/usr/local/lib64/python3.6/site-packages/torch/include/TH
Edit: /usr/local/lib64/python3.6/site-packages/torch/include/TH/THTensor.hpp (4061B)
#pragma once
// STOP!!! Thinking of including this header directly? Please
// read Note [TH abstraction violation]
#include
#include |
#include
#include
// Returns a Tensor given a TensorImpl. The TensorImpl remains valid after the
// the Tensor is destroyed.
inline at::Tensor THTensor_wrap(THTensor* tensor) {
c10::raw::intrusive_ptr::incref(tensor);
return at::Tensor(c10::intrusive_ptr::reclaim(tensor));
}
inline const int64_t* THTensor_getSizePtr(THTensor* tensor) {
return tensor->sizes().data();
}
inline const int64_t* THTensor_getStridePtr(THTensor* tensor) {
return tensor->strides().data();
}
// NB: Non-retaining
inline THStorage* THTensor_getStoragePtr(const THTensor* tensor) {
// Within PyTorch, the invariant is that storage_ is always
// initialized; we never have tensors that don't have any storage.
// However, for Caffe2, this is not true, because they have permitted
// tensors to be allocated without specifying what scalar type
// they should be, only to be filled when GetMutableData is called
// for the first time (providing the necessary type). It is an ERROR to
// invoke any PyTorch operations on such a half-constructed storage,
// and this check tests for that case.
TORCH_CHECK(tensor->storage(), "Cannot use PyTorch operations on a half-constructed "
"tensor. If this tensor came from Caffe2, please call GetMutableData on "
"it first; otherwise, this is a bug, please report it.");
return tensor->storage().unsafeGetStorageImpl();
}
// [NOTE: nDimension vs nDimensionLegacyNoScalars vs nDimensionLegacyAll]
// nDimension corresponds to the "true" ATen dimension.
// nDimensionLegacyNoScalars corresponds to the ATen dimension, except scalars are viewed as 1-dimensional tensors.
// nDimensionLegacyAll corresponds to the ATen dimension, except scalars are viewed as 1-dimensional tensors
// and tensors with a dimension of size zero are collapsed to 0-dimensional tensors.
//
// Eventually, everything should go through nDimension or tensor->dim().
inline int THTensor_nDimension(const THTensor* tensor) {
return tensor->dim();
}
inline int THTensor_nDimensionLegacyNoScalars(const THTensor* tensor) {
if (tensor->dim() == 0) {
return 1;
} else {
return tensor->dim();
}
}
inline int THTensor_nDimensionLegacyAll(const THTensor* tensor) {
if (tensor->is_empty()) {
return 0;
} else if (tensor->dim() == 0) {
return 1;
} else {
return tensor->dim();
}
}
inline int64_t THTensor_strideLegacyNoScalars(const THTensor *self, int dim) {
THArgCheck((dim >= 0) && (dim < THTensor_nDimensionLegacyNoScalars(self)), 2, "dimension %d out of range of %dD tensor",
dim, THTensor_nDimensionLegacyNoScalars(self));
return self->dim() == 0 ? 1 : self->stride(dim);
}
inline int64_t THTensor_sizeLegacyNoScalars(const THTensor *self, int dim)
{
THArgCheck((dim >= 0) && (dim < THTensor_nDimensionLegacyNoScalars(self)), 2, "dimension %d out of range of %dD tensor",
dim, THTensor_nDimensionLegacyNoScalars(self));
return self->dim() == 0 ? 1 : self->size(dim);
}
inline std::vector THTensor_sizesLegacyNoScalars(const THTensor *self) {
if (self->dim() == 0) {
return {1};
} else {
return self->sizes().vec();
}
}
TH_API void THTensor_free(THTensor *self);
TH_CPP_API void THTensor_resize(THTensor *self, at::IntArrayRef size, at::IntArrayRef stride);
TH_CPP_API void THTensor_setStorage(THTensor *self, THStorage *storage_, ptrdiff_t storageOffset_, at::IntArrayRef size_, at::IntArrayRef stride_);
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