FM / autograd

/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/autograd/

/usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/autograd

Name	Size	Mode	Actions
functions/	-	0755	rm
generated/	-	0755	rm
utils/	-	0755	rm
anomaly_mode.h	1525	0644	edit dl rm
autograd.h	5294	0644	edit dl rm
autograd_not_implemented_fallback.h	201	0644	edit dl rm
cpp_hook.h	518	0644	edit dl rm
custom_function.h	14470	0644	edit dl rm
edge.h	1627	0644	edit dl rm
engine.h	17237	0644	edit dl rm
forward_grad.h	8583	0644	edit dl rm
function.h	25046	0644	edit dl rm
FunctionsManual.h	19904	0644	edit dl rm
function_hook.h	641	0644	edit dl rm
grad_mode.h	207	0644	edit dl rm
InferenceMode.h	182	0644	edit dl rm
input_buffer.h	1597	0644	edit dl rm
input_metadata.h	1384	0644	edit dl rm
profiler.h	112	0644	edit dl rm
profiler_kineto.h	9111	0644	edit dl rm
profiler_legacy.h	16930	0644	edit dl rm
profiler_utils.h	439	0644	edit dl rm
python_anomaly_mode.h	1246	0644	edit dl rm
python_autograd.h	388	0644	edit dl rm
python_cpp_function.h	2456	0644	edit dl rm
python_engine.h	1262	0644	edit dl rm
python_fft_functions.h	128	0644	edit dl rm
python_function.h	4099	0644	edit dl rm
python_hook.h	700	0644	edit dl rm
python_legacy_variable.h	299	0644	edit dl rm
python_linalg_functions.h	131	0644	edit dl rm
python_mode.h	425	0644	edit dl rm
python_nn_functions.h	127	0644	edit dl rm
python_saved_variable_hooks.h	883	0644	edit dl rm
python_special_functions.h	132	0644	edit dl rm
python_torch_functions.h	671	0644	edit dl rm
python_variable.h	1645	0644	edit dl rm
python_variable_indexing.h	313	0644	edit dl rm
record_function_ops.h	587	0644	edit dl rm
saved_variable.h	4322	0644	edit dl rm
saved_variable_hooks.h	272	0644	edit dl rm
symbolic.h	330	0644	edit dl rm
variable.h	33411	0644	edit dl rm
VariableTypeUtils.h	15086	0644	edit dl rm

Edit: /usr/local/lib64/python3.6/site-packages/torch/include/torch/csrc/autograd/input_metadata.h (1384B)

#pragma once

#include <ATen/ATen.h>
#include <c10/core/Device.h>
#include <c10/core/DeviceType.h>
#include <c10/core/Stream.h>
#include <c10/core/impl/DeviceGuardImplInterface.h>

#include <cstdint>

namespace torch { namespace autograd {

/**
 * Records type, shape, and device of tensor and, where applicable,
 * the stream the correspondingoperation took place on.
 *
 * If is_valid() is false, then the corresponding input is not used and may be
 * an undefined tensor.
 */
struct InputMetadata {
  InputMetadata() = default;

InputMetadata(const at::TensorOptions options, at::IntArrayRef shape, at::Device device)
  : options_{options}, shape_{shape}, device_{device} {
    stream_ = c10::impl::getDeviceGuardImpl(device_.type())->getStream(device_);
  }

InputMetadata(const at::Tensor& t)
  : InputMetadata(t.options(), t.sizes(), t.device()) { }

const at::TensorOptions options() const {
    return options_;
  }

at::IntArrayRef shape() const {
    return shape_;
  }

at::Device device() const {
    return device_;
  }

c10::Stream stream() const {
    return stream_;
  }

at::Tensor zeros_like() const {
    return at::zeros(shape_, options_);
  }

private:
  const at::TensorOptions options_;
  at::DimVector shape_;
  at::Device device_ = at::kCPU;
  c10::Stream stream_ = c10::Stream(c10::Stream::Default::DEFAULT, device_);
};

}} // torch::autograd

#pragma once #include #include #include #include #include #include namespace torch { namespace autograd { /** * Records type, shape, and device of tensor and, where applicable, * the stream the correspondingoperation took place on. * * If is_valid() is false, then the corresponding input is not used and may be * an undefined tensor. */ struct InputMetadata { InputMetadata() = default; InputMetadata(const at::TensorOptions options, at::IntArrayRef shape, at::Device device) : options_{options}, shape_{shape}, device_{device} { stream_ = c10::impl::getDeviceGuardImpl(device_.type())->getStream(device_); } InputMetadata(const at::Tensor& t) : InputMetadata(t.options(), t.sizes(), t.device()) { } const at::TensorOptions options() const { return options_; } at::IntArrayRef shape() const { return shape_; } at::Device device() const { return device_; } c10::Stream stream() const { return stream_; } at::Tensor zeros_like() const { return at::zeros(shape_, options_); } private: const at::TensorOptions options_; at::DimVector shape_; at::Device device_ = at::kCPU; c10::Stream stream_ = c10::Stream(c10::Stream::Default::DEFAULT, device_); }; }} // torch::autograd