dmlc--dgl
VoVAllen
5b9147c464
* add rtfd * rrr * update * change env * temp fix * update * fix * fix * add * conf * Move file_pattern from Makefile to conf.py * remove yml * fix * fix * fix * fix * remove yml * remove yml * add doc docker * add dgl install script * change name * change dockerfile * fix * name * add * fix * fix * fix * fix * fix docker * delete sphinx.py for doc-build backend * Add softmax to test backend * Add group apply function and tests * Delete unnecessary file * Update comments and test * Fix lint * remove unused bucketing code * group apply edge bucketing code * gen degree bucket schedule for group apply edge * schedule and graph code * fix compiling * fix * fix lint * naming * harder test case * fix comments * more comments * tweak function name
110 行
2.9 KiB
Python
110 行
2.9 KiB
Python
"""This file defines the unified tensor framework interface required by DGL
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unit testing, other than the ones used in the framework itself.
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"""
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###############################################################################
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# Tensor, data type and context interfaces
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def cuda():
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"""Context object for CUDA."""
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pass
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###############################################################################
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# Tensor functions on feature data
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# --------------------------------
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# These functions are performance critical, so it's better to have efficient
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# implementation in each framework.
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def array_equal(a, b):
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"""Check whether the two tensors are *exactly* equal."""
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pass
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def allclose(a, b):
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"""Check whether the two tensors are numerically close to each other."""
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pass
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def randn(shape):
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"""Generate a tensor with elements from standard normal distribution."""
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pass
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def attach_grad(x):
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"""Flag the tensor *in-place* to have its gradient computed in backward
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pass.
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If the flag is already set, reset the gradient buffer as well.
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"""
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pass
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def backward(x, head_gradient=None):
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"""Invoke backward computation with an optional head gradient.
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Returns nothing."""
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pass
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def grad(x):
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"""Fetches the gradient from the tensor after backward computation."""
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pass
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def is_no_grad(x):
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"""Check whether a tensor has its gradient computed."""
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pass
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def full(shape, fill_value, dtype, ctx):
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pass
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def narrow_row_set(x, start, stop, new):
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"""Set a slice of the given tensor to a new value."""
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pass
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def sparse_to_numpy(x):
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"""Convert a sparse tensor to a numpy array."""
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pass
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def clone(x):
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pass
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def reduce_sum(x):
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"""Sums all the elements into a single scalar."""
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pass
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def softmax(x, dim):
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"""Softmax Operation on Tensors"""
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pass
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###############################################################################
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# Tensor functions used *only* on index tensor
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# ----------------
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# These operators are light-weighted, so it is acceptable to fallback to
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# numpy operators if currently missing in the framework. Ideally in the future,
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# DGL should contain all the operations on index, so this set of operators
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# should be gradually removed.
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###############################################################################
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# Other interfaces
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# ----------------
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# These are not related to tensors. Some of them are temporary workarounds that
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# should be included in DGL in the future.
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class record_grad(object):
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"""Context manager that records the gradients"""
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def __init__(self):
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pass
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def __enter__(self):
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pass
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def __exit__(self, exc_type, exc_value, exc_traceback):
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pass
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class no_grad(object):
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"""Context manager that explicitly disables gradient computation"""
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def __init__(self):
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pass
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def __enter__(self):
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pass
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def __exit__(self, exc_type, exc_value, exc_traceback):
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pass
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