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Unable to Retrieve Embedding Arrays From TensorBoard Logs
I am encountering difficulties in retrieving embedding arrays that were logged using add_embedding from TensorBoard logs. I am unable to locate the actual embedding arrays. Below is a detailed description of the issue and the steps I have taken so far.
Steps to Reproduce Logging Embeddings:
I used add_embedding to log embeddings in TensorBoard. Example code for logging embeddings:
from torch.utils.tensorboard import SummaryWriter
import numpy as np
# Create a SummaryWriter
log_dir = 'logs/embedding_example'
writer = SummaryWriter(log_dir)
# Generate some dummy embeddings
embedding_data = np.random.randn(100, 64) # 100 items with 64-dim embeddings
metadata = [f'Label {i}' for i in range(100)]
# Write the embeddings
writer.add_embedding(mat=embedding_data, metadata=metadata, global_step=1)
writer.close()
Attempting to Retrieve Embeddings:
I tried using EventAccumulator to load and parse the event files but was unable to locate the embedding arrays. Example code for extracting embeddings:
import os
import numpy as np
from tensorboard.backend.event_processing.event_accumulator import EventAccumulator
def extract_embeddings_from_log(log_dir):
event_acc = EventAccumulator(log_dir, size_guidance={'tensors': 0})
event_acc.Reload()
embeddings = {}
# Get tags for tensors (embeddings should be listed here)
tensor_tags = event_acc.Tags()
print(tensor_tags)
I would appreciate any guidance or suggestions on how to properly retrieve the embedding arrays logged using add_embedding. Specifically, I am looking for:
- Confirmation on whether add_embedding embeddings should be accessible through EventAccumulator.
- Corrections to my approach or alternative methods to extract the embeddings.
- Any additional information on the correct tags or structures to look for within the TensorBoard logs.
Environment Details Framework: PyTorch Logging Library: TensorBoard TensorBoard Version: 2.16.2 Python Version: 3.10 Operating System: Ubuntu 22.04
Thank you for your assistance.