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 |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 23 | from ethosu.vela.operation import Operation |
| 24 | from ethosu.vela.tensor import create_const_tensor |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 25 | from ethosu.vela.tensor import QuantizationParameters |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 26 | from ethosu.vela.tensor import Tensor |
| 27 | |
| 28 | |
| 29 | def create_arch(): |
Louis Verhaard | 5207830 | 2020-11-18 13:35:06 +0100 | [diff] [blame^] | 30 | return architecture_features.create_default_arch(architecture_features.Accelerator.Ethos_U55_128) |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 31 | |
| 32 | |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 33 | def default_quant_params(): |
| 34 | qp = QuantizationParameters() |
| 35 | qp.scale_f32 = np.float32(1) |
| 36 | qp.zero_point = 0 |
| 37 | return qp |
| 38 | |
| 39 | |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 40 | def create_elemwise_op( |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 41 | op_type, |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 42 | name, |
| 43 | ifm_shape, |
| 44 | ifm2_shape, |
| 45 | ofm_shape, |
| 46 | datatype=DataType.uint8, |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 47 | ifm_quant=default_quant_params(), |
| 48 | ifm2_quant=default_quant_params(), |
| 49 | ofm_quant=default_quant_params(), |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 50 | ): |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 51 | # Creates elementwise operation with constant IFM/IFM2 |
| 52 | if datatype.size_in_bytes() == 1: |
| 53 | np_type = np.uint8 |
| 54 | elif datatype.size_in_bytes() == 2: |
| 55 | np_type = np.int16 |
| 56 | else: |
| 57 | np_type = np.int32 |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 58 | op = Operation(op_type, name) |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 59 | op.add_input_tensor( |
| 60 | create_const_tensor(name + "_ifm", ifm_shape, datatype, np.zeros(ifm_shape), np_type, quantization=ifm_quant) |
| 61 | ) |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 62 | if ifm2_shape is not None: |
| 63 | op.add_input_tensor( |
| 64 | create_const_tensor( |
| 65 | name + "_ifm2", ifm2_shape, datatype, np.zeros(ifm2_shape), np_type, quantization=ifm2_quant |
| 66 | ) |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 67 | ) |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 68 | ofm = Tensor(ofm_shape, datatype, name + "_ofm") |
Dwight Lidman | 8359a47 | 2020-09-28 15:53:40 +0200 | [diff] [blame] | 69 | ofm.quantization = ofm_quant |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 70 | op.set_output_tensor(ofm) |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 71 | return op |
| 72 | |
| 73 | |
Dwight Lidman | c718743 | 2020-11-16 17:40:46 +0100 | [diff] [blame] | 74 | def create_op_with_quant_tensors( |
| 75 | op_type, ifm_shape, ofm_shape, weights_shape=None, bias_shape=None, datatype=DataType.uint8 |
| 76 | ): |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 77 | ifm = Tensor(ifm_shape, datatype, "in") |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 78 | ifm.quantization = default_quant_params() |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 79 | ofm = Tensor(ofm_shape, datatype, "out") |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 80 | ofm.quantization = default_quant_params() |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 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 |
Michael McGeagh | 65fd998 | 2020-10-20 11:49:28 +0100 | [diff] [blame] | 92 | qp = default_quant_params() |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 93 | qp.zero_point = np.zeros(weights_shape) |
| 94 | weights = create_const_tensor( |
| 95 | "weights", weights_shape, datatype, np.zeros(weights_shape), np_type, quantization=qp |
| 96 | ) |
| 97 | op.add_input_tensor(weights) |
Dwight Lidman | c718743 | 2020-11-16 17:40:46 +0100 | [diff] [blame] | 98 | # Optional bias tensor |
| 99 | if bias_shape is not None: |
| 100 | qp = default_quant_params() |
| 101 | qp.zero_point = np.zeros(bias_shape) |
| 102 | bias = create_const_tensor("bias", bias_shape, DataType.int32, np.zeros(bias_shape), np.int32, quantization=qp) |
| 103 | op.add_input_tensor(bias) |
Michael McGeagh | 1f951fc | 2020-10-14 09:30:02 +0100 | [diff] [blame] | 104 | return op |
| 105 | |
| 106 | |
Louis Verhaard | fa2f92a | 2020-09-21 11:56:18 +0200 | [diff] [blame] | 107 | def create_op(op_type, inputs, output, attrs=dict()): |
| 108 | op = Operation(op_type, output.name + "_op") |
| 109 | op.inputs = inputs |
| 110 | op.outputs = [output] |
| 111 | op.attrs = attrs |
| 112 | return op |
| 113 | |
| 114 | |
Louis Verhaard | 0b8268a | 2020-08-05 16:11:29 +0200 | [diff] [blame] | 115 | def create_subgraph(op_list): |
| 116 | # Creates subgraph using the given list of operations |
| 117 | sg = Subgraph() |
| 118 | all_inputs = set(tens for op in op_list for tens in op.inputs) |
| 119 | # Reversing, so that the resulting subgraph has same order as op_list |
| 120 | for op in op_list[::-1]: |
| 121 | for tens in op.outputs: |
| 122 | if tens not in all_inputs and tens not in sg.output_tensors: |
| 123 | sg.output_tensors.append(tens) |
| 124 | return sg |