ONE - On-device Neural Engine
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__init__.py
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1from test_utils import TestCase
2from test_utils import gen_random_tensor
3
4
6 def __init__(self):
7 self.name = _name_
8
9 def generate(self) -> dict:
10 json_content = dict()
11
12 # Generate ifm
13 json_content['ifm'] = gen_random_tensor(
14 "uint8", # dtype_str
15 (1), # scale_shape
16 (1), # zerop_shape
17 0) # quantized_dimension
18
19 # Generate ker
20 json_content['ker'] = gen_random_tensor(
21 "uint8", #dtype_str
22 (1), # scale_shape
23 (1), # zerop_shape
24 0, # quantized_dimension
25 (1, 1, 1, 2)) # value_shape (OHWI)
26
27 # Generate bias
28 json_content['bias'] = gen_random_tensor(
29 "int32", #dtype_str
30 (1), # scale_shape
31 (1), # zerop_shape
32 0, # quantized_dimension
33 (1)) # value_shape
34
35 # Generate ofm
36 json_content['ofm'] = gen_random_tensor(
37 "uint8", # dtype_str
38 (1), # scale_shape
39 (1), # zerop_shape
40 0) # quantized_dimension
41
42 return json_content
43
44
45_name_ = 'Conv2D_000_Q8'
46
47_test_case_ = Conv2D_000_Q8()