# Path: loom/util.py
# def cp_ns(source, destin):
#     'like cp -ns, link destin to source if destin does not exist'
#     if not os.path.exists(destin):
#         assert os.path.exists(source), source
#         dirname = os.path.dirname(destin)
#         if dirname:
#             mkdir_p(dirname)
#         try:
#             os.symlink(source, destin)
#         except OSError as e:
#             if not os.path.exists(destin):
#                 raise e
# 
# Path: loom/util.py
# def mkdir_p(dirname):
#     'like mkdir -p'
#     if not os.path.exists(dirname):
#         try:
#             os.makedirs(dirname)
#         except OSError as e:
#             if not os.path.exists(dirname):
#                 raise e
# 
# Path: loom/util.py
# def parallel_map(fun, args):
#     if not isinstance(args, list):
#         args = list(args)
#     is_daemon = multiprocessing.current_process().daemon
#     if THREADS == 1 or len(args) < 2 or is_daemon:
#         print 'Running {} in this thread'.format(fun.__name__)
#         return map(fun, args)
#     else:
#         print 'Running {} in {:d} threads'.format(fun.__name__, THREADS)
#         pool = multiprocessing.Pool(THREADS)
#         fun_args = [(fun, arg) for arg in args]
#         return pool.map(print_trace, fun_args, chunksize=1)
# 
# Path: loom/util.py
# def rm_rf(path):
#     'like rm -rf'
#     if os.path.exists(path):
#         if os.path.isdir(path):
#             shutil.rmtree(path)
#         else:
#             os.remove(path)


import os
import loom
import loom.config
import loom.consensus
import loom.generate
import loom.transforms
import loom.format
import loom.runner
import loom.store
import parsable
from distributions.io.stream import json_dump
from distributions.io.stream import json_load
from distributions.io.stream import open_compressed
from distributions.io.stream import protobuf_stream_dump
from loom.util import cp_ns
from loom.util import mkdir_p
from loom.util import parallel_map
from loom.util import rm_rf
        tares_in=paths['ingest']['tares'],
        rows_in=paths['ingest']['rows'],
        rows_out=paths['ingest']['diffs'],
        debug=debug)
    loom.format.export_rows(
        encoding_in=paths['ingest']['encoding'],
        rows_in=paths['ingest']['rows'],
        rows_csv_out=paths['ingest']['rows_csv'],
        chunk_size=chunk_size)
    loom.format.import_rowids(
        rows_csv_in=paths['ingest']['rows_csv'],
        rowids_out=paths['ingest']['rowids'],
        id_field='_id')
    protobuf_stream_dump([], paths['query']['query_log'])
    loom.config.config_dump({}, paths['query']['config'])
    for seed, sample in enumerate(paths['samples']):
        loom.config.config_dump({'seed': seed}, sample['config'])
        loom.generate.generate_init(
            encoding_in=paths['ingest']['encoding'],
            model_out=sample['init'],
            seed=seed)
        loom.runner.shuffle(
            rows_in=paths['ingest']['diffs'],
            rows_out=sample['shuffled'],
            seed=seed,
            debug=debug)
        protobuf_stream_dump([], sample['infer_log'])
    sample0 = paths['samples'][0]
    for seed, sample in enumerate(paths['samples'][1:]):
        if LOOM_DEBUG_MIX:

# Path: loom/util.py
# def cp_ns(source, destin):
#     'like cp -ns, link destin to source if destin does not exist'
#     if not os.path.exists(destin):
#         assert os.path.exists(source), source
#         dirname = os.path.dirname(destin)
#         if dirname:
#             mkdir_p(dirname)
#         try:
#             os.symlink(source, destin)
#         except OSError as e:
#             if not os.path.exists(destin):
#                 raise e
# 
# Path: loom/util.py
# def mkdir_p(dirname):
#     'like mkdir -p'
#     if not os.path.exists(dirname):
#         try:
#             os.makedirs(dirname)
#         except OSError as e:
#             if not os.path.exists(dirname):
#                 raise e
# 
# Path: loom/util.py
# def parallel_map(fun, args):
#     if not isinstance(args, list):
#         args = list(args)
#     is_daemon = multiprocessing.current_process().daemon
#     if THREADS == 1 or len(args) < 2 or is_daemon:
#         print 'Running {} in this thread'.format(fun.__name__)
#         return map(fun, args)
#     else:
#         print 'Running {} in {:d} threads'.format(fun.__name__, THREADS)
#         pool = multiprocessing.Pool(THREADS)
#         fun_args = [(fun, arg) for arg in args]
#         return pool.map(print_trace, fun_args, chunksize=1)
# 
# Path: loom/util.py
# def rm_rf(path):
#     'like rm -rf'
#     if os.path.exists(path):
#         if os.path.isdir(path):
#             shutil.rmtree(path)
#         else:
#             os.remove(path)


# Path: loom/datasets.py
import os
import loom
import loom.config
import loom.consensus
import loom.generate
import loom.transforms
import loom.format
import loom.runner
import loom.store
import parsable
from distributions.io.stream import json_dump
from distributions.io.stream import json_load
from distributions.io.stream import open_compressed
from distributions.io.stream import protobuf_stream_dump
from loom.util import cp_ns
from loom.util import mkdir_p
from loom.util import parallel_map
from loom.util import rm_rf

        tares_in=paths['ingest']['tares'],
        rows_in=paths['ingest']['rows'],
        rows_out=paths['ingest']['diffs'],
        debug=debug)
    loom.format.export_rows(
        encoding_in=paths['ingest']['encoding'],
        rows_in=paths['ingest']['rows'],
        rows_csv_out=paths['ingest']['rows_csv'],
        chunk_size=chunk_size)
    loom.format.import_rowids(
        rows_csv_in=paths['ingest']['rows_csv'],
        rowids_out=paths['ingest']['rowids'],
        id_field='_id')
    protobuf_stream_dump([], paths['query']['query_log'])
    loom.config.config_dump({}, paths['query']['config'])
    for seed, sample in enumerate(paths['samples']):
        loom.config.config_dump({'seed': seed}, sample['config'])
        loom.generate.generate_init(
            encoding_in=paths['ingest']['encoding'],
            model_out=sample['init'],
            seed=seed)
        loom.runner.shuffle(
            rows_in=paths['ingest']['diffs'],
            rows_out=sample['shuffled'],
            seed=seed,
            debug=debug)
        protobuf_stream_dump([], sample['infer_log'])
    sample0 = paths['samples'][0]
    for seed, sample in enumerate(paths['samples'][1:]):
        if LOOM_DEBUG_MIX:

            cp_ns(sample0['model'], sample['model'])