zhutian
69 lines
2.0 KiB
Python
69 lines
2.0 KiB
Python
from __future__ import absolute_import
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from __future__ import division
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from __future__ import print_function
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from __future__ import unicode_literals
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import unittest
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import numpy as np
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import caffe2.python.onnx.backend as c2
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import onnx
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import onnx_tf.backend as tf
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from onnx import helper
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from onnx import TensorProto
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def find_between(s, first, last):
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try:
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start = s.index(first) + len(first)
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end = s.index(last, start)
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return s[start:end]
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except ValueError:
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return ""
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class TestLargeModel(unittest.TestCase):
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MODEL_PATH = "../../onnx_models/"
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def test(self):
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_model = onnx.load(self.MODEL_PATH + "shufflenet/model.onnx")
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node_count = len(_model.graph.node)
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more_outputs = []
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output_to_check = []
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for node in _model.graph.node:
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more_outputs.append(
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helper.make_tensor_value_info(node.output[0], TensorProto.FLOAT,
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(100, 100)))
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output_to_check.append(node.output[0])
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_model.graph.output.extend(more_outputs)
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tf_rep = tf.prepare(_model)
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cf_rep = c2.prepare(_model)
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sample = np.load(
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self.MODEL_PATH + "shufflenet/test_data_{}.npz".format(str(1)),
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encoding='bytes')
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inputs = list(sample['inputs'])
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outputs = list(sample['outputs'])
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my_out = tf_rep.run(inputs)
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cf_out = cf_rep.run(inputs)
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for op in output_to_check:
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try:
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np.savetxt(
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op.replace("/", "__") + ".cf", cf_out[op].flatten(), delimiter='\t')
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np.savetxt(
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op.replace("/", "__") + ".tf", my_out[op].flatten(), delimiter='\t')
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np.testing.assert_allclose(my_out[op], cf_out[op], rtol=1e-2)
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print(op, "results of this layer are correct within tolerence.")
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except Exception as e:
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np.set_printoptions(threshold=np.inf)
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mismatch_percent = (find_between(str(e), "(mismatch", "%)"))
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print(op, "mismatch with percentage {} %".format(mismatch_percent))
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if __name__ == '__main__':
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unittest.main()
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pass
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