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* Change the curand_init parameter

* Change the curand_init parameter

* commit

* commit
Co-authored-by: nv-dlasalle <63612878+nv-dlasalle@users.noreply.github.com>

* implement pin_memory/unpin_memory/is_pinned for dgl.graph

* update python docstring

* update c++ docstring

* add test

* fix the broken UnifiedTensor

* XPU_SWITCH for kDLCPUPinned

* a rough version ready for testing

* eliminate extra context parameter for pin/unpin

* update train_sampling

* fix linting

* fix typo

* multi-gpu uva sampling case

* disable new format materialization for pinned graphs

* update python doc for pin_memory_

* fix unit test

* UVA sampling for link prediction

* dispatch most csr ops

* update graphsage example to combine uva sampling and UnifiedTensor

* update graphsage example to combine uva sampling and UnifiedTensor

* update graphsage example to combine uva sampling and UnifiedTensor

* update doc

* update examples

* change unitgraph and heterograph's PinMemory to in-place

* update examples for multi-gpu uva sampling

* update doc

* fix linting

* fix cpu build

* fix is_pinned for DistGraph

* fix is_pinned for DistGraph

* update graphsage unsupervised example

* update doc for gpu sampling

* update some check for sampling device switching

* fix linting

* adapt for new dataloader

* fix linting

* fix

* fix some name issue

* adjust device check

* add unit test for uva sampling & fix some zero_copy bug

* fix linting

* update num_threads in graphsage examples
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>

* remove

* remove

* fix

* remove

* remove

* Split out separate generators for each thread

* Amortize cost of curand_init

* Improve readability
Co-authored-by: Jinjing Zhou <VoVAllen@users.noreply.github.com>
Co-authored-by: Quan (Andy) Gan <coin2028@hotmail.com>

* Start on uniform GPU sampling

* Save more work

* Get cu file compiling

* Update sampling

* More changes

* Get GPU sampling for uniform probabilities solved

* Fix batch tensor migration

* Fix

* update kernels

* expand blocking

* Undo testing change

* Cut down on sampling overhead

* Fix replacement

* Update unit tests

* Add option to gpu sample in graphsage

* Copy only csc to gpu

* Add ogbn support

* Fix linting

* Remove nvtx from sample

* Improve documentation and error checking

* Expand documentation

* Update assert checking

* delete extra space

* Use standard dataloader when dataset is a dictionary

* ogb -> ogbn

* Fix edge selection determinism

* Fix typos

* Remove nvtx

* Add comment for self.fanout_arrays and assert

* Fix linting

* Migrate to scalarbatcher

* Fix indentation

* Fix batcher

* Fix indexing

* Only use databatcher for GPU

* Convert to DGL NDArray to PyTorch Tensor

* Add optimization for PyTorch's F.tensor() for list of GPU tensors
Co-authored-by: Da Zheng <zhengda1936@gmail.com>