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Louis Verhaard0b8268a2020-08-05 16:11:29 +02001# Copyright (C) 2020 Arm Limited or its affiliates. All rights reserved.
2#
3# SPDX-License-Identifier: Apache-2.0
4#
5# Licensed under the Apache License, Version 2.0 (the License); you may
6# not use this file except in compliance with the License.
7# You may obtain a copy of the License at
8#
9# www.apache.org/licenses/LICENSE-2.0
10#
11# Unless required by applicable law or agreed to in writing, software
12# distributed under the License is distributed on an AS IS BASIS, WITHOUT
13# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14# See the License for the specific language governing permissions and
15# limitations under the License.
16# Description:
17# Utilities used in vela unit tests
18import numpy as np
19
20from ethosu.vela import architecture_features
21from ethosu.vela.data_type import DataType
22from ethosu.vela.nn_graph import Subgraph
Louis Verhaard0b8268a2020-08-05 16:11:29 +020023from ethosu.vela.operation import Operation
24from ethosu.vela.tensor import create_const_tensor
Dwight Lidman8359a472020-09-28 15:53:40 +020025from ethosu.vela.tensor import QuantizationParameters
Louis Verhaard0b8268a2020-08-05 16:11:29 +020026from ethosu.vela.tensor import Tensor
27
28
29def create_arch():
30 return architecture_features.ArchitectureFeatures(
31 vela_config=None,
32 system_config=None,
33 accelerator_config=architecture_features.Accelerator.Ethos_U55_128.value,
Louis Verhaard0b8268a2020-08-05 16:11:29 +020034 override_block_config=None,
35 block_config_limit=None,
36 global_memory_clock_scale=1.0,
37 max_blockdep=0,
Patrik Gustavsson90831bc2020-08-24 16:26:11 +020038 weight_estimation_scaling=1.0,
Louis Verhaard0b8268a2020-08-05 16:11:29 +020039 )
40
41
Dwight Lidman8359a472020-09-28 15:53:40 +020042def create_elemwise_op(
43 type,
44 name,
45 ifm_shape,
46 ifm2_shape,
47 ofm_shape,
48 datatype=DataType.uint8,
49 ifm_quant=QuantizationParameters(),
50 ifm2_quant=QuantizationParameters(),
51 ofm_quant=QuantizationParameters(),
52):
Louis Verhaard0b8268a2020-08-05 16:11:29 +020053 # Creates elementwise operation with constant IFM/IFM2
54 if datatype.size_in_bytes() == 1:
55 np_type = np.uint8
56 elif datatype.size_in_bytes() == 2:
57 np_type = np.int16
58 else:
59 np_type = np.int32
60 op = Operation(type, name)
Dwight Lidman8359a472020-09-28 15:53:40 +020061 op.add_input_tensor(
62 create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type, quantization=ifm_quant)
63 )
64 op.add_input_tensor(
65 create_const_tensor(
66 name + "_ifm2", ifm2_shape, datatype, np.zeros(ifm2_shape), np_type, quantization=ifm2_quant
67 )
68 )
Louis Verhaard0b8268a2020-08-05 16:11:29 +020069 ofm = Tensor(ofm_shape, datatype, name + "_ofm")
Dwight Lidman8359a472020-09-28 15:53:40 +020070 ofm.quantization = ofm_quant
Louis Verhaard0b8268a2020-08-05 16:11:29 +020071 op.set_output_tensor(ofm)
Louis Verhaard0b8268a2020-08-05 16:11:29 +020072 return op
73
74
Michael McGeagh1f951fc2020-10-14 09:30:02 +010075def create_op_with_quant_tensors(op_type, ifm_shape, ofm_shape, weights_shape=None, datatype=DataType.uint8):
76 qp = QuantizationParameters()
77 ifm = Tensor(ifm_shape, datatype, "in")
78 ifm.quantization = qp
79 ofm = Tensor(ofm_shape, datatype, "out")
80 ofm.quantization = qp
81 op = Operation(op_type, "op")
82 op.add_input_tensor(ifm)
83 op.set_output_tensor(ofm)
84 # Optional weight tensor
85 if weights_shape is not None:
86 if datatype.size_in_bytes() == 1:
87 np_type = np.uint8
88 elif datatype.size_in_bytes() == 2:
89 np_type = np.int16
90 else:
91 np_type = np.int32
92 qp.zero_point = np.zeros(weights_shape)
93 weights = create_const_tensor(
94 "weights", weights_shape, datatype, np.zeros(weights_shape), np_type, quantization=qp
95 )
96 op.add_input_tensor(weights)
97 return op
98
99
Louis Verhaardfa2f92a2020-09-21 11:56:18 +0200100def create_op(op_type, inputs, output, attrs=dict()):
101 op = Operation(op_type, output.name + "_op")
102 op.inputs = inputs
103 op.outputs = [output]
104 op.attrs = attrs
105 return op
106
107
Louis Verhaard0b8268a2020-08-05 16:11:29 +0200108def create_subgraph(op_list):
109 # Creates subgraph using the given list of operations
110 sg = Subgraph()
111 all_inputs = set(tens for op in op_list for tens in op.inputs)
112 # Reversing, so that the resulting subgraph has same order as op_list
113 for op in op_list[::-1]:
114 for tens in op.outputs:
115 if tens not in all_inputs and tens not in sg.output_tensors:
116 sg.output_tensors.append(tens)
117 return sg