tensor_parser_aten: tag planned tensor DataPtr with its real device #21289
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| Original file line number | Diff line number | Diff line change |
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| /* | ||
| * Copyright (c) Meta Platforms, Inc. and affiliates. | ||
| * All rights reserved. | ||
| * | ||
| * This source code is licensed under the BSD-style license found in the | ||
| * LICENSE file in the root directory of this source tree. | ||
| */ | ||
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| /** | ||
| * Unit tests for the ATen-mode tensor parser's device handling. These exercise | ||
| * the validation and CPU-tagging paths that run without a real accelerator. The | ||
| * end-to-end CUDA device-pointer path is covered separately by | ||
| * tensor_parser_device_test (portable mode) with a mock allocator; ATen-mode | ||
| * CUDA execution needs a real device and is out of scope here. | ||
| */ | ||
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| #include <executorch/runtime/executor/tensor_parser.h> | ||
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| #include <executorch/runtime/core/exec_aten/exec_aten.h> | ||
| #include <executorch/runtime/executor/test/managed_memory_manager.h> | ||
| #include <executorch/runtime/platform/runtime.h> | ||
| #include <executorch/schema/program_generated.h> | ||
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| #include <gtest/gtest.h> | ||
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| #include <vector> | ||
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| using executorch::aten::Tensor; | ||
| using executorch::runtime::Error; | ||
| using executorch::runtime::MemoryManager; | ||
| using executorch::runtime::Result; | ||
| using executorch::runtime::aten::deserialization::parseTensor; | ||
| using executorch::runtime::testing::ManagedMemoryManager; | ||
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| namespace { | ||
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| constexpr size_t kMemBytes = 32 * 1024U; | ||
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| // Builds a standalone serialized Tensor with no data_buffer and no | ||
| // allocation_info, i.e. an input/placeholder. parseTensor then resolves a null | ||
| // data pointer, so these tests reach the device validation and tagging logic | ||
| // without needing a Program or any device memory. | ||
| const executorch_flatbuffer::Tensor* buildTensor( | ||
| flatbuffers::FlatBufferBuilder& builder, | ||
| executorch_flatbuffer::TensorShapeDynamism dynamism, | ||
| bool with_extra_info, | ||
| executorch_flatbuffer::DeviceType device_type, | ||
| int8_t device_index) { | ||
| flatbuffers::Offset<executorch_flatbuffer::ExtraTensorInfo> extra_info = 0; | ||
| if (with_extra_info) { | ||
| executorch_flatbuffer::ExtraTensorInfoBuilder eti(builder); | ||
| eti.add_device_type(device_type); | ||
| eti.add_device_index(device_index); | ||
| extra_info = eti.Finish(); | ||
| } | ||
| const std::vector<int32_t> sizes = {2, 2}; | ||
| const std::vector<uint8_t> dim_order = {0, 1}; | ||
| const auto sizes_offset = builder.CreateVector(sizes); | ||
| const auto dim_order_offset = builder.CreateVector(dim_order); | ||
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| executorch_flatbuffer::TensorBuilder tb(builder); | ||
| tb.add_scalar_type(executorch_flatbuffer::ScalarType::FLOAT); | ||
| tb.add_storage_offset(0); | ||
| tb.add_sizes(sizes_offset); | ||
| tb.add_dim_order(dim_order_offset); | ||
| tb.add_data_buffer_idx(0); | ||
| tb.add_shape_dynamism(dynamism); | ||
| if (with_extra_info) { | ||
| tb.add_extra_tensor_info(extra_info); | ||
| } | ||
| builder.Finish(tb.Finish()); | ||
| return flatbuffers::GetRoot<executorch_flatbuffer::Tensor>( | ||
| builder.GetBufferPointer()); | ||
| } | ||
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| } // namespace | ||
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| class TensorParserAtenTest : public ::testing::Test { | ||
| protected: | ||
| void SetUp() override { | ||
| executorch::runtime::runtime_init(); | ||
| } | ||
| }; | ||
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| // A CPU tensor must stay unindexed. An explicit cpu:0 would mismatch the | ||
| // graph's default cpu tensors and trip ATen's same-device check. | ||
| TEST_F(TensorParserAtenTest, CpuTensorIsUnindexed) { | ||
| flatbuffers::FlatBufferBuilder builder; | ||
| const auto* s_tensor = buildTensor( | ||
| builder, | ||
| executorch_flatbuffer::TensorShapeDynamism::STATIC, | ||
| /*with_extra_info=*/true, | ||
| executorch_flatbuffer::DeviceType::CPU, | ||
| /*device_index=*/0); | ||
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| ManagedMemoryManager mmm(kMemBytes, kMemBytes); | ||
| Result<Tensor> tensor = parseTensor(nullptr, &mmm.get(), s_tensor); | ||
| ASSERT_EQ(tensor.error(), Error::Ok); | ||
| EXPECT_TRUE(tensor->is_cpu()); | ||
| EXPECT_FALSE(tensor->device().has_index()); | ||
| EXPECT_EQ(tensor->scalar_type(), executorch::aten::ScalarType::Float); | ||
| } | ||
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| // A tensor with no extra_tensor_info (older PTE files) defaults to CPU. | ||
| TEST_F(TensorParserAtenTest, MissingExtraInfoDefaultsToCpu) { | ||
| flatbuffers::FlatBufferBuilder builder; | ||
| const auto* s_tensor = buildTensor( | ||
| builder, | ||
| executorch_flatbuffer::TensorShapeDynamism::STATIC, | ||
| /*with_extra_info=*/false, | ||
| executorch_flatbuffer::DeviceType::CPU, | ||
| /*device_index=*/0); | ||
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| ManagedMemoryManager mmm(kMemBytes, kMemBytes); | ||
| Result<Tensor> tensor = parseTensor(nullptr, &mmm.get(), s_tensor); | ||
| ASSERT_EQ(tensor.error(), Error::Ok); | ||
| EXPECT_TRUE(tensor->is_cpu()); | ||
| EXPECT_FALSE(tensor->device().has_index()); | ||
| } | ||
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| // An unmapped DeviceType from the untrusted PTE is rejected before it can reach | ||
| // c10::Device as garbage. | ||
| TEST_F(TensorParserAtenTest, InvalidDeviceTypeIsRejected) { | ||
| flatbuffers::FlatBufferBuilder builder; | ||
| const auto* s_tensor = buildTensor( | ||
| builder, | ||
| executorch_flatbuffer::TensorShapeDynamism::STATIC, | ||
| /*with_extra_info=*/true, | ||
| static_cast<executorch_flatbuffer::DeviceType>(7), | ||
| /*device_index=*/0); | ||
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| ManagedMemoryManager mmm(kMemBytes, kMemBytes); | ||
| EXPECT_EQ( | ||
| parseTensor(nullptr, &mmm.get(), s_tensor).error(), | ||
| Error::InvalidProgram); | ||
| } | ||
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| // A negative accelerator index is not a valid serialized placement. | ||
| TEST_F(TensorParserAtenTest, NegativeAcceleratorIndexIsRejected) { | ||
| flatbuffers::FlatBufferBuilder builder; | ||
| const auto* s_tensor = buildTensor( | ||
| builder, | ||
| executorch_flatbuffer::TensorShapeDynamism::STATIC, | ||
| /*with_extra_info=*/true, | ||
| executorch_flatbuffer::DeviceType::CUDA, | ||
| /*device_index=*/-1); | ||
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| ManagedMemoryManager mmm(kMemBytes, kMemBytes); | ||
| EXPECT_EQ( | ||
| parseTensor(nullptr, &mmm.get(), s_tensor).error(), | ||
| Error::InvalidProgram); | ||
| } | ||
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| // A fully dynamic tensor gets a CPU-resizable allocator, so a non-CPU device | ||
| // cannot be honored and must be rejected rather than silently tagged CPU. | ||
| TEST_F(TensorParserAtenTest, DynamicUnboundCudaIsRejected) { | ||
| flatbuffers::FlatBufferBuilder builder; | ||
| const auto* s_tensor = buildTensor( | ||
| builder, | ||
| executorch_flatbuffer::TensorShapeDynamism::DYNAMIC_UNBOUND, | ||
| /*with_extra_info=*/true, | ||
| executorch_flatbuffer::DeviceType::CUDA, | ||
| /*device_index=*/0); | ||
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| ManagedMemoryManager mmm(kMemBytes, kMemBytes); | ||
| EXPECT_EQ( | ||
| parseTensor(nullptr, &mmm.get(), s_tensor).error(), Error::NotSupported); | ||
| } | ||
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| // The DYNAMIC_UNBOUND guard only rejects non-CPU; CPU resizable tensors still | ||
| // parse so the guard does not regress the common case. | ||
| TEST_F(TensorParserAtenTest, DynamicUnboundCpuIsAllowed) { | ||
| flatbuffers::FlatBufferBuilder builder; | ||
| const auto* s_tensor = buildTensor( | ||
| builder, | ||
| executorch_flatbuffer::TensorShapeDynamism::DYNAMIC_UNBOUND, | ||
| /*with_extra_info=*/false, | ||
| executorch_flatbuffer::DeviceType::CPU, | ||
| /*device_index=*/0); | ||
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| ManagedMemoryManager mmm(kMemBytes, kMemBytes); | ||
| Result<Tensor> tensor = parseTensor(nullptr, &mmm.get(), s_tensor); | ||
| ASSERT_EQ(tensor.error(), Error::Ok); | ||
| EXPECT_TRUE(tensor->is_cpu()); | ||
| EXPECT_FALSE(tensor->device().has_index()); | ||
| } |
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