repo stringlengths 1 152 ⌀ | file stringlengths 14 221 | code stringlengths 501 25k | file_length int64 501 25k | avg_line_length float64 20 99.5 | max_line_length int64 21 134 | extension_type stringclasses 2
values |
|---|---|---|---|---|---|---|
null | pytorch-main/torch/csrc/api/include/torch/serialize/output-archive.h | #pragma once
#include <torch/csrc/Export.h>
#include <torch/csrc/jit/api/module.h>
#include <iosfwd>
#include <memory>
#include <string>
#include <utility>
namespace at {
class Tensor;
} // namespace at
namespace torch {
using at::Tensor;
namespace jit {
struct Module;
} // namespace jit
} // namespace torch
names... | 2,315 | 26.903614 | 79 | h |
null | pytorch-main/torch/csrc/autograd/VariableTypeUtils.h | #pragma once
#include <c10/util/irange.h>
#include <ATen/core/boxing/KernelFunction.h>
#include <ATen/core/dispatch/Dispatcher.h>
#include <torch/csrc/autograd/edge.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/functions/basic_ops.h>
#include <torch/csrc/autograd/functions/tensor.h>
#inc... | 18,647 | 34.052632 | 123 | h |
null | pytorch-main/torch/csrc/autograd/anomaly_mode.h | #pragma once
#include <torch/csrc/Export.h>
#include <memory>
#include <string>
namespace torch {
namespace autograd {
// forward declaration of Node from function.h
struct Node;
struct TORCH_API AnomalyMode {
static bool is_enabled() {
return _enabled;
}
static bool should_check_nan() {
return _check... | 1,749 | 22.648649 | 71 | h |
null | pytorch-main/torch/csrc/autograd/autograd.h | #pragma once
#include <torch/csrc/autograd/variable.h>
namespace torch {
namespace autograd {
/// Computes the sum of gradients of given tensors with respect to graph leaves.
///
/// The graph is differentiated using the chain rule. If any of ``tensors``
/// are non-scalar (i.e. their data has more than one element)... | 5,334 | 48.859813 | 80 | h |
null | pytorch-main/torch/csrc/autograd/autograd_not_implemented_fallback.h | #pragma once
#include <torch/library.h>
namespace torch {
namespace autograd {
// Default DispatchKey::Autograd fallback for built-in operators.
// Can be registered for custom operators.
TORCH_API torch::CppFunction autogradNotImplementedFallback();
// Default DispatchKey::AdInplaceOrView fallback for built-in ope... | 1,167 | 32.371429 | 78 | h |
null | pytorch-main/torch/csrc/autograd/cpp_hook.h | #pragma once
#include <torch/csrc/autograd/function_hook.h>
#include <functional>
#include <memory>
namespace torch {
namespace autograd {
using hooks_list =
std::vector<std::function<at::TensorBase(const at::TensorBase&)>>;
struct CppFunctionTensorPreHook : public FunctionPreHook {
CppFunctionTensorPreHook(st... | 878 | 26.46875 | 77 | h |
null | pytorch-main/torch/csrc/autograd/custom_function.h | #pragma once
#include <ATen/core/ivalue.h>
#include <c10/core/SymInt.h>
#include <c10/util/flat_hash_map.h>
#include <c10/util/irange.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/variable.h>
#include <vector>
namespace torch {
namespace autograd {
using optional_variable_list = std::vec... | 15,411 | 34.675926 | 80 | h |
null | pytorch-main/torch/csrc/autograd/edge.h | #pragma once
#include <cstdint>
#include <functional>
#include <memory>
#include <c10/util/hash.h>
namespace torch {
namespace autograd {
struct Node;
/// Represents a particular input of a function.
struct Edge {
Edge() noexcept : function(nullptr), input_nr(0) {}
Edge(std::shared_ptr<Node> function_, uint32... | 1,640 | 26.813559 | 80 | h |
null | pytorch-main/torch/csrc/autograd/engine.h | #pragma once
// Engine implements backpropagation from output variables and their gradients
// to "root" variables (variables created by the user with requires_grad=True).
#include <ATen/Tensor.h>
#include <ATen/ThreadLocalState.h>
#include <ATen/core/ivalue.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/auto... | 10,400 | 35.367133 | 82 | h |
null | pytorch-main/torch/csrc/autograd/forward_grad.h | #pragma once
#include <ATen/core/Tensor.h>
#include <unordered_set>
namespace torch {
namespace autograd {
// [ Using ForwardGrad ]
// ForwardGrad needs to be a shared_ptr to satisfy constraints of its inner
// design. But this shared_ptr must be uniquely associated with the object that
// stores it (as of writing, ... | 8,963 | 41.084507 | 80 | h |
null | pytorch-main/torch/csrc/autograd/function_hook.h | #pragma once
#include <ATen/Tensor.h>
#include <torch/csrc/Export.h>
#include <vector>
// A hook that's called on gradients
namespace torch {
namespace autograd {
using Variable = at::Tensor;
using variable_list = std::vector<Variable>;
struct TORCH_API FunctionPreHook {
virtual ~FunctionPreHook() = default;
v... | 664 | 21.931034 | 67 | h |
null | pytorch-main/torch/csrc/autograd/graph_task.h | #pragma once
#include <ATen/ThreadLocalState.h>
#include <ATen/core/Tensor.h>
#include <c10/util/ThreadLocal.h>
#include <torch/csrc/autograd/input_buffer.h>
#include <torch/csrc/autograd/utils/warnings.h>
#include <vector>
namespace torch {
namespace autograd {
using edge_list = std::vector<Edge>;
struct ReadyQueue;... | 9,715 | 38.983539 | 80 | h |
null | pytorch-main/torch/csrc/autograd/input_buffer.h | #pragma once
// The InputBuffer class accumulates a list of Variables for use by a
// function. It implements logic to avoid modifying the passed
// values in-place (adding an input twice will accumulate the result).
// This behaviour is needed and used only in backward graphs.
#include <memory>
#include <utility>
#i... | 1,461 | 28.836735 | 77 | h |
null | pytorch-main/torch/csrc/autograd/input_metadata.h | #pragma once
#include <ATen/ExpandUtils.h>
#include <ATen/NestedTensorImpl.h>
#include <ATen/core/Tensor.h>
#include <c10/core/Device.h>
#include <c10/core/DeviceType.h>
#include <c10/core/Stream.h>
#include <c10/core/SymIntArrayRef.h>
#include <c10/core/TensorImpl.h>
#include <c10/core/impl/DeviceGuardImplInterface.h... | 5,261 | 28.561798 | 86 | h |
null | pytorch-main/torch/csrc/autograd/jit_decomp_interface.h | #pragma once
#include <ATen/core/Tensor.h>
#include <ATen/core/function_schema.h>
#include <c10/macros/Export.h>
// NOTE: [Jit Decomposition Interface]
//
// For some context of why we need this at all, see NOTE: [forward-mode AD
// decompositions mechanism]
//
// Introducing that mechanism from the NOTE is problemat... | 1,848 | 32.618182 | 80 | h |
null | pytorch-main/torch/csrc/autograd/profiler_kineto.h | #pragma once
#include <string>
#include <vector>
#include <torch/csrc/profiler/api.h>
#include <torch/csrc/profiler/events.h>
#include <torch/csrc/profiler/stubs/base.h>
#include <torch/csrc/profiler/util.h>
namespace torch {
namespace profiler {
namespace impl {
struct Result;
namespace kineto {
struct ActivityTrac... | 6,803 | 34.623037 | 80 | h |
null | pytorch-main/torch/csrc/autograd/profiler_legacy.h | #pragma once
#include <cstdint>
#include <forward_list>
#include <iostream>
#include <memory>
#include <mutex>
#include <sstream>
#include <string>
#include <tuple>
#include <vector>
#include <torch/csrc/Export.h>
#include <torch/csrc/profiler/api.h>
#include <torch/csrc/profiler/stubs/base.h>
#include <torch/csrc/pr... | 11,161 | 25.703349 | 131 | h |
null | pytorch-main/torch/csrc/autograd/python_anomaly_mode.h | #pragma once
#include <pybind11/pybind11.h>
#include <torch/csrc/autograd/anomaly_mode.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/auto_gil.h>
#include <torch/csrc/utils/pybind.h>
namespace torch {
namespace autograd {
struct PyAnomalyMetadata : public AnomalyMetadata {
static constexpr co... | 1,127 | 24.066667 | 72 | h |
null | pytorch-main/torch/csrc/autograd/python_cpp_function.h | #pragma once
#include <torch/csrc/python_headers.h>
#include <memory>
#include <typeinfo>
#include <torch/csrc/Exceptions.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/utils/object_ptr.h>
namespace torch {
namespace autograd {
struct THPCppFunction {
PyObject_HEAD std::shared_ptr<Node> cdata;
... | 4,076 | 38.970588 | 80 | h |
null | pytorch-main/torch/csrc/autograd/python_engine.h | #pragma once
#include <torch/csrc/python_headers.h>
#include <torch/csrc/autograd/engine.h>
#include <torch/csrc/autograd/function.h>
bool THPEngine_initModule(PyObject* module);
namespace torch {
namespace autograd {
namespace python {
struct PythonEngine : public Engine {
static Engine& get_python_engine();
... | 1,299 | 25.530612 | 72 | h |
null | pytorch-main/torch/csrc/autograd/python_function.h | #pragma once
#include <torch/csrc/python_headers.h>
#include <torch/csrc/Exceptions.h>
#include <torch/csrc/autograd/custom_function.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/saved_variable.h>
#include <torch/csrc/autograd/variable.h>
#include <torch/csrc/utils/object_ptr.h>
#include... | 4,428 | 32.55303 | 79 | h |
null | pytorch-main/torch/csrc/autograd/python_hook.h | #pragma once
#include <torch/csrc/autograd/function_hook.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/object_ptr.h>
namespace torch {
namespace autograd {
struct PyFunctionTensorPreHook : public FunctionPreHook {
PyFunctionTensorPreHook(PyObject* dict, int value_idx);
~PyFunctionTensorPre... | 954 | 25.527778 | 65 | h |
null | pytorch-main/torch/csrc/autograd/python_saved_variable_hooks.h | #pragma once
#include <ATen/ATen.h>
#include <pybind11/pybind11.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/python_variable.h>
#include <torch/csrc/autograd/saved_variable_hooks.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/pybind.h>
namespace py = pybind11;
namespace torch... | 958 | 25.638889 | 77 | h |
null | pytorch-main/torch/csrc/autograd/python_torch_functions.h | #include <Python.h>
#include <vector>
namespace torch {
namespace autograd {
extern PyObject* THPVariableFunctionsModule;
// Wrapper converts a raised TypeError into returning NotImplemented
// Used to implement binary arithmetic operators
template <PyObject* (*Func)(PyObject*, PyObject*, PyObject*)>
inline PyObjec... | 694 | 22.166667 | 68 | h |
null | pytorch-main/torch/csrc/autograd/python_variable.h | #pragma once
#include <ATen/core/Tensor.h>
#include <torch/csrc/python_headers.h>
#include <memory>
#include <ATen/core/function_schema.h>
#include <pybind11/pybind11.h>
#include <torch/csrc/Exceptions.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/variable.h>
#include <torch/csrc/utils/pybind.h>
na... | 3,031 | 27.87619 | 75 | h |
null | pytorch-main/torch/csrc/autograd/python_variable_indexing.h | #pragma once
#include <c10/core/SymInt.h>
#include <torch/csrc/autograd/python_variable.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/pybind.h>
#include <torch/csrc/utils/python_symnode.h>
namespace torch {
namespace autograd {
struct UnpackedSlice {
c10::SymInt start;
c10::SymInt stop;
... | 2,947 | 27.07619 | 78 | h |
null | pytorch-main/torch/csrc/autograd/record_function_ops.h | #pragma once
#include <ATen/record_function.h>
#include <c10/util/Optional.h>
#include <torch/custom_class.h>
namespace torch {
namespace autograd {
namespace profiler {
struct PythonRecordFunction : public torch::CustomClassHolder {
at::RecordFunction record;
explicit PythonRecordFunction(
at::RecordScope... | 996 | 30.15625 | 81 | h |
null | pytorch-main/torch/csrc/autograd/saved_variable.h | #pragma once
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/forward_grad.h>
#include <torch/csrc/autograd/saved_variable_hooks.h>
#include <ATen/core/Tensor.h>
#include <cstdint>
#include <memory>
namespace torch {
namespace autograd {
using Variable = at::Tensor;
struct Node;
TORCH_API extern const... | 4,709 | 36.983871 | 80 | h |
null | pytorch-main/torch/csrc/autograd/functions/accumulate_grad.h | #pragma once
#include <ATen/CachedTensorUtils.h>
#include <ATen/LegacyBatchedTensorImpl.h>
#include <ATen/TensorOperators.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/utils/grad_layout_contract.h>
#include <torch/csrc/autograd/variable.h>
#ifndef AT_PER_OPE... | 13,105 | 48.643939 | 88 | h |
null | pytorch-main/torch/csrc/autograd/functions/basic_ops.h | #pragma once
#include <c10/util/irange.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/variable.h>
#include <memory>
#include <string>
#include <vector>
namespace torch {
namespace autograd {
struct TORCH_API Error : public Node {
Error(std::string msg, ed... | 2,701 | 27.442105 | 80 | h |
null | pytorch-main/torch/csrc/autograd/functions/comm.h | #pragma once
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/variable.h>
#include <ATen/ATen.h>
#include <ATen/cuda/ATenCUDAGeneral.h>
#include <ATen/cuda/CUDAContext.h>
#include <cstddef>
#include <vector>
namespace torch {
namespace autograd {
struct TORCH_C... | 1,243 | 24.916667 | 79 | h |
null | pytorch-main/torch/csrc/autograd/functions/tensor.h | #pragma once
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/variable.h>
#include <ATen/TensorGeometry.h>
#include <ATen/core/DeprecatedTypeProperties.h>
#include <c10/util/Optional.h>
#include <cstdint>
#include <memory>
namespace torch {
namespace autograd {
... | 6,834 | 38.057143 | 82 | h |
null | pytorch-main/torch/csrc/autograd/functions/utils.h | #pragma once
#include <torch/csrc/Export.h>
#include <torch/csrc/autograd/InferenceMode.h>
#include <torch/csrc/autograd/autograd.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/variable.h>
#include <torch/csrc/utils/variadic.h>
#include <ATen/core/Tensor.h>
#include <functional>
#include ... | 3,374 | 26.439024 | 80 | h |
null | pytorch-main/torch/csrc/autograd/utils/error_messages.h | #pragma once
#include <sstream>
namespace torch {
namespace autograd {
namespace utils {
inline std::string requires_grad_leaf_error(bool requires_grad) {
std::ostringstream oss;
oss << "you can only change requires_grad flags of leaf variables.";
if (requires_grad == false) {
oss << " If you want to use a... | 545 | 22.73913 | 70 | h |
null | pytorch-main/torch/csrc/autograd/utils/grad_layout_contract.h | #pragma once
#include <ATen/Tensor.h>
namespace torch {
namespace autograd {
namespace utils {
// Helper functions to enforce the "Gradient Layout Contract" described in
// torch/csrc/autograd/functions/accumulate_grad.h.
// Checks if grad obeys the contract with variable.
inline bool obeys_layout_contract(
con... | 2,829 | 34.375 | 77 | h |
null | pytorch-main/torch/csrc/autograd/utils/lambda_post_hook.h | #pragma once
#include <torch/csrc/autograd/function_hook.h>
namespace torch {
namespace autograd {
namespace utils {
// Turns lambda into a torch::autograd::FunctionPostHook.
class LambdaPostHook : public torch::autograd::FunctionPostHook {
using variable_list = std::vector<torch::autograd::Variable>;
public:
... | 976 | 26.914286 | 79 | h |
null | pytorch-main/torch/csrc/autograd/utils/python_arg_parsing.h | #pragma once
#include <ATen/core/Tensor.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/python_arg_parser.h>
namespace torch {
namespace autograd {
namespace utils {
// The parameter allow_copy is to accept copy for Tensor.to (and by proxy
// PackedSequences.to) but not nn.Module.to.
inline std... | 1,473 | 26.296296 | 73 | h |
null | pytorch-main/torch/csrc/autograd/utils/warnings.h | #pragma once
#include <c10/util/Exception.h>
#include <mutex>
#include <vector>
namespace torch {
namespace autograd {
namespace utils {
// Warning handler for multi-threaded contexts. Gather warnings from
// all threads into a single queue, then process together at the end
// in the main thread.
class DelayWarningH... | 633 | 20.862069 | 68 | h |
null | pytorch-main/torch/csrc/autograd/utils/wrap_outputs.h | #pragma once
// Wrap tensor operation outputs as PyObject*
#include <ATen/ScalarOps.h>
#include <ATen/core/Tensor.h>
#include <c10/util/irange.h>
#include <torch/csrc/python_headers.h>
#include <initializer_list>
#include <tuple>
#include <torch/csrc/Dtype.h>
#include <torch/csrc/DynamicTypes.h>
#include <torch/csrc... | 3,723 | 23.5 | 72 | h |
null | pytorch-main/torch/csrc/cuda/CUDAPluggableAllocator.h | #pragma once
#include <c10/core/Allocator.h>
#include <c10/cuda/CUDAGraphsC10Utils.h>
#include <c10/cuda/CUDAMacros.h>
#include <c10/cuda/CUDAStream.h>
#include <c10/cuda/CUDACachingAllocator.h>
#include <array>
#include <mutex>
namespace torch {
namespace cuda {
namespace CUDAPluggableAllocator {
#if defined(TO... | 5,443 | 35.293333 | 79 | h |
null | pytorch-main/torch/csrc/cuda/comm.h | #pragma once
#include <ATen/ATen.h>
#include <ATen/cuda/ATenCUDAGeneral.h>
#include <ATen/cuda/CUDAContext.h>
#include <c10/util/Optional.h>
#include <torch/csrc/Export.h>
#include <cstddef>
#include <vector>
namespace torch {
namespace cuda {
using tensor_list2d = std::vector<std::vector<at::Tensor>>;
TORCH_CUDA_... | 1,549 | 27.703704 | 74 | h |
null | pytorch-main/torch/csrc/cuda/memory_snapshot.h | #pragma once
#include <torch/csrc/Export.h>
#include <string>
namespace torch {
namespace cuda {
// C++-only versions of these, for python use
// those defined in cuda/Module.cpp which also record python state.
TORCH_CUDA_CU_API void _record_memory_history(
bool enabled,
bool record_context = true,
int64... | 536 | 23.409091 | 67 | h |
null | pytorch-main/torch/csrc/cuda/nccl.h | #pragma once
#include <ATen/ATen.h>
#include <ATen/cuda/CUDAContext.h>
#include <c10/util/Optional.h>
#include <cstddef>
#include <vector>
// NCCL BFloat16 is enabled only for CUDA 11+ and NCCL versions 2.10+, or for
// HIP 3.1+
#if defined(__CUDA_BF16_TYPES_EXIST__)
#define HAS_NCCL_BF16_DATATYPE \
((NCCL_MAJOR >... | 5,917 | 25.657658 | 80 | h |
null | pytorch-main/torch/csrc/cuda/python_nccl.h | #pragma once
#include <torch/csrc/python_headers.h>
PyObject* THCPModule_nccl_version(PyObject* self, PyObject* args);
PyObject* THCPModule_nccl_unique_id(PyObject* self, PyObject* args);
PyObject* THCPModule_nccl_init_rank(PyObject* self, PyObject* args);
PyObject* THCPModule_nccl_reduce(PyObject* self, PyObject* ar... | 608 | 45.846154 | 73 | h |
null | pytorch-main/torch/csrc/distributed/autograd/autograd.h | #pragma once
#include <torch/csrc/distributed/autograd/context/container.h>
#include <torch/csrc/distributed/autograd/engine/dist_engine.h>
namespace torch {
namespace distributed {
namespace autograd {
using torch::autograd::variable_list;
/// C++ API of Distributed Autograd that kicks off the distributed backward... | 1,686 | 40.146341 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/utils.h | #pragma once
#include <torch/csrc/distributed/autograd/context/context.h>
#include <torch/csrc/distributed/autograd/rpc_messages/rpc_with_autograd.h>
#include <torch/csrc/distributed/autograd/rpc_messages/rpc_with_profiling_req.h>
#include <torch/csrc/distributed/autograd/rpc_messages/rpc_with_profiling_resp.h>
names... | 2,697 | 43.229508 | 81 | h |
null | pytorch-main/torch/csrc/distributed/autograd/context/container.h | #pragma once
#include <mutex>
#include <unordered_map>
#include <torch/csrc/distributed/autograd/context/context.h>
namespace torch {
namespace distributed {
namespace autograd {
// Singleton class per worker which is responsible for storing the distributed
// autograd context for each autograd pass and also cleans... | 6,435 | 37.309524 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/context/context.h | #pragma once
#include <cstdint>
#include <functional>
#include <ATen/core/Dict.h>
#include <torch/csrc/autograd/engine.h>
#include <torch/csrc/distributed/autograd/functions/recvrpc_backward.h>
#include <torch/csrc/distributed/autograd/functions/sendrpc_backward.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
n... | 6,623 | 36.851429 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/engine/dist_engine.h | #pragma once
#include <mutex>
#include <unordered_set>
#include <torch/csrc/autograd/engine.h>
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/autograd/functions/basic_ops.h>
#include <torch/csrc/distributed/autograd/context/context.h>
namespace torch {
namespace distributed {
namespace autograd {
//... | 7,465 | 41.180791 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/functions/recvrpc_backward.h | #pragma once
#include <torch/csrc/autograd/function.h>
#include <torch/csrc/distributed/autograd/context/context.h>
#include <torch/csrc/distributed/autograd/rpc_messages/autograd_metadata.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
namespace torch {
namespace distributed {
namespace autograd {
// Forward d... | 1,705 | 33.12 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/functions/sendrpc_backward.h | #pragma once
#include <torch/csrc/autograd/function.h>
namespace torch {
namespace distributed {
namespace autograd {
// As part of our distributed autograd implementation, whenever we send an RPC
// from one node to another, we add a 'SendRpcBackward' autograd function to the
// autograd graph. This is more or less... | 1,373 | 35.157895 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/autograd_metadata.h | #pragma once
#include <torch/csrc/Export.h>
#include <cstdint>
namespace torch {
namespace distributed {
namespace autograd {
// This structure represents autograd metadata that we need to pass across
// different nodes when we call an RPC which needs autograd computation.
struct TORCH_API AutogradMetadata {
Autog... | 750 | 27.884615 | 75 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/cleanup_autograd_context_req.h | #pragma once
#include <torch/csrc/distributed/autograd/rpc_messages/autograd_metadata.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
namespace torch {
namespace distributed {
namespace autograd {
// Used to request other workers to clean up their autograd ... | 886 | 28.566667 | 75 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/cleanup_autograd_context_resp.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
namespace torch {
namespace distributed {
namespace autograd {
// Empty response for CleanupAutogradContextReq. Send to acknowledge receipt of
// a CleanupAutogradContextReq.
class TORCH_API CleanupA... | 711 | 28.666667 | 79 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/propagate_gradients_req.h | #pragma once
#include <torch/csrc/distributed/autograd/rpc_messages/autograd_metadata.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <vector>
namespace torch {
namespace distributed {
namespace autograd {
// Used to propagate gradients from one no... | 1,298 | 29.209302 | 76 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/propagate_gradients_resp.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
namespace torch {
namespace distributed {
namespace autograd {
// Response for the PropagateGradients call. Currently, this class is mostly
// just a placeholder and sends an empty message over the w... | 804 | 31.2 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/rpc_with_autograd.h | #pragma once
#include <torch/csrc/distributed/autograd/rpc_messages/autograd_metadata.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
namespace torch {
namespace distributed {
namespace autograd {
// Represents an RPC that includes autograd information. T... | 3,556 | 34.929293 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/rpc_with_profiling_req.h | #pragma once
#include <torch/csrc/autograd/profiler.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
namespace torch {
namespace distributed {
namespace autograd {... | 2,347 | 36.269841 | 77 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/rpc_with_profiling_resp.h | #pragma once
#include <torch/csrc/autograd/profiler.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
namespace torch {
namespace distributed {
namespace autograd {... | 2,307 | 37.466667 | 80 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/rref_backward_req.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
namespace torch {
namespace distributed {
namespace autograd {
// Internal system RPC to invoke distributed backward pass on remote nodes when
// 'rref.b... | 1,027 | 24.7 | 79 | h |
null | pytorch-main/torch/csrc/distributed/autograd/rpc_messages/rref_backward_resp.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
namespace torch {
namespace distributed {
namespace autograd {
// Response for the RRefBackwardReq.
class TORCH_API RRefBackwardResp : public rpc::RpcCommandBase {
public:
RRefBackwardResp() = def... | 558 | 24.409091 | 63 | h |
null | pytorch-main/torch/csrc/distributed/c10d/TraceUtils.h | #pragma once
#include <c10/util/irange.h>
#include <torch/csrc/distributed/c10d/Store.hpp>
#include <torch/csrc/distributed/c10d/Types.hpp>
#include <sys/types.h>
#include <cstdlib>
#include <string>
#include <system_error>
#include <vector>
namespace c10d {
inline std::string getTraceStartKey(const std::string& pg... | 6,944 | 25.711538 | 80 | h |
null | pytorch-main/torch/csrc/distributed/c10d/debug.h | // Copyright (c) Meta Platforms, Inc. and its 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.
#pragma once
#include <c10/macros/Macros.h>
namespace c10d {
enum class DebugLevel { Off = 0, Info ... | 604 | 24.208333 | 75 | h |
null | pytorch-main/torch/csrc/distributed/c10d/error.h | // Copyright (c) Facebook, Inc. and its 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.
#pragma once
#include <cstring>
#include <system_error>
#include <fmt/format.h>
namespace fmt {
template... | 1,361 | 22.894737 | 80 | h |
null | pytorch-main/torch/csrc/distributed/c10d/logging.h | // Copyright (c) Meta Platforms, Inc. and its 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.
#pragma once
#include <string>
#include <c10/macros/Macros.h>
#include <c10/util/Logging.h>
#include... | 2,059 | 38.615385 | 80 | h |
null | pytorch-main/torch/csrc/distributed/c10d/python_comm_hook.h | #pragma once
#include <torch/csrc/distributed/c10d/comm.hpp>
#include <ATen/ATen.h>
#include <ATen/core/ivalue.h>
#include <torch/csrc/distributed/c10d/ProcessGroup.hpp>
#include <torch/csrc/utils/pybind.h>
namespace c10d {
class TORCH_PYTHON_API PythonCommHook : public CommHookInterface {
public:
// Takes a sta... | 1,072 | 29.657143 | 80 | h |
null | pytorch-main/torch/csrc/distributed/c10d/quantization/quantization.h | // Copyright (c) Meta Platforms, Inc. and affiliates.
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#pragma once
#include <ATen/ATen.h>
#include <vector>
namespace torch {
namespace distributed {
namespace c10d {
namespace quant... | 548 | 22.869565 | 72 | h |
null | pytorch-main/torch/csrc/distributed/c10d/quantization/quantization_gpu.h | // Copyright (c) Meta Platforms, Inc. and affiliates.
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#pragma once
#include <ATen/ATen.h>
#include <vector>
namespace torch {
namespace distributed {
namespace c10d {
namespace quant... | 550 | 22.956522 | 72 | h |
null | pytorch-main/torch/csrc/distributed/c10d/quantization/quantization_utils.h | // Copyright (c) Meta Platforms, Inc. and affiliates.
//
// This source code is licensed under the BSD-style license found in the
// LICENSE file in the root directory of this source tree.
#pragma once
#include <ATen/ATen.h>
#include <typeinfo>
inline std::string torch_tensor_device_name(const at::Tensor& ten) {
... | 1,256 | 34.914286 | 72 | h |
null | pytorch-main/torch/csrc/distributed/rpc/agent_utils.h | #pragma once
#include <torch/csrc/distributed/c10d/PrefixStore.hpp>
#include <torch/csrc/distributed/rpc/utils.h>
namespace torch {
namespace distributed {
namespace rpc {
// All RPC peers should call into this function at the same time. Each peer
// provides its own id and name, and this function uses the given Sto... | 1,639 | 33.893617 | 79 | h |
null | pytorch-main/torch/csrc/distributed/rpc/message.h | #pragma once
#include <torch/types.h>
#include <vector>
namespace torch {
namespace distributed {
namespace rpc {
// An enum denoting common RPC errors to allow specific error handling for them.
enum RPCErrorType {
UNKNOWN_ERROR = 0, /* Indicates that error type could not be parsed */
TIMEOUT = 1, /* Indicates t... | 7,527 | 37.804124 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/py_rref.h | #pragma once
#include <torch/csrc/distributed/rpc/rref_impl.h>
#include <torch/csrc/python_headers.h>
#include <torch/csrc/utils/pybind.h>
namespace torch {
namespace distributed {
namespace rpc {
enum RRefProxyType { RPC_SYNC, RPC_ASYNC, REMOTE };
// Python wrapper of an RRef shared_ptr that supports Python
// pic... | 2,939 | 34 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/python_call.h | #pragma once
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
namespace torch {
namespace distributed {
namespace rpc {
// RPC call representing calling a Python function over RPC.
class TORCH_API PythonCall final : public RpcCommandBase {
public:
PythonCall(S... | 790 | 22.969697 | 73 | h |
null | pytorch-main/torch/csrc/distributed/rpc/python_functions.h | #pragma once
#include <torch/csrc/distributed/rpc/py_rref.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/jit/python/pybind_utils.h>
#include <torch/csrc/utils/pybind.h>
namespace torch {
namespace distributed {
namespace rpc {
// Converts an internal ivalue::Future of Message into a user-f... | 2,307 | 31.507042 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/python_remote_call.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/jit/serialization/pickler.h>
#include <vector>
namespace torch {
namespace distributed {
namespace rpc {
class TORCH_API PythonRemot... | 1,184 | 22.7 | 79 | h |
null | pytorch-main/torch/csrc/distributed/rpc/python_resp.h | #pragma once
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
namespace torch {
namespace distributed {
namespace rpc {
// RPC call representing the response of a Python UDF over RPC.
class TORCH_API PythonResp final : public RpcCommandBase {
public:
explicit ... | 671 | 23 | 73 | h |
null | pytorch-main/torch/csrc/distributed/rpc/python_rpc_handler.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/jit/frontend/script_type_parser.h>
#include <torch/csrc/utils/pybind.h>
namespace torch {
namespace distributed {
namespace rpc {
// Singleton class provides interface to execute python UDF... | 5,004 | 36.350746 | 79 | h |
null | pytorch-main/torch/csrc/distributed/rpc/request_callback.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
namespace torch {
namespace distributed {
namespace rpc {
// Functor which is invoked to process an RPC message. This is an abstract class
// with some common functionality across all request handlers. Users need to
// implement this interface to perform t... | 1,276 | 33.513514 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/request_callback_impl.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/request_callback_no_python.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/jit/python/pybind.h>
namespace torch {
namespace distributed {
namespace rpc {
class TORCH_API RequestCallbackI... | 2,083 | 30.575758 | 77 | h |
null | pytorch-main/torch/csrc/distributed/rpc/request_callback_no_python.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/request_callback.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/rref_impl.h>
#include <torch/csrc/distributed/rpc/script_call.h>
#include <torch/csrc/distributed/rpc/scrip... | 3,884 | 31.375 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/rpc_agent.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/request_callback.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <algorithm>
#include <cctype>
#include <chrono>
#include <condition_variable>
#include <mutex>
#include <thread>
namespace torch {
namespace dis... | 13,445 | 38.315789 | 85 | h |
null | pytorch-main/torch/csrc/distributed/rpc/rpc_command_base.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/types.h>
namespace torch {
namespace distributed {
namespace rpc {
// Base class for all RPC request and responses.
class RpcCommandBase {
public:
// Need to override this to serialize the RPC. This should destructiv... | 728 | 25.035714 | 74 | h |
null | pytorch-main/torch/csrc/distributed/rpc/rref_context.h | #pragma once
#include <c10/util/Optional.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/distributed/rpc/rref_impl.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/distributed/rpc/utils.h>
#include <atomic>
namespace torch... | 15,829 | 45.558824 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/rref_impl.h | #pragma once
#include <ATen/core/jit_type.h>
#include <ATen/core/rref_interface.h>
#include <c10/core/Event.h>
#include <c10/util/Optional.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <atomic>
namespace tor... | 16,159 | 37.384798 | 115 | h |
null | pytorch-main/torch/csrc/distributed/rpc/rref_proto.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/jit/runtime/operator.h>
#include <torch/csrc/jit/serialization/pickler.h>
#include <vector>
namespace torch {
namespace distributed {... | 5,332 | 30.934132 | 79 | h |
null | pytorch-main/torch/csrc/distributed/rpc/script_call.h | #pragma once
#include <c10/util/Optional.h>
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/jit/runtime/operator.h>
#include <torch/csrc/jit/serialization/pickler.h>
#include <vector>
namespace torch {
namespace distributed {
namespace rpc ... | 2,527 | 34.111111 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/script_remote_call.h | #pragma once
#include <torch/csrc/distributed/rpc/script_call.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/jit/runtime/operator.h>
#include <torch/csrc/jit/serialization/pickler.h>
#include <vector>
namespace torch {
namespace distributed {
namespace rpc {
using torch::jit::Operator;
// A S... | 1,652 | 27.5 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/script_resp.h | #pragma once
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/jit/serialization/pickler.h>
namespace torch {
namespace distributed {
namespace rpc {
// Return value of a builtin operator or a TorchScript function.
class TORCH_API ScriptResp... | 678 | 24.148148 | 73 | h |
null | pytorch-main/torch/csrc/distributed/rpc/tensorpipe_agent.h | #pragma once
#ifdef USE_TENSORPIPE
#include <atomic>
#include <thread>
#include <c10/core/thread_pool.h>
#include <torch/csrc/distributed/c10d/PrefixStore.hpp>
#include <torch/csrc/distributed/c10d/Store.hpp>
#include <torch/csrc/distributed/rpc/rpc_agent.h>
// Forward-declare the TensorPipe classes we need, to avo... | 17,423 | 34.129032 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/tensorpipe_utils.h | #pragma once
#ifdef USE_TENSORPIPE
#include <torch/csrc/distributed/rpc/utils.h>
namespace tensorpipe {
class Message;
class Allocation;
class Descriptor;
} // namespace tensorpipe
namespace torch {
namespace distributed {
namespace rpc {
TORCH_API const c10::Stream& getStreamForDevice(
const std::vector<c10::... | 4,748 | 37.298387 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/torchscript_functions.h | #pragma once
#include <ATen/core/ivalue.h>
#include <torch/csrc/autograd/profiler.h>
#include <torch/csrc/distributed/autograd/utils.h>
#include <torch/csrc/distributed/rpc/rref_context.h>
#include <torch/csrc/distributed/rpc/script_remote_call.h>
namespace torch {
namespace distributed {
namespace rpc {
// This fun... | 1,707 | 39.666667 | 78 | h |
null | pytorch-main/torch/csrc/distributed/rpc/types.h | #pragma once
#include <ATen/core/ivalue.h>
#include <atomic>
namespace torch {
namespace distributed {
namespace rpc {
using worker_id_t = int16_t;
using local_id_t = int64_t;
bool getAllowJitRRefPickle();
TORCH_API void enableJitRRefPickle();
TORCH_API void disableJitRRefPickle();
struct TORCH_API JitRRefPickleGu... | 1,720 | 24.686567 | 75 | h |
null | pytorch-main/torch/csrc/distributed/rpc/unpickled_python_call.h | #pragma once
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/utils/pybind.h>
namespace torch {
namespace distributed {
namespace rpc {
// This class converts the content in a PythonCall into py::object. This is a
// helper class to make sure... | 1,367 | 31.571429 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/unpickled_python_remote_call.h | #pragma once
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <torch/csrc/distributed/rpc/unpickled_python_call.h>
#include <torch/csrc/utils/pybind.h>
namespace torch {
namespace distributed {
namespace rpc {
// This class converts the content in a Pyth... | 1,257 | 32.105263 | 79 | h |
null | pytorch-main/torch/csrc/distributed/rpc/utils.h | #pragma once
#include <c10/core/Device.h>
#include <c10/core/Event.h>
#include <c10/core/Stream.h>
#include <torch/csrc/autograd/profiler.h>
#include <torch/csrc/distributed/rpc/rpc_command_base.h>
#include <torch/csrc/jit/serialization/pickle.h>
#include <torch/csrc/utils/byte_order.h>
namespace tensorpipe {
class M... | 3,905 | 40.115789 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/metrics/RpcMetricsHandler.h | #pragma once
#include <c10/util/Registry.h>
#include <string>
namespace torch {
namespace distributed {
namespace rpc {
// All metrics are prefixed with the following key.
// NOLINTNEXTLINE(cppcoreguidelines-avoid-c-arrays,modernize-avoid-c-arrays)
constexpr char kRpcMetricsKeyPrefix[] = "torch.distributed.rpc.";
// ... | 1,617 | 34.955556 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/profiler/remote_profiler_manager.h | #pragma once
#include <c10/util/Optional.h>
#include <torch/csrc/Export.h>
#include <torch/csrc/distributed/rpc/types.h>
#include <mutex>
#include <unordered_map>
namespace torch {
namespace distributed {
namespace rpc {
extern const std::string REMOTE_PROFILING_KEY_PREFIX;
class TORCH_API RemoteProfilerManager {
pu... | 2,287 | 37.133333 | 80 | h |
null | pytorch-main/torch/csrc/distributed/rpc/profiler/server_process_global_profiler.h | #pragma once
#include <shared_mutex>
#include <torch/csrc/autograd/profiler.h>
namespace torch {
namespace distributed {
namespace rpc {
namespace profiler {
namespace processglobal {
using namespace torch::autograd::profiler;
// Process global profiler state.
//
// This class holds information about a profiling r... | 4,334 | 31.111111 | 79 | h |
null | pytorch-main/torch/csrc/distributed/rpc/testing/faulty_tensorpipe_agent.h | #pragma once
#ifdef USE_TENSORPIPE
#include <torch/csrc/distributed/rpc/message.h>
#include <torch/csrc/distributed/rpc/tensorpipe_agent.h>
namespace torch {
namespace distributed {
namespace rpc {
struct TORCH_API FaultyTensorPipeRpcBackendOptions
: public TensorPipeRpcBackendOptions {
FaultyTensorPipeRpcBac... | 3,819 | 34.045872 | 80 | h |
null | pytorch-main/torch/csrc/dynamo/cpython_defs.c | #include <torch/csrc/dynamo/cpython_defs.h>
#ifdef _WIN32
#define unlikely(x) (x)
#else
#define unlikely(x) __builtin_expect((x), 0)
#endif
#define CHECK(cond) \
if (unlikely(!(cond))) { \
fprintf(stderr, "DEBUG CHE... | 12,876 | 36.216763 | 124 | c |
Subsets and Splits
No community queries yet
The top public SQL queries from the community will appear here once available.