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[OP] Experimental assign op (apache#389)
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| /*! | ||
| * Copyright (c) 2018 by Contributors | ||
| * \file state_op.cc | ||
| * \brief Experimental operators | ||
| * Currently we only support assign | ||
| */ | ||
| #include <nnvm/op.h> | ||
| #include <nnvm/node.h> | ||
| #include <nnvm/op_attr_types.h> | ||
| #include <nnvm/compiler/op_attr_types.h> | ||
| #include <nnvm/top/tensor.h> | ||
| #include <topi/elemwise.h> | ||
| #include "../op_common.h" | ||
| #include "../elemwise_op_common.h" | ||
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| namespace nnvm { | ||
| namespace top { | ||
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| using namespace tvm; | ||
| using namespace nnvm::compiler; | ||
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| NNVM_REGISTER_OP(_assign) | ||
| .describe(R"doc(Assign rhs to the lhs. | ||
| lhs must be a Variable. | ||
| This is an experimental operator. | ||
| )doc" NNVM_ADD_FILELINE) | ||
| .set_num_inputs(2) | ||
| .set_num_outputs(1) | ||
| .set_attr<FMutateInputs>( | ||
| "FMutateInputs", [](const NodeAttrs& attrs) { | ||
| return std::vector<uint32_t>{0}; | ||
| }) | ||
| .set_attr<FTVMCompute>( | ||
| "FTVMCompute", [](const NodeAttrs& attrs, | ||
| const Array<Tensor>& inputs, | ||
| const Array<Tensor>& out_info) { | ||
| // This implementation is needed for the special | ||
| // logic handling assign in the compiler | ||
| // It simply copies the result of rhs the output | ||
| // The later decoration in compiler will change | ||
| // the memory assignment of assign to tie | ||
| // the lhs to the output. | ||
| return Array<Tensor>{ topi::identity(inputs[1]) }; | ||
| }) | ||
| .set_attr<FInferShape>("FInferShape", SameShape) | ||
| .set_attr<FInplaceOption>( | ||
| "FInplaceOption", [](const NodeAttrs& attrs) { | ||
| return std::vector<std::pair<int, int> >{{1, 0}}; | ||
| }); | ||
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| } // namespace top | ||
| } // namespace nnvm |
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| @@ -0,0 +1,41 @@ | ||
| import numpy as np | ||
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| import tvm | ||
| from tvm.contrib import graph_runtime | ||
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| import nnvm.symbol as sym | ||
| import nnvm.compiler | ||
| from nnvm.testing.config import ctx_list | ||
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| def test_update(): | ||
| w = sym.Variable("w") | ||
| w2 = sym.Variable("w2") | ||
| w = sym._assign(w, w + 1) | ||
| w2 = sym._assign(w2, w + 1) | ||
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| dshape = (5, 3, 18, 18) | ||
| shape_dict = {"w": dshape, "w2":dshape} | ||
| dtype = "float32" | ||
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| def check(target, ctx): | ||
| graph, lib, _ = nnvm.compiler.build(w2, target, shape_dict) | ||
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| m = graph_runtime.create(graph, lib, ctx) | ||
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| data = tvm.nd.array(np.random.uniform(size=dshape).astype(dtype)) | ||
| m.set_input("w", data) | ||
| m.run() | ||
| out = m.get_input("w2", tvm.nd.empty(dshape, dtype)) | ||
| np.testing.assert_allclose(out.asnumpy(), data.asnumpy() + 2, rtol=1e-5) | ||
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| m.run() | ||
| out = m.get_input("w2", tvm.nd.empty(dshape, dtype)) | ||
| np.testing.assert_allclose(out.asnumpy(), data.asnumpy() + 3, rtol=1e-5) | ||
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| for target, ctx in ctx_list(): | ||
| check(target, ctx) | ||
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| if __name__ == "__main__": | ||
| test_update() |