def test_fromFiber_wo_ids(self):
"""Test construction of a tensor from a fiber without rank ids"""
tensor_in = Tensor.fromYAMLfile("./data/test_tensor-1.yaml")
root = tensor_in.getRoot()
tensor_ref = Tensor.fromFiber(["R1", "R0"], root)
tensor = Tensor.fromFiber(fiber=root)
self.assertEqual(tensor, tensor_ref)
def test_fromUncompressed_2D_wo_ids(self):
"""Test construction of a tensor from nested lists without ids"""
tensor_in = Tensor.fromYAMLfile("./data/test_tensor-1.yaml")
root = tensor_in.getRoot()
tensor_ref = Tensor.fromFiber(["R1", "R0"], root)
# Manual copy of test_tensor-1.yaml
# 0 1 2 3
#
t = [
[0, 0, 0, 0], # 0
[100, 101, 102, 0], # 1
[0, 201, 0, 203], # 2
[0, 0, 0, 0], # 3
[400, 0, 402, 0], # 4
[0, 0, 0, 0], # 5
[0, 601, 0, 603]
] # 6
tensor = Tensor.fromUncompressed(["R1", "R0"], t)
self.assertEqual(tensor, tensor_ref)
def test_shape_fromFiber_authoritative(self):
"""Test shape of a tensor from a fiber with authoritative shape"""
y1 = Tensor.fromYAMLfile("./data/test_tensor-1.yaml")
f1 = y1.getRoot()
t1 = Tensor.fromFiber(["M", "K"], f1, [100, 200])
with self.subTest(test="All ranks"):
self.assertEqual(t1.getRankIds(), ["M", "K"])
self.assertEqual(t1.getShape(), [100, 200])
with self.subTest(test="All ranks specified"):
self.assertEqual(t1.getShape(["M", "K"]), [100, 200])
with self.subTest(test="Just rank 'M'"):
self.assertEqual(t1.getShape(["M"]), [100])
with self.subTest(test="Just rank 'K'"):
self.assertEqual(t1.getShape(["K"]), [200])
with self.subTest(test="Just rank 'M'"):
self.assertEqual(t1.getShape("M"), 100)
with self.subTest(test="Just rank 'K'"):
self.assertEqual(t1.getShape("K"), 200)
with self.subTest(test="Check authoritative"):
self.assertEqual(t1.getShape(authoritative=True), [100, 200])
self.assertEqual(t1.getShape(["M", "K"], authoritative=True),
[100, 200])
self.assertEqual(t1.getShape(["M"], authoritative=True), [100])
self.assertEqual(t1.getShape(["K"], authoritative=True), [200])
self.assertEqual(t1.getShape("M", authoritative=True), 100)
self.assertEqual(t1.getShape("K", authoritative=True), 200)
def test_shape_fromFiber(self):
"""Test shape of a tensor from a fiber without authoritative shape"""
y1 = Tensor.fromYAMLfile("./data/test_tensor-1.yaml")
f1 = y1.getRoot()
t1 = Tensor.fromFiber(["M", "K"], f1)
with self.subTest(test="All ranks"):
self.assertEqual(t1.getRankIds(), ["M", "K"])
self.assertEqual(t1.getShape(), [7, 4])
with self.subTest(test="All ranks specified"):
self.assertEqual(t1.getShape(["M", "K"]), [7, 4])
with self.subTest(test="Just rank 'M' as list"):
self.assertEqual(t1.getShape(["M"]), [7])
with self.subTest(test="Just rank 'K' as list"):
self.assertEqual(t1.getShape(["K"]), [4])
with self.subTest(test="Just rank 'M'"):
self.assertEqual(t1.getShape("M"), 7)
with self.subTest(test="Just rank 'K'"):
self.assertEqual(t1.getShape("K"), 4)
with self.subTest(test="Check authoritative"):
self.assertIsNone(t1.getShape(authoritative=True))
self.assertIsNone(t1.getShape(["M", "K"], authoritative=True))
self.assertIsNone(t1.getShape(["M"], authoritative=True))
self.assertIsNone(t1.getShape(["K"], authoritative=True))
self.assertIsNone(t1.getShape("M", authoritative=True))
self.assertIsNone(t1.getShape("K", authoritative=True))
def test_fromFiber(self):
"""Test construction of a tensor from a fiber"""
tensor_ref = Tensor.fromYAMLfile("./data/test_tensor-1.yaml")
root = tensor_ref.getRoot()
tensor = Tensor.fromFiber(["M", "K"], root)
self.assertEqual(tensor, tensor_ref)
def test_flattenRanks_f02(self):
""" Test flattenRanks - f02 """
t0 = Tensor.fromYAMLfile("./data/tensor_3d-0.yaml")
t1 = Tensor.fromYAMLfile("./data/tensor_3d-1.yaml")
t2 = Tensor.fromFiber(["A", "B", "C", "D"],
Fiber([1, 4], [t0.getRoot(), t1.getRoot()]),
name="t2")
f13 = t2.flattenRanks(depth=1, levels=2)
u13 = f13.unflattenRanks(depth=1, levels=2)
self.assertEqual(u13, t2)
f04 = t2.flattenRanks(depth=0, levels=3)
u04 = f04.unflattenRanks(depth=0, levels=3)
self.assertEqual(u04, t2)
def setUp(self):
self.input = {}
self.input['f'] = Fiber([0, 1, 2], [
Fiber([0, 1, 2], [
Fiber([0, 1, 2, 3], [2, 4, 2, 4]),
Fiber([0, 1, 2, 3], [3, 2, 4, 3]),
Fiber([0, 1, 3], [3, 2, 1])
]),
Fiber([0, 1, 2], [
Fiber([0, 1, 2, 3], [3, 2, 5, 4]),
Fiber([0, 1, 3], [5, 2, 1]),
Fiber([0, 1, 2], [1, 1, 5])
]),
Fiber([0, 1, 2], [
Fiber([1, 2], [4, 2]),
Fiber([0, 1, 2, 3], [2, 2, 2, 3]),
Fiber([0, 1, 2, 3], [2, 4, 3, 1])
])
])
self.input['t'] = Tensor.fromFiber(["C", "H", "W"], self.input['f'])
from fibertree import Fiber, Tensor, TensorImage
x = [[[1, 2, 8, 20, 0, 0, 11], [1, 0, 0, 11, 0, 0, 33], [0, 0, 0, 0, 0, 0, 0],
[1, 1, 8, 12, 0, 0, 44], [1, 3, 0, 13, 0, 0, 42], [0, 0, 4, 14, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]],
[[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]],
[[1, 2, 8, 20, 0, 0, 11], [1, 0, 0, 11, 0, 0, 33], [0, 0, 0, 0, 0, 0, 0],
[1, 1, 8, 12, 0, 0, 44], [1, 3, 0, 13, 0, 0, 42], [0, 0, 4, 14, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0]]]
f = Fiber.fromUncompressed(x)
f.dump("/tmp/tensor-3d.yaml")
f.print("Fiber from uncompressed")
t1 = Tensor.fromFiber(["X", "Y", "Z"], f)
t1.print("Tensor from fiber")
t2 = Tensor.fromUncompressed(["X", "Y", "Z"], x)
t2.print("Tensor from uncompressed")
def __init__(self,
*tensors,
animation='movie',
style='tree',
enable_wait=False):
"""__init__
"""
#
# Set up logging
#
self.logger = logging.getLogger('fibertree.graphics.tensor_canvas')
#
# Places to collect information about the frames
#
num_tensors = len(tensors)
self.num_tensors = num_tensors
self.orig_tensors = []
self.shadow_tensors = []
self.using_spacetimestamp = None
self.update_times = [] if enable_wait else None
self.waitname_map = {}
for t in tensors:
#
# Build list of orignal tensors,
# but convert Fibers into a Tensor with the Fiber as its root
#
if isinstance(t, Fiber):
# TBD: We do not really know if the fiber is mutable...
t = Tensor.fromFiber(fiber=t)
self.orig_tensors.append(t)
#
# Create a tensor to hold a shadow tensor that tracks
# updates to the tracked tensors at the right time
#
if t.isMutable():
self.shadow_tensors.append(copy.deepcopy(t))
else:
self.shadow_tensors.append(t)
#
# Create a tensor to hold last update time
# of each element of a tensor
#
if enable_wait:
self.update_times.append(Tensor(rank_ids=t.getRankIds()))
#
# Create a list to hold a record of activity at each timestamp
#
self.log = []
#
# Flag to help addFrame() know if it is adding activity
# to an existing frame
#
self.inframe = False
#
# Global cycle tracker
#
self.cycle = 0
#
# Reset image highlighting
#
ImageUtils.resetColors()
#
# Create desired canvas
#
# Note: We create the canvas with the shadow tensors, so that
# the visualized activity happens in the desired order
#
if animation == 'movie':
self.canvas = MovieCanvas(*self.shadow_tensors, style=style)
elif animation == 'spacetime':
self.canvas = SpacetimeCanvas(*self.shadow_tensors)
elif animation == 'none':
self.canvas = NoneCanvas(*self.shadow_tensors, style=style)
else:
self.logger.warning("TensorCanvas: No animation type: %s",
animation)
#
print("a - single highlights")
i = UncompressedImage(a, {"PE": [(1, 2)]})
i.show()
#
print("b")
b = Tensor.fromUncompressed(["X"], [1, 2, 0, 0, 4])
i = UncompressedImage(b, {"PE": [(1, ), (4, )]})
i.show()
#
print("c")
a_root = a.getRoot()
c = Tensor.fromFiber(["X", "Y", "Z"],
Fiber([0, 1, 2],
[a_root, Fiber([], []), a_root]))
i = UncompressedImage(c)
i.show()
#
print("d")
d = c.getRoot()
print("Original")
i = UncompressedImage(d)
i.show()
#
# print("e")
# d_flattened = d.flattenRanks()
# print("Flattened")
