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def matmul(a: T.handle, b: T.handle, c: T.handle) -> None:
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A = T.match_buffer(a, [M, K], dtype=dtype)
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B = T.match_buffer(b, [N, K], dtype=dtype)
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C = T.match_buffer(c, [M, N], dtype=dtype)
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for i, j, k in T.grid(M, N, K):
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with T.sblock():
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vi, vj, vk = T.axis.remap("SSR", [i, j, k])
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with T.init():
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C[vi, vj] = T.float32(0)
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C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vj, vk]
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return matmul
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@T.prim_func(s_tir=True)
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def matmul_128_128_128_fp16(a: T.handle, b: T.handle, c: T.handle) -> None:
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A = T.match_buffer(a, [128, 128], dtype="float16")
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B = T.match_buffer(b, [128, 128], dtype="float16")
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C = T.match_buffer(c, [128, 128], dtype="float16")
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for i, j, k in T.grid(128, 128, 128):
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with T.sblock():
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vi, vj, vk = T.axis.remap("SSR", [i, j, k])
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with T.init():
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C[vi, vj] = T.float32(0)
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C[vi, vj] = C[vi, vj] + A[vi, vk] * B[vj, vk]
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f = matmul_generator(128, 128, 128, "float16").with_attr("global_symbol", "main")
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tvm.ir.assert_structural_equal(f, matmul_128_128_128_fp16.with_attr("global_symbol", "main"))
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def test_meta_programming_uncaptured_var():
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def generate_erf(dtype):
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@T.prim_func(s_tir=True)
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def main(A: T.Buffer((1,), dtype), C: T.Buffer((1,), dtype)):
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for i in range(1):
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with T.sblock("C"):
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C[i] = T.erf(A[i])
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return main
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@T.prim_func(s_tir=True)
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def fp32(A: T.Buffer((1,), "float32"), C: T.Buffer((1,), "float32")):
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for i in range(1):
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with T.sblock("C"):
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C[i] = T.erf(A[i])
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@T.prim_func(s_tir=True)
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def fp16(A: T.Buffer((1,), "float16"), C: T.Buffer((1,), "float16")):
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for i in range(1):
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with T.sblock("C"):
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C[i] = T.erf(A[i])
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f1 = generate_erf("float32").with_attr("global_symbol", "main")
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tvm.ir.assert_structural_equal(f1, fp32.with_attr("global_symbol", "main"))
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f2 = generate_erf("float16").with_attr("global_symbol", "main")
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tvm.ir.assert_structural_equal(f2, fp16.with_attr("global_symbol", "main"))
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if __name__ == "__main__":
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test_meta_programming_matmul()
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test_meta_programming_uncaptured_var()
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