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JacobSzwejbkafacebook-github-bot
JacobSzwejbka
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MethodMeta
Summary: There is a growing class of usecases that want to be able to inspect meta data about methods without paying the full init cost. These classes provide a safe and cheap way to view this information Reviewed By: dbort Differential Revision: D48039273 fbshipit-source-id: 261e7ac7d7ea6b1cc63f52d54815fd30711059b8
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‎runtime/executor/method_meta.cpp

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/*
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* Copyright (c) Meta Platforms, Inc. and affiliates.
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* All rights reserved.
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*
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* This source code is licensed under the BSD-style license found in the
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* LICENSE file in the root directory of this source tree.
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*/
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#include <executorch/runtime/core/error.h>
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#include <executorch/runtime/core/exec_aten/exec_aten.h>
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#include <executorch/runtime/core/exec_aten/util/scalar_type_util.h>
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#include <executorch/runtime/core/result.h>
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#include <executorch/runtime/core/span.h>
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#include <executorch/runtime/core/tag.h>
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#include <executorch/runtime/executor/method_meta.h>
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#include <executorch/schema/program_generated.h>
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namespace torch {
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namespace executor {
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namespace {
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Result<Tag> get_tag(
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flatbuffers::Vector<flatbuffers::Offset<executorch_flatbuffer::EValue>>::
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return_type serialization_value,
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size_t index) {
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switch (serialization_value->val_type()) {
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case executorch_flatbuffer::KernelTypes::Int: {
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return Tag::Int;
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} break;
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case executorch_flatbuffer::KernelTypes::Double: {
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return Tag::Double;
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} break;
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case executorch_flatbuffer::KernelTypes::Bool: {
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return Tag::Bool;
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} break;
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case executorch_flatbuffer::KernelTypes::String: {
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return Tag::String;
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} break;
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case executorch_flatbuffer::KernelTypes::Tensor: {
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return Tag::Tensor;
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} break;
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default:
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ET_LOG(
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Error,
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"Invalid tag: %zu input: %zu",
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(size_t)serialization_value->val_type(),
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index);
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return Error::Internal;
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}
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}
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size_t calculate_nbytes(
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Span<const int32_t> sizes,
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exec_aten::ScalarType scalar_type) {
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ssize_t n = 1;
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for (ssize_t i = 0; i < sizes.size(); i++) {
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n *= sizes[i];
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}
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return n * sizeof_scalar_type(scalar_type);
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}
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} // namespace
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TensorInfo::TensorInfo(
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Span<const int32_t> sizes,
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Span<const uint8_t> dim_order,
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exec_aten::ScalarType scalar_type) noexcept
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: sizes_(sizes),
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dim_order_(dim_order),
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scalar_type_(scalar_type),
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nbytes_(calculate_nbytes(sizes_, scalar_type_)) {}
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Span<const int32_t> TensorInfo::sizes() const noexcept {
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return sizes_;
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}
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Span<const uint8_t> TensorInfo::dim_order() const noexcept {
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return dim_order_;
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}
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exec_aten::ScalarType TensorInfo::scalar_type() const noexcept {
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return scalar_type_;
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}
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size_t TensorInfo::nbytes() const noexcept {
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return nbytes_;
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}
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MethodMeta::MethodMeta(
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const executorch_flatbuffer::ExecutionPlan* s_plan) noexcept
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: s_plan_(s_plan) {}
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const char* MethodMeta::name() const noexcept {
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return s_plan_->name()->c_str();
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}
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size_t MethodMeta::num_inputs() const noexcept {
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return s_plan_->inputs()->size();
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}
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Result<Tag> MethodMeta::input_tag(size_t index) const noexcept {
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auto num_inputs = this->num_inputs();
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ET_CHECK_OR_RETURN_ERROR(
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index >= 0 && index < num_inputs,
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InvalidArgument,
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"index %zu out of range. num_inputs: %zu",
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index,
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num_inputs);
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auto input_index = s_plan_->inputs()->Get(index);
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auto serialization_value = s_plan_->values()->Get(input_index);
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return get_tag(serialization_value, index);
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}
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Result<TensorInfo> MethodMeta::input_tensor_meta(size_t index) const noexcept {
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auto tag = this->input_tag(index);
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if (!tag.ok()) {
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return tag.error();
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}
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ET_CHECK_OR_RETURN_ERROR(
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tag.get() == Tag::Tensor,
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InvalidArgument,
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"Tag: %zu input: %zu is not Tensor",
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(size_t)tag.get(),
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index);
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auto input_index = s_plan_->inputs()->Get(index);
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auto tensor_value = s_plan_->values()->Get(input_index)->val_as_Tensor();
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return TensorInfo(
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Span<const int32_t>(
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tensor_value->sizes()->data(), tensor_value->sizes()->size()),
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Span<const uint8_t>(
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tensor_value->dim_order()->data(), tensor_value->dim_order()->size()),
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static_cast<exec_aten::ScalarType>(tensor_value->scalar_type()));
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}
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size_t MethodMeta::num_outputs() const noexcept {
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return s_plan_->outputs()->size();
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}
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Result<Tag> MethodMeta::output_tag(size_t index) const noexcept {
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auto num_outputs = this->num_outputs();
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ET_CHECK_OR_RETURN_ERROR(
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index >= 0 && index < num_outputs,
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InvalidArgument,
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"index %zu out of range. num_outputs: %zu",
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index,
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num_outputs);
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auto input_index = s_plan_->outputs()->Get(index);
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auto serialization_value = s_plan_->values()->Get(input_index);
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return get_tag(serialization_value, index);
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}
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Result<TensorInfo> MethodMeta::output_tensor_meta(size_t index) const noexcept {
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auto tag = this->output_tag(index);
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if (!tag.ok()) {
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return tag.error();
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}
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ET_CHECK_OR_RETURN_ERROR(
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tag.get() == Tag::Tensor,
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InvalidArgument,
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"Tag: %zu output: %zu is not Tensor",
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(size_t)tag.get(),
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index);
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auto input_index = s_plan_->outputs()->Get(index);
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auto tensor_value = s_plan_->values()->Get(input_index)->val_as_Tensor();
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return TensorInfo(
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Span<const int32_t>(
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tensor_value->sizes()->data(), tensor_value->sizes()->size()),
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Span<const uint8_t>(
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tensor_value->dim_order()->data(), tensor_value->dim_order()->size()),
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static_cast<exec_aten::ScalarType>(tensor_value->scalar_type()));
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}
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size_t MethodMeta::num_non_const_buffers() const noexcept {
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return s_plan_->non_const_buffer_sizes()->size();
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}
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Result<int64_t> MethodMeta::non_const_buffer_size(size_t index) const noexcept {
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auto num_buffers = this->num_non_const_buffers();
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ET_CHECK_OR_RETURN_ERROR(
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index >= 0 && index < num_buffers,
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InvalidArgument,
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"index %zu out of range. num_buffers: %zu",
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index,
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num_buffers);
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return s_plan_->non_const_buffer_sizes()->Get(index);
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}
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} // namespace executor
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} // namespace torch

‎runtime/executor/method_meta.h

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/*
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* Copyright (c) Meta Platforms, Inc. and affiliates.
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* All rights reserved.
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*
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* This source code is licensed under the BSD-style license found in the
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* LICENSE file in the root directory of this source tree.
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*/
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#pragma once
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#include <executorch/runtime/core/exec_aten/exec_aten.h>
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#include <executorch/runtime/core/result.h>
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#include <executorch/runtime/core/span.h>
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#include <executorch/runtime/core/tag.h>
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// Forward declare flatbuffer types. This is a public header and must not
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// include the generated flatbuffer header.
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namespace executorch_flatbuffer {
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struct ExecutionPlan;
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} // namespace executorch_flatbuffer
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namespace torch {
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namespace executor {
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/**
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* Metadata about a specific tensor of an Executorch Program.
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*
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* The program used to create the MethodMeta object that created this
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* TensorInfo must outlive this TensorInfo.
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*/
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class TensorInfo final {
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public:
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TensorInfo() = delete;
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TensorInfo(const TensorInfo&) = default;
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TensorInfo(TensorInfo&&) = default;
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TensorInfo& operator=(const TensorInfo&) = default;
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TensorInfo& operator=(TensorInfo&& other) = default;
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~TensorInfo() = default;
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/**
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* Returns the sizes of the tensor.
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*/
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Span<const int32_t> sizes() const;
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/**
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* Returns the dim order of the tensor.
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*/
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Span<const uint8_t> dim_order() const;
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/**
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* Returns the scalar type of the input/output.
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*/
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exec_aten::ScalarType scalar_type() const;
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/**
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* Returns the size of the tensor in bytes.
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*/
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size_t nbytes() const;
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private:
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// Let MethodMeta create TensorInfo.
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friend class MethodMeta;
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TensorInfo(
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Span<const int32_t> sizes,
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Span<const uint8_t> dim_order,
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exec_aten::ScalarType scalar_type);
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/**
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* The sizes of the tensor.
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*
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* NOTE: References data from the Program, so the Program must outlive the
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* TensorInfo.
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*/
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Span<const int32_t> sizes_;
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/**
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* The dim order of the tensor.
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*
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* NOTE: References data from the Program, so the Program must outlive the
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* TensorInfo.
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*/
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Span<const uint8_t> dim_order_;
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/// The scalar type of the tensor.
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exec_aten::ScalarType scalar_type_;
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/// The size in bytes of the tensor.
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size_t nbytes_;
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};
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/**
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* Describes a a method in an Executorch program.
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*
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* The program used to create a MethodMeta object must outlive the MethodMeta.
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* It is separate from Method so that this information can be accessed without
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* paying the initialization cost of loading the full Method.
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*/
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class MethodMeta final {
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public:
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MethodMeta() = delete;
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MethodMeta(const MethodMeta&) = default;
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MethodMeta(MethodMeta&&) = default;
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MethodMeta& operator=(const MethodMeta&) = default;
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MethodMeta& operator=(MethodMeta&& other) = default;
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~MethodMeta() = default;
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/**
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* Get the name of this method.
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*
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* @returns The method name.
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*/
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const char* name() const;
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/**
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* Get the number of inputs to this method.
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*
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* @returns The number of inputs.
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*/
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size_t num_inputs() const;
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/**
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* Get the tag of the specified input.
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*
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* @param[in] index The index of the input to look up.
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* @returns The tag of input, can only be [Tensor, Int, Bool, Double, String].
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*/
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Result<Tag> input_tag(size_t index) const;
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/**
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* Get metadata about the specified input.
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*
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* @param[in] index The index of the input to look up.
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* @returns The metadata on success, or an error on failure. Only valid for
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* tag::Tensor
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*/
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Result<TensorInfo> input_tensor_meta(size_t index) const;
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/**
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* Get the number of outputs to this method.
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*
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* @returns The number of outputs.
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*/
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size_t num_outputs() const;
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/**
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* Get the tag of the specified output.
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*
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* @param[in] index The index of the output to look up.
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* @returns The tag of output, can only be [Tensor, Int, Bool, Double,
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* String].
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*/
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Result<Tag> output_tag(size_t index) const;
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/**
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* Get metadata about the specified output.
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*
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* @param[in] index The index of the output to look up.
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* @returns The metadata on success, or an error on failure. Only valid for
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* tag::Tensor
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*/
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Result<TensorInfo> output_tensor_meta(size_t index) const;
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/**
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* Get the number of non-constant buffers this method requires.
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*
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* @returns The number of non-constant buffers.
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*/
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size_t num_non_const_buffers() const;
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/**
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* Get the size in bytes of the specified non-constant buffer.
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*
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* @param[in] index The index of the buffer to look up.
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* @returns The size in bytes on success, or an error on failure.
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*/
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Result<int64_t> non_const_buffer_size(size_t index) const;
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private:
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// Let Program create MethodMeta.
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friend class Program;
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explicit MethodMeta(const executorch_flatbuffer::ExecutionPlan* s_plan);
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/// Source of truth for method information
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const executorch_flatbuffer::ExecutionPlan* s_plan_;
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};
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} // namespace executor
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} // namespace torch

‎runtime/executor/program.cpp

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@@ -206,6 +206,18 @@ Result<Method> Program::load_method(
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return Error::InvalidArgument;
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}
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Result<MethodMeta> Program::method_meta(const char* method_name) const {
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EXECUTORCH_SCOPE_PROF("Program::method_meta");
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auto execution_plans = internal_program_->execution_plan();
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for (size_t i = 0; i < execution_plans->size(); i++) {
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auto serialization_plan = execution_plans->GetMutableObject(i);
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if (std::strcmp(serialization_plan->name()->c_str(), method_name) == 0) {
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return MethodMeta(serialization_plan);
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}
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}
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return Error::InvalidArgument;
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}
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const void* Program::get_constant_buffer_data(size_t buffer_idx) const {
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ET_CHECK(is_valid());
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auto internal_program =

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