delete Constants.h

Summary:
https://docs.google.com/spreadsheets/d/17mEkBHN0XwXN21pG2IxpANX-jd4hNMrX4x9FthYB5Ok/edit#gid=0

I dont think this is a file thats worth maintaining in executorch repo, so I'm deleting it.

With this change executorch/core is fully gone

Reviewed By: dbort

Differential Revision:
D47338165

Privacy Context Container: L1124100

fbshipit-source-id: a63eb84aeb18b35d60824f2a1a91fc6d88e55bfb

Author: JacobSzwejbka

backends/test/demos/rpc/ExecutorBackend.cpp

@@ -5,7 +5,6 @@
 #include <cstdlib> /* strtol */
 #include <memory>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/backend/backend_registry.h>
 #include <executorch/runtime/core/error.h>
 #include <executorch/runtime/core/evalue.h>
@@ -88,7 +87,7 @@ class ExecutorBackend final : public PyTorchBackendInterface {
     // dedicated to this specific hardware
     auto client_runtime_allocator = ET_ALLOCATE_INSTANCE_OR_RETURN_ERROR(
         runtime_allocator, MemoryAllocator);
-    const size_t kClientRuntimeMemorySize = 4 * kKB;
+    const size_t kClientRuntimeMemorySize = 4 * 1024U;
     auto runtime_pool = ET_ALLOCATE_OR_RETURN_ERROR(
         runtime_allocator, kClientRuntimeMemorySize);
     new (client_runtime_allocator) MemoryAllocator(

core/Constants.h

@@ -5,7 +5,6 @@
 #include <pybind11/pybind11.h>
 #include <pybind11/stl.h>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/core/data_loader.h>
 #include <executorch/runtime/executor/executor.h>
 #include <executorch/runtime/executor/program.h>
@@ -274,9 +273,10 @@ py::object pyFromEValue(const EValue& v, KeepAlive& keep_alive) {
   ET_ASSERT_UNREACHABLE();
 }
 
-static constexpr size_t kDEFAULT_NON_CONSTANT_POOL_SIZE = 256 * kMB;
-static constexpr size_t kRUNTIME_POOL_SIZE = 256 * kMB;
-static constexpr size_t kDEFAULT_BUNDLED_INPUT_POOL_SIZE = 16 * kKB;
+static constexpr size_t kDEFAULT_NON_CONSTANT_POOL_SIZE =
+    256 * 1024U * 1024U; // 256 MB
+static constexpr size_t kRUNTIME_POOL_SIZE = 256 * 1024U * 1024U; // 256 MB
+static constexpr size_t kDEFAULT_BUNDLED_INPUT_POOL_SIZE = 16 * 1024U;
 
 struct PyBundledModule final {
   explicit PyBundledModule(

core/TARGETS

@@ -27,7 +27,6 @@ def define_common_targets():
         ],
         exported_deps = [
             "//executorch/runtime/platform:platform",
-            "//executorch/core:core",  # for legacy clients that need Constants.h or macros.h TODO remove this
         ],
     )
 
@@ -48,9 +47,11 @@ def define_common_targets():
             "hierarchical_allocator.h",
             "memory_allocator.h",
         ],
+        deps = [
+            "//executorch/profiler:profiler",
+        ],
         exported_deps = [
             ":core",
-            "//executorch/profiler:profiler",
         ],
         visibility = [
             "//executorch/...",

core/targets.bzl

@@ -2,7 +2,6 @@
 #include <filesystem>
 #include <memory>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/core/exec_aten/exec_aten.h>
 #include <executorch/runtime/executor/executor.h>
 #include <executorch/runtime/executor/test/managed_memory_manager.h>
@@ -18,16 +17,15 @@ using exec_aten::Scalar;
 using exec_aten::Tensor;
 using torch::executor::Error;
 using torch::executor::Executor;
-using torch::executor::kKB;
 using torch::executor::MemoryAllocator;
 using torch::executor::MemoryManager;
 using torch::executor::Program;
 using torch::executor::Result;
 using torch::executor::testing::ManagedMemoryManager;
 using torch::executor::util::FileDataLoader;
 
-constexpr size_t kDefaultNonConstMemBytes = 32 * kKB;
-constexpr size_t kDefaultRuntimeMemBytes = 32 * kKB;
+constexpr size_t kDefaultNonConstMemBytes = 32 * 1024U;
+constexpr size_t kDefaultRuntimeMemBytes = 32 * 1024U;
 
 class AllocationFailureStressTest : public ::testing::Test {
  protected:

pybindings/module.cpp

@@ -1,7 +1,6 @@
 #include <cstdlib>
 #include <filesystem>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/core/exec_aten/exec_aten.h>
 #include <executorch/runtime/executor/executor.h>
 #include <executorch/runtime/executor/test/managed_memory_manager.h>
@@ -15,14 +14,13 @@ using exec_aten::ArrayRef;
 using torch::executor::Error;
 using torch::executor::EValue;
 using torch::executor::Executor;
-using torch::executor::kKB;
 using torch::executor::Program;
 using torch::executor::Result;
 using torch::executor::testing::ManagedMemoryManager;
 using torch::executor::util::FileDataLoader;
 
-constexpr size_t kDefaultNonConstMemBytes = 32 * kKB;
-constexpr size_t kDefaultRuntimeMemBytes = 32 * kKB;
+constexpr size_t kDefaultNonConstMemBytes = 32 * 1024U;
+constexpr size_t kDefaultRuntimeMemBytes = 32 * 1024U;
 
 class ExecutionPlanTest : public ::testing::Test {
  protected:

runtime/core/targets.bzl

@@ -4,7 +4,6 @@
 #include <cstring>
 #include <memory>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/core/error.h>
 #include <executorch/runtime/core/result.h>
 #include <executorch/runtime/executor/executor.h>
@@ -24,7 +23,6 @@ using torch::executor::Executor;
 using torch::executor::Kernel;
 using torch::executor::KernelKey;
 using torch::executor::KernelRuntimeContext;
-using torch::executor::kKB;
 using torch::executor::Program;
 using torch::executor::register_kernels;
 using torch::executor::Result;
@@ -34,8 +32,8 @@ using torch::executor::TensorMeta;
 using torch::executor::testing::ManagedMemoryManager;
 using torch::executor::util::FileDataLoader;
 
-constexpr size_t kDefaultNonConstMemBytes = 32 * kKB;
-constexpr size_t kDefaultRuntimeMemBytes = 32 * kKB;
+constexpr size_t kDefaultNonConstMemBytes = 32 * 1024U;
+constexpr size_t kDefaultRuntimeMemBytes = 32 * 1024U;
 
 class KernelResolutionTest : public ::testing::Test {
  protected:

runtime/executor/test/allocation_failure_stress_test.cpp

@@ -1,6 +1,5 @@
 #include <gflags/gflags.h>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/executor/executor.h>
 #include <executorch/runtime/platform/log.h>
 #include <executorch/runtime/platform/profiler.h>
@@ -32,9 +31,9 @@
 
 using namespace torch::executor;
 
-static constexpr size_t kRuntimeMemorySize = 4 * kMB;
+static constexpr size_t kRuntimeMemorySize = 4 * 1024U * 1024U; // 4 MB
 static uint8_t runtime_pool[kRuntimeMemorySize];
-static constexpr size_t kBundledAllocatorPoolSize = 16 * kKB;
+static constexpr size_t kBundledAllocatorPoolSize = 16 * 1024U;
 static uint8_t bundled_allocator_pool[kBundledAllocatorPoolSize];
 
 DEFINE_bool(

runtime/executor/test/execution_plan_test.cpp

@@ -23,7 +23,6 @@
 #include <thread>
 #include <tuple>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/core/error.h>
 #include <executorch/runtime/core/result.h>
 #include <executorch/runtime/executor/executor.h>
@@ -56,7 +55,6 @@ using torch::executor::DataLoader;
 using torch::executor::Error;
 using torch::executor::Executor;
 using torch::executor::FreeableBuffer;
-using torch::executor::kMB;
 using torch::executor::MemoryAllocator;
 using torch::executor::MemoryManager;
 using torch::executor::Program;
@@ -141,8 +139,8 @@ class ModelFactory {
       const std::string& name, // For debugging
       std::shared_ptr<const char> model_data,
       size_t model_data_size,
-      size_t non_const_mem_bytes = 40 * kMB,
-      size_t runtime_mem_bytes = 2 * kMB)
+      size_t non_const_mem_bytes = 40 * 1024U * 1024U, // 40 MB
+      size_t runtime_mem_bytes = 2 * 1024U * 1024U) // 2 MB
       : name_(name),
         model_data_(model_data),
         model_data_size_(model_data_size),

runtime/executor/test/kernel_resolution_test.cpp

@@ -1,7 +1,6 @@
 #include <memory>
 #include <vector>
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/executor/executor.h>
 #include <executorch/runtime/platform/log.h>
 #include <executorch/runtime/platform/runtime.h>
@@ -29,12 +28,12 @@ using namespace torch::executor;
  * This tool demonstrates that the memory can be managed this way.
  */
 
-static constexpr size_t kRuntimeMemorySize = 2 * kMB;
+static constexpr size_t kRuntimeMemorySize = 2 * 1024U * 1024U; // 2MB
 static uint8_t runtime_pool[kRuntimeMemorySize];
 
 // This is to emulate the local memory that a particular instance of hardware
 // own and shared across different model instances
-static constexpr size_t kNonConstantMemorySize = 10 * kMB;
+static constexpr size_t kNonConstantMemorySize = 10 * 1024U * 1024U; // 10MB
 static uint8_t shared_local_non_constant_pool[kNonConstantMemorySize];
 
 #define MAX_INPUTS_PER_MODEL 16
@@ -247,7 +246,7 @@ int main(int argc, char** argv) {
    * Step 2: Prepare the memory space required for worker core
    */
   // The actual allocation size can be backend/model specific and smaller
-  constexpr size_t kWorkerBufferSize = 1 * kMB;
+  constexpr size_t kWorkerBufferSize = 1 * 1024U * 1024U; // 1 MB
   auto worker_buffer = std::make_unique<uint8_t[]>(kWorkerBufferSize);
   MemoryAllocator worker_allocator(kWorkerBufferSize, worker_buffer.get());
 

test/executor_runner.cpp

@@ -1,4 +1,3 @@
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/executor/executor.h>
 #include <executorch/runtime/executor/program.h>
 #include <executorch/runtime/platform/log.h>

test/multi_runner.cpp

@@ -1,6 +1,5 @@
 #pragma once
 
-#include <executorch/core/Constants.h>
 #include <executorch/runtime/executor/memory_manager.h>
 #include <memory>
 
@@ -12,10 +11,10 @@
 constexpr size_t NUM_NON_CONSTANT_POOLS = 1;
 
 // NON_CONSTANT_POOL_SIZE is set at compilation
-constexpr size_t NON_CONSTANT_POOL_SIZE = 2 * torch::executor::kMB;
+constexpr size_t NON_CONSTANT_POOL_SIZE = 2 * 1024U * 1024U; // 2MB
 
 // Memory used to save executor related structures
-constexpr size_t EXECUTOR_POOL_SIZE = 128 * torch::executor::kKB;
+constexpr size_t EXECUTOR_POOL_SIZE = 128 * 1024U;
 
 namespace torch {
 namespace executor {