def test_new(self):
av = 1
bv = 1
a = Payload(av)
self.assertEqual(a.value, av)
b = Payload(bv)
self.assertEqual(b.value, bv)
def test_minus(self):
av = 1
bv = 1
a = Payload(av)
b = Payload(bv)
a_sub_1 = a - 1
self.assertEqual(a_sub_1.value, av - 1)
a_sub_b = a - b
self.assertEqual(a_sub_b.value, av - bv)
def _replayChanges(self):
"""replayChanges """
if len(self.log) == 0:
return
points = self.log[0].points
values = self.log[0].values
for shadow, point_list, value_list in zip(self.shadow_tensors, points,
values):
if shadow.isMutable():
for point, value in zip(point_list, value_list):
if Payload.isEmpty(value):
continue
ref = shadow.getPayloadRef(*point)
ref <<= value
del self.log[0]
#
# Increment cycle
#
if not self.using_spacetimestamp:
self.cycle += 1
def __init__(self, object, highlights={}, extent=(30, 200)):
"""__init__"""
#
# Set up logging
#
self.logger = logging.getLogger('fibertree.graphics.tree_image')
#
# Record parameters
#
# Note: We conditionally unwrap Payload objects
#
self.object = Payload.get(object)
self.row_extent = extent[0]
self.col_extent = extent[1]
level = self.object.getDepth() - 1
self.highlight_manager = HighlightManager(highlights, level=level)
#
# Cache worker colors
#
worker_color = {}
for n, worker in enumerate(highlights.keys()):
worker_color[worker] = ImageUtils.getColor(worker)
self.worker_color = worker_color
#
# Create the tree image
#
self._create_tree()
def test_union_2x_1d2d(self):
"""Test union 2-way for 1d/2d fibers"""
ans = Fiber([0, 2, 4, 6],
[('AB', 1, Fiber([0, 2, 3], [2, 4, 5])),
('AB', 3, Fiber([0, 1, 2], [3, 4, 6])),
('AB', 5, Fiber([0, 1, 2, 3], [1, 2, 3, 4])),
('A', 7, Fiber([], []))])
a_m = self.input["a1_m"]
b_m = self.input["b2_m"]
z_m1 = a_m | b_m
z_m2 = Fiber.union(a_m, b_m)
for test, z_m in enumerate([z_m1, z_m2]):
with self.subTest(test=test):
# Check for right answer
self.assertEqual(z_m, ans)
# Check that payloads are of correct type
self.assertIsInstance(z_m[0].payload.value[1], Payload)
self.assertIsInstance(z_m[0].payload.value[2], Fiber)
self.assertIsInstance(z_m[2].payload.value[1], Payload)
self.assertIsInstance(z_m[3].payload.value[2], Fiber)
# Check that default was set properly
z_m_default = z_m.getDefault()
self.assertEqual(z_m_default, Payload(('', 0, Fiber)))
self.assertIsInstance(z_m_default, Payload)
# Check final shape is correct (note it is 1-D)
z_m_shape = z_m.getShape()
self.assertEqual(z_m_shape, [7])
def test_plus(self):
av = 1
bv = 1
a = Payload(av)
b = Payload(bv)
a_plus_1 = a + 1
self.assertEqual(a_plus_1.value, av + 1)
a_plus_b = a + b
self.assertEqual(a_plus_b.value, av + bv)
a += 1
self.assertEqual(a.value, av + 1)
a += b
self.assertEqual(a.value, av + 1 + bv)
def __init__(self, object, *args, highlights={}, style='tree', **kwargs):
"""__init__"""
#
# Set up logging
#
self.logger = logging.getLogger('fibertree.graphics.tensor_image')
highlights = HighlightManager.canonicalizeHighlights(highlights)
#
# Conditionally unwrap Payload objects
#
object = Payload.get(object)
#
# Create the subimages
#
if "tree" in style:
im1 = TreeImage(object, *args, highlights=highlights, **kwargs).im
if "uncompressed" in style:
im2 = UncompressedImage(object, *args, highlights=highlights, **kwargs).im
#
# Create the final image
#
# TBD: Allow style to be a list
#
if style == "tree":
self.im = im1
elif style == "uncompressed":
self.im = im2
elif style == "tree+uncompressed":
color="wheat"
im = Image.new('RGB', (max(im1.width, im2.width), im1.height + im2.height), color)
diff = im1.width - im2.width
if diff > 0:
# im1 is bigger
im1_xoffset = 0
im2_xoffset = diff//2
else:
# im2 is bigger
im1_xoffset = -diff//2
im2_xoffset = 0
im.paste(im1, (im1_xoffset, 0))
im.paste(im2, (im2_xoffset, im1.height))
self.im = im
else:
print(f"TensorImage: Unsupported image style - {style}")
def test_multiply(self):
av = 1
bv = 2
a = Payload(av)
b = Payload(bv)
a_mul_2 = a * 2
self.assertEqual(a_mul_2.value, av * 2)
two_mul_a = 2 * a
self.assertEqual(two_mul_a.value, 2 * av)
a_mul_b = a * b
self.assertEqual(a_mul_b.value, av * bv)
a *= 2
self.assertEqual(a.value, av * 2)
a *= b
self.assertEqual(a.value, av * 2 * b)
def __init__(self, *tensors):
"""__init__"""
#
# Set up logging
#
self.logger = logging.getLogger('fibertree.graphics.spacetime_canvas')
#
# Structures to hold infomation about each tracked tensor
#
self.tensors = []
self.spacetime = []
self.highlights = []
for tensor in tensors:
#
# Append each tensor being tracked, conditionally
# unwraping it if it is a Payload object
#
self.tensors.append(Payload.get(tensor))
#
# Create a "spacetime" tensor to hold the spacetime
# information for this tracked tensor
#
if isinstance(tensor, Tensor):
assert tensor.getShape() != [], "No support for 0-D tensors"
spacetime = Tensor(rank_ids=["T"] + tensor.getRankIds())
spacetime.setName(tensor.getName())
spacetime.setColor(tensor.getColor())
else:
assert tensor.getDepth() == 1, "Only 1-D fibers are supported"
spacetime = Tensor(rank_ids=["T", "S"])
#
# Append the "spacetime" tensor to hold this tracked
# tensor's spacetime information
#
self.spacetime.append(spacetime)
#
# Append an empty highlight object to hold the highlighting
# information for this tracked tensor
#
self.highlights.append({})
self.frame_num = 0
def test_equality(self):
cv = 8
dv = 8
ev = 1
c = Payload(cv)
d = Payload(dv)
e = Payload(ev)
self.assertTrue(c == d)
self.assertFalse(c == e)
self.assertFalse(c != d)
self.assertTrue(c != e)
self.assertTrue(c == 8)
self.assertFalse(c == 1)
self.assertFalse(c != 8)
self.assertTrue(c != 1)
self.assertTrue(8 == c)
self.assertFalse(1 == c)
self.assertFalse(8 != c)
self.assertTrue(1 != c)
def test_multiply(self):
cp1 = CoordPayload(5, 4)
cp2 = CoordPayload(6, 5)
payload_ref = Payload(20)
self.assertEqual(cp1 * 5, payload_ref)
self.assertEqual(cp1 * cp2, payload_ref)
self.assertEqual(5 * cp1, payload_ref)
cp1 *= cp2
self.assertEqual(cp1, payload_ref)
cp2 *= 4
self.assertEqual(cp2, payload_ref)
def test_sub(self):
cp1 = CoordPayload(5, 12)
cp2 = CoordPayload(6, 10)
payload_ref = Payload(2)
self.assertEqual(cp1 - 10, payload_ref)
self.assertEqual(cp1 - cp2, payload_ref)
self.assertEqual(14 - cp1, payload_ref)
cp1 -= cp2
self.assertEqual(cp1, payload_ref)
cp2 -= 8
self.assertEqual(cp2, payload_ref)
def test_add(self):
cp1 = CoordPayload(5, 11)
cp2 = CoordPayload(6, 12)
payload_ref = Payload(23)
self.assertEqual(cp1 + 12, payload_ref)
self.assertEqual(cp1 + cp2, payload_ref)
self.assertEqual(12 + cp1, payload_ref)
cp1 += cp2
self.assertEqual(cp1, payload_ref)
cp2 += 11
self.assertEqual(cp2, payload_ref)
def test_mul_payload(self):
"""Test __mul__ payload"""
f_in = Fiber.fromUncompressed([1, 2, 3, 0, 0, 6])
f_ref = Fiber([0, 1, 2, 5], [2, 4, 6, 12])
two = Payload(2)
with self.subTest("f_in * 2"):
f_out = f_in * two
self.assertEqual(f_ref, f_out)
with self.subTest("2*f_in"):
f_out = two * f_in
self.assertEqual(f_ref, f_out)
with self.subTest("f_in *=2"):
# f_in gets clobbered!
f_in *= two
self.assertEqual(f_ref, f_in)
def test_add_payload(self):
"""Test __add__ payload"""
f_in = Fiber.fromUncompressed([1, 2, 3, 0, 0, 6])
f_ref = Fiber.fromUncompressed([3, 4, 5, 2, 2, 8])
two = Payload(2)
with self.subTest("f_in + 2"):
f_out = f_in + two
self.assertEqual(f_ref, f_out)
with self.subTest("2 + f_in"):
f_out = two + f_in
self.assertEqual(f_ref, f_out)
with self.subTest("f_in += 2"):
# f_in gets clobbered!
f_in += two
self.assertEqual(f_ref, f_in)
def _traverse(self, fiber):
"""traverse"""
#
# Assume this is a rank-3 or less tensor
#
if not Payload.contains(fiber, Fiber):
#
# Draw a 0-D tensor, i.e., a value (NOT a fiber)
#
# TBD
region_size = [1, 1]
else:
#
# Recursively draw the fibers of a non-0-D tensor
#
shape = fiber.getShape(all_ranks=True)
dimensions = len(shape)
hl_manager = self.highlight_manager
if dimensions == 4:
region_size = self._traverse_hypercube(
shape, fiber, highlight_manager=hl_manager)
elif dimensions == 3:
region_size = self._traverse_cube(shape,
fiber,
highlight_manager=hl_manager)
elif dimensions == 2:
region_size = self._traverse_matrix(
shape, fiber, highlight_manager=hl_manager)
elif dimensions == 1:
region_size = self._traverse_vector(
shape, fiber, highlight_manager=hl_manager)
else:
self.logger.info(
f"Unsupported number of ranks for uncompressed image ({dimensions})"
)
region_size = [1, 1]
return region_size
def __init__(self, *tensors, style='tree', progress=True):
"""__init__"""
#
# Set up logging
#
self.logger = logging.getLogger('fibertree.graphics.movie_canvas')
#
# Set image type
#
self.style = style
#
# Set tqdm control
#
self.use_tqdm = progress
#
# Set up tensor class variables
#
# Note: We conditionally unwrap Payload objects
#
self.tensors = []
self.image_list_per_tensor = []
for tensor in tensors:
self.tensors.append(Payload.get(tensor))
self.image_list_per_tensor.append([])
#
# Font to use for text
#
self.font = ImageFont.truetype('Pillow/Tests/fonts/DejaVuSans.ttf', 16)
#
# Add an initial frame with nothing highlighted (it looks good)
#
self.addFrame()
def _create_tree(self):
"""create_tree
Create an image of a tensor or fiber tree
Notes
------
The drawing is made in a coordinate space where the X
dimension is measured in the number of non-empty fiber
coordinates being displayed and the Y dimension is measured in
layers of the tree. Translation to pixels happens in the
draw_*() methods.
"""
object = self.object
#
# Create the objects for the image
#
self._image_setup()
#
# Display either the root of a tensor or a raw fiber
#
if isinstance(object, Tensor):
#
# Displaying a tensor
#
root = object.getRoot()
#
# Get tensor's name
#
name = object.getName()
#
# Get tensor's color
#
self._color = object.getColor()
#
# Create rank_id string
#
# Note: if rank_id is a list, convert to a string
#
ranks = ", ".join([str(r) for r in object.getRankIds()])
if name:
self._draw_rank(0, f"Tensor: {name}[{ranks}]")
else:
self._draw_rank(0, f"File: {object.yamlfile}")
elif isinstance(object, Fiber):
#
# Displaying a fiber
#
root = object
self._color = "red"
else:
#
# Displaying nothing?
#
root = None
self._color = "red"
#
# Process appropriately if root has 0 dimensions or more
#
if not Payload.contains(root, Fiber):
#
# Draw a 0-D tensor, i.e., a value
#
hlm = self.highlight_manager
hl = hlm.getColorCoord(0)
self._draw_coord(0, 0, "R")
self._draw_line(0, 1 / 2, 1, 1 / 2)
self._draw_value(1, 0, Payload.get(root), hl)
region_end = 1
else:
#
# Draw a non-0-D tensor or a fiber, i.e., the fiber tree
#
region_end = self._traverse(
root, highlight_manager=self.highlight_manager)
#
# Crop the image
#
right = 200 + self._offset2x(region_end)
lower = 20 + self.max_y
self.im = self.im.crop((0, 0, right, lower))
def _create_uncompressed(self):
"""Create uncompressed image
Create an image of a tensor or fiber tree
Notes
------
The drawing is made in a coordinate space where the X
and Y are the positions in the tensor.
Translation to pixels happens in the draw_*() methods.
"""
object = self.object
#
# Create the objects for the image
#
self._image_setup()
#
# Display either the root of a tensor or a raw fiber
#
if isinstance(object, Tensor):
#
# Handle a tensor
#
root = object.getRoot()
self._color = object.getColor()
#
# Print tensor name
#
name = object.getName()
if not name:
name = "unknown"
ranks = ", ".join([str(r) for r in object.getRankIds()])
self._draw_label(0, 0, f"Tensor: {name}[{ranks}]")
elif isinstance(object, Fiber):
#
# Handle a fiber
#
root = object
self._color = "red"
else:
#
# Handle a scalar
#
root = None
self._color = "red"
#
# Process appropriately if root has 0 dimensions or more
#
if not Payload.contains(root, Fiber):
# Draw a 0-D tensor, i.e., a value
# TBD
region_size = [1, 1]
else:
# Draw a non-0-D tensor or a fiber, i.e., the fiber tree
region_size = self._traverse(root)
#
# Crop the image
#
if region_size[0] > self.row_extent or region_size[1] > self.col_extent:
msg = f"Uncompressed image too large [ {region_size[0]}, {region_size[1]}"
self.logger.info(msg)
return
right = 200 + self._col2x(region_size[1])
lower = 20 + self._row2y(region_size[0])
self.logger.debug(
f"right: {region_size[1]}/{right}, lower: {region_size[0]}/{lower}"
)
self.im = self.im.crop((0, 0, right, lower))
print(f"b = CoordPayload(6, 2) -> {b}")
print("")
z = a + b
print(f"a+b -> {z}")
z = a + 1
print(f"a+1 -> {z}")
z = 1 + a
print(f"1+a -> {z}")
print("")
p = Payload(4)
print(f"p = Payload(4) -> {p}")
z = a + p
print(f"a+p -> {z}")
z = p + a
print(f"p+a -> {z}")
print("")
a += b
print(f"a+=b -> {a}")
a = CoordPayload(5, 4)
a += 2
def test_union_2x_1d(self):
"""Test union 2-way for 1d fibers"""
ans = Fiber([0, 2, 3, 4, 6], [('AB', Payload(1), Payload(2)),
('AB', Payload(3), Payload(4)),
('B', Payload(0), Payload(5)),
('A', Payload(5), Payload(0)),
('A', Payload(7), Payload(0))])
a_m = self.input["a1_m"]
b_m = self.input["b1_m"]
z_m1 = a_m | b_m
z_m2 = Fiber.union(a_m, b_m)
for test, z_m in enumerate([z_m1, z_m2]):
with self.subTest(test=test):
# Check for right answer
self.assertEqual(z_m, ans)
# Check that payloads are of correct type
self.assertIsInstance(z_m[0].payload.value[1], Payload)
self.assertIsInstance(z_m[2].payload.value[1], Payload)
self.assertIsInstance(z_m[3].payload.value[2], Payload)
# Check that default was set properly
z_m_default = z_m.getDefault()
self.assertEqual(z_m_default, Payload(('', 0, 0)))
self.assertIsInstance(z_m_default, Payload)
# Check final shape is correct
z_m_shape = z_m.getShape()
self.assertEqual(z_m_shape, [7])
# print(f"\na_d:\n{a_d}")
# print(f"\nd_d:\n{d_d})")
# a_less_d = a_d - d_d
# print(f"\na_less_d:\n{a_less_d})")
# assignment1 = d_d << a_less_d
# print(f"\nd_d << (a_d - d_d):\n{assignment1}")
# assignment2 = f1_d << assignment1
# print(f"\nf1_d << (d_d << (a_d - d_d)):\n{assignment2}")
for d, (f1_ref, (d_ref, _)) in f1_d << (d_d << a_d):
print(f" Processing destination {d} = {d_ref}")
if Payload.isEmpty(d_ref):
print(f"Adding destination {d}")
f1_ref += 1
d_ref += level
level += 1
f0 = f1
f0_d = f0.getRoot()
d_d.print("\nDistance Tensor")
print("")
print("--------------------------------------")
print("")
def _traverse(self, fiber, level=0, offset=0, highlight_manager=None):
"""traverse"""
#
# Check if this is level0, which may just be a payload
#
if level == 0:
region_start = 0
if not Payload.contains(fiber, Fiber):
#
# Draw a 0-D tensor, i.e., a value (NOT a fiber)
#
self._draw_coord(0, 0, "R")
self._draw_line(0, 1 / 2, 1, 1 / 2)
self._draw_value(1, 0, Payload.get(fiber))
region_end = 1
else:
#
# Recursively traverse and draw the fibers of a non-0-D tensor
#
region_end = self._traverse(
fiber,
level=1,
offset=offset,
highlight_manager=highlight_manager)
region_size = region_end - region_start
#
# Draw root of tree
#
fiber_size = 1
fiber_start = region_start + (region_size - fiber_size) / 2
self._draw_coord(0, fiber_start, "R")
self._draw_line(0, region_size / 2, 1, region_size / 2)
return region_end
#
# Process the fibers of the tree (level > 0)
#
#
# Print out the rank information (if available)
#
if offset == 0 and not fiber.getOwner() is None:
self._draw_rank(level, "Rank: %s " % fiber.getOwner().getId())
#
# Initialize drawing region information
#
region_start = offset
region_end = offset
#
# Figure out space of region below this fiber
#
targets = []
coordinate_start = region_start
#
# Traverse the fiber at this level
#
for n, (c, p) in enumerate(fiber):
#
# TBD: Truncate fibers with too many elements
#
# if n > 10: break
if Payload.contains(p, Fiber):
#
# Configure highlights for this fiber
#
next_highlight_manager = highlight_manager.addFiber(c)
#
# Draw the object below this coordinate (in "c")
#
region_end = self._traverse(
Payload.get(p),
level=level + 1,
offset=region_end,
highlight_manager=next_highlight_manager)
else:
region_end += 1
#
# Record (in "targets") the middle of the object below
# this coordinate to draw a line to it later, and
# calculate where the next object starts ("coordinate_start")
#
targets.append(coordinate_start +
(region_end - coordinate_start) / 2)
coordinate_start = region_end
#
# If the fiber was empty we still occupy a single space
#
if len(fiber) == 0:
region_end += 1
region_size = region_end - region_start
#
# Set up the highlighting for this level
#
highlight_subtensor = highlight_manager.highlight_subtensor
#
# Display fiber for this level
#
fiber_size = len(fiber)
fiber_start = region_start + (region_size - fiber_size) / 2
self._draw_fiber(level, fiber_start, fiber_start + fiber_size,
highlight_subtensor)
pos = fiber_start
for c, p in fiber:
#
# Gets sets of workers to be colored
#
color_coord = highlight_manager.getColorCoord(c)
color_subtensor = highlight_manager.getColorSubtensor()
color_coord_or_subtensor = color_coord | color_subtensor
#
# Draw the coordinates, lines and maybe values
#
self._draw_coord(level, pos, c, color_coord_or_subtensor)
if len(color_coord - color_subtensor):
self._draw_intra_line(level, fiber_start + fiber_size / 2,
pos + 0.5, True)
#
# Draw the line if the next level will actually draw something.
#
if not Payload.contains(p, Fiber) or len(p.coords) > 0:
self._draw_line(level, pos + 0.5, level + 1, targets.pop(0),
len(color_coord_or_subtensor) > 0)
else:
#
# Nothing to connect a line to so pop target
#
targets.pop(0)
if not Payload.contains(p, Fiber):
#
# How could this not be the leaf ---
# "and rest_of_highlighting == []"
#
self._draw_value(level + 1, pos, Payload.get(p),
color_coord_or_subtensor)
pos += 1
return region_end
