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# Owner(s): ["module: onnx"]
import glob
import os
import caffe2.python.onnx.backend as c2
import numpy as np
import onnx.backend.test
from onnx import numpy_helper
def load_tensor_as_numpy_array(f):
tensor = onnx.TensorProto()
with open(f, "rb") as file:
tensor.ParseFromString(file.read())
return tensor
def assert_similar(ref, real):
np.testing.assert_equal(len(ref), len(real))
for i in range(len(ref)):
np.testing.assert_allclose(ref[i], real[i], rtol=1e-3)
def run_generated_test(model_file, data_dir, device="CPU"):
model = onnx.load(model_file)
input_num = len(glob.glob(os.path.join(data_dir, "input_*.pb")))
inputs = []
for i in range(input_num):
inputs.append(
numpy_helper.to_array(
load_tensor_as_numpy_array(os.path.join(data_dir, f"input_{i}.pb"))
)
)
output_num = len(glob.glob(os.path.join(data_dir, "output_*.pb")))
outputs = []
for i in range(output_num):
outputs.append(
numpy_helper.to_array(
load_tensor_as_numpy_array(os.path.join(data_dir, f"output_{i}.pb"))
)
)
prepared = c2.prepare(model, device=device)
c2_outputs = prepared.run(inputs)
assert_similar(outputs, c2_outputs)
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