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Summary: Expose IMethod interface, which provides a unified interface to either script or python methods backed by torchscript or torchdeploy. IMethod provides a way to depend on a torch method without depending on a particular runtime implementation such as torchscript or python/deploy. Test Plan: add unit tests. Reviewed By: suo Differential Revision: D29463455 fbshipit-source-id: 903391d9af9fbdd8fcdb096c1a136ec6ac153b7c
45 lines
1.6 KiB
C++
45 lines
1.6 KiB
C++
// (c) Facebook, Inc. and its affiliates. Confidential and proprietary.
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#include <gtest/gtest.h>
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#include <torch/csrc/deploy/deploy.h>
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#include <torch/script.h>
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#include <torch/torch.h>
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using namespace ::testing;
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using namespace caffe2;
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TEST(IMethodTest, CallMethod) {
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auto script_model = torch::jit::load(getenv("SIMPLE_JIT"));
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auto script_method = script_model.get_method("forward");
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torch::deploy::InterpreterManager manager(3);
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torch::deploy::Package p = manager.load_package(getenv("SIMPLE"));
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auto py_model = p.load_pickle("model", "model.pkl");
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torch::deploy::PythonMethodWrapper py_method(py_model, "forward");
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auto input = torch::ones({10, 20});
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auto output_py = py_method({input});
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auto output_script = script_method({input});
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EXPECT_TRUE(output_py.isTensor());
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EXPECT_TRUE(output_script.isTensor());
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auto output_py_tensor = output_py.toTensor();
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auto output_script_tensor = output_script.toTensor();
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EXPECT_TRUE(output_py_tensor.equal(output_script_tensor));
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EXPECT_EQ(output_py_tensor.numel(), 200);
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}
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TEST(IMethodTest, GetArgumentNames) {
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auto script_model = torch::jit::load(getenv("SIMPLE_JIT"));
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auto script_method = script_model.get_method("forward");
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torch::deploy::InterpreterManager manager(3);
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torch::deploy::Package p = manager.load_package(getenv("SIMPLE"));
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auto py_model = p.load_pickle("model", "model.pkl");
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torch::deploy::PythonMethodWrapper py_method(py_model, "forward");
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// TODO(whc) implement and test these
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EXPECT_THROW(script_method.getArgumentNames(), std::runtime_error);
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EXPECT_THROW(py_method.getArgumentNames(), std::runtime_error);
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}
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