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T4
| # coding=utf-8 | |
| # Copyright 2020 The HuggingFace Team. All rights reserved. | |
| # | |
| # Licensed under the Apache License, Version 2.0 (the "License"); | |
| # you may not use this file except in compliance with the License. | |
| # You may obtain a copy of the License at | |
| # | |
| # http://www.apache.org/licenses/LICENSE-2.0 | |
| # | |
| # Unless required by applicable law or agreed to in writing, software | |
| # distributed under the License is distributed on an "AS IS" BASIS, | |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. | |
| # See the License for the specific language governing permissions and | |
| # limitations under the License. | |
| from math import ceil | |
| def assert_device_map(device_map, num_blocks): | |
| blocks = list(range(0, num_blocks)) | |
| device_map_blocks = [item for sublist in list(device_map.values()) for item in sublist] | |
| # Duplicate check | |
| duplicate_blocks = [] | |
| for i in device_map_blocks: | |
| if device_map_blocks.count(i) > 1 and i not in duplicate_blocks: | |
| duplicate_blocks.append(i) | |
| # Missing blocks | |
| missing_blocks = [i for i in blocks if i not in device_map_blocks] | |
| extra_blocks = [i for i in device_map_blocks if i not in blocks] | |
| if len(duplicate_blocks) != 0: | |
| raise ValueError( | |
| "Duplicate attention blocks specified in device_map. Attention blocks must be specified to one device." | |
| " These attention blocks were specified more than once: " + str(duplicate_blocks) | |
| ) | |
| if len(missing_blocks) != 0: | |
| raise ValueError( | |
| "There are attention blocks for this model that are not specified in the device_map. Add these attention " | |
| "blocks to a device on the device_map: " + str(missing_blocks) | |
| ) | |
| if len(extra_blocks) != 0: | |
| raise ValueError( | |
| "The device_map contains more attention blocks than this model has. Remove these from the device_map:" | |
| + str(extra_blocks) | |
| ) | |
| def get_device_map(n_layers, devices): | |
| """Returns a dictionary of layers distributed evenly across all devices.""" | |
| layers = list(range(n_layers)) | |
| n_blocks = int(ceil(n_layers / len(devices))) | |
| layers_list = [layers[i : i + n_blocks] for i in range(0, n_layers, n_blocks)] | |
| return dict(zip(devices, layers_list)) | |