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"""Conversion utility from binary numpy files to JSON and the reverse."""
# Copyright (c) 2021-2022, ARM Limited.
# SPDX-License-Identifier: Apache-2.0
import json
from pathlib import Path
from typing import Optional
from typing import Union
import numpy as np
class NumpyArrayEncoder(json.JSONEncoder):
"""A JSON encoder for Numpy data types."""
def default(self, obj):
"""Encode default operation."""
if isinstance(obj, np.integer):
return int(obj)
elif isinstance(obj, np.floating):
return float(obj)
elif isinstance(obj, np.ndarray):
return obj.tolist()
return super(NumpyArrayEncoder, self).default(obj)
def get_shape(t: Union[list, tuple]):
"""Get the shape of an N-Dimensional tensor."""
# TODO: validate shape is consistent for all rows and ccolumns
if isinstance(t, (list, tuple)) and t:
return [len(t)] + get_shape(t[0])
return []
def npy_to_json(n_path: Path, j_path: Optional[Path] = None):
"""Load a numpy data file and save it as a JSON file.
n_path: the Path to the numpy file
j_path: the Path to the JSON file, if None, it is derived from n_path
"""
if not j_path:
j_path = n_path.parent / (n_path.stem + ".json")
with open(n_path, "rb") as fd:
data = np.load(fd)
jdata = {
"type": data.dtype.name,
"data": data.tolist(),
}
with open(j_path, "w") as fp:
json.dump(jdata, fp, indent=2)
def json_to_npy(j_path: Path, n_path: Optional[Path] = None):
"""Load a JSON file and save it as a numpy data file.
j_path: the Path to the JSON file
n_path: the Path to the numpy file, if None, it is derived from j_path
"""
if not n_path:
n_path = j_path.parent / (j_path.stem + ".npy")
with open(j_path, "rb") as fd:
jdata = json.load(fd)
raw_data = jdata["data"]
raw_type = jdata["type"]
shape = get_shape(raw_data)
data = np.asarray(raw_data).reshape(shape).astype(raw_type)
with open(n_path, "wb") as fd:
np.save(fd, data)
# ------------------------------------------------------------------------------
def test():
"""Test conversion routines."""
shape = [2, 3, 4]
elements = 1
for i in shape:
elements *= i
# file names
n_path = Path("data.npy")
j_path = Path("data.json")
j2n_path = Path("data_j2n.npy")
datatypes = [
np.bool_,
np.int8,
np.int16,
np.int32,
np.int64,
np.uint8,
np.uint16,
np.uint32,
np.uint64,
np.float16,
np.float32,
np.float64,
# np.float128,
# np.complex64,
# np.complex128,
# np.complex256,
# np.datetime64,
# np.str,
]
for data_type in datatypes:
dt = np.dtype(data_type)
print(data_type, dt, dt.char, dt.num, dt.name, dt.str)
# create a tensor of the given shape
tensor = np.arange(elements).reshape(shape).astype(data_type)
# print(tensor)
# save the tensor in a binary numpy file
with open(n_path, "wb") as fd:
np.save(fd, tensor)
# read back the numpy file for verification
with open(n_path, "rb") as fd:
tensor1 = np.load(fd)
# confirm the loaded tensor matches the original
assert tensor.shape == tensor1.shape
assert tensor.dtype == tensor1.dtype
assert (tensor == tensor1).all()
# convert the numpy file to json
npy_to_json(n_path, j_path)
# convert the json file to numpy
json_to_npy(j_path, j2n_path)
# read back the json-to-numpy file for verification
with open(j2n_path, "rb") as fd:
tensor1 = np.load(fd)
# confirm the loaded tensor matches the original
assert tensor.shape == tensor1.shape
assert tensor.dtype == tensor1.dtype
assert (tensor == tensor1).all()
# delete the files, if no problems were found
# they are left for debugging if any of the asserts failed
n_path.unlink()
j_path.unlink()
j2n_path.unlink()
return 0
def main(argv=None):
"""Load and convert supplied file based on file suffix."""
import argparse
parser = argparse.ArgumentParser()
parser.add_argument(
"path", type=Path, help="the path to the file to convert, or 'test'"
)
args = parser.parse_args(argv)
path = args.path
if str(path) == "test":
print("test")
return test()
if not path.is_file():
print(f"Invalid file - {path}")
return 2
if path.suffix == ".npy":
npy_to_json(path)
elif path.suffix == ".json":
json_to_npy(path)
else:
print("Unknown file type - {path.suffix}")
return 2
return 0
if __name__ == "__main__":
exit(main())
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