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https://github.com/firestar5683/StarPilot.git
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firestar5683
22a8575199
Keep official openpilot ancestry and dependency licenses. Store resources directly in Git, remove LFS setup requirements, and leave the downloadable big model outside the source tree.
47 lines
1.3 KiB
Python
47 lines
1.3 KiB
Python
# https://tvm.apache.org/docs/tutorial/tensor_expr_get_started.html#example-2-manually-optimizing-matrix-multiplication-with-te
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M, N, K = 1024, 1024, 1024
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try:
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import tvm
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from tvm import te
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#print(tvm.target.Target.list_kinds())
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# c, opencl
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target = tvm.target.Target(target="c")
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# TVM Matrix Multiplication using TE
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k = te.reduce_axis((0, K), "k")
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A = te.placeholder((M, K), name="A")
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B = te.placeholder((K, N), name="B")
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C = te.compute((M, N), lambda x, y: te.sum(A[x, k] * B[k, y], axis=k), name="C")
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# Default schedule
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s = te.create_schedule(C.op)
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#print(tvm.lower(s, [A, B, C], simple_mode=True))
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# Output C code
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func = tvm.build(s, [A, B, C], target=target, name="mmult")
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print(func.get_source())
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except ImportError:
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print("** please install TVM for TVM output")
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# tinygrad version
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import os
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from tinygrad.tensor import Tensor
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# define the compute
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A = Tensor.rand(M, K, device="CPU")
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B = Tensor.rand(K, N, device="CPU")
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C = (A.reshape(M, 1, K) * B.permute(1,0).reshape(1, N, K)).sum(axis=2)
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linear = C.schedule_linear()
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from tinygrad.codegen.opt.kernel import Kernel
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from tinygrad.device import CompilerOptions
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lin = Kernel(linear.src[-1].src[0], CompilerOptions(has_local=False, supports_float4=False))
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lin.to_program()
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from tinygrad.runtime.ops_cpu import renderer
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src = renderer("mmult", lin.uops)
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print(src)
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