noether.data.pipeline.sample_processors.concat_tensor¶

Classes¶

ConcatTensorSampleProcessor

Concatenates multiple tensors into a single tensor.

Module Contents¶

class noether.data.pipeline.sample_processors.concat_tensor.ConcatTensorSampleProcessor(items, target_key, dim=0)¶

Bases: noether.data.pipeline.SampleProcessor

Concatenates multiple tensors into a single tensor.

# dummy example
processor = ConcatTensorSampleProcessor(items=["image_part1", "image_part2"], target_key="full_image", dim=0)
input_sample = {
    "image_part1": torch.randn(3, 224, 224),
    "image_part2": torch.randn(3, 224, 224),
}
output_sample = processor(input_sample)
# output_sample['full_image'] will be a tensor of shape (6, 224, 224)

Parameters:

items (list[str]) – A list of keys in the input_sample dict whose tensors should be concatenated.
target_key (str) – The key in the sample dict where the concatenated tensor will be stored.
dim (int) – The dimension along which to concatenate the tensors. Defaults to 0.

items¶

target_key¶

dim = 0¶