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Commit 4d626291 authored by Franck Galpin's avatar Franck Galpin
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correct flake8 python errors

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training/training_scripts/NN_Intra_Prediction/generating_data_intra.py
+ 32
− 10
View file @ 4d626291
......@@ -543,7 +543,7 @@ class GeneratorDataPart(object):
"--ALF=0",
"--CCALF=0",
"--LMCSEnable=0",
"--NnlfOption=0"
"--NnlfOption=0",
]
if dict_picked["descr_stacked_up"]:
args_encoding.append(
......@@ -609,11 +609,17 @@ class GeneratorDataPart(object):
)
if rpr_scaling_ratio is not None:
if rpr_scaling_ratio != 2:
raise ValueError("`rpr_scaling_ratio` is not None and `rpr_scaling_ratio` is not equal to 2.")
raise ValueError(
"`rpr_scaling_ratio` is not None and `rpr_scaling_ratio` is not equal to 2."
)
if height_video % 8 * rpr_scaling_ratio != 0:
raise ValueError("`rpr_scaling_ratio` is not None and `height_video` is not divisible by 8*`rpr_scaling_ratio`.")
raise ValueError(
"`rpr_scaling_ratio` is not None and `height_video` is not divisible by 8*`rpr_scaling_ratio`."
)
if width_video % 8 * rpr_scaling_ratio != 0:
raise ValueError("`rpr_scaling_ratio` is not None and `width_video` is not divisible by 8*`rpr_scaling_ratio`.")
raise ValueError(
"`rpr_scaling_ratio` is not None and `width_video` is not divisible by 8*`rpr_scaling_ratio`."
)
args_encoding.append("--ScalingRatioHor={}".format(rpr_scaling_ratio))
args_encoding.append("--ScalingRatioVer={}".format(rpr_scaling_ratio))
subprocess.check_call(args_encoding, stdout=None, shell=False)
......@@ -673,7 +679,9 @@ class GeneratorDataPart(object):
os.remove(dict_picked["tuple_reference_writing"][1])
os.remove(dict_picked["tuple_reference_writing"][2])
os.remove(dict_picked["path_provided_2"])
numpy.testing.assert_equal(outs_intims[1], outs_intims[2], err_msg="Unexpected")
numpy.testing.assert_equal(
outs_intims[1], outs_intims[2], err_msg="Unexpected"
)
ch_single_or_pair_given = numpy.concatenate(
(outs_intims[0][:, :, 0:1], outs_intims[2][:, :, 0:1]), axis=2
)
......@@ -1334,7 +1342,7 @@ if __name__ == "__main__":
)
parser.add_argument(
"--is_dry_run",
help="if given, \"dry-run\" is activated. \"dry-run\" enables to run quickly the entire training of the neural network-based intra prediction mode on very little data, for the purpose of forecasting grid issues",
help='if given, "dry-run" is activated. "dry-run" enables to run quickly the entire training of the neural network-based intra prediction mode on very little data, for the purpose of forecasting grid issues',
action="store_true",
default=False,
)
......@@ -1407,7 +1415,7 @@ if __name__ == "__main__":
),
),
}
# In "dry-run, for an encoding via VTM-11-NNVC, QP belongs to {32, 42}.
if args.is_dry_run:
dict_picked["qps_int"] = numpy.array([32, 42])
......@@ -1421,7 +1429,15 @@ if __name__ == "__main__":
dict_supp = None
for pair_key in ((4, 4), (4, 8), (4, 16), (4, 32), (8, 8), (8, 16), (16, 16)):
if constants.IS_DATA_RAW_LARGE:
if pair_key in ((4, 16), (16, 4), (8, 16), (16, 8), (4, 32), (32, 4), (16, 16)):
if pair_key in (
(4, 16),
(16, 4),
(8, 16),
(16, 8),
(4, 32),
(32, 4),
(16, 16),
):
dict_hwt[pair_key] = 32768
else:
dict_hwt[pair_key] = 1024
......@@ -1431,7 +1447,9 @@ if __name__ == "__main__":
else:
dict_hwt[pair_key] = 131072
path_location = os.path.join(
args.path_to_directory_sets_training, "target_{0}_{1}".format(pair_key[0], pair_key[1]), tag_suffix_job
args.path_to_directory_sets_training,
"target_{0}_{1}".format(pair_key[0], pair_key[1]),
tag_suffix_job,
)
create_dconcurrently(path_location)
dict_in[pair_key] = os.path.join(path_location, "data.tfrecord")
......@@ -1439,7 +1457,11 @@ if __name__ == "__main__":
dict_supp[pair_key] = os.path.join(path_location, "ccs_tm_saved.npy")
with open(
os.path.join(
"results", "dispatching_paths_to_raw", "list_dicts_characteristics_own", "job_{}".format(args.index_job), "list_dicts_characteristics_own.pkl"
"results",
"dispatching_paths_to_raw",
"list_dicts_characteristics_own",
"job_{}".format(args.index_job),
"list_dicts_characteristics_own.pkl",
),
"rb",
) as file:
......
training/training_scripts/NN_Intra_Prediction/quantize/quantize.py
+ 45
− 13
View file @ 4d626291
......@@ -36,16 +36,37 @@ import os
import subprocess
DICT_QUANTIZERS = {
(4, 4): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 18 10 -2 11 10 13 0 15 13 16 -1 17 0 19 17 20 -2 21 9",
(4, 8): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 17 10 -2 11 10 13 0 15 13 16 -2 17 0 19 18 20 -2 21 9",
(4, 16): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 17 10 -2 11 10 13 0 15 13 16 -2 17 0 19 18 20 -2 21 9",
(4, 32): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 15 10 -2 11 10 13 0 15 14 16 -2 17 0 19 18 20 -2 21 9",
(8, 8): "0 7 1 13 2 1 3 18 5 13 6 1 7 18 9 17 10 -2 11 10 13 0 15 14 16 -2 17 0 19 18 20 -2 21 9",
(8, 16): "0 7 1 13 2 1 3 18 5 12 6 1 7 18 9 15 10 -2 11 9 13 0 15 14 16 -2 17 0 19 18 20 -2 21 9",
(16, 16): "0 7 1 13 2 1 3 18 5 12 6 1 7 18 9 13 10 0 11 18 13 15 14 -2 15 10 17 0 19 13 20 -2 21 0 23 17 24 -2 25 9"
(
4,
4,
): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 18 10 -2 11 10 13 0 15 13 16 -1 17 0 19 17 20 -2 21 9",
(
4,
8,
): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 17 10 -2 11 10 13 0 15 13 16 -2 17 0 19 18 20 -2 21 9",
(
4,
16,
): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 17 10 -2 11 10 13 0 15 13 16 -2 17 0 19 18 20 -2 21 9",
(
4,
32,
): "0 7 1 14 2 0 3 18 5 12 6 2 7 18 9 15 10 -2 11 10 13 0 15 14 16 -2 17 0 19 18 20 -2 21 9",
(
8,
8,
): "0 7 1 13 2 1 3 18 5 13 6 1 7 18 9 17 10 -2 11 10 13 0 15 14 16 -2 17 0 19 18 20 -2 21 9",
(
8,
16,
): "0 7 1 13 2 1 3 18 5 12 6 1 7 18 9 15 10 -2 11 9 13 0 15 14 16 -2 17 0 19 18 20 -2 21 9",
(
16,
16,
): "0 7 1 13 2 1 3 18 5 12 6 1 7 18 9 13 10 0 11 18 13 15 14 -2 15 10 17 0 19 13 20 -2 21 0 23 17 24 -2 25 9",
}
if __name__ == '__main__':
if __name__ == "__main__":
parser = argparse.ArgumentParser(
prog="Quantize SADL model in float into SADL model in 16-bit signed integer"
)
......@@ -62,7 +83,7 @@ if __name__ == '__main__':
parser.add_argument(
"path_to_exe_quantization_naive",
type=str,
help="Path to SADL naive quantizer executable"
help="Path to SADL naive quantizer executable",
)
parser.add_argument(
"height",
......@@ -75,13 +96,24 @@ if __name__ == '__main__':
help="Width of the blocks predicted by the neural network model at `args.path_to_input`",
)
args = parser.parse_args()
if not os.path.isfile(args.path_to_exe_quantization_naive):
raise OSError("The executable at `args.path_to_exe_quantization_naive` does not exist.")
raise OSError(
"The executable at `args.path_to_exe_quantization_naive` does not exist."
)
else:
if (args.height, args.width) in DICT_QUANTIZERS:
p = subprocess.Popen([args.path_to_exe_quantization_naive, args.path_to_input, args.path_to_output], stdin=subprocess.PIPE)
p = subprocess.Popen(
[
args.path_to_exe_quantization_naive,
args.path_to_input,
args.path_to_output,
],
stdin=subprocess.PIPE,
)
p.communicate(input=DICT_QUANTIZERS[(args.height, args.width)])
print("[INFO] Output model at {}".format(args.path_to_output))
else:
raise KeyError('`(args.height, args.width)` is not a key of `DICT_QUANTIZERS`.')
raise KeyError(
"`(args.height, args.width)` is not a key of `DICT_QUANTIZERS`."
)
training/training_scripts/NN_Intra_Prediction/training_nn_intra.py
+ 0
− 1
View file @ 4d626291
......@@ -58,7 +58,6 @@ IS_LOSS_VISUALIZED = False
if IS_LOSS_VISUALIZED:
import matplotlib
try:
import PyQt5
matplotlib.use('Qt5Agg')
except ImportError:
matplotlib.use('Agg')
......
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