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[TVM PyTorch Integration] libstdc++ CXX11 ABI Compatibility & boolean…
… tensor support (#12232) * first commit * rename * cmake * deprecated * newline * config * config * typo * skip tvm_class * rename * delete ptr * delete ptr * save progress * boolean support * cmake file * polish code * compile config * improving the codes * format * doc&errormsg * zero-cost copy * one step * to ndarray * extra output * delete extra codes * update test * boolean support * strong test * decrease memory copy * polish * reformat * polish * remove redundant import Co-authored-by: juda <yzhou@octoml.ai>
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| #!/usr/bin/env python | ||
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| # Licensed to the Apache Software Foundation (ASF) under one | ||
| # or more contributor license agreements. See the NOTICE file | ||
| # distributed with this work for additional information | ||
| # regarding copyright ownership. The ASF licenses this file | ||
| # to you under the Apache License, Version 2.0 (the | ||
| # "License"); you may not use this file except in compliance | ||
| # with the License. You may obtain a copy of the License at | ||
| # | ||
| # http://www.apache.org/licenses/LICENSE-2.0 | ||
| # | ||
| # Unless required by applicable law or agreed to in writing, | ||
| # software distributed under the License is distributed on an | ||
| # "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY | ||
| # KIND, either express or implied. See the License for the | ||
| # specific language governing permissions and limitations | ||
| # under the License. | ||
| """Test script for boolean tensor support""" | ||
| import tempfile | ||
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| import torch | ||
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| import tvm | ||
| import tvm.testing | ||
| from tvm.contrib.torch import as_torch, optimize_torch | ||
| from tvm.script import tir as T | ||
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| def negate(x): | ||
| return x.logical_not() | ||
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| def sum_up_tensor(x): | ||
| return x.size(dim=0) - torch.sum(x.int()) | ||
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| def tensor_boolean_operation(x): | ||
| arr1 = (x + 0.3).floor().bool() | ||
| arr2 = (~((x + 0.7).int().bool())).bool() | ||
| ret = ((arr1 & arr2).byte() + 0.5).half() | ||
| return ~(ret.bool()) | ||
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| def test_bool_tensor_negate(): | ||
| input = torch.ones(1, dtype=torch.bool) | ||
| optimized_negate = optimize_torch( | ||
| negate, | ||
| input, | ||
| ) | ||
| with tempfile.NamedTemporaryFile(suffix=".pt") as tmp: | ||
| torch.save(optimized_negate, tmp.name) | ||
| loaded_mod = torch.load(tmp.name) | ||
| output = loaded_mod(negate(input)) | ||
| tvm.testing.assert_allclose(input.numpy(), output.numpy(), atol=1e-5, rtol=1e-5) | ||
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| def test_sum_up_tensor(): | ||
| x = torch.randint(0, 2, (16,)) | ||
| y = x.bool() | ||
| optimized_func = optimize_torch( | ||
| sum_up_tensor, | ||
| (y,), | ||
| ) | ||
| ret1 = (x[x == 0]).size(dim=0) | ||
| ret2 = optimized_func(y).numpy() | ||
| tvm.testing.assert_allclose(ret1, ret2, atol=1e-5, rtol=1e-5) | ||
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| def test_tensor_boolean_operation(): | ||
| input = torch.rand(200) | ||
| model = optimize_torch( | ||
| tensor_boolean_operation, | ||
| input, | ||
| ) | ||
| ret1 = tensor_boolean_operation(input) | ||
| ret2 = model(input) | ||
| tvm.testing.assert_allclose(ret1, ret2, atol=1e-5, rtol=1e-5) | ||
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| @as_torch | ||
| @T.prim_func | ||
| def negate_tvmscript( | ||
| X: T.Buffer[(8, 8), "bool"], | ||
| Y: T.Buffer[(8, 8), "float32"], | ||
| Z: T.Buffer[(8, 8), "bool"], | ||
| U: T.Buffer[(8, 8), "float32"], | ||
| ) -> None: | ||
| for i, j in T.grid(8, 8): | ||
| with T.block(): | ||
| if Y[i, j] > 0.0: | ||
| Z[i, j] = X[i, j] | ||
| U[i, j] = Y[i, j] | ||
| else: | ||
| Z[i, j] = not X[i, j] | ||
| U[i, j] = 0.0 - Y[i, j] | ||
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| def negate_vanila(x, y): | ||
| z = torch.zeros(8, 8).bool() | ||
| for i in range(8): | ||
| for j in range(8): | ||
| if y[i, j] > 0: | ||
| z[i, j] = x[i, j] | ||
| else: | ||
| z[i, j] = ~x[i, j] | ||
| return z | ||
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| def test_tvmscript_torch_decorator(): | ||
| q1 = (torch.rand(8, 8) + 0.5).int().bool() | ||
| q2 = torch.rand(8, 8) - 0.5 | ||
| q3 = torch.zeros(8, 8).bool() | ||
| q4 = torch.zeros(8, 8) | ||
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| std1 = negate_vanila(q1, q2) | ||
| std2 = torch.abs(q2) | ||
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| negate_tvmscript(q1, q2, q3, q4) | ||
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| tvm.testing.assert_allclose(std1.numpy(), q3.numpy(), atol=1e-5, rtol=1e-5) | ||
| tvm.testing.assert_allclose(std2.numpy(), q4.numpy(), atol=1e-5, rtol=1e-5) | ||
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| if __name__ == "__main__": | ||
| test_tvmscript_torch_decorator() | ||
| test_bool_tensor_negate() | ||
| test_sum_up_tensor() | ||
| test_tensor_boolean_operation() |
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