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Preprocessing: create a Numpy array

examples/np_array_tensorproto.ipynb

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Original Source
python
import numpy
import onnx
import os
from onnx import numpy_helper


# Preprocessing: create a Numpy array
numpy_array = numpy.array([[1.0, 2.0, 3.0], [4.0, 5.0, 6.0]], dtype=float)
print("Original Numpy array:\n{}\n".format(numpy.array2string(numpy_array)))
python
# Convert the Numpy array to a TensorProto
tensor = numpy_helper.from_array(numpy_array)
print("TensorProto:\n{}".format(tensor))
python
# Convert the TensorProto to a Numpy array
new_array = numpy_helper.to_array(tensor)
print("After round trip, Numpy array:\n{}\n".format(numpy.array2string(numpy_array)))
python
# Save the TensorProto
with open(os.path.join("resources", "tensor.pb"), "wb") as f:
    f.write(tensor.SerializeToString())
python
# Load the TensorProto
new_tensor = onnx.TensorProto()
with open(os.path.join("resources", "tensor.pb"), "rb") as f:
    new_tensor.ParseFromString(f.read())
print("After saving and loading, new TensorProto:\n{}".format(new_tensor))