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Terminology change Object Reference -> Object ID (#330)
This commit is contained in:
Robert Nishihara
committed by
Philipp Moritz
Philipp Moritz
parent
a89aa30f24
commit
98a508d6ca
@@ -9,20 +9,20 @@ __all__ = ["BLOCK_SIZE", "DistArray", "assemble", "zeros", "ones", "copy",
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BLOCK_SIZE = 10
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class DistArray(object):
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def construct(self, shape, objrefs=None):
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def construct(self, shape, objectids=None):
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self.shape = shape
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self.ndim = len(shape)
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self.num_blocks = [int(np.ceil(1.0 * a / BLOCK_SIZE)) for a in self.shape]
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self.objrefs = objrefs if objrefs is not None else np.empty(self.num_blocks, dtype=object)
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if self.num_blocks != list(self.objrefs.shape):
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raise Exception("The fields `num_blocks` and `objrefs` are inconsistent, `num_blocks` is {} and `objrefs` has shape {}".format(self.num_blocks, list(self.objrefs.shape)))
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self.objectids = objectids if objectids is not None else np.empty(self.num_blocks, dtype=object)
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if self.num_blocks != list(self.objectids.shape):
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raise Exception("The fields `num_blocks` and `objectids` are inconsistent, `num_blocks` is {} and `objectids` has shape {}".format(self.num_blocks, list(self.objectids.shape)))
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def deserialize(self, primitives):
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(shape, objrefs) = primitives
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self.construct(shape, objrefs)
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(shape, objectids) = primitives
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self.construct(shape, objectids)
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def serialize(self):
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return (self.shape, self.objrefs)
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return (self.shape, self.objectids)
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def __init__(self, shape=None):
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if shape is not None:
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@@ -54,14 +54,14 @@ class DistArray(object):
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return [int(np.ceil(1.0 * a / BLOCK_SIZE)) for a in shape]
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def assemble(self):
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"""Assemble an array on this node from a distributed array object reference."""
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first_block = ray.get(self.objrefs[(0,) * self.ndim])
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"""Assemble an array on this node from a distributed array of object IDs."""
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first_block = ray.get(self.objectids[(0,) * self.ndim])
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dtype = first_block.dtype
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result = np.zeros(self.shape, dtype=dtype)
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for index in np.ndindex(*self.num_blocks):
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lower = DistArray.compute_block_lower(index, self.shape)
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upper = DistArray.compute_block_upper(index, self.shape)
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result[[slice(l, u) for (l, u) in zip(lower, upper)]] = ray.get(self.objrefs[index])
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result[[slice(l, u) for (l, u) in zip(lower, upper)]] = ray.get(self.objectids[index])
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return result
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def __getitem__(self, sliced):
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@@ -80,28 +80,28 @@ def numpy_to_dist(a):
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for index in np.ndindex(*result.num_blocks):
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lower = DistArray.compute_block_lower(index, a.shape)
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upper = DistArray.compute_block_upper(index, a.shape)
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result.objrefs[index] = ray.put(a[[slice(l, u) for (l, u) in zip(lower, upper)]])
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result.objectids[index] = ray.put(a[[slice(l, u) for (l, u) in zip(lower, upper)]])
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return result
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@ray.remote([List, str], [DistArray])
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def zeros(shape, dtype_name="float"):
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result = DistArray(shape)
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for index in np.ndindex(*result.num_blocks):
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result.objrefs[index] = ra.zeros.remote(DistArray.compute_block_shape(index, shape), dtype_name=dtype_name)
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result.objectids[index] = ra.zeros.remote(DistArray.compute_block_shape(index, shape), dtype_name=dtype_name)
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return result
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@ray.remote([List, str], [DistArray])
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def ones(shape, dtype_name="float"):
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result = DistArray(shape)
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for index in np.ndindex(*result.num_blocks):
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result.objrefs[index] = ra.ones.remote(DistArray.compute_block_shape(index, shape), dtype_name=dtype_name)
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result.objectids[index] = ra.ones.remote(DistArray.compute_block_shape(index, shape), dtype_name=dtype_name)
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return result
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@ray.remote([DistArray], [DistArray])
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def copy(a):
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result = DistArray(a.shape)
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for index in np.ndindex(*result.num_blocks):
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result.objrefs[index] = a.objrefs[index] # We don't need to actually copy the objects because cluster-level objects are assumed to be immutable.
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result.objectids[index] = a.objectids[index] # We don't need to actually copy the objects because cluster-level objects are assumed to be immutable.
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return result
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@ray.remote([int, int, str], [DistArray])
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@@ -112,9 +112,9 @@ def eye(dim1, dim2=-1, dtype_name="float"):
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for (i, j) in np.ndindex(*result.num_blocks):
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block_shape = DistArray.compute_block_shape([i, j], shape)
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if i == j:
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result.objrefs[i, j] = ra.eye.remote(block_shape[0], block_shape[1], dtype_name=dtype_name)
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result.objectids[i, j] = ra.eye.remote(block_shape[0], block_shape[1], dtype_name=dtype_name)
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else:
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result.objrefs[i, j] = ra.zeros.remote(block_shape, dtype_name=dtype_name)
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result.objectids[i, j] = ra.zeros.remote(block_shape, dtype_name=dtype_name)
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return result
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@ray.remote([DistArray], [DistArray])
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@@ -124,11 +124,11 @@ def triu(a):
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result = DistArray(a.shape)
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for (i, j) in np.ndindex(*result.num_blocks):
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if i < j:
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result.objrefs[i, j] = ra.copy.remote(a.objrefs[i, j])
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result.objectids[i, j] = ra.copy.remote(a.objectids[i, j])
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elif i == j:
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result.objrefs[i, j] = ra.triu.remote(a.objrefs[i, j])
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result.objectids[i, j] = ra.triu.remote(a.objectids[i, j])
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else:
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result.objrefs[i, j] = ra.zeros_like.remote(a.objrefs[i, j])
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result.objectids[i, j] = ra.zeros_like.remote(a.objectids[i, j])
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return result
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@ray.remote([DistArray], [DistArray])
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@@ -138,11 +138,11 @@ def tril(a):
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result = DistArray(a.shape)
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for (i, j) in np.ndindex(*result.num_blocks):
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if i > j:
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result.objrefs[i, j] = ra.copy.remote(a.objrefs[i, j])
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result.objectids[i, j] = ra.copy.remote(a.objectids[i, j])
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elif i == j:
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result.objrefs[i, j] = ra.tril.remote(a.objrefs[i, j])
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result.objectids[i, j] = ra.tril.remote(a.objectids[i, j])
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else:
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result.objrefs[i, j] = ra.zeros_like.remote(a.objrefs[i, j])
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result.objectids[i, j] = ra.zeros_like.remote(a.objectids[i, j])
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return result
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@ray.remote([np.ndarray], [np.ndarray])
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@@ -167,8 +167,8 @@ def dot(a, b):
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shape = [a.shape[0], b.shape[1]]
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result = DistArray(shape)
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for (i, j) in np.ndindex(*result.num_blocks):
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args = list(a.objrefs[i, :]) + list(b.objrefs[:, j])
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result.objrefs[i, j] = blockwise_dot.remote(*args)
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args = list(a.objectids[i, :]) + list(b.objectids[:, j])
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result.objectids[i, j] = blockwise_dot.remote(*args)
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return result
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@ray.remote([DistArray, List], [DistArray])
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@@ -176,9 +176,9 @@ def subblocks(a, *ranges):
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"""
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This function produces a distributed array from a subset of the blocks in the `a`. The result and `a` will have the same number of dimensions.For example,
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subblocks(a, [0, 1], [2, 4])
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will produce a DistArray whose objrefs are
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[[a.objrefs[0, 2], a.objrefs[0, 4]],
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[a.objrefs[1, 2], a.objrefs[1, 4]]]
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will produce a DistArray whose objectids are
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[[a.objectids[0, 2], a.objectids[0, 4]],
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[a.objectids[1, 2], a.objectids[1, 4]]]
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We allow the user to pass in an empty list [] to indicate the full range.
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"""
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ranges = list(ranges)
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@@ -198,7 +198,7 @@ def subblocks(a, *ranges):
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shape = [(len(ranges[i]) - 1) * BLOCK_SIZE + last_block_shape[i] for i in range(a.ndim)]
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result = DistArray(shape)
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for index in np.ndindex(*result.num_blocks):
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result.objrefs[index] = a.objrefs[tuple([ranges[i][index[i]] for i in range(a.ndim)])]
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result.objectids[index] = a.objectids[tuple([ranges[i][index[i]] for i in range(a.ndim)])]
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return result
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@ray.remote([DistArray], [DistArray])
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@@ -208,7 +208,7 @@ def transpose(a):
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result = DistArray([a.shape[1], a.shape[0]])
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for i in range(result.num_blocks[0]):
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for j in range(result.num_blocks[1]):
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result.objrefs[i, j] = ra.transpose.remote(a.objrefs[j, i])
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result.objectids[i, j] = ra.transpose.remote(a.objectids[j, i])
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return result
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# TODO(rkn): support broadcasting?
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@@ -218,7 +218,7 @@ def add(x1, x2):
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raise Exception("add expects arguments `x1` and `x2` to have the same shape, but x1.shape = {}, and x2.shape = {}.".format(x1.shape, x2.shape))
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result = DistArray(x1.shape)
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for index in np.ndindex(*result.num_blocks):
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result.objrefs[index] = ra.add.remote(x1.objrefs[index], x2.objrefs[index])
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result.objectids[index] = ra.add.remote(x1.objectids[index], x2.objectids[index])
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return result
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# TODO(rkn): support broadcasting?
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@@ -228,5 +228,5 @@ def subtract(x1, x2):
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raise Exception("subtract expects arguments `x1` and `x2` to have the same shape, but x1.shape = {}, and x2.shape = {}.".format(x1.shape, x2.shape))
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result = DistArray(x1.shape)
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for index in np.ndindex(*result.num_blocks):
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result.objrefs[index] = ra.subtract.remote(x1.objrefs[index], x2.objrefs[index])
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result.objectids[index] = ra.subtract.remote(x1.objectids[index], x2.objectids[index])
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return result
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@@ -32,7 +32,7 @@ def tsqr(a):
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q_tree = np.empty((num_blocks, K), dtype=object)
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current_rs = []
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for i in range(num_blocks):
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block = a.objrefs[i, 0]
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block = a.objectids[i, 0]
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q, r = ra.linalg.qr.remote(block)
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q_tree[i, 0] = q
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current_rs.append(r)
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@@ -57,8 +57,8 @@ def tsqr(a):
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q_shape = [a.shape[0], a.shape[0]]
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q_num_blocks = DistArray.compute_num_blocks(q_shape)
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q_result = DistArray()
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q_objrefs = np.empty(q_num_blocks, dtype=object)
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q_result.construct(q_shape, q_objrefs)
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q_objectids = np.empty(q_num_blocks, dtype=object)
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q_result.construct(q_shape, q_objectids)
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# reconstruct output
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for i in range(num_blocks):
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@@ -73,7 +73,7 @@ def tsqr(a):
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upper = [2 * a.shape[1], BLOCK_SIZE]
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ith_index /= 2
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q_block_current = ra.dot.remote(q_block_current, ra.subarray.remote(q_tree[ith_index, j], lower, upper))
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q_result.objrefs[i] = q_block_current
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q_result.objectids[i] = q_block_current
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r = current_rs[0]
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return q_result, r
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@@ -126,7 +126,7 @@ def tsqr_hr(a):
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q, r_temp = tsqr.remote(a)
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y, u, s = modified_lu.remote(q)
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y_blocked = ray.get(y)
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t, y_top = tsqr_hr_helper1.remote(u, s, y_blocked.objrefs[0, 0], a.shape[1])
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t, y_top = tsqr_hr_helper1.remote(u, s, y_blocked.objectids[0, 0], a.shape[1])
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r = tsqr_hr_helper2.remote(s, r_temp)
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return y, t, y_top, r
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@@ -146,9 +146,9 @@ def qr(a):
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# we will store our scratch work in a_work
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a_work = DistArray()
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a_work.construct(a.shape, np.copy(a.objrefs))
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a_work.construct(a.shape, np.copy(a.objectids))
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result_dtype = np.linalg.qr(ray.get(a.objrefs[0, 0]))[0].dtype.name
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result_dtype = np.linalg.qr(ray.get(a.objectids[0, 0]))[0].dtype.name
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r_res = ray.get(zeros.remote([k, n], result_dtype)) # TODO(rkn): It would be preferable not to get this right after creating it.
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y_res = ray.get(zeros.remote([m, k], result_dtype)) # TODO(rkn): It would be preferable not to get this right after creating it.
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Ts = []
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@@ -159,27 +159,27 @@ def qr(a):
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y_val = ray.get(y)
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for j in range(i, a.num_blocks[0]):
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y_res.objrefs[j, i] = y_val.objrefs[j - i, 0]
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y_res.objectids[j, i] = y_val.objectids[j - i, 0]
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if a.shape[0] > a.shape[1]:
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# in this case, R needs to be square
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R_shape = ray.get(ra.shape.remote(R))
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eye_temp = ra.eye.remote(R_shape[1], R_shape[0], dtype_name=result_dtype)
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r_res.objrefs[i, i] = ra.dot.remote(eye_temp, R)
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r_res.objectids[i, i] = ra.dot.remote(eye_temp, R)
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else:
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r_res.objrefs[i, i] = R
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r_res.objectids[i, i] = R
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Ts.append(numpy_to_dist.remote(t))
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for c in range(i + 1, a.num_blocks[1]):
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W_rcs = []
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for r in range(i, a.num_blocks[0]):
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y_ri = y_val.objrefs[r - i, 0]
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W_rcs.append(qr_helper2.remote(y_ri, a_work.objrefs[r, c]))
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y_ri = y_val.objectids[r - i, 0]
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W_rcs.append(qr_helper2.remote(y_ri, a_work.objectids[r, c]))
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W_c = ra.sum_list.remote(*W_rcs)
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for r in range(i, a.num_blocks[0]):
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y_ri = y_val.objrefs[r - i, 0]
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A_rc = qr_helper1.remote(a_work.objrefs[r, c], y_ri, t, W_c)
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a_work.objrefs[r, c] = A_rc
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r_res.objrefs[i, c] = a_work.objrefs[i, c]
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y_ri = y_val.objectids[r - i, 0]
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A_rc = qr_helper1.remote(a_work.objectids[r, c], y_ri, t, W_c)
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a_work.objectids[r, c] = A_rc
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r_res.objectids[i, c] = a_work.objectids[i, c]
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# construct q_res from Ys and Ts
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q = eye.remote(m, k, dtype_name=result_dtype)
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@@ -9,9 +9,9 @@ from core import *
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@ray.remote([List], [DistArray])
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def normal(shape):
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num_blocks = DistArray.compute_num_blocks(shape)
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objrefs = np.empty(num_blocks, dtype=object)
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objectids = np.empty(num_blocks, dtype=object)
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for index in np.ndindex(*num_blocks):
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objrefs[index] = ra.random.normal.remote(DistArray.compute_block_shape(index, shape))
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objectids[index] = ra.random.normal.remote(DistArray.compute_block_shape(index, shape))
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result = DistArray()
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result.construct(shape, objrefs)
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result.construct(shape, objectids)
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return result
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