import os
os.environ["SEAMLESS_COMMUNION_ID"] = "jobmaster"
os.environ["SEAMLESS_COMMUNION_INCOMING"] = "localhost:8602"
import seamless
seamless.set_ncores(0)
from seamless import communion_server
communion_server.configure_master(
buffer=True,
buffer_status=True,
transformation_job=True,
transformation_status=True
)
from seamless.highlevel import load_graph
import sys, json
infile, outfile = sys.argv[1:]
graph = json.load(open(infile))
seamless.database_cache.connect()
ctx = load_graph(graph)
import asyncio
done = asyncio.sleep(1)
asyncio.get_event_loop().run_until_complete(done)
ctx.compute()
colored_graph = ctx.get_graph()
"""
Retrieval of buffers and computation results from database cache
First run simple.py with Seamless database running
"""
import seamless
from seamless.core import context, cell, transformer, unilink
seamless.set_ncores(0) # Forbids Seamless to add 1 and 2 by itself
seamless.database_cache.connect()
ctx = context(toplevel=True)
ctx.cell1 = cell("int").set_checksum(
"bc4bb29ce739b5d97007946aa4fdb987012c647b506732f11653c5059631cd3d" # 1
)
ctx.cell2 = cell("int").set_checksum(
"191fb5fc4a9bf2ded9a09a0a2c4eb3eb90f15ee96deb1eec1a970df0a79d09ba" # 2
)
ctx.code = cell("transformer").set_checksum(
"1cbba7cc10e067273fdec7cc350d2b87508c1959d26bbab4f628f6f59ec49607" # a + b
)
ctx.result = cell("int")
ctx.tf = transformer({"a": "input", "b": "input", "c": "output"})
ctx.cell1_unilink = unilink(ctx.cell1)
ctx.cell1_unilink.connect(ctx.tf.a)
ctx.cell2.connect(ctx.tf.b)
ctx.code_copy = cell("transformer")
ctx.code.connect(ctx.code_copy)
ctx.code_copy.connect(ctx.tf.code)
ctx.result_unilink = unilink(ctx.result)
import seamless
from seamless.core import macro_mode_on
from seamless.core import context, cell, transformer, pytransformercell, link
from seamless import get_hash
seamless.set_ncores(0)
from seamless import communionserver
communionserver.configure_master(
value=True,
transformer_job=True,
transformer_result=True,
transformer_result_level2=True
)
communionserver.configure_servant(value=True)
#redis_cache = seamless.RedisCache()
with macro_mode_on():
ctx = context(toplevel=True)
ctx.cell1 = cell().set(2)
ctx.cell2 = cell().set(3)
ctx.result = cell()
ctx.tf = transformer({
"a": "input",
"b": "input",
"c": "output"
})
ctx.cell1.connect(ctx.tf.a)
ctx.cell2.connect(ctx.tf.b)
ctx.code = pytransformercell()
ctx.code.connect(ctx.tf.code)
# will not work until load_graph will be much smarter
if args.database:
communion_server.configure_servant({
"buffer": False,
"buffer_status": False,
"buffer_length": False,
"transformation_job": False,
"transformation_status": False,
"semantic_to_syntactic": False,
"hard_cancel": False, # allow others to hard cancel our jobs
"clear_exception": False, # allow others to clear exceptions on our jobs
})
"""
if args.ncores is not None:
seamless.set_ncores(args.ncores)
shareserver_address = env.get("SHARESERVER_ADDRESS")
if shareserver_address is not None:
if shareserver_address == "HOSTNAME":
shareserver_address = subprocess.getoutput("hostname -I | awk '{print $1}'")
seamless.shareserver.DEFAULT_ADDRESS = shareserver_address
print("Setting shareserver address to: {}".format(shareserver_address))
import seamless.stdlib
from seamless.highlevel import load_graph, Context
graph = json.load(args.graph)
if args.zipfile is None and not args.add_zip:
ctx = load_graph(graph, mounts=args.mounts, shares=args.shares)
else:
"""
import sys
import seamless
import seamless.core.execute
seamless.core.execute.DIRECT_PRINT = True
seamless.database_sink.connect()
seamless.database_cache.connect()
#seamless.set_ncores(2)
#seamless.set_parallel_evaluations(5)
seamless.set_ncores(8) ###
seamless.set_parallel_evaluations(100) ###
# for the big testing, 20 evaluations
seamless.set_parallel_evaluations(20) ###
"""
import logging
logging.basicConfig()
logging.getLogger("seamless").setLevel(logging.DEBUG)
"""
from seamless.highlevel import Context, Cell, Macro
from seamless.highlevel.library import LibraryContainer
import time
import cProfile
return v["a"] + 2
ctx.code = cell("transformer").set(func)
ctx.tf = transformer(params)
ctx.code.connect(ctx.tf.code)
ctx.cell1.connect(ctx.tf.v)
ctx.result = cell()
ctx.tf.result.connect(ctx.result)
ctx.equilibrate()
print(ctx.result.value)
tcache = ctx._get_manager().transform_cache
tf1 = tcache.transformer_to_level1[ctx.tf]
print("TF level 1", tf1.get_hash())
tf2 = tcache.hlevel1_to_level2[tf1.get_hash()]
print("TF level 2", tf2.get_hash())
seamless.set_ncores(0) # no more local computations
ctx.ttf = transformer(params)
ctx.code.connect(ctx.ttf.code)
ctx.cell1a.connect(ctx.ttf.v)
ctx.result2 = cell()
ctx.ttf.result.connect(ctx.result2)
ctx.equilibrate()
print(ctx.result2.value)
ttf1 = tcache.transformer_to_level1[ctx.ttf]
print("TTF level 1", ttf1.get_hash())
ttf2 = tcache.hlevel1_to_level2[ttf1.get_hash()]
print("TTF level 2", ttf2.get_hash())
assert ttf2.get_hash() == tf2.get_hash()
# Version of high-in-low4.py where the input and result are really big
# To be run with Seamless database with flatfile, so that the memory usage stays low
import seamless
import seamless.core.execute
seamless.core.execute.DIRECT_PRINT = True
seamless.database_sink.connect()
seamless.database_cache.connect()
seamless.set_ncores(2)
seamless.set_parallel_evaluations(5)
"""
import logging
logging.basicConfig()
logging.getLogger("seamless").setLevel(logging.DEBUG)
"""
from seamless.highlevel import Context, Cell, Macro
sctx = Context()
sctx.inp = Cell("mixed")
sctx.inp2 = Cell()
sctx.inp2 = sctx.inp
sctx.a = Cell("str")
sctx.b = Cell("str")
sctx.a = sctx.inp2.a
sctx.b = sctx.inp2.b
def add(a, b):
print(ctx.cell1.value)
print(ctx.cell1.semantic_checksum)
print(ctx.cell1a.value)
print(ctx.cell1a.semantic_checksum)
params = {"v": ("input", "plain"), "result": "output"}
def func(v):
return v["a"] + 2
ctx.code = cell("transformer").set(func)
ctx.tf = transformer(params)
ctx.code.connect(ctx.tf.code)
ctx.cell1.connect(ctx.tf.v)
ctx.result = cell()
ctx.tf.result.connect(ctx.result)
ctx.compute()
print(ctx.result.value)
seamless.set_ncores(0) # no more local computations
ctx.ttf = transformer(params)
ctx.code.connect(ctx.ttf.code)
ctx.cell1a.connect(ctx.ttf.v)
ctx.result2 = cell()
ctx.ttf.result.connect(ctx.result2)
ctx.compute()
print(ctx.result2.value)