Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 1 | # 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 |
| 18 | import numpy as np |
| 19 | |
| 20 | from ethosu.vela import architecture_features |
| 21 | from ethosu.vela.data_type import DataType |
| 22 | from ethosu.vela.nn_graph import Subgraph |
Dwight Lidman | 0dd21c7 | 2020-11-24 13:45:50 +0100 | [diff] [blame] | 23 | from ethosu.vela.operation import Op |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 24 | from ethosu.vela.operation import Operation |
| 25 | from ethosu.vela.tensor import create_const_tensor |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 26 | from ethosu.vela.tensor import QuantizationParameters |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 27 | from ethosu.vela.tensor import Tensor |
| 28 | |
| 29 | |
| 30 | def create_arch(): |
Louis Verhaard | 5207830 | 2020-11-18 13:35:06 +0100 | [diff] [blame] | 31 | return architecture_features.create_default_arch(architecture_features.Accelerator.Ethos_U55_128) |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 32 | |
| 33 | |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 34 | def default_quant_params(): |
| 35 | qp = QuantizationParameters() |
| 36 | qp.scale_f32 = np.float32(1) |
| 37 | qp.zero_point = 0 |
| 38 | return qp |
| 39 | |
| 40 | |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 41 | def create_elemwise_op( |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 42 | op_type, |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 43 | name, |
| 44 | ifm_shape, |
| 45 | ifm2_shape, |
| 46 | ofm_shape, |
| 47 | datatype=DataType.uint8, |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 48 | ifm_quant=default_quant_params(), |
| 49 | ifm2_quant=default_quant_params(), |
| 50 | ofm_quant=default_quant_params(), |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 51 | ): |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 52 | # Creates elementwise operation with constant IFM/IFM2 |
| 53 | if datatype.size_in_bytes() == 1: |
| 54 | np_type = np.uint8 |
| 55 | elif datatype.size_in_bytes() == 2: |
| 56 | np_type = np.int16 |
| 57 | else: |
| 58 | np_type = np.int32 |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 59 | op = Operation(op_type, name) |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 60 | op.add_input_tensor( |
| 61 | create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type, quantization=ifm_quant) |
| 62 | ) |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 63 | if ifm2_shape is not None: |
| 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 | ) |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 68 | ) |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 69 | ofm = Tensor(ofm_shape, datatype, name + "_ofm") |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 70 | ofm.quantization = ofm_quant |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 71 | op.set_output_tensor(ofm) |
Patrik Gustavsson | 2349d42 | 2020-12-01 16:02:29 +0100 | [diff] [blame] | 72 | op.set_ifm_ofm_shapes() |
| 73 | |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 74 | return op |
| 75 | |
| 76 | |
Dwight Lidman | c718743 | 2020-11-16 17:40:46 +0100 | [diff] [blame] | 77 | def create_op_with_quant_tensors( |
patrik.gustavsson | eeb8515 | 2020-12-21 17:10:40 +0000 | [diff] [blame] | 78 | op_type, ifm_shape, ofm_shape, weights_shape=None, bias_shape=None, datatype=DataType.uint8, set_ifm_ofm_shapes=True |
Dwight Lidman | c718743 | 2020-11-16 17:40:46 +0100 | [diff] [blame] | 79 | ): |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 80 | ifm = Tensor(ifm_shape, datatype, "in") |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 81 | ifm.quantization = default_quant_params() |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 82 | ofm = Tensor(ofm_shape, datatype, "out") |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 83 | ofm.quantization = default_quant_params() |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 84 | op = Operation(op_type, "op") |
| 85 | op.add_input_tensor(ifm) |
| 86 | op.set_output_tensor(ofm) |
| 87 | # Optional weight tensor |
| 88 | if weights_shape is not None: |
| 89 | if datatype.size_in_bytes() == 1: |
| 90 | np_type = np.uint8 |
| 91 | elif datatype.size_in_bytes() == 2: |
| 92 | np_type = np.int16 |
| 93 | else: |
| 94 | np_type = np.int32 |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 95 | qp = default_quant_params() |
Dwight Lidman | 0dd21c7 | 2020-11-24 13:45:50 +0100 | [diff] [blame] | 96 | if op.type is not Op.FullyConnected: |
| 97 | qp.zero_point = np.zeros(weights_shape) |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 98 | weights = create_const_tensor( |
| 99 | "weights", weights_shape, datatype, np.zeros(weights_shape), np_type, quantization=qp |
| 100 | ) |
| 101 | op.add_input_tensor(weights) |
Dwight Lidman | c718743 | 2020-11-16 17:40:46 +0100 | [diff] [blame] | 102 | # Optional bias tensor |
| 103 | if bias_shape is not None: |
| 104 | qp = default_quant_params() |
Dwight Lidman | 0dd21c7 | 2020-11-24 13:45:50 +0100 | [diff] [blame] | 105 | if op.type is not Op.FullyConnected: |
| 106 | qp.zero_point = np.zeros(bias_shape) |
Dwight Lidman | c718743 | 2020-11-16 17:40:46 +0100 | [diff] [blame] | 107 | bias = create_const_tensor("bias", bias_shape, DataType.int32, np.zeros(bias_shape), np.int32, quantization=qp) |
| 108 | op.add_input_tensor(bias) |
Patrik Gustavsson | 2349d42 | 2020-12-01 16:02:29 +0100 | [diff] [blame] | 109 | |
patrik.gustavsson | eeb8515 | 2020-12-21 17:10:40 +0000 | [diff] [blame] | 110 | if set_ifm_ofm_shapes: |
| 111 | op.set_ifm_ofm_shapes() |
| 112 | |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 113 | return op |
| 114 | |
| 115 | |
Michael McGeagh | 6f72526 | 2020-12-03 15:21:36 +0000 | [diff] [blame] | 116 | def create_op(op_type, inputs, output, attrs=None): |
Louis Verhaard | fa2f92a | 2020-09-21 11:56:18 +0200 | [diff] [blame] | 117 | op = Operation(op_type, output.name + "_op") |
Louis Verhaard | ae2d553 | 2020-12-11 17:19:54 +0100 | [diff] [blame] | 118 | for input in inputs: |
| 119 | op.add_input_tensor(input) |
| 120 | op.set_output_tensor(output) |
Michael McGeagh | 6f72526 | 2020-12-03 15:21:36 +0000 | [diff] [blame] | 121 | if attrs is not None: |
| 122 | op.attrs = attrs |
Patrik Gustavsson | 2349d42 | 2020-12-01 16:02:29 +0100 | [diff] [blame] | 123 | op.set_ifm_ofm_shapes() |
Louis Verhaard | fa2f92a | 2020-09-21 11:56:18 +0200 | [diff] [blame] | 124 | return op |
| 125 | |
| 126 | |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 127 | def create_subgraph(op_list): |
| 128 | # Creates subgraph using the given list of operations |
| 129 | sg = Subgraph() |
| 130 | all_inputs = set(tens for op in op_list for tens in op.inputs) |
| 131 | # Reversing, so that the resulting subgraph has same order as op_list |
| 132 | for op in op_list[::-1]: |
| 133 | for tens in op.outputs: |
| 134 | if tens not in all_inputs and tens not in sg.output_tensors: |
| 135 | sg.output_tensors.append(tens) |
| 136 | return sg |