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Tensor.cpp
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Tensor.cpp
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#include <ATen/core/Tensor.h>
#include <ATen/core/Formatting.h>
#include <ATen/core/VariableHooksInterface.h>
#include <ATen/core/LegacyTypeDispatch.h>
#include <ATen/FunctionalTensorWrapper.h>
#ifndef AT_PER_OPERATOR_HEADERS
#include <ATen/MethodOperators.h>
#else
#include <ATen/ops/contiguous_ops.h>
#include <ATen/ops/fill_ops.h>
#include <ATen/ops/to_ops.h>
#include <ATen/ops/zero_ops.h>
#endif
#include <iostream>
namespace at {
const TensorBase& get_tensor_base(const Tensor &t) {
return t;
}
TensorBase TensorBase::__dispatch_contiguous(c10::MemoryFormat memory_format) const {
OptionalTensorRef self(*this);
return at::_ops::contiguous::call(*self, memory_format);
}
const TensorBase& TensorBase::fill_(const c10::Scalar &fill_value) const {
Tensor self(*this);
at::_ops::fill__Scalar::call(self, fill_value);
return *this;
}
const TensorBase& TensorBase::zero_() const {
Tensor self(*this);
at::_ops::zero_::call(self);
return *this;
}
TensorBase TensorBase::to(
at::TensorOptions options,
bool non_blocking,
bool copy,
c10::optional<at::MemoryFormat> memory_format) const {
Tensor self(*this);
return at::_ops::to_dtype_layout::call(
self, optTypeMetaToScalarType(options.dtype_opt()),
options.layout_opt(), options.device_opt(),
options.pinned_memory_opt(), non_blocking, copy, memory_format);
}
void TensorBase::enforce_invariants() {
if (impl_.get() == nullptr) {
throw std::runtime_error("TensorImpl with nullptr is not supported");
}
// Following line throws if the method is not a POD data type or is not
// supported by ATen
scalar_type();
if (defined()) {
TORCH_INTERNAL_ASSERT(
impl_->dtype_initialized(),
"Partially-initialized tensor not supported by Tensor");
TORCH_INTERNAL_ASSERT(
!impl_->is_sparse(),
"Sparse Tensors are supported by Tensor, but invariant checking isn't implemented. Please file a bug.");
TORCH_INTERNAL_ASSERT(
!impl_->has_storage() || impl_->is_meta() || impl_->storage_initialized(),
"Partially-initialized tensor not supported by Tensor");
}
}
void TensorBase::print() const {
if (defined()) {
std::cerr << "[" << toString() << " " << sizes() << "]" << std::endl;
} else {
std::cerr << "[UndefinedTensor]" << std::endl;
}
}
std::string TensorBase::toString() const {
std::string base_str;
if (scalar_type() == ScalarType::Undefined) {
base_str = "UndefinedType";
} else {
base_str = std::string(at::toString(options().computeDispatchKey())) + at::toString(scalar_type()) + "Type";
}
return base_str;
}
TensorBase TensorBase::variable_data() const {
return impl::GetVariableHooks()->variable_data(*this);
}
TensorBase TensorBase::tensor_data() const {
return impl::GetVariableHooks()->tensor_data(*this);
}
bool TensorBase::is_leaf() const {
return impl::GetVariableHooks()->is_leaf(*this);
}
int64_t TensorBase::output_nr() const {
return impl::GetVariableHooks()->output_nr(*this);
}
void TensorBase::set_data(const TensorBase & new_data) const {
impl::GetVariableHooks()->set_data(*this, new_data);
}
TensorBase TensorBase::data() const {
return impl::GetVariableHooks()->data(*this);
}
int64_t TensorBase::_version() const {
return impl::GetVariableHooks()->_version(*this);
}
void TensorBase::retain_grad() const {
impl::GetVariableHooks()->retain_grad(*this);
}
bool TensorBase::retains_grad() const {
return impl::GetVariableHooks()->retains_grad(*this);
}
void Tensor::_backward(TensorList inputs,
const c10::optional<Tensor>& gradient,
c10::optional<bool> keep_graph,
bool create_graph) const {
return impl::GetVariableHooks()->_backward(*this, inputs, gradient, keep_graph, create_graph);
}
const TensorBase& TensorBase::requires_grad_(bool _requires_grad) const {
impl::GetVariableHooks()->requires_grad_(*this, _requires_grad);
return *this;
}
// View Methods
//~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
bool TensorBase::is_view() const {
return impl::GetVariableHooks()->is_view(*this);
}
const TensorBase& TensorBase::_base() const {
return impl::GetVariableHooks()->base(*this);
}
const std::string& TensorBase::name() const {
return impl::GetVariableHooks()->name(*this);
}
const std::shared_ptr<torch::autograd::Node>& TensorBase::grad_fn() const {
return impl::GetVariableHooks()->grad_fn(*this);
}
void TensorBase::remove_hook(unsigned pos) const {
impl::GetVariableHooks()->remove_hook(*this, pos);
}
unsigned TensorBase::_register_hook(std::function<TensorBase(const TensorBase&)> hook) const {
return impl::GetVariableHooks()->_register_hook(*this, std::move(hook));
}
} // namespace at