def test_import_wrong_date():
from returnn.import_ import import_
from returnn.import_.common import InvalidVersion
try:
import_("github.com/rwth-i6/returnn-experiments", "common/test.py",
"20210301-01094bef2761")
except InvalidVersion as exc:
print("got expected exception:", exc)
else:
raise Exception(
"We expected an invalid version exception but got nothing.")
def test_import_wrong_pkg_py_import():
from pprint import pprint
from returnn.import_ import import_
from returnn.import_.common import _registered_modules, MissingExplicitImport
# Use some other commit here which is not used by the other tests, to not mess up.
mod = import_("github.com/rwth-i6/returnn-experiments", "common",
"20210302-10beb9d1c57e")
print("Loaded mod %s, name %s, file %s" %
(mod, mod.__name__, mod.__file__))
print("Registered modules:")
pprint(_registered_modules)
# Mod name, without "common".
mod_name = "returnn_import.github_com.rwth_i6.returnn_experiments.v20210302153450_10beb9d1c57e"
assert mod_name in _registered_modules
assert mod_name in sys.modules
# Remove from both to force a reload.
del _registered_modules[mod_name]
del sys.modules[mod_name]
try:
import returnn_import.github_com.rwth_i6.returnn_experiments.v20210302153450_10beb9d1c57e
except MissingExplicitImport as exc: # but *not* a normal ImportError
print("Got expected exception:", exc)
else:
raise Exception(
"We expected an import error exception but got nothing.")
def test_import_root_repo_sub_mod():
from returnn.import_ import import_
mod = import_("github.com/rwth-i6/returnn_common", "test/hello.py",
"20210603-3752d77")
print("Loaded mod %s, name %s, file %s" %
(mod, mod.__name__, mod.__file__))
assert_equal(mod.hello(), "hello world")
def test_import_():
from returnn.import_ import import_
mod = import_("github.com/rwth-i6/returnn-experiments", "common/test.py",
"20210302-01094bef2761")
print("Loaded mod %s, name %s, file %s" %
(mod, mod.__name__, mod.__file__))
assert_equal(mod.hello(), "hello world")
def test_import_root_repo_pkg():
from returnn.import_ import import_
mod = import_("github.com/rwth-i6/returnn_common", ".", "20210602-1bc6822")
print("Loaded mod %s, name %s, file %s" %
(mod, mod.__name__, mod.__file__))
from returnn_import.github_com.rwth_i6.returnn_common.v20210602162042_1bc6822b2fd1 import test
assert_equal(test.hello(), "hello world")
def test_import_pkg_py_import():
from returnn.import_ import import_
mod = import_("github.com/rwth-i6/returnn-experiments", "common",
"20210302-01094bef2761")
print("Loaded mod %s, name %s, file %s" %
(mod, mod.__name__, mod.__file__))
# noinspection PyUnresolvedReferences
from returnn_import.github_com.rwth_i6.returnn_experiments.v20210302133012_01094bef2761 import common
assert common is mod
#!crnn/rnn.py
# kate: syntax python;
# vim: ft=python sw=2:
# based on Andre Merboldt rnnt-fs.bpe1k.readout.zoneout.lm-embed256.lr1e_3.no-curric.bs12k.mgpu.retrain1.config
from returnn.import_ import import_
import_("github.com/rwth-i6/returnn-experiments", "common")
from returnn_import.github_com.rwth_i6.returnn_experiments.dev.common.common_config import *
from returnn_import.github_com.rwth_i6.returnn_experiments.dev.common.datasets.asr.librispeech import oggzip
from returnn_import.github_com.rwth_i6.returnn_experiments.dev.common.models.transducer.transducer_fullsum import make_net
from returnn_import.github_com.rwth_i6.returnn_experiments.dev.common.training.pretrain import Pretrain
# data
globals().update(oggzip.Librispeech().get_config_opts())
get_network = Pretrain(make_net, {
"enc_lstm_dim": (512, 1024),
"enc_num_layers": (3, 6)
},
num_epochs=20).get_network
# trainer
batching = "random"
batch_size = 1000 if debug_mode else 12000
max_seqs = 10 if debug_mode else 200
max_seq_length = {"classes": 75}
num_epochs = 100
model = "net-model/network"
cleanup_old_models = True
from typing import Union, Optional, Tuple, List, Dict, Any
from returnn.import_ import import_
# common = import_("github.com/rwth-i6/returnn_common", "models/base", "20210805-a44e7fa4209663c4ea6f71a7406d6839ed699df2")
# from returnn_import.github_com.rwth_i6.returnn_common.v20210805202428_a44e7fa42096.models.base import\
# LayerRef, LayerDictRaw, Module, get_root_extern_data
# import returnn_import.github_com.rwth_i6.returnn_common.v20210805202428_a44e7fa42096.models._generated_layers as layers
common = import_("github.com/rwth-i6/returnn_common", "models/base",
"20210929-2243f105ba0befb2eba63f53a2350d4e26639532")
from returnn_import.github_com.rwth_i6.returnn_common.v20210929142536_2243f105ba0b.models.base import \
LayerRef, LayerDictRaw, Module, get_root_extern_data
import returnn_import.github_com.rwth_i6.returnn_common.v20210929142536_2243f105ba0b.models._generated_layers as layers
from returnn.util.basic import NotSpecified
from .specaugment_clean import SpecAugmentBlock, SpecAugmentSettings
class Encoder2DConvBlock(Module):
def __init__(self,
l2=0.001,
dropout=0.3,
act='relu',
filter_sizes=[(3, 3)],
pool_sizes=[(1, 2)],
channel_sizes=[32],
padding='same'):
super().__init__()
self.split_feature_layer = layers.SplitDims(axis="F", dims=(-1, 1))
self.conv_layers = []
self.pool_layers = []
'tdp_scale': 0.0
},
'n_out': 139,
'target': None
},
#'source': {'class': 'eval', 'eval': "self.network.get_config().typed_value('_specaugment_eval_func')(source(0, as_data=True), network=self.network)"}
'source': {
'class': 'copy',
'from': ["data"]
}
}
import time
start = time.time()
from returnn.import_ import import_
common = import_("github.com/rwth-i6/returnn_common", "nn",
"20211202-c025fdeef1843ab06e9888b6a17d217463b961bc")
from returnn_import.github_com.rwth_i6.returnn_common.v20211202164723_c025fdeef184 import nn
from returnn_import.github_com.rwth_i6.returnn_common.v20211202164723_c025fdeef184.nn \
import Module, LayerRef, get_extern_data, get_root_extern_data, NameCtx, make_root_net_dict
from .specaugment_clean_v2 import specaugment, SpecAugmentSettings
print("old imports took %f" % (time.time() - start))
class BLSTMPoolModule(Module):
def __init__(self, hidden_size, pool, dropout=None, l2=None):
super().__init__()
self.fw_rec = nn.LSTM(n_out=hidden_size, direction=1, l2=l2)
self.bw_rec = nn.LSTM(n_out=hidden_size, direction=-1, l2=l2)
#!crnn/rnn.py
# kate: syntax python;
# vim: ft=python sw=2:
# adapted for import_ & common recipes
from returnn.tf.util.data import DimensionTag, Data
from returnn.import_ import import_
import_("github.com/rwth-i6/returnn-experiments", "common", "20210324-75f7809")
from returnn_import.github_com.rwth_i6.returnn_experiments.v20210324123103_75f78096518b.common.common_config import *
from returnn_import.github_com.rwth_i6.returnn_experiments.v20210324123103_75f78096518b.common.datasets.asr.librispeech import oggzip, vocabs
from returnn_import.github_com.rwth_i6.returnn_experiments.v20210324123103_75f78096518b.common.data import get_common_data_path
# This config is mostly for testing.
# Probably you want `--task eval`.
# I get: dev: score 4.636750261205999 error None devtrain: score 1.5685920611769462 error None
load = get_common_data_path(
"librispeech/transducer/"
"andre-rnnt-fs.bpe1k.readout.zoneout.lm-embed256.lr1e_3.no-curric.bs12k.mgpu.retrain1/"
"net-model/network.160")
if task == "search":
_task = "search"
else:
# The config does not really expect anything else than task=="train"...
# But this is what we want, also for task=="eval" etc.
_task = "train"
use_horovod = config.bool("use_horovod", False)
horovod_dataset_distribution = "random_seed_offset"
horovod_reduce_type = "param"
