# Copyright 2021 Zilliz. 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. import pprint class EmbeddingOutput: """ Container for embedding extractor. """ def __init__(self): self.embeddings = [] def __call__(self, module, module_in, module_out): self.embeddings.append(module_out) def clear(self): """ clear list """ self.embeddings = [] class EmbeddingExtractor: """ Embedding extractor from a layer Args: model (`nn.Module`): Model used for inference. """ def __init__(self, model): # self.modules = model.modules() # self.modules_list = list(model.named_modules(remove_duplicate=False)) self.modules_dict = dict(model.named_modules(remove_duplicate=False)) self.emb_out = EmbeddingOutput() def disp_modules(self, full=False): """ Display the the modules of the model. """ if not full: pprint.pprint(list(self.modules_dict.keys())) else: pprint.pprint(self.modules_dict) def register(self, layer_name: str): """ Registration for embedding extraction. Args: layer_name (`str`): Name of the layer from which the embedding is extracted. """ if layer_name in self.modules_dict: layer = self.modules_dict[layer_name] layer.register_forward_hook(self.emb_out) else: raise ValueError('layer_name not in modules')